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Volume 7
Issue 12
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J. Mar. Sci. Eng., Volume 7, Issue 12 (December 2019) – 48 articles

Cover Story (view full-size image): This study investigates subtidal circulation in the Maroni Estuary on the border of French Guiana and Suriname. The Maroni has yet to be modified by anthropogenic change, presenting a unique opportunity to study subtidal flow forcing mechanisms and structure in a natural estuarine environment. A combination of in-situ collected data and analytical models revealed that river discharge was responsible for subtidal out-estuary flow, but wind can alter this pattern despite elevated river flow. Further, channel curvature and lateral density gradients influence lateral flows, producing a three-layer flow structure that lends to the elevated sediment accumulation on the Suriname coast. View this paper.
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15 pages, 4384 KiB  
Article
A Study on the Air Cavity under a Stepped Planing Hull
by Dongmei Yang, Zhiyuan Sun, Yi Jiang and Zeyang Gao
J. Mar. Sci. Eng. 2019, 7(12), 468; https://doi.org/10.3390/jmse7120468 - 17 Dec 2019
Cited by 17 | Viewed by 4629
Abstract
Based on the FVM (finite volume method) numerical method, the flow field around the stepped planing hull in Taunton series was simulated. According to the general procedure of numerical uncertainty analysis, the numerical uncertainty in the high-speed flow field simulation of the stepped [...] Read more.
Based on the FVM (finite volume method) numerical method, the flow field around the stepped planing hull in Taunton series was simulated. According to the general procedure of numerical uncertainty analysis, the numerical uncertainty in the high-speed flow field simulation of the stepped planing hull was discussed. Combined with the wave-making characteristics of the hull, the generation mechanism, shape evolution of air cavity, and the pressure distribution characteristics under the influence of the cavity, focuses on the variation of the flow around the stepped planing when the hull is in the triangle planing stage. Numerical results suggest that, as the air cavity enlarges, the cover rate of the air cavity can rise up to 77.8% of the whole wetted surface of the planing hull bottom. While, in the triangle planing stage, there is additional wetting at the aft bilge, which leads to the decrease of the air cavity rate and the increase of the wetted area. At the same time, the pressure distribution concentrates to the center of gravity. Full article
(This article belongs to the Special Issue Ship Hydrodynamics)
►▼ Show Figures

Figure 1

Figure 1
<p>Taunton Series (C1) stepped hull form model test at a speed of Fr<sub>▽</sub> = 7.12.</p> Full article ">Figure 2
<p>C1 stepped hull form in Taunton series.</p> Full article ">Figure 3
<p>Dimensions and boundary conditions of the numerical tank.</p> Full article ">Figure 4
<p>Mesh generation.</p> Full article ">Figure 5
<p>The y+ value at the hull bottom, Fr<b><sub>▽</sub></b> =5.99.</p> Full article ">Figure 6
<p>Calculated values of different mesh strategies.(<b>a</b>) Resistance, (<b>b</b>) Trim, (<b>c</b>) Sinkage.</p> Full article ">Figure 7
<p>Typical resistance convergence time-history curve for planing hull simulation.</p> Full article ">Figure 8
<p>Comparison of resistance, trim, and sinkage between numerical and experimental results. (<b>a</b>) Resistance, (<b>b</b>) Trim, (<b>c</b>) Sinkage.</p> Full article ">Figure 9
<p>Wetted area on broadside and transverse wave cuts after step, Fr<b><sub>▽</sub></b> = 2.41.</p> Full article ">Figure 10
<p>Bottom view of wetted area and wave-making characteristics.</p> Full article ">Figure 11
<p>Longitudinal wave form in the central section.</p> Full article ">Figure 12
<p>Dimensionless wetted and cover rate of air cavity.</p> Full article ">Figure 13
<p>Bottom view of pressure distribution.</p> Full article ">Figure 14
<p>Load coefficient and longitudinal location of pressure center of fore and aft planning surface. (<b>a</b>) Hull lift, (<b>b</b>) Longitudinal position of pressure center.</p> Full article ">
19 pages, 5982 KiB  
Article
Sea Waves Transport of Inertial Micro-Plastics: Mathematical Model and Applications
by Alessandro Stocchino, Francesco De Leo and Giovanni Besio
J. Mar. Sci. Eng. 2019, 7(12), 467; https://doi.org/10.3390/jmse7120467 - 17 Dec 2019
Cited by 15 | Viewed by 3281
Abstract
Plastic pollution in seas and oceans has recently been recognized as one of the most impacting threats for the environment, and the increasing number of scientific studies proves that this is an issue of primary concern. Being able to predict plastic paths and [...] Read more.
Plastic pollution in seas and oceans has recently been recognized as one of the most impacting threats for the environment, and the increasing number of scientific studies proves that this is an issue of primary concern. Being able to predict plastic paths and concentrations within the sea is therefore fundamental to properly face this challenge. In the present work, we evaluated the effects of sea waves on inertial micro-plastics dynamics. We hypothesized a stationary input number of particles in a given control volume below the sea surface, solving their trajectories and distributions under a second-order regular wave. We developed an exhaustive group of datasets, spanning the most plausible values for particles densities and diameters and wave characteristics, with a specific focus on the Mediterranean Sea. Results show how the particles inertia significantly affects the total transport of such debris by waves. Full article
►▼ Show Figures

Figure 1

Figure 1
<p>Geographical location of hindcast points used to set the wave parameters for the present study.</p> Full article ">Figure 2
<p>Each row corresponds to a single reanalysis point among those indicated in <a href="#jmse-07-00467-f001" class="html-fig">Figure 1</a>. <b>Left column</b>: wave period <span class="html-italic">T</span> versus wave height <span class="html-italic">H</span>, colormap indicates the number of events encountered in the time frame of the meteocean hindcast; <b>right column</b>: histograms of the dimensionless parameter <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> </mrow> </semantics></math> having set a threshold on the wave height equal to 0.3 m.</p> Full article ">Figure 3
<p>Example of numerical trajectories for a series of simulations with increasing <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> </mrow> </semantics></math> RUN 12: 0.001; RUN 13: 0.002; RUN 16: 0.005; RUN 17: 0.007 (cfr. <a href="#jmse-07-00467-t001" class="html-table">Table 1</a>). The plots correspond to runs with a fixed density ratio <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>ρ</mi> <mi>f</mi> </msub> <mo>=</mo> <mn>1.05</mn> </mrow> </semantics></math> and for several particle diameter <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math>. The duration of the simulations are about 3000 wave periods.</p> Full article ">Figure 4
<p>Close up of the trajectories of RUN12 for the larger diameters.</p> Full article ">Figure 5
<p>Example of numerical trajectories for a series of simulations with increasing <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> </mrow> </semantics></math>. RUN 12: 0.001; RUN 13: 0.002; RUN 16: 0.005; RUN 17: 0.007 (cfr. <a href="#jmse-07-00467-t001" class="html-table">Table 1</a>). The plots correspond to runs with a fixed value of the particle diameter <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m and for several density ratio. The duration of the simulations are about 3000 wave periods.</p> Full article ">Figure 6
<p>Normalized maximum horizontal distance <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>/</mo> <mi>λ</mi> </mrow> </semantics></math> as a function of <math display="inline"><semantics> <mi>τ</mi> </semantics></math>. Each panel corresponds to a series of experiments with fixed wave period, wave length and density ratio and varying wave amplitude and particle diameter.</p> Full article ">Figure 6 Cont.
<p>Normalized maximum horizontal distance <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>/</mo> <mi>λ</mi> </mrow> </semantics></math> as a function of <math display="inline"><semantics> <mi>τ</mi> </semantics></math>. Each panel corresponds to a series of experiments with fixed wave period, wave length and density ratio and varying wave amplitude and particle diameter.</p> Full article ">Figure 7
<p>Normalized maximum horizontal distance <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>/</mo> <mi>λ</mi> </mrow> </semantics></math> as a function of the Stokes number <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mi>t</mi> </msub> <mo>=</mo> <mi>ω</mi> <mi>τ</mi> </mrow> </semantics></math> and wave parameter <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mfenced separators="" open="(" close=")"> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> </mfenced> </mrow> </semantics></math>, for a fixed density ratio <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>ρ</mi> <mi>f</mi> </msub> <mo>=</mo> <mn>1.05</mn> </mrow> </semantics></math>. The plot is in log-log scales. The theoretical curve of [<a href="#B28-jmse-07-00467" class="html-bibr">28</a>] is reported for a single <math display="inline"><semantics> <mrow> <mi>F</mi> <mi>r</mi> </mrow> </semantics></math> number just to highlight the functional dependence between <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>/</mo> <mi>λ</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <msub> <mi>S</mi> <mi>t</mi> </msub> </semantics></math>.</p> Full article ">Figure 8
<p>Normalized maximum horizontal distance <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>/</mo> <mi>λ</mi> </mrow> </semantics></math> as a function of the added-mass parameter <math display="inline"><semantics> <mi>β</mi> </semantics></math>. The curves represent a series of experiments with fixed wave period, wave length and particle diameter and varying wave amplitude and <math display="inline"><semantics> <mi>β</mi> </semantics></math>.</p> Full article ">Figure 9
<p>Time evolution of the vertical velocity for different particle diameter: (<b>a</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m; (<b>b</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 500 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m; (<b>c</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 700 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m; (<b>d</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 1000 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m. Wave parameter <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mi>s</mi> </msub> <mo>/</mo> <mi>g</mi> <msubsup> <mi>T</mi> <mi>p</mi> <mn>2</mn> </msubsup> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math>.</p> Full article ">Figure 10
<p>Time evolution of the normalized period averaged vertical velocity <math display="inline"><semantics> <mrow> <mi>w</mi> <mo>/</mo> <msub> <mi>w</mi> <mi>s</mi> </msub> </mrow> </semantics></math> for different particle diameter at fixed wave parameter <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mi>s</mi> </msub> <mo>/</mo> <mi>g</mi> <msubsup> <mi>T</mi> <mi>p</mi> <mn>2</mn> </msubsup> <mo>=</mo> <mn>0.001</mn> </mrow> </semantics></math>.</p> Full article ">Figure 11
<p>Vertical distribution of plastic particles for experiments with fixed particle density (<math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>1050</mn> </mrow> </semantics></math> kg/m<math display="inline"><semantics> <msup> <mrow/> <mn>3</mn> </msup> </semantics></math>) and fixed wave field ( <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.007</mn> </mrow> </semantics></math>) and varying particle sizes: (<b>a</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 200 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m; (<b>b</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 400 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m; (<b>c</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 600 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m; (<b>d</b>) <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 1000 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m. Vertical profiles are taken after 100 wave periods.</p> Full article ">Figure 12
<p>Vertical distribution of plastic particles for experiments with fixed particle size (<math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m) and fixed wave field (<math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.007</mn> </mrow> </semantics></math>) and varying density ratio: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>1100</mn> </mrow> </semantics></math> kg/m<math display="inline"><semantics> <msup> <mrow/> <mn>3</mn> </msup> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>1150</mn> </mrow> </semantics></math> kg/m<math display="inline"><semantics> <msup> <mrow/> <mn>3</mn> </msup> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>1200</mn> </mrow> </semantics></math> kg/m<math display="inline"><semantics> <msup> <mrow/> <mn>3</mn> </msup> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>1250</mn> </mrow> </semantics></math> kg/m<math display="inline"><semantics> <msup> <mrow/> <mn>3</mn> </msup> </semantics></math>. Vertical profiles are taken after 200 wave periods.</p> Full article ">Figure 13
<p>Vertical distribution of plastic particles for experiments with fixed particle density (<math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>=</mo> <mn>1050</mn> </mrow> </semantics></math> kg/m<math display="inline"><semantics> <msup> <mrow/> <mn>3</mn> </msup> </semantics></math>) and fixed particle size (<math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> =100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m) and varying sea wave state. <b>Top panels</b>: <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.002</mn> </mrow> </semantics></math>; (<b>a</b>) after 100 <span class="html-italic">T</span>; (<b>b</b>) after 500 <span class="html-italic">T</span>; (<b>c</b>) after 1000. <b>Middle panels</b>: <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.004</mn> </mrow> </semantics></math>; (<b>d</b>) after 100 <span class="html-italic">T</span>; (<b>e</b>) after 500 <span class="html-italic">T</span>; (<b>f</b>) after 1000 <span class="html-italic">T</span>. <b>Bottom panels</b>: <math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.007</mn> </mrow> </semantics></math> (<b>g</b>) after 100 <span class="html-italic">T</span>; (<b>h</b>) after 500 <span class="html-italic">T</span>; (<b>i</b>) after 1000 <span class="html-italic">T</span>.</p> Full article ">Figure 14
<p><b>Top panel</b>: Example of numerical trajectories for a random distribution of particles, <math display="inline"><semantics> <msub> <mi>d</mi> <mi>p</mi> </msub> </semantics></math> ranging from 100 to 500 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m and <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>ρ</mi> <mi>f</mi> </msub> </mrow> </semantics></math> ranging between 0.95 and 1.25. Vertical distribution of plastic particles obtained for the experiments <span class="html-italic">rand1</span> (<math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.006</mn> </mrow> </semantics></math>) and <span class="html-italic">rand4</span> (<math display="inline"><semantics> <mrow> <mi>H</mi> <mo>/</mo> <mi>g</mi> <msup> <mi>T</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.016</mn> </mrow> </semantics></math>) after 100 wave periods panel (<b>a</b>) and (<b>c</b>) and 200 wave periods panel (<b>b</b>) and (<b>d</b>).</p> Full article ">Figure 15
<p><b>Top panel</b>: Example of numerical trajectories simulated for particle of different sizes and constant density ratio <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mi>p</mi> </msub> <mo>/</mo> <msub> <mi>ρ</mi> <mi>f</mi> </msub> <mo>=</mo> <mn>1.05</mn> </mrow> </semantics></math> showing the effect of a uniform current <math display="inline"><semantics> <mrow> <msub> <mi>U</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math> m/s and <math display="inline"><semantics> <mrow> <msub> <mi>H</mi> <mi>s</mi> </msub> <mo>/</mo> <mi>g</mi> <msubsup> <mi>T</mi> <mi>p</mi> <mn>2</mn> </msubsup> <mo>=</mo> <mn>0.009</mn> </mrow> </semantics></math>. <b>Bottom panels</b>: comparison of frequency distribution for the same wave, for two particle diameter, for a run with the uniform flow, panels (<b>a</b>,<b>b</b>) and without current panels (<b>c</b>,<b>d</b>). Integration time equal to 100 <span class="html-italic">T</span>.</p> Full article ">
18 pages, 1838 KiB  
Article
Bioconcentration of Essential and Nonessential Elements in Black Sea Turbot (Psetta Maxima Maeotica Linnaeus, 1758) in Relation to Fish Gender
by Ira-Adeline Simionov, Victor Cristea, Stefan-Mihai Petrea, Alina Mogodan, Mircea Nicoara, Emanuel Stefan Baltag, Stefan-Adrian Strungaru and Caterina Faggio
J. Mar. Sci. Eng. 2019, 7(12), 466; https://doi.org/10.3390/jmse7120466 - 17 Dec 2019
Cited by 34 | Viewed by 4151
Abstract
This study investigates the influence of gender in the bioconcentration of essential and nonessential elements in different parts of Black Sea turbot (Psetta maxima maeotica) body, from an area considered under high anthropogenic pressure (the Constanta City Black Sea Coastal Area [...] Read more.
This study investigates the influence of gender in the bioconcentration of essential and nonessential elements in different parts of Black Sea turbot (Psetta maxima maeotica) body, from an area considered under high anthropogenic pressure (the Constanta City Black Sea Coastal Area in Romania). A number of 13 elements (Ca, Mg, Na, K, Fe, Zn, Mn, Cu, Ni, Cr, As, Pb and Cd) were measured in various sample types: muscle, stomach, stomach content, intestine, intestine content, gonads, liver, spleen, gills and caudal fin. Turbot adults (4–5 years old) were separated, according to their gender, into two groups (20 males, 20 females, respectively), and a high total number of samples (1200 from both groups) were prepared and analyzed, in triplicate, with Flame Atomic Absorption Spectrometry and High-Resolution Continuum Source Atomic Absorption Spectrometry with Graphite Furnace techniques. The results were statistically analyzed in order to emphasize the bioconcentration of the determined elements in different tissues of wild turbot males vs. females, and also to contribute to an upgraded characterization of the Romanian Black Sea Coast, around Constanta City, in terms of heavy metals pollution. The essential elements Mg and Zn have different roles in the gonads of males and females, as they were the only elements with completely different patterns between the analyzed groups of specimens. The concentrations of studied elements in muscle were not similar with the data provided by literature, suggesting that chemistry of the habitat and food plays a major role in the availability of the metals in the body of analyzed fish species. The gender influenced the bioaccumulation process of all analyzed elements in most tissues since turbot male specimens accumulated higher concentration of metals compared to females. The highest bioaccumulation capacity in terms of Ca, Mg, Na, Ni, As, Zn and Cd was registered in caudal fin, liver and intestine tissues. Also, other elements such as K, Fe, Cu and Mn had the highest bioaccumulation in their muscle, spleen, liver and gills tissues. The concentrations of toxic metals in Black Sea turbot from this study were lower in the muscle samples compared with the studies conducted in Turkey, suggesting that the anthropogenic activity in the studied area did not pose a major impact upon the habitat contamination. Full article
►▼ Show Figures

Figure 1

Figure 1
<p>Romanian Black Sea targeted fishing territorial area and Constanta City fish market location.</p> Full article ">Figure 2
<p>The representation of elements’ affinity and variation in the body of male and female specimens of Black Sea turbot, based on the registered results (µg∙g<sup>−1</sup> fresh weight). (one-way analysis of variance (ANOVA) was applied for males and females in order to determine the variation of each studied element; *p &lt; 0.05). (<b>a</b>) The Ca concentration in analysed turbot tissues (<b>b</b>) The Mg concentration in analysed turbot tissues (<b>c</b>) The Na concentration in analysed turbot tissues (<b>d</b>) The K concentration in analysed turbot tissues (<b>e</b>) The Zn concentration in analysed turbot tissues (<b>f</b>) The Fe concentration in analysed turbot tissues (<b>g</b>) The Mn concentration in analysed turbot tissues (<b>h</b>) The Cu concentration in analysed turbot tissues (<b>i</b>) The Ni concentration in analysed turbot tissues (<b>j</b>) The As concentration in analysed turbot tissues (<b>k</b>) The Cd concentration in analysed turbot tissues.</p> Full article ">Figure 2 Cont.
<p>The representation of elements’ affinity and variation in the body of male and female specimens of Black Sea turbot, based on the registered results (µg∙g<sup>−1</sup> fresh weight). (one-way analysis of variance (ANOVA) was applied for males and females in order to determine the variation of each studied element; *p &lt; 0.05). (<b>a</b>) The Ca concentration in analysed turbot tissues (<b>b</b>) The Mg concentration in analysed turbot tissues (<b>c</b>) The Na concentration in analysed turbot tissues (<b>d</b>) The K concentration in analysed turbot tissues (<b>e</b>) The Zn concentration in analysed turbot tissues (<b>f</b>) The Fe concentration in analysed turbot tissues (<b>g</b>) The Mn concentration in analysed turbot tissues (<b>h</b>) The Cu concentration in analysed turbot tissues (<b>i</b>) The Ni concentration in analysed turbot tissues (<b>j</b>) The As concentration in analysed turbot tissues (<b>k</b>) The Cd concentration in analysed turbot tissues.</p> Full article ">
22 pages, 8338 KiB  
Article
Noise Characteristics Analysis of the Horizontal Axis Hydrokinetic Turbine Designed for Unmanned Underwater Mooring Platforms
by Zhigao Dang, Zhaoyong Mao, Baowei Song and Wenlong Tian
J. Mar. Sci. Eng. 2019, 7(12), 465; https://doi.org/10.3390/jmse7120465 - 17 Dec 2019
Cited by 14 | Viewed by 2937
Abstract
Operating horizontal axis hydrokinetic turbine (HAHT) generates noise affecting the ocean environment adversely. Therefore, it is essential to determine the noise characteristics of such types of HAHT, as large-scale turbine sets would release more noise pollution to the ocean. Like other rotating machinery, [...] Read more.
Operating horizontal axis hydrokinetic turbine (HAHT) generates noise affecting the ocean environment adversely. Therefore, it is essential to determine the noise characteristics of such types of HAHT, as large-scale turbine sets would release more noise pollution to the ocean. Like other rotating machinery, the hydrodynamic noise generated by the rotating turbine has been known to be the most important noise source. In the present work, the transient turbulent flow field of the HAHT is obtained by incompressible large eddy simulation, thereafter, the Ffowcs Williams and Hawkings acoustic analogy formulation is carried out to predict the noise generated from the pressure fluctuations of the blade surface. The coefficient of power is compared with the experimental results, with a good agreement being achieved. It is seen from the pressure contours that the 80% span of the blade has the most severe pressure fluctuations, which concentrate on the region of leading the edge of the airfoil and the suction surface of the airfoil. Then, the noise characteristics around a single turbine are systematically studied, in accordance with the results of the flow field. The noise characteristics around the whole turbine are also investigated to determine the directionality of the noise emission of HAHT. Full article
(This article belongs to the Section Ocean Engineering)
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<p>Diagrammatic sketch of the working principle of the horizontal axis hydrokinetic turbine (HAHT) designed for unmanned underwater mooring platforms (UUMPs).</p> Full article ">Figure 2
<p>The closer views of the solid view of the blade: (<b>a</b>) three-dimensional view of the blade in a direct way and (<b>b</b>) view of the blade from blade tip to blade root.</p> Full article ">Figure 3
<p>Flowchart of the noise characteristics analysis of the HAHT. FW–H—Ffowcs Williams and Hawkings; LES—large eddy simulations.</p> Full article ">Figure 4
<p>Domains, boundary conditions, and the details of the interfaces applied in the model.</p> Full article ">Figure 5
<p>Mesh generation for the computational model: (<b>a</b>) mesh on the surface of the computational model from the A-A plane, (<b>b</b>) mesh of the blade subdomain in three different cross sections with the view from blade tip to blade root, and (<b>c</b>) a view of the mesh near the blade from the cross section along the spanwise direction.</p> Full article ">Figure 6
<p>Results of the present numerical method validation for the flow field.</p> Full article ">Figure 7
<p>Vortices generated around the HAHT.</p> Full article ">Figure 8
<p>Pressure contours of the blade at different cross sections.</p> Full article ">Figure 9
<p>Observing the points arrangement around a single blade: (<b>a</b>) Noise observing points located at different spanwise positions with <span class="html-italic">h</span> = 0.2 R, <span class="html-italic">h</span> = 0.4 R, <span class="html-italic">h</span> = 0.6 R, and <span class="html-italic">h</span> = 0.8 R, and <span class="html-italic">h</span> = 1.0 R, and (<b>b</b>) a representative layout of the noise observing points at the cross section of <span class="html-italic">h</span> = 0.6 R.</p> Full article ">Figure 10
<p>Comparison of the predicted the overall sound pressure level (OASPL) of the single blade for noise observing points with different radii: (<b>a</b>) <span class="html-italic">r<sub>1</sub></span>; (<b>b</b>) <span class="html-italic">r<sub>2</sub></span>.</p> Full article ">Figure 11
<p>A comparison of the predicted OASPLs of the single blade for noise observing points at different cross sections: (<b>a</b>) 0.2 R; (<b>b</b>) 0.4 R; (<b>c</b>) 0.6 R; (<b>d</b>) 0.8 R; (<b>e</b>) 1.0 R.</p> Full article ">Figure 12
<p>The predicted SPL spectra of Point A with a frequency-axis in a linear and logarithmic form.</p> Full article ">Figure 13
<p>Comparison of the predicted SPL of the single blade for noise observing points in different directions at the spanwise position of 0.6 R: (Point A, Point B, Point C, and Point D).</p> Full article ">Figure 14
<p>Comparison of the predicted SPL of the single blade for noise observing points at different cross sections (Point 1, Point 2, Point 3, Point 4, and Point 5).</p> Full article ">Figure 15
<p>Observing points’ arrangement around the whole turbine (24 observing points evenly distributed along each circle at intervals of 15°).</p> Full article ">Figure 16
<p>Diagrammatic sketch of point <span class="html-italic">p</span> in the surface of the spherical.</p> Full article ">Figure 17
<p>Comparison of the predicted OASPL of the whole turbine for noise observing points in a spherical surface.</p> Full article ">Figure 18
<p>Comparison of the predicted OASPL of the whole turbine along six directions of three coordinate axes.</p> Full article ">Figure 19
<p>Comparison of the cumulative sum of the sound power spectrum E(<span class="html-italic">f</span>) of the noise observing points along <span class="html-italic">x</span>-axis and <span class="html-italic">y</span>-axis.</p> Full article ">
19 pages, 1290 KiB  
Article
A Reasoned Comparison between Two Hydrodynamic Models: Delft3D-Flow and ROMS (Regional Oceanic Modelling System)
by Stefano Putzu, Francesco Enrile, Giovanni Besio, Andrea Cucco, Laura Cutroneo, Marco Capello and Alessandro Stocchino
J. Mar. Sci. Eng. 2019, 7(12), 464; https://doi.org/10.3390/jmse7120464 - 17 Dec 2019
Cited by 9 | Viewed by 5470
Abstract
Useful information, such as water levels, currents, salinity and temperature dynamics in water bodies, are obtained through numerical models in order to pursue scientific research or consultancy. Model validation dates back long ago, since such models started to be developed in the 1960s. [...] Read more.
Useful information, such as water levels, currents, salinity and temperature dynamics in water bodies, are obtained through numerical models in order to pursue scientific research or consultancy. Model validation dates back long ago, since such models started to be developed in the 1960s. Despite their usefulness and reliability in complex situations, some issues related to well-known benchmarks are still present. This work aims to analyse in detail the behaviour of the velocity profile, vertical eddy viscosity and tangential stresses at the bed in two cases of free surface flows; namely: uniform flow in an inclined rectangular channel and a wind-induced circulation in a closed basin. Computational results strongly depend on the turbulence closure model employed and a reasoned comparison is necessary to highlight possible improvements of these models. The strong differences that arise are deeply analysed in this work. Full article
(This article belongs to the Section Coastal Engineering)
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<p>Sketch of uniform open-channel flow modelled with Delft3D and ROMS. Velocity, tangential stresses and vertical eddy viscosity are plotted in order to show the expected theoretical trends; i.e., a logarithmic, linear and parabolic profiles, respectively.</p> Full article ">Figure 2
<p>(<b>a</b>) Geometry of the trapezoidal closed basin in blue. (<b>b</b>) Vectors in black show the presence of two counter-rotating vortices. (<b>c</b>) The free surface is depicted in red. The set-up is highlighted through the colour shading. Points A, B and C refer to the results reported in the respective panels of <a href="#jmse-07-00464-f003" class="html-fig">Figure 3</a> and Figure 6.</p> Full article ">Figure 3
<p>Shear stresses and velocity profiles moving from the lateral banks to the centre of the basin. (<b>a</b>) shows a profile where surface and bed shear stresses have concordant signs. This profile is associated to point A of <a href="#jmse-07-00464-f002" class="html-fig">Figure 2</a>. The velocity profile is that of a turbulent Couette–Poiseuille flow. (<b>b</b>) shows a zero tangential stress at the bed that occurs at the transition from the lateral bank to the centre of the channel. It refers to point B of <a href="#jmse-07-00464-f002" class="html-fig">Figure 2</a>. The velocity profile tends to a zero-gradient towards the bottom. (<b>c</b>) shows discordant shear stresses at the surface and at the bed. This condition occurs at the centre of the channel; i.e., point C of <a href="#jmse-07-00464-f002" class="html-fig">Figure 2</a>. The velocity profile shows an inversion along the water column.</p> Full article ">Figure 4
<p>Comparison of turbulence models used in Delft3D and ROMS for the open channel flow. (<b>a</b>) Velocity profile made non dimensional with bed friction velocity model outputs. (<b>b</b>) Velocity profile made non dimensional with theoretical bed friction velocity. (<b>c</b>) Vertical eddy viscosity <math display="inline"><semantics> <msub> <mi>ν</mi> <mrow> <mi>t</mi> <mi>v</mi> </mrow> </msub> </semantics></math> and (<b>d</b>) turbulent kinetic energy <span class="html-italic">k</span>.</p> Full article ">Figure 5
<p>Comparison of x-component tangential stress profiles for the open channel flow. The profiles are compared with the model output values at the bottom. Profiles are computed since they are not part of the output of the models.</p> Full article ">Figure 6
<p>Comparison of x-component velocity profiles for the trapezoidal closed basin. Panels (<b>a</b>–<b>c</b>) correspond to the respective panels of <a href="#jmse-07-00464-f003" class="html-fig">Figure 3</a>.</p> Full article ">Figure 7
<p>Comparison of turbulence models used in Delt3D and ROMS for the closed basin. (<b>a</b>) Bed shear stresses for Delft3D <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>−</mo> <mi>ϵ</mi> </mrow> </semantics></math>. (<b>b</b>) Bed shear stresses for ROMS <math display="inline"><semantics> <mrow> <mi>k</mi> <mo>−</mo> <mi>ϵ</mi> </mrow> </semantics></math>.</p> Full article ">Figure 8
<p>Comparison of x-component velocity profiles that correspond to the points of the basin in which the bed shear stress is zero. The position in the basin of these points changes as a function of the turbulence closure model, as seen in <a href="#jmse-07-00464-f007" class="html-fig">Figure 7</a>. The theoretical trend was proposed by [<a href="#B32-jmse-07-00464" class="html-bibr">32</a>].</p> Full article ">Figure 9
<p>(<b>a</b>) Spreading of results for the different turbulent models expressed as a function of <math display="inline"><semantics> <mrow> <msubsup> <mi>τ</mi> <mi>b</mi> <mi>x</mi> </msubsup> <mspace width="-1.111pt"/> <mo>/</mo> <mspace width="-0.55542pt"/> <msubsup> <mi>τ</mi> <mi>s</mi> <mi>x</mi> </msubsup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>U</mi> <mspace width="-1.111pt"/> <mo>/</mo> <mspace width="-0.55542pt"/> <msubsup> <mi>u</mi> <mi>s</mi> <mo>*</mo> </msubsup> </mrow> </semantics></math>. The square represents the zoom depicted in (<b>b</b>). (<b>b</b>) Zoom around the crossing of the x-axis by the curves of (<b>a</b>). The greater differences can be seen for high values of <math display="inline"><semantics> <mrow> <mi>U</mi> <mspace width="-1.111pt"/> <mo>/</mo> <mspace width="-0.55542pt"/> <msubsup> <mi>u</mi> <mi>s</mi> <mo>*</mo> </msubsup> </mrow> </semantics></math> in (<b>a</b>) where the behaviour tends to be quadratic.</p> Full article ">
18 pages, 3951 KiB  
Article
A Machine-Learning Model for Zonal Ship Flow Prediction Using AIS Data: A Case Study in the South Atlantic States Region
by Xuantong Wang, Jing Li and Tong Zhang
J. Mar. Sci. Eng. 2019, 7(12), 463; https://doi.org/10.3390/jmse7120463 - 16 Dec 2019
Cited by 23 | Viewed by 3615
Abstract
Predicting traffic flow is critical in efficient maritime transportation management, coordination, and planning. Scientists have proposed many prediction methods, most of which are designed for specific locations or for short-term prediction. For the purpose of management, methods that enable long-term prediction for large [...] Read more.
Predicting traffic flow is critical in efficient maritime transportation management, coordination, and planning. Scientists have proposed many prediction methods, most of which are designed for specific locations or for short-term prediction. For the purpose of management, methods that enable long-term prediction for large areas are highly desirable. Therefore, we propose developing a spatiotemporal approach that can describe and predict traffic flows within a region. We designed the model based on a multiple hexagon-based convolutional neural network (mh-CNN) model that takes both the flow dynamics and environmental conditions into account. This model is highly flexible in that it predicts zonal traffic flow within variable time windows. We applied the method to measure and predict the daily and hourly traffic flows in the South Atlantic States region by taking the impacts of extreme weather events into consideration. Results show that our method outperformed other methods in daily prediction during normal days and hourly prediction during hurricane events. Based on the results, we also provide some recommendations regarding the future usage and customization of the model. Full article
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<p>Distribution of the 11 selected H3 hexagons at level 3 used for the case studies. Zones are labeled as ‘lx_Zy’ because this indicates the resolution/level of the hexagons and the unique zone identifier at that level.</p> Full article ">Figure 2
<p>Flow chart of ROI identification and H3 zone selection.</p> Full article ">Figure 3
<p>Methods to compute ship traffic. (<b>a</b>) Counting total ship traffic in the surrounding regions and (<b>b</b>) counting ship flows moving toward the central zone.</p> Full article ">Figure 4
<p>Spatial autocorrelation using the local version of Moran’s I results: (<b>a</b>) LISA significance and (<b>b</b>) LISA clusters.</p> Full article ">Figure 5
<p>Time series analysis using two regions as examples: (<b>a</b>) demonstration of level 3 hexagons near Port Miami, (<b>b</b>) the annual ship flow in the central and surrounding hexagons, (<b>c</b>) demonstration of level 3 hexagons near Key West, and (<b>d</b>) the annual ship flow change flow in the central and surrounding hexagons.</p> Full article ">Figure 6
<p>A demonstration of searching for hurricanes using the H3’s distance function based on a search radius of 5.</p> Full article ">Figure 7
<p>Traffic flow fluctuations during the extreme weather events.</p> Full article ">Figure 8
<p>mh-CNN model design.</p> Full article ">Figure A1
<p>Average <span class="html-italic">RMSE</span> and <span class="html-italic">MAE</span> results for each model using level 3 hexagons for Group 1. (<b>a</b>) <span class="html-italic">RMSE</span> for 1-day prediction, (<b>b</b>) <span class="html-italic">RMSE</span> for 3-day prediction, (<b>c</b>) <span class="html-italic">MAE</span> for 1-day prediction, (<b>d</b>) <span class="html-italic">MAE</span> for 3-day prediction.</p> Full article ">Figure A2
<p>Average <span class="html-italic">RMSE</span> and <span class="html-italic">MAE</span> results for each model using level 4 hexagons for Group 1. (<b>a</b>) <span class="html-italic">RMSE</span> for 1-day prediction, (<b>b</b>) <span class="html-italic">RMSE</span> for 3-day prediction, (<b>c</b>) <span class="html-italic">MAE</span> for 1-day prediction, (<b>d</b>) <span class="html-italic">MAE</span> for 3-day prediction.</p> Full article ">Figure A3
<p>Average <span class="html-italic">RMSE</span> and <span class="html-italic">MAE</span> results for each model using level 4 hexagons for Group 2. (<b>a</b>) <span class="html-italic">RMSE</span> for 4-hour prediction, (<b>b</b>) <span class="html-italic">RMSE</span> for 8-hour prediction, (<b>c</b>) <span class="html-italic">MAE</span> for 4-hour prediction, (<b>d</b>) <span class="html-italic">MAE</span> for 8-hour prediction.</p> Full article ">
22 pages, 6658 KiB  
Article
Origin of Pumice in Sediments from the Middle Okinawa Trough: Constraints from Whole-Rock Geochemical Compositions and Sr-Nd-Pb Isotopes
by Xue Fang, Zhigang Zeng, Siyi Hu, Xiaohui Li, Zuxing Chen, Shuai Chen and Bowen Zhu
J. Mar. Sci. Eng. 2019, 7(12), 462; https://doi.org/10.3390/jmse7120462 - 16 Dec 2019
Cited by 3 | Viewed by 3627
Abstract
Frequent volcanic activity has occurred in the Okinawa Trough (OT) during the late Quaternary, which attracted much attention to the origin of volcanic rocks. Pumice collected from the seafloor has been extensively investigated, whereas few studies paid attention to the pumice in the [...] Read more.
Frequent volcanic activity has occurred in the Okinawa Trough (OT) during the late Quaternary, which attracted much attention to the origin of volcanic rocks. Pumice collected from the seafloor has been extensively investigated, whereas few studies paid attention to the pumice in the sediment. The geochemical compositions of pumice preserved in sediments generally provide insight into past volcanic activity and regional magmatism. Here, we present major and trace element compositions and Sr-Nd-Pb isotope data, together with the established age framework for pumice samples recovered from sediment core S9 in the middle OT (MOT) to investigate their possible formation. Compositionally, the S9 pumice samples are dacite and are characterized by relatively higher Sr (87Sr/86Sr = 0.70480–0.70502) and Pb (206Pb/204Pb = 18.321-18.436, 207Pb/204Pb = 15.622–15.624, and 208Pb/204Pb = 38.52–38.63) and lower Nd (143Nd/144Nd = 0.51272–0.51274) isotope compositions than basalts from the MOT. The geochemical compositions of pumice clasts from different layers of core S9 display no temporal variation trends and vary within narrow ranges. On the basis of the geochemical characteristics of S9 pumice samples, we infer that the parent magma of these samples might generate from hybrid magma through an extensive fractional crystallization process. The Indian Ocean MORB-type mantle was first metasomatized by the subducted Philippine Sea sediments to form the primitive magma; then, followed by assimilation of a small amount of lower crustal component occurred in the lower crust. The long-term magmatism and relatively consistent isotopic compositions indicate that a magma chamber might have existed in the lower crust of the MOT between 11.22 and 12.96 cal. ka BP. Full article
(This article belongs to the Section Geological Oceanography)
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<p>Simplified tectonic map of the Okinawa Trough (OT), showing sampling locations of the studied pumice and volcanic rocks used in this study. Yellow star represents the sampling location of core S9. Blue inverted triangles and green circles represent andesites [<a href="#B26-jmse-07-00462" class="html-bibr">26</a>] and basalts [<a href="#B16-jmse-07-00462" class="html-bibr">16</a>,<a href="#B17-jmse-07-00462" class="html-bibr">17</a>,<a href="#B24-jmse-07-00462" class="html-bibr">24</a>,<a href="#B27-jmse-07-00462" class="html-bibr">27</a>] from the middle OT (MOT), respectively. Red triangle represents a Quaternary volcano named Kuro-shima [<a href="#B37-jmse-07-00462" class="html-bibr">37</a>]. Two black dashed lines represent the Tokara Fault and Kerama Gap [<a href="#B12-jmse-07-00462" class="html-bibr">12</a>]. Solid arrows indicate plate motion vectors of the Philippine Sea Plate relative to the Eurasian Plate [<a href="#B35-jmse-07-00462" class="html-bibr">35</a>].</p> Full article ">Figure 2
<p>(<b>a</b>) Close-up image of core S9 containing centimeter-thick pumice clasts layers. (<b>b</b>) Hand specimen photographs of pumice recovered from core S9. (<b>c</b>–<b>f</b>) Representative scanning electron microscope (SEM) images of S9 pumice. The eruption ages of S9 pumice samples were calculated with Bayesian analysis.</p> Full article ">Figure 3
<p>Classification diagrams of S9 pumice and volcanic rocks from the MOT. (<b>a</b>) Total alkali versus silica (TAS) diagram [<a href="#B47-jmse-07-00462" class="html-bibr">47</a>]; (<b>b</b>) K<sub>2</sub>O versus SiO<sub>2</sub> diagram, the boundaries of different series were drawn according to [<a href="#B48-jmse-07-00462" class="html-bibr">48</a>]. MOT = middle Okinawa Trough. Data sources are from Zhang et al. [<a href="#B23-jmse-07-00462" class="html-bibr">23</a>]; Hoang and Uto [<a href="#B27-jmse-07-00462" class="html-bibr">27</a>]; Zhai and Gan [<a href="#B16-jmse-07-00462" class="html-bibr">16</a>]; Shinjo and Kato [<a href="#B26-jmse-07-00462" class="html-bibr">26</a>]; Guo et al. [<a href="#B24-jmse-07-00462" class="html-bibr">24</a>]; Guo et al. [<a href="#B19-jmse-07-00462" class="html-bibr">19</a>]; Zhai et al. [<a href="#B9-jmse-07-00462" class="html-bibr">9</a>]; Huang et al. [<a href="#B25-jmse-07-00462" class="html-bibr">25</a>]; Shinjo et al. [<a href="#B17-jmse-07-00462" class="html-bibr">17</a>].</p> Full article ">Figure 4
<p>Harker diagrams of S9 pumice samples, basalts, andesites, dacites, and other types of pumice from the MOT. The data sources are the same as in <a href="#jmse-07-00462-f003" class="html-fig">Figure 3</a>.</p> Full article ">Figure 5
<p>Normal-MORB normalized trace element concentration patterns (<b>a</b>,<b>b</b>), and chondrite-normalized REE patterns (<b>c</b>,<b>d</b>) for the studied pumice compared with basalts from the MOT [<a href="#B16-jmse-07-00462" class="html-bibr">16</a>,<a href="#B17-jmse-07-00462" class="html-bibr">17</a>,<a href="#B24-jmse-07-00462" class="html-bibr">24</a>,<a href="#B27-jmse-07-00462" class="html-bibr">27</a>], and basalts from the northern and central Ryukyu volcanic front [<a href="#B37-jmse-07-00462" class="html-bibr">37</a>,<a href="#B50-jmse-07-00462" class="html-bibr">50</a>,<a href="#B51-jmse-07-00462" class="html-bibr">51</a>,<a href="#B52-jmse-07-00462" class="html-bibr">52</a>,<a href="#B53-jmse-07-00462" class="html-bibr">53</a>]. The normalization constants are from Sun and McDonough [<a href="#B54-jmse-07-00462" class="html-bibr">54</a>]. MOT = middle Okinawa Trough; NRVF = northern Ryukyu volcanic front; MRVF = middle Ryukyu volcanic front.</p> Full article ">Figure 6
<p><sup>87</sup>Sr/<sup>86</sup>Sr versus <sup>143</sup>Nd/<sup>144</sup>Nd diagram for the studied pumice compared to volcanic rocks from the MOT [<a href="#B17-jmse-07-00462" class="html-bibr">17</a>,<a href="#B24-jmse-07-00462" class="html-bibr">24</a>,<a href="#B26-jmse-07-00462" class="html-bibr">26</a>,<a href="#B27-jmse-07-00462" class="html-bibr">27</a>,<a href="#B57-jmse-07-00462" class="html-bibr">57</a>], basalts from the northern West Philippine Basin [<a href="#B55-jmse-07-00462" class="html-bibr">55</a>,<a href="#B56-jmse-07-00462" class="html-bibr">56</a>], basalts from the northern Ryukyu volcanic front [<a href="#B37-jmse-07-00462" class="html-bibr">37</a>,<a href="#B50-jmse-07-00462" class="html-bibr">50</a>,<a href="#B51-jmse-07-00462" class="html-bibr">51</a>], basalts from the central Ryukyu arc [<a href="#B37-jmse-07-00462" class="html-bibr">37</a>]. Indian MORB, Pacific MORB and Philippine Sea sediments (PetDB database; <a href="http://www.earthchem.org/petdb" target="_blank">http://www.earthchem.org/petdb</a>) are also shown for comparison. EMI and EMII data are from Zindler and Hart [<a href="#B61-jmse-07-00462" class="html-bibr">61</a>].</p> Full article ">Figure 7
<p>Plots of (<b>a</b>,<b>b</b>) <sup>207</sup>Pb/<sup>204</sup>Pb versus <sup>206</sup>Pb/<sup>204</sup>Pb and (<b>c</b>,<b>d</b>) <sup>208</sup>Pb/<sup>204</sup>Pb versus <sup>206</sup>Pb/<sup>204</sup>Pb diagrams of S9 pumice samples and basalts from the MOT [<a href="#B17-jmse-07-00462" class="html-bibr">17</a>,<a href="#B57-jmse-07-00462" class="html-bibr">57</a>] and its adjacent regions. The Northern Hemisphere reference line (NHRL) [<a href="#B62-jmse-07-00462" class="html-bibr">62</a>] and representative fields (DM, EMI, EMII, PREMA, and BSE) [<a href="#B61-jmse-07-00462" class="html-bibr">61</a>] are shown for reference. Yellow inverted triangles represent basalts from the southern segment of northern Ryukyu volcanic front [<a href="#B37-jmse-07-00462" class="html-bibr">37</a>]. Data of Indian MORB and Pacific MORB are from PetDB database (<a href="http://www.earthchem.org/petdb" target="_blank">http://www.earthchem.org/petdb</a>), data of Philippine Sea sediments are from Hauff et al. [<a href="#B58-jmse-07-00462" class="html-bibr">58</a>], Plank and Langmuir [<a href="#B59-jmse-07-00462" class="html-bibr">59</a>], and Shu et al. [<a href="#B57-jmse-07-00462" class="html-bibr">57</a>]. Letters A-D in (b) and (d) represent different components discussed in the text. MOT = middle Okinawa Trough. NRVF = northern Ryukyu volcanic front.</p> Full article ">Figure 8
<p>Plots of (<b>a</b>–<b>c</b>) <sup>87</sup>Sr/<sup>86</sup>Sr versus SiO<sub>2</sub>, MgO, and Th/La, and (<b>d</b>–<b>f</b>) <sup>143</sup>Nd/<sup>144</sup>Nd versus SiO<sub>2</sub>, MgO, and Th/La diagrams for the studied pumice and volcanic rocks from the MOT. The source data of volcanic rocks from the MOT are the same as in <a href="#jmse-07-00462-f006" class="html-fig">Figure 6</a>. MOT = middle Okinawa Trough.</p> Full article ">Figure 9
<p>Calculation diagram of <sup>87</sup>Sr/<sup>86</sup>Sr versus <sup>143</sup>Nd/<sup>144</sup>Nd for S9 pumice samples and volcanic rocks from the MOT. Igneous rocks from the southern Kyushu, which exhibit a lower crustal provenance are also shown for comparison [<a href="#B13-jmse-07-00462" class="html-bibr">13</a>,<a href="#B77-jmse-07-00462" class="html-bibr">77</a>,<a href="#B78-jmse-07-00462" class="html-bibr">78</a>]. The black lines represent mixing between two endmembers (UCC = upper continental crust; PSs = Philippine Sea sediments; SK = southern Kyushu). The compositions of endmembers used for the calculations are listed in <a href="#jmse-07-00462-t004" class="html-table">Table 4</a>. MOT = middle Okinawa Trough. The source data of volcanic rocks in the MOT are the same as in <a href="#jmse-07-00462-f006" class="html-fig">Figure 6</a>.</p> Full article ">Figure 10
<p>Calculation diagram of <sup>143</sup>Nd/<sup>144</sup>Nd versus <sup>206</sup>Pb/<sup>204</sup>Pb for S9 pumice and volcanic rocks from the MOT. The endmembers used for calculations in this figure are the same as in <a href="#jmse-07-00462-f009" class="html-fig">Figure 9</a>. The source data of basalts in the MOT are the same as in <a href="#jmse-07-00462-f006" class="html-fig">Figure 6</a>. UCC = upper continental crust; PSs = Philippine Sea sediments; LC = lower crust.</p> Full article ">Figure 11
<p>REE patterns of liquids modeled by Rayleigh fractional crystallization from mixed andesite to dacite. The detailed calculation process is shown in <a href="#app1-jmse-07-00462" class="html-app">Supplementary Table S1</a>. The K<sub>d</sub> values used in modeling are shown in <a href="#jmse-07-00462-t005" class="html-table">Table 5</a>. Pl = plagioclase, Opx = orthopyroxene, Amph = amphibole, Mt = magnetite, and Ap = apatite. LC = lower crust.</p> Full article ">
14 pages, 4310 KiB  
Article
Synergistic Use of Synthetic Aperture Radar and Optical Imagery to Monitor Surface Accumulation of Cyanobacteria in the Curonian Lagoon
by Francesca De Santi, Giulia Luciani, Mariano Bresciani, Claudia Giardino, Francesco Paolo Lovergine, Guido Pasquariello, Diana Vaiciute and Giacomo De Carolis
J. Mar. Sci. Eng. 2019, 7(12), 461; https://doi.org/10.3390/jmse7120461 - 14 Dec 2019
Cited by 13 | Viewed by 3150
Abstract
Phytoplankton blooms in internal water bodies are an unpleasant sight that often emerges on top like a layer of foam containing high concentrations of toxins (scum event). Monitoring the concentration of algae and the occurrence of scum in lakes and lagoons has become [...] Read more.
Phytoplankton blooms in internal water bodies are an unpleasant sight that often emerges on top like a layer of foam containing high concentrations of toxins (scum event). Monitoring the concentration of algae and the occurrence of scum in lakes and lagoons has become a topic of interest for management and science. Optical remote sensing is a validated tool but unfortunately it is highly hindered by clouds. For regions with frequent cloud cover, such as the Baltic region, this means loss of data, which limits the purpose of sensing to spatially and temporally characterize any scum for a comprehensive ecological analysis. The aim of this paper is to investigate whether the use of synthetic aperture radar (SAR) images can compensate for the weaknesses of optical images for cyanobacteria bloom monitoring purposes in the event of cloudy skies. A “ready to use” approach to detect cyanobacteria bloom in the Curonian Lagoon based on the level 2 ocean product of Sentinel-1 images is proposed. This method is empirically validated for the images of summer/autumn 2018 of the Curonian Lagoon. Full article
(This article belongs to the Special Issue Radar Technology for Coastal Areas and Open Sea Monitoring)
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<p>(<b>a</b>) Study area: the Curonian Lagoon; (<b>b</b>,<b>c</b>) examples of scum phenomena formed by cyanobacteria on the water surface of the Curonian Lagoon.</p> Full article ">Figure 2
<p>(<b>a</b>) Scatter-density plot between the a-priori European Centre for Medium-Range Weather Forecasts (ECMWF) wind velocity, <math display="inline"><semantics> <msub> <mi mathvariant="normal">w</mi> <mrow> <mi>E</mi> <mi>C</mi> <mi>M</mi> <mi>W</mi> <mi>F</mi> </mrow> </msub> </semantics></math> and the wind velocity estimated from Sentinel 1, <math display="inline"><semantics> <msub> <mi mathvariant="normal">w</mi> <mrow> <mi>S</mi> <mn>1</mn> </mrow> </msub> </semantics></math>, from L2OCN products of internal points of the Curonian lagoon. Wind data showed are from 1 of May 2019 and 30 of June 2019, when no scum events were observed. The condition WR &lt; 0.1, which sets empirically a “scum” alert, is colored in red (<math display="inline"><semantics> <mrow> <msup> <mi>R</mi> <mn>2</mn> </msup> <mo>=</mo> <mn>0.72</mn> </mrow> </semantics></math>, rmse = 1.7589); (<b>b</b>) Attenuation of the backscattering for WR = 0.1 as a function of the incidence angle <math display="inline"><semantics> <mi>θ</mi> </semantics></math>. For data showed in panel (<b>a</b>), <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>∈</mo> </mrow> </semantics></math> [30°, 46°]. Effect of wind direction <math display="inline"><semantics> <mi>ϕ</mi> </semantics></math> is also showed, where <math display="inline"><semantics> <mrow> <mi>ϕ</mi> <mo>=</mo> </mrow> </semantics></math> 0° corresponds to wind blowing towards the radar.</p> Full article ">Figure 3
<p>Qualitative comparison between optical and radar products for single day acquisitions: Chl-a maps concentration derived from S3 (<b>a</b>,<b>e</b>) and from S2 (<b>b</b>,<b>f</b>); WR index maps from S1 (<b>c</b>,<b>g</b>); Top panels show results of 28 August 2018, bottom panels show results of 10 October 2018. (<b>d</b>,<b>h</b>) report wind vector spatiotemporal evolution during the time interval between acquisitions. Wind vector come from ERA5 hourly data on single levels reanalysis database.</p> Full article ">Figure 4
<p>Qualitative comparison between S3 and S1 products for single day acquisitions: Chl-a maps concentration derived from S3 (<b>a</b>,<b>e</b>) and WR index maps from S1 (<b>b</b>,<b>d</b>); Top panels show results of the 17 August 2018, bottom panels show results of the 17 October 2018. Panels (<b>c</b>,<b>f</b>) report wind vector spatio-temporal evolution during the time interval between acquisitions. Wind vector come from ERA5 hourly data on single levels reanalysis database.</p> Full article ">Figure 5
<p>Qualitative comparison between S2 and S1 products for single day acquisitions: Chl-a maps concentration derived from S2 (<b>a</b>,<b>e</b>) and WR index maps from S1 (<b>b</b>,<b>d</b>); Top panels show results of the 9 September 2018, bottom panels show results of the 18 October 2018; Panels (<b>c</b>,<b>f</b>) report wind vector spatio-temporal evolution during the time interval between acquisitions. Wind vector come from ERA5 hourly data on single levels reanalysis database.</p> Full article ">Figure 6
<p>Temporal trends of WR (red bars), Chl-a concentrations (black bars) and Total Precipitation (TP) (gray bars) from July to October 2018. Images with Chl-a <math display="inline"><semantics> <mrow> <mo>&lt;</mo> <mn>72</mn> <mspace width="3.33333pt"/> <mrow> <mi>mg</mi> <mo>/</mo> <msup> <mi mathvariant="normal">m</mi> <mn>3</mn> </msup> </mrow> </mrow> </semantics></math> or <math display="inline"><semantics> <mrow> <mi>WR</mi> <mo>&gt;</mo> <mn>0.1</mn> </mrow> </semantics></math> in all the domain are classified as “No BAD” [<a href="#B43-jmse-07-00461" class="html-bibr">43</a>]. Total Precipitation, indicated as a grey background when positive, come from ERA5 hourly data on single level reanalysis database and when is greater than zero is indicated as gray background. Temporal scheme is explained in the insert on the left.</p> Full article ">
14 pages, 303 KiB  
Article
Prospects for Genetic Improvement in Objective Measurements of Body Colour in Pacific Whiteleg Shrimp (Litopenaeus vannamei)
by Cao Truong Giang, Wayne Knibb, Tran The Muu, Nguyen Huu Ninh and Nguyen Hong Nguyen
J. Mar. Sci. Eng. 2019, 7(12), 460; https://doi.org/10.3390/jmse7120460 - 14 Dec 2019
Cited by 10 | Viewed by 3287
Abstract
Body colour, together with growth and survival, are traits of commercial importance in Pacific whiteleg shrimp (Litopenaeus vannamei). However, heritability estimates for objective measurements of body colour are not available in Whiteleg shrimp species, including L. vannamei. Further, the effect [...] Read more.
Body colour, together with growth and survival, are traits of commercial importance in Pacific whiteleg shrimp (Litopenaeus vannamei). However, heritability estimates for objective measurements of body colour are not available in Whiteleg shrimp species, including L. vannamei. Further, the effect of genotype by environment interactions (G × E) on this trait (i.e., the objective measures of body colour) and its genetic associations with growth are not known in this species. The present study presented the first attempt at understanding the genetic architecture of this complex character (body colour) that is of economic significance to the shrimp aquaculture sector world-wide. Specifically, we investigated the quantitative genetic basis of shrimp colour, while using the measurement tool (colorimeter) for a Whiteleg shrimp population reared in two contrasting environments. A total of 5464 shrimp had the objective measurements of body colour (lightness, yellowness, and redness) and growth trait records (weight, length and width). They were the offspring of 204 dams and 197 sires. The restricted maximum likelihood mixed model analysis showed that there were heritable additive genetic components for all of the measurements of shrimp colour, with the heritability (h2) ranging from 0.11–0.55. The h2 estimates for redness and yellowness traits differed between the two environments (h2 = 0.66–0.82 in Khanhhoa vs. 0.00–0.03 in Haiphong). However, the heritability for colour traits was moderate (0.11–0.55) when the two environments were combined. There is existence of (co)-genetic variances between the studied traits. The genetic correlations of body traits with redness or yellowness colour of the shrimp were moderate and positive (a*: 0.13–0.32 for redness and b*: 0.19–0.40 for yellowness). The effect of G × E interactions on shrimp colours could be important, as the genetic correlations for these traits between the two environments were low (−0.41 to 0.16). Our results showed that the genetic improvement for body colour can be achieved through direct selection and the increased redness colour is also expected to have favorable impacts on growth traits. Breeding programs to improve shrimp colour should account for the effects of environmental factors. Full article
(This article belongs to the Special Issue Genomic Prediction and Functional Genomics in Aquaculture)
15 pages, 9591 KiB  
Article
Automatic Shoreline Detection from Eight-Band VHR Satellite Imagery
by Maria Alicandro, Valerio Baiocchi, Raffaella Brigante and Fabio Radicioni
J. Mar. Sci. Eng. 2019, 7(12), 459; https://doi.org/10.3390/jmse7120459 - 13 Dec 2019
Cited by 11 | Viewed by 3824
Abstract
Coastal erosion, which is naturally present in many areas of the world, can be significantly increased by factors such as the reduced transport of sediments as a result of hydraulic works carried out to minimize flooding. Erosion has a significant impact on both [...] Read more.
Coastal erosion, which is naturally present in many areas of the world, can be significantly increased by factors such as the reduced transport of sediments as a result of hydraulic works carried out to minimize flooding. Erosion has a significant impact on both marine ecosystems and human activities; for this reason, several international projects have been developed to study monitoring techniques and propose operational methodologies. The increasing number of available high-resolution satellite platforms (i.e., Copernicus Sentinel) and algorithms to treat them allows the study of original approaches for the monitoring of the land in general and for the study of the coastline in particular. The present project aims to define a methodology for identifying the instantaneous shoreline, through images acquired from the WorldView 2 satellite, on eight spectral bands, with a geometric resolution of 0.5 m for the panchromatic image and 1.8 m for the multispectral one. A pixel-based classification methodology is used to identify the various types of land cover and to make combinations between the eight available bands. The experiments were carried out on a coastal area with contrasting morphologies. The eight bands in which the images are taken produce good results both in the classification process and in the combination of the bands, through the algorithms of normalized difference vegetation index (NDVI), normalized difference water index (NDWI), spectral angle mapper (SAM), and matched filtering (MF), with regard to the identification of the various soil coverings and, in particular, the separation line between dry and wet sand. In addition, the real applicability of an algorithm that extracts bathymetry in shallow water using the “coastal blue” band was tested. These data refer to the instantaneous shoreline and could be corrected in the future with morphological and tidal data of the coastal areas under study. Full article
(This article belongs to the Special Issue Remote Sensing in Coastline Detection)
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<p>Indicators of the coastline.</p> Full article ">Figure 2
<p>WorldView-2 spectral bands.</p> Full article ">Figure 3
<p>The test site area on the Adriatic coast (red circle).</p> Full article ">Figure 4
<p>Test site area: the yellow box is the area shown in the following figures.</p> Full article ">Figure 5
<p>Some band combinations: (<b>a</b>) NIR1-G-B; (<b>b</b>) NIR1-Rededge-R; (<b>c</b>) R-G-B; (<b>d</b>) Rededge-R-Y.</p> Full article ">Figure 6
<p>The pansharpening process: (<b>a</b>) MultiSpectral; (<b>b</b>) Panchromatic; (<b>c</b>) PanSharpened.</p> Full article ">Figure 7
<p>(<b>a</b>) Normalized difference vegetation index (NDVI) and (<b>b</b>) normalized difference water index (NDWI) processed images in gray scale.</p> Full article ">Figure 8
<p>NE to SW NDVI profile path on (<b>a</b>) RGB and (<b>b</b>) NDVI processed images; (<b>c</b>) NE to SW NDVI profile, distances on the x-axis are expressed in metres. The profile trend shows sharp discontinuities at sea/land limits.</p> Full article ">Figure 9
<p>NE to SW matched filtering (MF) muddy profile path on (<b>a</b>) RGB and (<b>b</b>) MF muddy processed images; (<b>c</b>) NE to SW MF muddy profile, distances on the x-axis are expressed in metres. The profile trend does not show sharp discontinuities at sea/land limits.</p> Full article ">Figure 10
<p>NE to SW MF/spectral angle mapper (SAM) profile path on (<b>a</b>) RGB and (<b>b</b>) MF/SAM processed images; (<b>c</b>) NE to SW MF/SAM profile, distances on the x-axis are expressed in metres. The profile trend shows visible discontinuities at sea/land limits.</p> Full article ">Figure 11
<p>Relative depth algorithm results represented in (<b>a</b>) gray and (<b>b</b>) pseudocolor scales.</p> Full article ">Figure 12
<p>NE to SW relative depth profile path on (<b>a</b>) RGB and (<b>b</b>) relative depth processed images; (<b>c</b>) NE to SW relative depth profile, distances on the x-axis are expressed in metres. The profile trend shows almost vertical discontinuities at sea/land limits.</p> Full article ">Figure 13
<p>Comparison of the different algorithms on the same profile, black dashed lines are the actual water/ground limits (distances in the <span class="html-italic">x</span> direction are in meters along the profile, values in the <span class="html-italic">y</span> direction are reported for every specific algorithm so are not directly comparable).</p> Full article ">Figure 14
<p>Detail of relative depth algorithm results using coastal blue band; on (<b>a</b>) the profile trac, on (<b>b</b>) the resulting profile were open water is on the right, distances in the x direction are in meters along the profile.</p> Full article ">Figure 15
<p>“Absolute depth” profile: along the <span class="html-italic">y</span> direction is the absolute depth and along the <span class="html-italic">x</span> direction is the progressive distance; all distances are in meters and open water is on the right.</p> Full article ">Figure 16
<p>“Absolute depth” bathymetric lines; open water is on the right.</p> Full article ">Figure 17
<p>Detail of a vegetated area on RGB image on (<b>a</b>) and corresponding classification classes on (<b>b</b>).</p> Full article ">Figure 18
<p>(<b>a</b>) Pansharpened image; (<b>b</b>) classified image; (<b>c</b>) classes legend.</p> Full article ">
22 pages, 8638 KiB  
Article
Estimation of a Mechanical Recovery System’s Oil Recovery Capacity by Considering Boom Loss
by Hyeonuk Kim, Yunseon Choe and Cheol Huh
J. Mar. Sci. Eng. 2019, 7(12), 458; https://doi.org/10.3390/jmse7120458 - 13 Dec 2019
Cited by 7 | Viewed by 3245
Abstract
Ability to estimate the recovery potential of countermeasures is vital in establishing a rational response solution for oil spills at sea. This requires estimation of how much oil can be recovered and the determination of the rational quantities and operating conditions of the [...] Read more.
Ability to estimate the recovery potential of countermeasures is vital in establishing a rational response solution for oil spills at sea. This requires estimation of how much oil can be recovered and the determination of the rational quantities and operating conditions of the response equipment. In this study, a constant loss rate model and a variable loss rate model were developed to estimate the recovery potential of a mechanical oil recovery system, while considering the escape of oil containment booms. The latter model could calculate the speed at which oil loss began to occur and the volume of oil lost. A case study was performed to analyze the significance of oil loss and to calculate changes in recovery potential with respect to adjustable vital variables. The developed model was able to estimate the best operating situation, which optimizes the recovery potential for different response times and environmental conditions. Full article
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<p>Schematic of the mechanical recovery system.</p> Full article ">Figure 2
<p>Schematic of the developed model for estimating the recovery potential (variable loss rate model).</p> Full article ">Figure 3
<p>Calculation procedure for quantifying boom loss.</p> Full article ">Figure 4
<p>Comparison of predicted first loss speed to measured entrainment loss speed, based on Equation (6) and the measured entrainment loss speed of Schulze [<a href="#B21-jmse-07-00458" class="html-bibr">21</a>].</p> Full article ">Figure 5
<p>Critical loss speed according to the B/W ratio and wave steepness.</p> Full article ">Figure 6
<p>Loss rate per preload volume (<span class="html-italic">q<sub>loss</sub>/V<sup>2/3</sup></span>) according to the draft of the oil boom and the difference between the tow speed and the first loss speed.</p> Full article ">Figure 7
<p>Wave steepness variation of three environmental cases with time.</p> Full article ">Figure 8
<p>Wind speed variation of three environmental cases with time.</p> Full article ">Figure 9
<p>First loss speed of boom B (<a href="#jmse-07-00458-t001" class="html-table">Table 1</a>) with spilled time: regular, calm, and harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 10
<p>Encounter rate and loss rate for constant tow speed (0.5 knots) by applying boom B (<a href="#jmse-07-00458-t001" class="html-table">Table 1</a>) over spilled time: regular, calm, and harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 11
<p>Throughput efficiency for constant tow speed (0.5 knots) applying boom B (<a href="#jmse-07-00458-t001" class="html-table">Table 1</a>) over spilled time: regular, calm, and harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 12
<p>Emulsion recovery rate (<span class="html-italic">ERR</span>)for a constant tow speed (0.5 knots) and proposed tow speed (<span class="html-italic">U<sub>1st</sub></span>) applying boom B (<a href="#jmse-07-00458-t001" class="html-table">Table 1</a>) over spilled time: regular, calm, and harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 13
<p>Total collected volume comparison with a constant tow speed (0.5 knots) and proposed tow speed (<span class="html-italic">U<sub>1st</sub></span>) applying boom B (<a href="#jmse-07-00458-t001" class="html-table">Table 1</a>) for three days: regular, calm, and harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 14
<p>Total collected volume (<b>a</b>) and total lost volume (<b>b</b>) depending on constant tow speed applying boom B (<a href="#jmse-07-00458-t001" class="html-table">Table 1</a>) for recovery days in a calm case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 15
<p>Critical loss speed with a different boom type at a constant tow speed (0.5 knots) over spilled time: regular, calm, and harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 16
<p>Loss fraction with a different boom type at a constant tow speed (0.5 knots) over spilled time: regular, calm, and harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 17
<p>Comparison of total collected and lost oil volumes at a constant tow speed (0.5 knots) in the harbor chop case (<a href="#jmse-07-00458-t002" class="html-table">Table 2</a>) over three days for booms A, B, and C (<a href="#jmse-07-00458-t001" class="html-table">Table 1</a>).</p> Full article ">Figure 18
<p>Comparison of the total volume of oil collected and effective time of collection using the variable loss rate model with a constant tow speed (calculation result by case 2 in <a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">Figure 19
<p>Comparison of the total volume of oil collected and effective time of collection using a constant loss rate model with a constant tow speed (calculation result by case 2 in <a href="#jmse-07-00458-t002" class="html-table">Table 2</a>).</p> Full article ">
11 pages, 1048 KiB  
Article
Calculation of the Mass Transfer Coefficient for the Dissolution of Multiple Carbon Dioxide Bubbles in Sea Water under Varying Conditions
by Hee-Joo Cho and Jungho Choi
J. Mar. Sci. Eng. 2019, 7(12), 457; https://doi.org/10.3390/jmse7120457 - 13 Dec 2019
Cited by 5 | Viewed by 6998
Abstract
Underwater weapon systems with reforming fuel cells have been developed to increase the number of possible days that the former can be submerged. Reforming hydrocarbons generate a large quantity of carbon dioxide gas that must be completely dissolved in water and released. In [...] Read more.
Underwater weapon systems with reforming fuel cells have been developed to increase the number of possible days that the former can be submerged. Reforming hydrocarbons generate a large quantity of carbon dioxide gas that must be completely dissolved in water and released. In this study, the mass transfer coefficient was derived experimentally while changing the process variables that affect mass transfer, such as bubble size, presence/absence of an inline mixer, retention time, pressure, and solvent type. It was found that retention time was most affected, followed by type of solvent, presence/absence of the inline mixer, and bubble size. In addition, by reducing bubble size and retention time and applying an inline mixer, the effect can be like that dissolved at high pressure even at low pressure. Applications of this study are expected to reduce the size of underwater weapon systems. Therefore, further studies on increasing the power consumption of underwater weapon systems due to reduction of bubble size and the application of inline mixers should be conducted. Full article
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<p>CO<sub>2</sub> injection and separation system process flow diagram (PFD).</p> Full article ">Figure 2
<p>Experimental variables: (<b>a</b>) porous filter, (<b>b</b>) inline mixer, (<b>c</b>) pipes.</p> Full article ">Figure 3
<p>Comparison of mass transfer coefficients by bubble size.</p> Full article ">Figure 4
<p>Comparison of mass transfer coefficients by turbulence intensity.</p> Full article ">Figure 5
<p>Comparison of mass transfer coefficients by retention time.</p> Full article ">Figure 6
<p>Comparison of dissolution by retention time.</p> Full article ">Figure 7
<p>Comparison of mass transfer coefficients by solvent.</p> Full article ">
24 pages, 9210 KiB  
Article
Experimental and Numerical Investigation of Self-Burial Mechanism of Pipeline with Spoiler under Steady Flow Conditions
by Woo-Dong Lee, Hyo-Jae Jo, Han-Sol Kim, Min-Jun Kang, Kwang-Hyo Jung and Dong-Soo Hur
J. Mar. Sci. Eng. 2019, 7(12), 456; https://doi.org/10.3390/jmse7120456 - 12 Dec 2019
Cited by 11 | Viewed by 3661
Abstract
Herein, hydraulic model experiments and numerical simulations were performed to understand the self-burial mechanism of subsea pipelines with spoilers under steady flow conditions. First, scour characteristics and self-burial functions according to the spoiler length-to-pipe diameter ratio (S/D) were investigated through hydraulic [...] Read more.
Herein, hydraulic model experiments and numerical simulations were performed to understand the self-burial mechanism of subsea pipelines with spoilers under steady flow conditions. First, scour characteristics and self-burial functions according to the spoiler length-to-pipe diameter ratio (S/D) were investigated through hydraulic experiments. Further, the Navier–Stokes solver was verified. The experimental values of the velocity at the bottom of the pipeline with a spoiler and the pressure on the sand foundation where the pipeline rested were represented with the degree of conformity. Scour characteristics of a sand foundation were investigated from the numerical analysis results of the velocity and vorticity surrounding the pipelines with spoilers. The compilation of results from the hydraulic experiment and numerical analysis showed that the projected area increased when a spoiler was attached to the subsea pipes. This consequently increased the velocity of fluid leaving the top and bottom of the pipe, and high vorticity was formed within and above the sand foundation. This aggravated scouring at the pipe base and increased the top and bottom asymmetry of the dynamic pressure field, which developed a downward force on the pipeline. These two primary effects acting simultaneously under steady flow conditions explained the self-burial of pipelines with a spoiler attachment. Full article
(This article belongs to the Special Issue Numerical Models in Coastal Hazards and Coastal Environment)
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<p>Concept sketch of structural risks of the subsea pipeline by local scour.</p> Full article ">Figure 2
<p>Schematic of water tank including pipeline with spoiler, set up for laboratory experiments.</p> Full article ">Figure 3
<p>Arrangement of spoiler on pipeline: (<b>a</b>) No spoiler, (<b>b</b>) <span class="html-italic">S/D</span> = 0.3, (<b>c</b>) <span class="html-italic">S/D</span> = 0.5.</p> Full article ">Figure 4
<p>Measured points of acoustic Doppler velocimeter (ADV) for determining incident flow velocity: (<b>a</b>) side view, (<b>b</b>) plan view.</p> Full article ">Figure 5
<p>Comparison of scour depths under fixed-pipeline in time domain. The black circle is Run-1 with no spoiler; the blue square is Run-2 with a spoiler length to pipe diameter ratio (<span class="html-italic">S</span>/<span class="html-italic">D</span>) of 0.3; and the red triangle is Run-3 with an <span class="html-italic">S</span>/<span class="html-italic">D</span> of 0.5.</p> Full article ">Figure 6
<p>Equilibrium profiles of sandy bed under steady flow in case of fixed-pipeline: (<b>a</b>) Run-1 (no spoiler), (<b>b</b>) Run-2 (<span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.3), (<b>c</b>) Run-3 (<span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.5). The yellow circle represents the cross section of the subsea pipeline, the black grid sizes are 1 cm (L) × 1 cm (H), and the mint-colored grid sizes are 10 cm (L) × 10 cm (H).</p> Full article ">Figure 7
<p>Comparison of burial depth of free-pipeline in time domain. The black dot represents Run-1 with no spoiler, the blue square represents Run-2 with a spoiler length to pipe diameter ratio of 0.3, and the red triangle represents Run-3 with an <span class="html-italic">S</span>/<span class="html-italic">D</span> of 0.5.</p> Full article ">Figure 8
<p>Equilibrium profiles of seabed under steady flow in case of free-pipeline: (<b>a</b>) Run-1 (no spoiler), (<b>b</b>) Run-2 (<span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.3), (<b>c</b>) Run-3 (<span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.5). The yellow circle is the subsea pipeline cross-section, the black grid sizes are 1 cm × 1 cm, and the mint-colored grid sizes are 10 cm × 10 cm.</p> Full article ">Figure 9
<p>Spatial distribution of bed elevations and location of pipeline in equilibrium state: (<b>a</b>) Run-1 (no spoiler), (<b>b</b>) Run-2 (<span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.3), (<b>c</b>) Run-3 (<span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.5).</p> Full article ">Figure 10
<p>Definition sketch of the numerical water tank (NWT) based on the experiment water tank [<a href="#B21-jmse-07-00456" class="html-bibr">21</a>].</p> Full article ">Figure 11
<p>Measured sections of velocities under pipeline.</p> Full article ">Figure 12
<p>Comparison between measured [<a href="#B21-jmse-07-00456" class="html-bibr">21</a>] and calculated time-averaged velocities under the pipeline without a spoiler. The markers represent the experimental results and the solid line represents the calculated results. The circles are the horizontal velocities; the diamonds are the vertical velocities. The error bars have an error range of ± 10%.</p> Full article ">Figure 13
<p>Comparison between measured [<a href="#B21-jmse-07-00456" class="html-bibr">21</a>] and calculated time-averaged velocities under the pipeline with a spoiler.</p> Full article ">Figure 14
<p>Definition sketch of analysis zone in NWT based on the experimental water tank [<a href="#B41-jmse-07-00456" class="html-bibr">41</a>].</p> Full article ">Figure 15
<p>Comparison between measured and calculated time-averaged pressures on a sandy bed. The red circle represents values measured by Yang et al. [<a href="#B41-jmse-07-00456" class="html-bibr">41</a>] and the black solid line represents the numerically calculated values. The error bars have an error range of ± 10%.</p> Full article ">Figure 16
<p>Statistical comparisons between measured and calculated values: (<b>a</b>) pressures on sandy bed, (<b>b</b>) horizontal velocity under pipeline, (<b>c</b>) vertical velocity under pipeline. The solid line shows the trend line, and the dotted line area indicates within error range of ± 10%. The blue circle shows the case with no spoiler, the red triangle shows the case with <span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.2. RMSE, root mean square error; NRMSE, normalized RMSE.</p> Full article ">Figure 17
<p>Definition sketch of NWT based on laboratory experiments.</p> Full article ">Figure 18
<p>Spatial distributions of (<b>a</b>) depth-averaged velocities and (<b>b</b>) velocities, water surface elevations, and turbulent kinetic energy at steady state in NWT without a pipeline. The colors grow redder when <math display="inline"><semantics> <mi>K</mi> </semantics></math> increase.</p> Full article ">Figure 19
<p>Spatial distributions of (<b>a</b>) vorticities and (<b>b</b>) dynamic pressures at steady state in NWT without a pipeline. Blue tones represent clockwise vortex and negative pressure distribution; red tones represent anti-clockwise vortex and positive pressure distribution.</p> Full article ">Figure 20
<p>Spatial distributions of pattern-averaged velocities and vorticities around pipeline without a spoiler: (<b>a</b>) <span class="html-italic">t</span> = 0 s (initial condition), (<b>b</b>) <span class="html-italic">t</span> = 15 s (in the process of scouring), (<b>c</b>) <span class="html-italic">t</span> = 120 s (in the process of scouring), (<b>d</b>) <span class="html-italic">t</span> = 2400 s (equilibrium state). Blue tones represent clockwise vortex; red tones represent anti-clockwise vortex.</p> Full article ">Figure 21
<p>Spatial distributions of pattern-averaged velocities and vorticities around pipeline with a spoiler in the case of <span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.3: (<b>a</b>) <span class="html-italic">t</span> = 0 s (initial condition), (<b>b</b>) <span class="html-italic">t</span> = 15 s (in the process of scouring), (<b>c</b>) <span class="html-italic">t</span> = 120 s (in the process of scouring), (<b>d</b>) <span class="html-italic">t</span> = 2400 s (equilibrium state).</p> Full article ">Figure 22
<p>Comparison of spatial averaged vorticities owing to <span class="html-italic">S</span>/<span class="html-italic">D</span> in front and rear side under pipeline. The lateral axis is the ratio of spoiler length to pipe diameter (<span class="html-italic">S</span>/<span class="html-italic">D</span>) and the longitudinal axis is the spatial-average vortex (<math display="inline"><semantics> <mrow> <msub> <mover accent="true"> <mi>ω</mi> <mo stretchy="false">¯</mo> </mover> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math>). The circle is the front, and the triangle is the rear end average vorticity.</p> Full article ">Figure 23
<p>Estimated domains under pipeline for spatial averaged vorticity: (<b>a</b>) Rear side, (<b>b</b>) Front side.</p> Full article ">Figure 24
<p>Spatial distributions of pattern-averaged dynamic pressures around the pipeline without a spoiler: (<b>a</b>) <span class="html-italic">t</span> = 0 s (initial condition), (<b>b</b>) <span class="html-italic">t</span> = 15 s (in the process of scouring), (<b>c</b>) <span class="html-italic">t</span> = 120 s (in the process of scouring), (<b>d</b>) <span class="html-italic">t</span> = 2400 s (equilibrium state). Blue tones represent negative pressure distribution and red tones represent positive pressure distribution.</p> Full article ">Figure 24 Cont.
<p>Spatial distributions of pattern-averaged dynamic pressures around the pipeline without a spoiler: (<b>a</b>) <span class="html-italic">t</span> = 0 s (initial condition), (<b>b</b>) <span class="html-italic">t</span> = 15 s (in the process of scouring), (<b>c</b>) <span class="html-italic">t</span> = 120 s (in the process of scouring), (<b>d</b>) <span class="html-italic">t</span> = 2400 s (equilibrium state). Blue tones represent negative pressure distribution and red tones represent positive pressure distribution.</p> Full article ">Figure 25
<p>Spatial distributions of pattern-averaged dynamic pressures around the pipeline with a spoiler where <span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.3: (<b>a</b>) <span class="html-italic">t</span> = 0 s (initial condition), (<b>b</b>) <span class="html-italic">t</span> = 15 s (in the process of scouring), (<b>c</b>) <span class="html-italic">t</span> = 120 s (in the process of scouring), (<b>d</b>) <span class="html-italic">t</span> = 2400 s (equilibrium state).</p> Full article ">Figure 25 Cont.
<p>Spatial distributions of pattern-averaged dynamic pressures around the pipeline with a spoiler where <span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.3: (<b>a</b>) <span class="html-italic">t</span> = 0 s (initial condition), (<b>b</b>) <span class="html-italic">t</span> = 15 s (in the process of scouring), (<b>c</b>) <span class="html-italic">t</span> = 120 s (in the process of scouring), (<b>d</b>) <span class="html-italic">t</span> = 2400 s (equilibrium state).</p> Full article ">Figure 26
<p>Comparison of fluid force due to <span class="html-italic">S</span>/<span class="html-italic">D</span> at the pipeline: (<b>a</b>) horizontal force (<math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>x</mi> </msub> </mrow> </semantics></math>), (<b>b</b>) vertical force (<math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mi>z</mi> </msub> </mrow> </semantics></math>). The black solid line shows the case with no spoiler, the blue circle shows the case with <span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.3, and the red triangle shows the case with <span class="html-italic">S</span>/<span class="html-italic">D</span> = 0.5.</p> Full article ">Figure 27
<p>Comparison of mean force due to <span class="html-italic">S</span>/<span class="html-italic">D</span> at the pipeline. The black circle represents the mean horizontal force (<math display="inline"><semantics> <mrow> <msub> <mi>F</mi> <mi>x</mi> </msub> </mrow> </semantics></math>) and the red inverted triangle represents the vertical force (<math display="inline"><semantics> <mrow> <msub> <mi>F</mi> <mi>z</mi> </msub> </mrow> </semantics></math>).</p> Full article ">
20 pages, 12820 KiB  
Article
The Effect of Rudder Existence on Propeller Eccentric Force
by Gisu Song, Hyounggil Park and Taegoo Lee
J. Mar. Sci. Eng. 2019, 7(12), 455; https://doi.org/10.3390/jmse7120455 - 12 Dec 2019
Cited by 8 | Viewed by 3495
Abstract
In order to design a safe shafting system in a ship, it is vital to precisely predict load on stern tube bearing. It is well known that load on stern tube bearing is directly influenced by the eccentric force of a propeller. In [...] Read more.
In order to design a safe shafting system in a ship, it is vital to precisely predict load on stern tube bearing. It is well known that load on stern tube bearing is directly influenced by the eccentric force of a propeller. In this paper, the effect of rudder existence on propeller eccentric force was studied based on numerical analysis with a 10,000 TEU class container vessel. To obtain propeller eccentric force, numerical simulations including propeller rotation motion using a sliding mesh technique were carried out. When a ship is turning, propeller eccentric force significantly changes compared to those of straight run. For starboard turning especially, the propeller vertical moment was decreased by about 50% due to the existence of a rudder compared to that without a rudder. In contrast, as for port turning, the results of simulations with and without a rudder were similar to each other. This difference is fundamentally due to the interaction between the direction of propeller rotation and the inflow direction to a propeller. Based on this study, it is inferred that the influence of appendages around a propeller need to be considered to ensure the reliable prediction of propeller eccentric force. Full article
(This article belongs to the Special Issue Selected Papers from the Sixth International Symposium on Marine Propulsors)
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<p>The target vessel.</p> Full article ">Figure 2
<p>Computational domain (side view and front view).</p> Full article ">Figure 3
<p>Boundary conditions.</p> Full article ">Figure 4
<p>Grid system for the resistance simulation.</p> Full article ">Figure 5
<p>Time history of the resistance at the model scale (Rtm) at 23Kn.</p> Full article ">Figure 6
<p>The difference of effective horsepower (EHP) between the model test and the CFD simulation at various ship speeds.</p> Full article ">Figure 7
<p>Wave pattern around Aft-hull at 24Kn in the (<b>a</b>) model test; (<b>b</b>) CFD simulation.</p> Full article ">Figure 8
<p>Ranges of wall y+ values at 23Kn ship speed in resistance test (<b>a</b>) side view; (<b>b</b>) bottom view.</p> Full article ">Figure 9
<p>Computational domain (side view and front view).</p> Full article ">Figure 10
<p>Boundary conditions for POW simulation.</p> Full article ">Figure 11
<p>Grid system for POW simulation.</p> Full article ">Figure 12
<p>Comparison of K<sub>T</sub>, 10 K<sub>Q</sub> and EtaO from the model test and the CFD simulation at various advance ratios (J).</p> Full article ">Figure 13
<p>Reproduced from [<a href="#B4-jmse-07-00455" class="html-bibr">4</a>], with permission from Mitsubishi Heavy Industries, Ltd., 2007.</p> Full article ">Figure 14
<p>Ship motion during the turning circle test (starboard turning) in the sea trial.</p> Full article ">Figure 15
<p>Ship motion during the turning circle test (port turning) in the sea trial.</p> Full article ">Figure 16
<p>Asymmetric rudder configurations (<b>a</b>) Side view; (<b>b</b>) three-dimensional (3D) view.</p> Full article ">Figure 17
<p>The coordinate system for propeller lateral forces and moments.</p> Full article ">Figure 18
<p>Nominal wake distribution. (<b>a</b>) Measurement; (<b>b</b>) simulation without rudder; (<b>c</b>) simulation with rudder.</p> Full article ">Figure 19
<p>Instantaneous normalized pressure distribution on the propeller face side (looking upstream) during the straight run (<b>a</b>) without a rudder; (<b>b</b>) with a rudder.</p> Full article ">Figure 20
<p>Propeller lateral force and moment during the starboard turn (without rudder).</p> Full article ">Figure 21
<p>Propeller lateral force and moment during the starboard turn (with rudder).</p> Full article ">Figure 22
<p>Propeller lateral force and moment during the port turn (without rudder).</p> Full article ">Figure 23
<p>Propeller lateral force and moment during the port turn (with rudder).</p> Full article ">Figure 24
<p>The rudder effect on the propeller’s lateral moment during the straight run or the turning motion.</p> Full article ">Figure 25
<p>Instantaneous normalized pressure distribution on the propeller face side without rudder during starboard turning (<b>a</b>) At yaw rate max.; (<b>b</b>) at steady.</p> Full article ">Figure 26
<p>Instantaneous normalized pressure distribution on the propeller face side with rudder during starboard turning (<b>a</b>) At yaw rate max.; (<b>b</b>) at steady.</p> Full article ">Figure 27
<p>Instantaneous normalized pressure distributions on a plane at three different heights during starboard turning at yaw rate max. status (<b>a</b>) without rudder; (<b>b</b>) with rudder.</p> Full article ">Figure 28
<p>Instantaneous normalized pressure distribution on the propeller face side without rudder during port turning (<b>a</b>) At yaw rate max.; (<b>b</b>) at steady.</p> Full article ">Figure 29
<p>Instantaneous normalized pressure distribution on the propeller face side with rudder during port turning (<b>a</b>) at yaw rate max.; (<b>b</b>) at steady.</p> Full article ">Figure 30
<p>Instantaneous normalized pressure distributions on a plane at three different heights during port turning at yaw rate max. status (<b>a</b>) without a rudder; (<b>b</b>) with a rudder.</p> Full article ">Figure 31
<p>Instantaneous normalized pressure distributions on a rudder during starboard turning (<b>a</b>) At yaw rate max. (<b>b</b>) at steady (looking downstream).</p> Full article ">Figure 32
<p>Instantaneous normalized pressure distributions on a rudder during port turning. (<b>a</b>) At yaw rate max., (<b>b</b>) at steady turning (looking downstream).</p> Full article ">
19 pages, 8871 KiB  
Article
Numerical Investigation on Vortex-Induced Vibration Suppression of a Circular Cylinder with Axial-Slats
by Wei Wang, Zhaoyong Mao, Wenlong Tian and Tingying Zhang
J. Mar. Sci. Eng. 2019, 7(12), 454; https://doi.org/10.3390/jmse7120454 - 11 Dec 2019
Cited by 13 | Viewed by 4213
Abstract
The vortex-induced vibration (VIV) suppression of a circular cylinder with the axial-slats is numerically investigated using the computational fluid dynamics (CFD) method for Reynolds number range of 8.0 × 103–5.6 × 104. The two-dimensional unsteady Reynolds averaged Navier–Stokes (RANS) [...] Read more.
The vortex-induced vibration (VIV) suppression of a circular cylinder with the axial-slats is numerically investigated using the computational fluid dynamics (CFD) method for Reynolds number range of 8.0 × 103–5.6 × 104. The two-dimensional unsteady Reynolds averaged Navier–Stokes (RANS) equations and Shear-Stress-Transport (SST) turbulence model are used to calculate the flow around the cylinder in ANSYS Fluent. The Newmark-β method is used to evaluate structural dynamics. The amplitude response, frequency response and vortex pattern are discussed. The suppression effect of the axial-slats is the best when the gap ratio is 0.10 and the coverage ratio is 30%. Based on the VIV response, the whole VIV response region is divided into four regions (Region I, Region II, Region III and Region IV). The frequency ratio of isolated cylinder jumps between region II and region III. However, the frequency ratio jumps between region I and region II for a cylinder with the axial-slats. The axial-slats destroy the original vortex and make the vortex easier to separate. The online amplitude ratio is almost completely suppressed, and the cross-flow amplitude ratio is significantly suppressed. Full article
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<p>(<b>a</b>) The 2-degrees of freedom (DOF) vortex-induced vibration (VIV) system and (<b>b</b>) a main cylinder with axial-slats (N = 4).</p> Full article ">Figure 2
<p>The process of the numerical simulation</p> Full article ">Figure 3
<p>The computational domain.</p> Full article ">Figure 4
<p>Mesh (M5, <span class="html-italic">ε</span> = 60% and δ = 0.15 D): (<b>a</b>) mesh structure; (<b>b</b>) mesh around the cylinder and (<b>c</b>) the boundary layer mesh.</p> Full article ">Figure 5
<p>Numerical model validation: (<b>a</b>) comparisons of amplitude responses and (<b>b</b>) comparisons of frequency responses.</p> Full article ">Figure 6
<p>The time histories of amplitude responses of a circular cylinder with different coverage ratios of axial-slats (Re = 2.8 × 10<sup>4</sup> and <span class="html-italic">δ</span> = 0.15).</p> Full article ">Figure 7
<p>The frequencies responses in cross-flow of a circular cylinder with different coverage ratio of axial-slats (Re = 2.8 × 10<sup>4</sup> and <span class="html-italic">δ</span> = 0.15).</p> Full article ">Figure 8
<p>The vorticity contours of a circular cylinder with a different coverage ratio of axial-slats at Re = 2.8 × 10<sup>4</sup> and <span class="html-italic">δ</span> = 0.15.</p> Full article ">Figure 9
<p>The time histories of amplitude responses of a circular cylinder with different gap ratio of axial-slats (Re = 2.8 × 10<sup>4</sup> and <span class="html-italic">ε</span> = 30%).</p> Full article ">Figure 10
<p>The cross-flow frequency responses of a circular cylinder with different gap ratios of axial-slats (Re = 2.8 × 10<sup>4</sup> and <span class="html-italic">ε</span> = 30%).</p> Full article ">Figure 11
<p>The vorticity contours of a circular cylinder with different gap ratios of axial-slats at Re = 2.8 × 10<sup>4</sup> and <span class="html-italic">ε</span> = 30%.</p> Full article ">Figure 12
<p>Comparisons of VIV responses of isolated cylinder and cylinder with axial-slats (<span class="html-italic">δ</span> = 0.10, <span class="html-italic">ε</span> = 30%).</p> Full article ">Figure 13
<p>The comparisons of VIV responses of isolated cylinder and cylinder with axial-slats (<span class="html-italic">δ</span> = 0.10, <span class="html-italic">ε</span> = 30%) at Ur = 4.0 (Re = 1.6 × 10<sup>4</sup>).</p> Full article ">Figure 14
<p>The comparisons of VIV responses of isolated cylinder and cylinder with axial-slats (<span class="html-italic">δ</span> = 0.10, <span class="html-italic">ε</span> = 30%) at Ur = 7.0 (Re = 2.8 × 10<sup>4</sup>).</p> Full article ">Figure 15
<p>The comparisons of VIV responses of isolated cylinder and cylinder with axial-slats (<span class="html-italic">δ</span> = 0.10, <span class="html-italic">ε</span> = 30%) at Ur = 10.0 (Re = 4.0 × 10<sup>4</sup>).</p> Full article ">Figure 16
<p>The comparisons of VIV responses of isolated cylinder and cylinder with axial-slats (<span class="html-italic">δ</span> = 0.10, <span class="html-italic">ε</span> = 30%) at Ur = 13.0 (Re = 5.2 × 10<sup>4</sup>).</p> Full article ">Figure 17
<p>Mean drag coefficient versus reduced velocity of isolated cylinder and cylinder with axial-slats (<span class="html-italic">δ</span> = 0.10, <span class="html-italic">ε</span> = 30%).</p> Full article ">
18 pages, 6048 KiB  
Article
Experimental and Numerical Analysis of the Hydrodynamics around a Vertical Cylinder in Waves
by Sara Corvaro, Andrea Crivellini, Francesco Marini, Andrea Cimarelli, Loris Capitanelli and Alessandro Mancinelli
J. Mar. Sci. Eng. 2019, 7(12), 453; https://doi.org/10.3390/jmse7120453 - 10 Dec 2019
Cited by 14 | Viewed by 3046
Abstract
The present study provides an extensive analysis on the hydrodynamics induced by a vertical slender pile under wave action. The authors carried out the study both experimentally and numerically, thus enabling a deep understanding of the flow physics. The experiments took place at [...] Read more.
The present study provides an extensive analysis on the hydrodynamics induced by a vertical slender pile under wave action. The authors carried out the study both experimentally and numerically, thus enabling a deep understanding of the flow physics. The experiments took place at a wave flume of the Università Politecnica delle Marche. Two different experimental campaigns were performed: In the former one, a mobile bed model was realized with the aims to study both the scour process and the hydrodynamics around the cylinder; in the latter one, the seabed was rigid in order to make undisturbed optical measurements, providing a deeper analysis of the hydrodynamics. The numerical investigation was made by performing a direct numerical simulation. A second order numerical discretization, both in time and in space, was used to solve the Navier–Stokes equations while a volume of fluid (VOF) approach was adopted for tracking the free surface. The comparison between experimental and numerical results is provided in terms of velocity, pressure distributions around the cylinder, and total force on it. The analysis of the pressure gradient was used to evaluate the generation and evolution of vortices around the cylinder. Finally, the relation between scour and bed shear stresses due to the structure of the vortex pattern around the pile was assessed. It is worth noting that the physical understanding of this last analysis was enabled by the combined use of experimental data on scour and numerical data on the flow pattern. Full article
(This article belongs to the Special Issue Selected Papers from Coastlab18 Conference)
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<p>Wave flume and location of the elevation gauges and of the cylinder (rigid-bed model).</p> Full article ">Figure 2
<p>Sketch of the rigid-bed model setup with the position of the elevation gauges S3, S4, S5, and of the acoustic Doppler velocimetry (ADV) at <span class="html-italic">φ</span> = 0° (<b>a</b>) and of the planar coordinate system, with the position of pressure sensors (<b>b</b>).</p> Full article ">Figure 3
<p>Numerical model domain (<b>a</b>) and detail of the mesh in the surroundings of the pile (<b>b</b>).</p> Full article ">Figure 4
<p>Force (<b>a</b>) and water level (<b>b</b>) comparisons in correspondence to the pile to evaluate the effectiveness of the numerical beach. Simulations 0 and 0a (continuous lines), 1 and 1a (dashed lines).</p> Full article ">Figure 5
<p>Comparison of the force over the pile (<b>a</b>) and the wet surface around it (<b>b</b>) among different mesh (1a–3a) with numerical beach.</p> Full article ">Figure 6
<p>Frequency spectra evaluated in the near-bed (z = 0.003m) at <span class="html-italic">φ</span> = 0° (<b>a</b>) and <span class="html-italic">φ</span> = 90° (<b>b</b>). The inertial subrange <math display="inline"><semantics> <mrow> <msup> <mi>f</mi> <mrow> <mo>−</mo> <mn>5</mn> <mo>/</mo> <mn>3</mn> </mrow> </msup> </mrow> </semantics></math> (black dotted line). The red and blue lines report the behavior for mesh 2a and 3a, respectively.</p> Full article ">Figure 7
<p>Comparison between numerical and experimental data of water surface elevation in correspondence of water gauges S3 (<b>a</b>), S4 (<b>b</b>), and S5 (<b>c</b>).</p> Full article ">Figure 8
<p>Comparison between numerical and experimental data of water particle velocity in position <span class="html-italic">φ</span> = 0° at <span class="html-italic">z</span> = 0.01 m (<b>a</b>) and <span class="html-italic">φ</span> = 0° at <span class="html-italic">z</span> = 0.24 m (<b>b</b>).</p> Full article ">Figure 9
<p>Vertical distributions of the pressure <span class="html-italic">P</span> and of the dynamic pressure <span class="html-italic">P<sub>d</sub></span> for the wave phase <span class="html-italic">ωt</span> = 45° (<b>a</b>,<b>b</b>) and <span class="html-italic">ωt</span> = 270° (<b>c,d</b>) in front of the pile at <span class="html-italic">φ</span> = 0° (<b>a</b>,<b>c</b>) and behind it at <span class="html-italic">φ</span> = 180° (<b>b</b>,<b>d</b>). Experimental data: Filled blue circle. Numerical data: Red empty triangle. The dashed line is the hydrostatic pressure.</p> Full article ">Figure 10
<p>Plan view (<span class="html-italic">xy-plane</span>) of the nondimensional dynamic pressure <span class="html-italic">Pd</span>, for the wave phase <span class="html-italic">ωt</span> = 36° (<b>a</b>), <span class="html-italic">ωt</span> = 54° (<b>b</b>), <span class="html-italic">ωt</span> = 72° (<b>c</b>), and <span class="html-italic">ωt</span> = 90° (<b>d</b>). Pressure gradients <span class="html-italic">dP/dx’</span> values (positive, null, or negative) in the area <span class="html-italic">φ =</span> 90°–180°.</p> Full article ">Figure 11
<p>Comparison between the force obtained from the load cell measurements, and as integral of the pressure measurements.</p> Full article ">Figure 12
<p>Comparison between experimental and numerical data of water level (<b>a</b>) and force over the pile (<b>b</b>).</p> Full article ">Figure 13
<p>Comparison between the experimental force and the force evaluated by applying Morison’s formula [<a href="#B1-jmse-07-00453" class="html-bibr">1</a>] with the linear wave theory (original formulation) and with Stokes V order wave theory (modified formulation).</p> Full article ">Figure 14
<p>Isosurface of <span class="html-italic">Q</span> = 10 colored with enstrophy.</p> Full article ">Figure 15
<p>Contour map of the measured scour pattern evaluated in the mobile-bed experiments (<b>a</b>) and of the bed-shear stress magnitude computed from simulation (<b>b</b>). The streamlines in (<b>b</b>) report the behavior of the bed-shear stress vector field (<span class="html-italic">μ∂u/∂z</span>, <span class="html-italic">μ∂v/∂z</span>). Wave direction from left to right.</p> Full article ">
18 pages, 2652 KiB  
Article
Sliding Mode Control in Backstepping Framework for a Class of Nonlinear Systems
by He Shen, Joseph Iorio and Ni Li
J. Mar. Sci. Eng. 2019, 7(12), 452; https://doi.org/10.3390/jmse7120452 - 9 Dec 2019
Cited by 13 | Viewed by 4437
Abstract
Both backstepping control (BC) and sliding mode control (SMC) have been studied extensively over the past few decades, and many variations of controller designs based on them can be found in the literature. In this paper, sliding mode control in a backstepping framework [...] Read more.
Both backstepping control (BC) and sliding mode control (SMC) have been studied extensively over the past few decades, and many variations of controller designs based on them can be found in the literature. In this paper, sliding mode control in a backstepping framework (SBC) for a class of nonlinear systems is proposed and its connections to SMC studied. SMC is shown to be a special case of SBC. Without losing generality, the regulation control problem is studied, while tracking control is achieved by replacing the states with the difference between the states and their desired values. The SBCs are designed for nonlinear single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) systems with the presence of bounded uncertainties from unmodeled dynamics, parametric variations, disturbances, and measurement noise, and the closed loop systems are proven to be asymptotically stable using the Lyapunov stability theory. The comparison of SBC to SMC from the design process, chattering effects, and chatter reduction are also discussed. SBC inherits the merits of backstepping control in choosing gains independently, while leveraging useful nonlinear dynamics for controller design simplification. Hence, it provides more flexibility in controller design in the sense of controlling coverage speed and making use of useful nonlinearities in the dynamics. To demonstrate the effectiveness of SBC, an application on cruise tracking control of an autonomous underwater vehicle was studied. Full article
(This article belongs to the Special Issue Intelligent Marine Robotics Modelling, Simulation and Applications)
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<p>Sketch of an autonomous underwater vehicle.</p> Full article ">Figure 2
<p>Performance comparison of SBC and SMC. (<b>a</b>), (<b>b</b>), (<b>c</b>) and (<b>d</b>) are the y-position, heading angle, angular rate, and control signal.</p> Full article ">Figure 2 Cont.
<p>Performance comparison of SBC and SMC. (<b>a</b>), (<b>b</b>), (<b>c</b>) and (<b>d</b>) are the y-position, heading angle, angular rate, and control signal.</p> Full article ">Figure 3
<p>Performance comparison of ISBC and ISMC.</p> Full article ">Figure 4
<p>Performance comparison of SBC (<b>a</b>) and SMC (<b>b</b>).</p> Full article ">Figure 5
<p>Performance comparison of ISBC (<b>a</b>) and ISMC (<b>b</b>).</p> Full article ">
3 pages, 158 KiB  
Editorial
Dynamics of the Coastal Zone
by Matteo Postacchini and Alessandro Romano
J. Mar. Sci. Eng. 2019, 7(12), 451; https://doi.org/10.3390/jmse7120451 - 9 Dec 2019
Cited by 8 | Viewed by 2293
Abstract
The coastal zone hosts many human activities and interests, which have significantly increased in the last few decades [...] Full article
(This article belongs to the Special Issue Dynamics of the Coastal Zone)
23 pages, 2398 KiB  
Article
A Model for Intact and Damage Stability Evaluation of CNG Ships during the Concept Design Stage
by Francesco Mauro, Luca Braidotti and Giorgio Trincas
J. Mar. Sci. Eng. 2019, 7(12), 450; https://doi.org/10.3390/jmse7120450 - 8 Dec 2019
Cited by 11 | Viewed by 2962
Abstract
To face the design of a new ship concept, the evaluation of multiple feasible solutions concerning several aspects of naval architecture and marine engineering is necessary. Compressed natural gas technologies are in continuous development; therefore, there are no available databases for existing ships [...] Read more.
To face the design of a new ship concept, the evaluation of multiple feasible solutions concerning several aspects of naval architecture and marine engineering is necessary. Compressed natural gas technologies are in continuous development; therefore, there are no available databases for existing ships to use as a basis for the design process of a new unit. In this sense, the adoption of a modern multi-attribute decision-based method can help the designer for the study of a completely new ship prototype. A database of compressed natural gas ships was generated starting from a baseline hull, varying six hull-form parameters by means of the design of experiment technique. Between the attributes involved in the concept design process, stability is for sure one of the most relevant topics, both for intact and damaged cases. This work describes two approaches to identify the compliance of a ship with the intact stability regulations based on the ship main geometrical quantities. Moreover, a metamodel based on the maximum floodable length concept (damage stability) allows determining the main internal subdivision of the ship. The metamodel outcomes were compared with results from direct calculations on a ship external to the database, highlighting the adequate accuracy given by the developed methods. Full article
(This article belongs to the Section Ocean Engineering)
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<p>Sketch of the weather criterion requirements according to ISC 2008.</p> Full article ">Figure 2
<p>Example of a set of CNG hull-forms together with the associated <math display="inline"><semantics> <mrow> <mi>G</mi> <mi>Z</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>G</mi> <mi>F</mi> <mi>L</mi> </mrow> </semantics></math> curves.</p> Full article ">Figure 3
<p>Calculated vs. estimated non-dimensional <math display="inline"><semantics> <mrow> <mi>G</mi> <msup> <mi>Z</mi> <mo>′</mo> </msup> </mrow> </semantics></math> values (<b>left</b>) and associated <math display="inline"><semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics></math> per each vessel inside the database (<b>right</b>) according to polynomial regression method.</p> Full article ">Figure 4
<p>Calculated vs. estimated non-dimensional <math display="inline"><semantics> <mrow> <mi>G</mi> <msup> <mi>Z</mi> <mo>′</mo> </msup> </mrow> </semantics></math> values (<b>left</b>) and associated <math display="inline"><semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics></math> per each vessel inside the database (<b>right</b>) according to angle-based regression method.</p> Full article ">Figure 5
<p>Calculated vs. estimated non-dimensional <math display="inline"><semantics> <mrow> <mi>G</mi> <mi>F</mi> <msup> <mi>L</mi> <mo>′</mo> </msup> </mrow> </semantics></math> values (<b>left</b>) and associated <math display="inline"><semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics></math> per each ship inside the database (<b>right</b>) imposing <math display="inline"><semantics> <mrow> <mi>G</mi> <mi>F</mi> <mi>L</mi> </mrow> </semantics></math> equal to 0 for unstable ships.</p> Full article ">Figure 6
<p>Calculated vs. estimated non-dimensional <math display="inline"><semantics> <mrow> <mi>G</mi> <mi>F</mi> <msup> <mi>L</mi> <mo>′</mo> </msup> </mrow> </semantics></math> values (<b>left</b>) and associated <math display="inline"><semantics> <msup> <mi>R</mi> <mn>2</mn> </msup> </semantics></math> per each ship inside the database (<b>right</b>).</p> Full article ">Figure 7
<p>The body plan for the test ship and the related <math display="inline"><semantics> <mrow> <mi>G</mi> <mi>Z</mi> </mrow> </semantics></math> curves according to direct calculation and the two proposed regression models.</p> Full article ">Figure 8
<p><math display="inline"><semantics> <mrow> <mi>G</mi> <mi>F</mi> <mi>L</mi> </mrow> </semantics></math> curves for the test ship according to direct calculation and the proposed regression model.</p> Full article ">Figure 9
<p><math display="inline"><semantics> <mrow> <mi>G</mi> <mi>F</mi> <mi>L</mi> </mrow> </semantics></math> curves for the test ship according to direct calculation and the proposed regression model.</p> Full article ">
13 pages, 2246 KiB  
Article
Migration and Diffusion of Heavy Metal Cu from the Interior of Sediment during Wave-Induced Sediment Liquefaction Process
by Fang Lu, Haoqing Zhang, Yonggang Jia, Wenquan Liu and Hui Wang
J. Mar. Sci. Eng. 2019, 7(12), 449; https://doi.org/10.3390/jmse7120449 - 8 Dec 2019
Cited by 9 | Viewed by 2941
Abstract
Sediments are an important sink for heavy metal pollutants on account of their strong adsorption capacity. Elevated content of Cu was observed in the Chengdao area of the Yellow River Delta, where the surface sediment is mainly silt and is prone to be [...] Read more.
Sediments are an important sink for heavy metal pollutants on account of their strong adsorption capacity. Elevated content of Cu was observed in the Chengdao area of the Yellow River Delta, where the surface sediment is mainly silt and is prone to be liquefied under hydrodynamic forces. The vertical transport of fine particles, along with pore water seepage, during the liquefaction process could promote the migration and diffusion of Cu from the interior of sediment. The present study involved a series of wave flume experiments to simulate the migration and diffusion of Cu from the interior of sediment in the subaqueous Yellow River Delta area under wave actions. The results indicated that sediment liquefaction significantly promoted the release of Cu from internal sediment to overlying water. The variations of Cu concentrations in the overlying water were opposite to the suspended sediment concentrations (SSCs). The sediment liquefaction caused high initial rises of SSCs, but led to a rapid decline of dissolved Cu concentration at the initial period of sediment liquefaction due to the adsorption by fine particles. Afterwards, the SSCs slightly increased and then gradually decreased. Meanwhile, the dissolved Cu concentration generally kept increasing under combined effects of intensively mix of sediment and overlying water, pore water seepage, and desorption. The dissolved Cu concentration in the overlying water during sediment liquefaction phase was 1.5–2.2 times that during the consolidation phase. Sediment liquefaction also caused vertical diffusion of Cu in sediment and the diffusion depth was in accordance with the liquefaction depth. The results of the present study may provide reference for the environmental management in the study area. Full article
(This article belongs to the Special Issue New Advances in Marine Engineering Geology)
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<p>Location of the study area.</p> Full article ">Figure 2
<p>Sketch of the wave flume used in the present study.</p> Full article ">Figure 3
<p>Layout of the sediment tank and sampling points.</p> Full article ">Figure 4
<p>Curves presenting the variation of liquefaction interfaces in Stage II (<b>a</b>) and Stage III (<b>b</b>).</p> Full article ">Figure 5
<p>Suspended sediments concentration (SSC) variation in the overlying water under wave actions in: (<b>a</b>) Stage II and (<b>b</b>) Stage III.</p> Full article ">Figure 6
<p>Variation of Cu concentration in water during different stages ((<b>a</b>): Stage I; (<b>b</b>): Stage II; (<b>c</b>): Stage III).</p> Full article ">Figure 7
<p>Vertical profiles of Cu concentration in the columnar sediment samples at the end of each stage.</p> Full article ">
16 pages, 7165 KiB  
Article
An Improved Ship Collision Risk Evaluation Method for Korea Maritime Safety Audit Considering Traffic Flow Characteristics
by Yunja Yoo and Tae-Goun Kim
J. Mar. Sci. Eng. 2019, 7(12), 448; https://doi.org/10.3390/jmse7120448 - 7 Dec 2019
Cited by 17 | Viewed by 4250
Abstract
Ship collision accidents account for the majority of marine accidents. The collision risk can be even greater in ports where the traffic density is high and terrain conditions are difficult. The proximity assessment model of the Korea Maritime Safety Audit (KMSA), which is [...] Read more.
Ship collision accidents account for the majority of marine accidents. The collision risk can be even greater in ports where the traffic density is high and terrain conditions are difficult. The proximity assessment model of the Korea Maritime Safety Audit (KMSA), which is a tool for improving maritime traffic safety, employs a normal distribution of ship traffic to calculate the ship collision risk. However, ship traffic characteristics can differ according to the characteristics of the sea area and shipping route. Therefore, this study simulates collision probabilities by estimating the best-fit distribution function of ship traffic flow in Ulsan Port, which is the largest hazardous cargo vessel handling port in Korea. A comparison of collision probability simulation results using the best-fit function and the normal distribution function reveals a difference of approximately 1.5–2.4 times for each route. Moreover, the collision probability estimates are not accurate when the normal distribution function is uniformly applied without considering the characteristics of each route. These findings can be used to improve the KMSA evaluation method for ship collision risks, particularly in hazardous port areas. Full article
(This article belongs to the Special Issue Maritime Safety)
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<p>Outline of the Korea Maritime Safety Audit (KMSA) process and audit items.</p> Full article ">Figure 2
<p>Geographical location of Ulsan Port on the Korean peninsula.</p> Full article ">Figure 3
<p>Daily ship entry (<b>a</b>) and three-day rolling sum (<b>b</b>) data for Ulsan Port in 2014. The data was from Port-MIS</p> Full article ">Figure 4
<p>Gate lines A–E across the fairway of Ulsan Port (<b>a</b>) and three-day rolling sum AIS ship track data for winter (<b>b</b>), spring (<b>c</b>), summer (<b>d</b>), and autumn (<b>e</b>) in 2014.</p> Full article ">Figure 4 Cont.
<p>Gate lines A–E across the fairway of Ulsan Port (<b>a</b>) and three-day rolling sum AIS ship track data for winter (<b>b</b>), spring (<b>c</b>), summer (<b>d</b>), and autumn (<b>e</b>) in 2014.</p> Full article ">Figure 5
<p>Distribution of inbound and outbound ship passing distances for each gate.</p> Full article ">Figure 6
<p>Frequency distribution and probability density for inbound and outbound vessels at gate lines A–E (<b>a</b>–<b>e</b>) in Ulsan Port in 2014.</p> Full article ">Figure 7
<p>Number of inbound vessels by ship type at gates A–E (inbound tankers = 71.1%, outbound tankers = 71.9%).</p> Full article ">Figure 8
<p>Number of outbound vessels by ship type at gates A–E.</p> Full article ">Figure 9
<p>Schematic of a head-on situation geometric collision model on a fairway.</p> Full article ">Figure 10
<p>Ship distribution models for gates A–E. (<b>a</b>) Best-fit PDF and (<b>b</b>) normal PDF.</p> Full article ">Figure 11
<p>Geometric collision probability for gates A–E (<b>a</b>–<b>e</b>) using the best-fit PDF and normal PDF (striped area).</p> Full article ">
17 pages, 2793 KiB  
Article
The Reproduction Ability of a Numerical Model for Simulating the Outflow Rate of Backfilling Materials from a Coastal Structure
by Kornvisith Silarom and Yoshimichi Yamamoto
J. Mar. Sci. Eng. 2019, 7(12), 447; https://doi.org/10.3390/jmse7120447 - 6 Dec 2019
Cited by 2 | Viewed by 2678
Abstract
In very shallow areas, the frequency by which coastal structures (like dikes and seawalls) are directly broken by large wave forces is low because large waves are broken in deeper areas. The main cause for such destruction is ground scour in front of [...] Read more.
In very shallow areas, the frequency by which coastal structures (like dikes and seawalls) are directly broken by large wave forces is low because large waves are broken in deeper areas. The main cause for such destruction is ground scour in front of the structures and outflow of backfilling materials by middle-scale waves; therefore, the scour and the outflow should be considered when designing a coastal structure in a very shallow area. In this paper, a numerical model consisting of CADMAS-SURF, which can calculate fluid motion in porous media, and empirical equations for simulating the outflow phenomena are introduced; thereafter, practical calculations on field cases in Thailand and Japan are demonstrated. Additionally, since the effects of wave periods and water depth to the outflow rate have never been clarified, hydraulic model experiments, empirical calculations using an existing formula, and numerical simulations are performed in order to examine these effects on the outflow rate. The simulated results using the numerical model align well with the experimental results. Moreover, both results show that the outflow rate is proportional to the wave period and inversely proportional to water depth. Full article
(This article belongs to the Special Issue Numerical Models in Coastal Hazards and Coastal Environment)
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<p>Scour and the outflow in a dike model. The dike model was filled with sand (<b>a</b>). When scour depth in front of the dike reached the lowest edge of the dike (<b>b</b>), the backfilling materials flowed out, and the cave was formed (<b>b</b>–<b>f</b>). t denotes the elapsed time (unit is minute).</p> Full article ">Figure 2
<p>Parameters in the empirical equations.</p> Full article ">Figure 3
<p>The calculated outflow volume on the Oarai–Isohama Coast.</p> Full article ">Figure 4
<p>Calculated formation of a cave inside the dike on the Oarai–Isohama Coast.</p> Full article ">Figure 5
<p>The calculated outflow volume on the Ishikawa–Komatsu Coast.</p> Full article ">Figure 6
<p>Calculated formation of a cave inside the dike on the Ishikawa–Komatsu Coast.</p> Full article ">Figure 7
<p>The calculated outflow volume on the Suan Son Coast.</p> Full article ">Figure 8
<p>Calculated formation of a cave inside the seawall on the Suan Son Coast.</p> Full article ">Figure 9
<p>Comparison between the measured values and the calculated values.</p> Full article ">Figure 10
<p>The setup of the wave flume in the experiments.</p> Full article ">Figure 11
<p>The trend of the dimensionless water depth for the outflow volume in the experiments, the simulations, and the calculations.</p> Full article ">Figure 12
<p>The trend of the wave period for the outflow volume in the experiments, the simulations, and the calculations.</p> Full article ">Figure 13
<p>The trend of the nondimensional wavelength for the outflow volume in the experiments, the simulations, and the calculations.</p> Full article ">Figure 14
<p>The time history of the outflow volume in the simulations.</p> Full article ">
12 pages, 814 KiB  
Article
Coastal Boulder Deposits of the Neogene World: A Synopsis
by Dmitry A. Ruban
J. Mar. Sci. Eng. 2019, 7(12), 446; https://doi.org/10.3390/jmse7120446 - 5 Dec 2019
Cited by 6 | Viewed by 2407
Abstract
Modern geoscience research pays significant attention to Quaternary coastal boulder deposits, although the evidence from the earlier geologic periods can be of great importance. The undertaken compilation of the literature permits to indicate 21 articles devoted to such deposits of Neogene age. These [...] Read more.
Modern geoscience research pays significant attention to Quaternary coastal boulder deposits, although the evidence from the earlier geologic periods can be of great importance. The undertaken compilation of the literature permits to indicate 21 articles devoted to such deposits of Neogene age. These are chiefly case studies. Such an insufficiency of investigations may be linked to poor preservation potential of coastal boulder deposits and methodological difficulties. Equal attention has been paid by geoscientists to Miocene and Pliocene deposits. Taking into account the much shorter duration of the Pliocene, an overemphasis of boulders of this age becomes evident. Hypothetically, this can be explained by more favorable conditions for boulder formation, including a larger number of hurricanes due to the Pliocene warming. Geographically, the studies of the Neogene coastal boulder deposits have been undertaken in different parts of the world, but generally in those locations where rocky shores occur nowadays. The relevance of these deposits to storms and tsunamis, rocky shores and deltas, gravity processes, and volcanism has been discussed; however, some other mechanisms of boulder production, transportation, and accumulation (e.g., linked to seismicity and weathering) have been missed. Full article
(This article belongs to the Special Issue Evaluation of Boulder Deposits Linked to Late Neogene Hurricane Events)
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<p>Different definition of boulders (see text for references).</p> Full article ">Figure 2
<p>Geographical focus of the studies of Neogene coastal boulder deposits (based on <a href="#jmse-07-00446-t004" class="html-table">Table 4</a>). See <a href="#jmse-07-00446-t002" class="html-table">Table 2</a> for locality IDs.</p> Full article ">Figure 3
<p>Genetic focus of the studies of Neogene coastal boulder deposits (based on <a href="#jmse-07-00446-t005" class="html-table">Table 5</a>).</p> Full article ">
23 pages, 1204 KiB  
Article
Design of an Adaptive Sliding Mode Control for a Micro-AUV Subject to Water Currents and Parametric Uncertainties
by Jonathan Rodriguez, Herman Castañeda and J. L. Gordillo
J. Mar. Sci. Eng. 2019, 7(12), 445; https://doi.org/10.3390/jmse7120445 - 4 Dec 2019
Cited by 25 | Viewed by 3136
Abstract
This paper addresses the design of an adaptive sliding mode control for an autonomous underwater vehicle with the objective to reject bounded internal and external perturbations. The proposed control is used to achieve velocity regulation and autonomous path-following using waypoints. Each task is [...] Read more.
This paper addresses the design of an adaptive sliding mode control for an autonomous underwater vehicle with the objective to reject bounded internal and external perturbations. The proposed control is used to achieve velocity regulation and autonomous path-following using waypoints. Each task is successfully performed in the presence of parametric uncertainties and irrotational water currents. Due to complex dynamics and random external perturbations, underwater vehicles need robust control. The closed-loop stability and finite-time convergence of the system are demonstrated using the Lyapunov direct method. To provide a detailed and realistic testing environment for the proposed adaptive controller, a dynamic model of the vehicle using the Lagrange method is derived where all underwater effects are included. On that basis, the proposed adaptive sliding mode controller is compared to its non-adaptive equivalent and PD (Proportional Derivative) computed torque control. The simulation results demonstrate that the proposed adaptive control has better robustness and precision for this particular type of vehicle. Full article
(This article belongs to the Special Issue Advances in Oceanic and Mechatronic Systems Engineering)
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<p>AUV model: frames definitions.</p> Full article ">Figure 2
<p>AUV model: joint vectors configuration.</p> Full article ">Figure 3
<p>LOS guidance schematic representation in the <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mi>x</mi> <mi>y</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> plane.</p> Full article ">Figure 4
<p>Model, control and navigation diagram.</p> Full article ">Figure 5
<p>1 m/s surge speed command (without disturbance): (<b>a</b>) AUV linear velocities (<b>b</b>) adaptive control gains (<b>c</b>) adaptive propeller forces (<b>d</b>) sliding variable vector <math display="inline"><semantics> <mi>σ</mi> </semantics></math> absolute value.</p> Full article ">Figure 6
<p>1 m/s surge speed command (with disturbance): (<b>a</b>) AUV linear velocities (<b>b</b>) AUV angular velocities (<b>c</b>) horizontal propellers forces (<b>d</b>) vertical propellers forces (<b>e</b>) adaptive control gains (<b>f</b>) sliding variable vector <math display="inline"><semantics> <mi>σ</mi> </semantics></math> absolute value.</p> Full article ">Figure 6 Cont.
<p>1 m/s surge speed command (with disturbance): (<b>a</b>) AUV linear velocities (<b>b</b>) AUV angular velocities (<b>c</b>) horizontal propellers forces (<b>d</b>) vertical propellers forces (<b>e</b>) adaptive control gains (<b>f</b>) sliding variable vector <math display="inline"><semantics> <mi>σ</mi> </semantics></math> absolute value.</p> Full article ">Figure 7
<p>1 m/s surge speed command: 3D trajectory of the AUV.</p> Full article ">Figure 8
<p>Steady state command (sudden oceanic current at t = 1 s): (<b>a</b>) AUV linear velocities (<b>b</b>) AUV angular velocities (<b>c</b>) horizontal propellers forces (<b>d</b>) vertical propellers forces (<b>e</b>) adaptive control gains (<b>f</b>) sliding variable vector <math display="inline"><semantics> <mi>σ</mi> </semantics></math> absolute value.</p> Full article ">Figure 9
<p>Steady state command (sudden oceanic current at t=1s): <math display="inline"><semantics> <mrow> <mo stretchy="false">(</mo> <mi>x</mi> <mi>y</mi> <mo stretchy="false">)</mo> </mrow> </semantics></math> plane trajectory of the AUV.</p> Full article ">Figure 10
<p>Path-following task: (<b>a</b>) AUV linear velocities (<b>b</b>) AUV rotational velocities (<b>c</b>) Surge/Sway propeller forces (<b>d</b>) Dive propeller forces.</p> Full article ">Figure 11
<p>Path-following task: adaptive gains.</p> Full article ">Figure 12
<p>Path-following task: sliding variable vector <math display="inline"><semantics> <mi>σ</mi> </semantics></math> absolute value.</p> Full article ">Figure 13
<p>Path-following task: 3D trajectory of the AUV.</p> Full article ">Figure 14
<p>Path-following task: norm of the control signal <span class="html-italic">u</span>, comparison of the 3 controllers.</p> Full article ">Figure 15
<p>Path-following task: norm of the sliding variable vector <math display="inline"><semantics> <mi>σ</mi> </semantics></math>, comparison of the 3 controllers.</p> Full article ">
22 pages, 4171 KiB  
Article
System Modeling and Simulation of an Unmanned Aerial Underwater Vehicle
by Yuqing Chen, Yaowen Liu, Yangrui Meng, Shuanghe Yu and Yan Zhuang
J. Mar. Sci. Eng. 2019, 7(12), 444; https://doi.org/10.3390/jmse7120444 - 4 Dec 2019
Cited by 29 | Viewed by 4432
Abstract
Unmanned Aerial Underwater Vehicles (UAUVs) with multiple propellers can operate in two distinct mediums, air and underwater, and the system modeling of the autonomous vehicles is a key issue to adapt to these different external environments. In this paper, only a single set [...] Read more.
Unmanned Aerial Underwater Vehicles (UAUVs) with multiple propellers can operate in two distinct mediums, air and underwater, and the system modeling of the autonomous vehicles is a key issue to adapt to these different external environments. In this paper, only a single set of aerial rotors with switching propulsion abilities are designed as driving components, and then a compound multi-model method is investigated to achieve good performance of the cross-medium motion. Furthermore, some additional variables, such as water resistance, buoyancy and their corresponding moments are considered for the underwater case. In particular, a critical coefficient for air-to-water switching is presented to express these gradually changing additional variables in the cross-medium motion process. Finally, the sliding mode control method is used to reduce the altitude error and attitude error of the vehicles with external environmental disturbances. The proposed scheme is tested and the model is verified on the simulation platform. Full article
(This article belongs to the Special Issue Intelligent Marine Robotics Modelling, Simulation and Applications)
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<p>Configuration of the aerial underwater vehicle.</p> Full article ">Figure 2
<p>Frames of the aerial underwater vehicle.</p> Full article ">Figure 3
<p>Mode switching for the cross-medium behavior of aerial underwater vehicle.</p> Full article ">Figure 4
<p>Aerial underwater vehicle control block diagram.</p> Full article ">Figure 5
<p>Diagram of the motion control process of the unmanned aerial underwater vehicle (UAUV).</p> Full article ">Figure 6
<p>Three-dimensional position graphic of the aerial underwater vehicle in the air.</p> Full article ">Figure 7
<p>Attitude response curves of the aerial underwater vehicle in the air.</p> Full article ">Figure 8
<p>Control inputs of the vehicle (Thrust force <span class="html-italic">U</span><sub>1</sub> and moments <span class="html-italic">U</span><sub>2–4</sub>).</p> Full article ">Figure 9
<p>Rotational speed outputs of the vehicle motors.</p> Full article ">Figure 10
<p>Three-dimensional position graphic of the aerial underwater vehicle underwater.</p> Full article ">Figure 11
<p>Attitude response curves of the vehicle underwater.</p> Full article ">Figure 12
<p>Control inputs of the vehicle (Thrust force <span class="html-italic">U</span><sub>1</sub> and moments <span class="html-italic">U</span><sub>2–4</sub>).</p> Full article ">Figure 13
<p>Rotational speed outputs of the vehicle motors.</p> Full article ">Figure 14
<p>Three-dimensional cross-medium trajectory of the UAUV.</p> Full article ">Figure 15
<p>Cross-medium attitude response curves of the aerial underwater vehicle.</p> Full article ">Figure 16
<p>Cross-medium control inputs of the vehicle (thrust force <span class="html-italic">U</span><sub>1</sub> and moments <span class="html-italic">U</span><sub>2–4</sub>).</p> Full article ">Figure 17
<p>Rotational speed outputs of the vehicle motors.</p> Full article ">
22 pages, 5795 KiB  
Article
Three-Dimensional Path Tracking Control of Autonomous Underwater Vehicle Based on Deep Reinforcement Learning
by Yushan Sun, Chenming Zhang, Guocheng Zhang, Hao Xu and Xiangrui Ran
J. Mar. Sci. Eng. 2019, 7(12), 443; https://doi.org/10.3390/jmse7120443 - 3 Dec 2019
Cited by 21 | Viewed by 3998
Abstract
In this paper, the three-dimensional (3D) path tracking control of an autonomous underwater vehicle (AUV) under the action of sea currents was researched. A novel reward function was proposed to improve learning ability and a disturbance observer was developed to observe the disturbance [...] Read more.
In this paper, the three-dimensional (3D) path tracking control of an autonomous underwater vehicle (AUV) under the action of sea currents was researched. A novel reward function was proposed to improve learning ability and a disturbance observer was developed to observe the disturbance caused by currents. Based on existing models, the dynamic and kinematic models of the AUV were established. Deep Deterministic Policy Gradient, a deep reinforcement learning, was employed for designing the path tracking controller. Compared with the backstepping sliding mode controller, the controller proposed in this article showed excellent performance, at least in the particular study developed in this article. The improved reward function and the disturbance observer were also found to work well with improving path tracking performance. Full article
(This article belongs to the Section Ocean Engineering)
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<p>Schematic diagram of three-dimensional path tracking of autonomous underwater vehicle.</p> Full article ">Figure 2
<p>Parameters update process of Deep Deterministic Policy Gradient algorithm.</p> Full article ">Figure 3
<p>Exploratory action selection.</p> Full article ">Figure 4
<p>(<b>a</b>) Top view of the simulation training environment. (<b>b</b>) Side view of the simulation training environment.</p> Full article ">Figure 5
<p>Path tracking simulation results.</p> Full article ">Figure 6
<p>Position errors in the geodetic coordinate system.</p> Full article ">Figure 7
<p>Rudder angle during the path tracking simulation.</p> Full article ">Figure 8
<p>Learning reward during the training.</p> Full article ">Figure 9
<p>Disturbance observer structure.</p> Full article ">Figure 10
<p>Path tracking simulation results.</p> Full article ">Figure 11
<p>Comparison of errors in the <math display="inline"><semantics> <mi>ξ</mi> </semantics></math>-direction.</p> Full article ">Figure 12
<p>Comparison of errors in the <math display="inline"><semantics> <mi>η</mi> </semantics></math>-direction.</p> Full article ">Figure 13
<p>Comparison of errors in the <math display="inline"><semantics> <mi>ζ</mi> </semantics></math>-direction.</p> Full article ">Figure 14
<p>Comparison of the AUV course angle.</p> Full article ">Figure 15
<p>Comparison of the AUV flight path angle.</p> Full article ">Figure 16
<p>of the AUV horizontal rudders angle.</p> Full article ">Figure 17
<p>Comparison of the AUV vertical rudders angle.</p> Full article ">Figure 18
<p>Learning reward applying the reward function improved DDPG.</p> Full article ">
19 pages, 6278 KiB  
Article
Coordination of Marine Functional Zoning Revision at the Provincial and Municipal Levels: A Case Study of Putian, China
by Faming Huang, Yanhong Lin, Huixin Liang, Rongrong Zhao, Qiuming Chen, Jie Lin and Jinliang Huang
J. Mar. Sci. Eng. 2019, 7(12), 442; https://doi.org/10.3390/jmse7120442 - 3 Dec 2019
Cited by 2 | Viewed by 3313
Abstract
Marine functional zoning (MFZ) is a type of marine spatial planning (MSP) implemented widely in China and one of the three major systems defined in the Law of the PRC on the Administration of Sea Area Use. China adopts “top-down management” for MFZ, [...] Read more.
Marine functional zoning (MFZ) is a type of marine spatial planning (MSP) implemented widely in China and one of the three major systems defined in the Law of the PRC on the Administration of Sea Area Use. China adopts “top-down management” for MFZ, in which upper management levels impose clear constraints and restrictions on lower levels. However, this approach has led to issues, such as a rigid MFZ classification system and unreasonable re-allocation of control indicators in the process of assigning MFZ classification at different levels. In this study, we propose and demonstrate the coordination of MFZ revision in terms of the classification system and the re-allocation of control indicators in the coastal city of Putian, China. The results show that the proposed measures could help realize the effective and reasonable coordination of MFZ revisions at the provincial and municipal levels, providing a reference for such MFZ revisions in other regions of China and the coordination of MSP between different levels in other countries. Full article
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<p>Location of Putian City, Fujian Province, China.</p> Full article ">Figure 2
<p>Framework of the MFZ revision process.</p> Full article ">Figure 3
<p>Map of provincial-level MFZ in Fujian (Putian City).</p> Full article ">Figure 4
<p>Revised zoning (<b>a</b>) provincial zoning, (<b>b</b>) municipal zoning.</p> Full article ">Figure 5
<p>Revised zoning at Meizhou Island: (<b>a</b>) provincial zoning, (<b>b</b>) municipal zoning.</p> Full article ">Figure 6
<p>Total reclamation area in Putian City predicted by two methods: (<b>a</b>) the reclamation potential assessment method and (<b>b</b>) the proportional growth method.</p> Full article ">Figure 7
<p>Prediction curve of fishery farming area.</p> Full article ">
18 pages, 2083 KiB  
Review
Foundations in Offshore Wind Farms: Evolution, Characteristics and Range of Use. Analysis of Main Dimensional Parameters in Monopile Foundations
by Sergio Sánchez, José-Santos López-Gutiérrez, Vicente Negro and M. Dolores Esteban
J. Mar. Sci. Eng. 2019, 7(12), 441; https://doi.org/10.3390/jmse7120441 - 2 Dec 2019
Cited by 71 | Viewed by 8940
Abstract
Renewable energies are the future, and offshore wind is undoubtedly one of the renewable energy sources for the future. Foundations of offshore wind turbines are essential for its right development. There are several types: monopiles, gravity-based structures, jackets, tripods, floating support, etc., being [...] Read more.
Renewable energies are the future, and offshore wind is undoubtedly one of the renewable energy sources for the future. Foundations of offshore wind turbines are essential for its right development. There are several types: monopiles, gravity-based structures, jackets, tripods, floating support, etc., being the first ones that are most used up to now. This manuscript begins with a review of the offshore wind power installed around the world and the exposition of the different types of foundations in the industry. For that, a database has been created, and all the data are being processed to be exposed in clear graphic summarizing the current use of the different foundation types, considering mainly distance to the coast and water depth. Later, the paper includes an analysis of the evolution and parameters of the design of monopiles, including wind turbine and monopile characteristics. Some monomials are considered in this specific analysis and also the soil type. So, a general view of the current state of monopile foundations is achieved, based on a database with the offshore wind farms in operation. Full article
(This article belongs to the Special Issue Offshore Wind Farms)
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<p>Average offshore wind turbine power installed every year.</p> Full article ">Figure 2
<p>Offshore wind farms in operation classified by depth and distance from the coast at the end of 2018 (the size of the bubbles represents the capacity installed).</p> Full article ">Figure 3
<p>Typologies of foundations in Europe at the end of 2018 according to the parameters of depth and distance to the coast.</p> Full article ">Figure 4
<p>Typologies of foundations in Asia at the end of 2018 according to the parameters of depth and distance to the coast.</p> Full article ">Figure 5
<p>Typologies of foundations by depth and distance to coast (1995–2018).</p> Full article ">Figure 6
<p>Accumulated share of monopile foundations (2003–2018).</p> Full article ">Figure 7
<p>Evolution of Hub Height, Blade Length and Monopile Length (1996–2018).</p> Full article ">Figure 8
<p>Soil composition of monopile windfarms by depth and distance to the coast.</p> Full article ">
18 pages, 4777 KiB  
Article
Riprap Scour Protection for Monopiles in Offshore Wind Farms
by M.Dolores Esteban, José-Santos López-Gutiérrez, Vicente Negro and Luciano Sanz
J. Mar. Sci. Eng. 2019, 7(12), 440; https://doi.org/10.3390/jmse7120440 - 2 Dec 2019
Cited by 21 | Viewed by 7475
Abstract
The scour phenomenon is critical for monopile structures in offshore wind farms. There are two possible strategies: allowing the development of scour holes around the monopile or avoiding it by placing scour protection. The last one is the most used up to now. [...] Read more.
The scour phenomenon is critical for monopile structures in offshore wind farms. There are two possible strategies: allowing the development of scour holes around the monopile or avoiding it by placing scour protection. The last one is the most used up to now. This paper is focused on the determination of the weight of the stones forming the scour protection. There are some formulas for the design of these parameters, having a lot of uncertainties around them. Some of them were created for fluvial environment, with a different flow to the marine one. Other formulas were elaborated specifically for coastal structures, closer to the coast than offshore wind farms, and with dimensions completely different. This paper presents the analysis of three formulas: Isbash, corresponding to fluvial environment, and Soulsby, and De Vos, corresponding to marine environment. The results of the application of those formulas are compared with real data of scour protection systems showing good results in five offshore wind facilities in operation (Arklow Bank phase 1, Egmond aan Zee, Horns Rev phase 1, Princess Amalia, and Scroby Sands), giving conclusion about the uncertainties of the use of these formulas and recommendations for using them in offshore wind. Full article
(This article belongs to the Special Issue Offshore Wind Farms)
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<p>Offshore wind power (MW) in Europe at the end of 2017: annual new power installed (<b>a</b>) and cumulative power (<b>b</b>). Reproduced from WindEurope 2018 with permission.</p> Full article ">Figure 2
<p>Total offshore wind power installed worldwide at the end of 2016 and 2017. Reproduced from Global Wind Energy Council (GWEC) 2018 with permission.</p> Full article ">Figure 3
<p>Main criteria for the selection of the foundation for offshore wind turbines depending on the depth. Reproduced from Esteban, M.D. 2009 with permission.</p> Full article ">Figure 4
<p>Share of foundation types in offshore wind turbines connected to the network in Europe, at the end of 2017. Reproduced from WindEurope 2018 with permission.</p> Full article ">Figure 5
<p>Different scour protection systems. Reproduced from Chen, H. et al. 2014 with permission.</p> Full article ">Figure 6
<p>Case studies selected for the research: Arklow Bank phase 1 (Ireland), Egmond aan Zee (Netherlands), Horns Rev phase 1 (Denmark), Princess Amalia (Netherlands), and Scroby Sands (United Kingdom).</p> Full article ">Figure 7
<p>Main dimensions of monopile and scour protection of Arklow Bank phase 1.</p> Full article ">Figure 8
<p>Main dimensions of monopile and scour protection of Egmond aan Zee.</p> Full article ">Figure 9
<p>Main dimensions of monopile and scour protection of Horns Rev phase 1.</p> Full article ">Figure 10
<p>Main dimensions of monopile and scour protection of Princess Amalia.</p> Full article ">Figure 11
<p>Main dimensions of monopile and scour protection of Scroby Sands.</p> Full article ">
23 pages, 12129 KiB  
Article
Numerical Study of the Interaction between Level Ice and Wind Turbine Tower for Estimation of Ice Crushing Loads on Structure
by Ming Song, Wei Shi, Zhengru Ren and Li Zhou
J. Mar. Sci. Eng. 2019, 7(12), 439; https://doi.org/10.3390/jmse7120439 - 1 Dec 2019
Cited by 15 | Viewed by 2935
Abstract
In this paper, the interaction between level ice and wind turbine tower is simulated by the explicit nonlinear code LS-DYNA. The isotropic elasto-plastic material model is used for the level ice, in which ice crushing failure is considered. The effects of ice mesh [...] Read more.
In this paper, the interaction between level ice and wind turbine tower is simulated by the explicit nonlinear code LS-DYNA. The isotropic elasto-plastic material model is used for the level ice, in which ice crushing failure is considered. The effects of ice mesh size and ice failure strain on ice forces are investigated. The results indicate that these parameters have a significant effect on the ice crushing loads. To validate and benchmark the numerical simulations, experimental data on level ice-wind turbine tower interactions are used. First, the failure strains of the ice models with different mesh sizes are calibrated using the measured maximum ice force from one test. Next, the calibrated ice models with different mesh sizes are applied for other tests, and the simulated results are compared to corresponding model test data. The effects of the impact speed and the size of wind turbine tower on the comparison between the simulated and measured results are studied. The comparison results show that the numerical simulations can capture the trend of the ice loads with the impact speed and the size of wind turbine tower. When a mesh size of ice model is 1.5 times the ice thickness, the simulations can give more accurate estimations in terms of maximum ice loads for all tests, i.e., good agreement between the simulated and measured results is achieved. Full article
(This article belongs to the Special Issue Ocean Renewable Energy Systems (ORES); Wave–Structure Interaction Analysis and Design Methods)
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<p>OWT exposed to wind field and in contact with ice.</p> Full article ">Figure 2
<p>The geometry of the 3-MW and 4-MW wind turbine towers in full scale.</p> Full article ">Figure 3
<p>Photograph of a 3-MW model test from Zhou et al. [<a href="#B19-jmse-07-00439" class="html-bibr">19</a>].</p> Full article ">Figure 4
<p>Numerical model of ice-structure interaction.</p> Full article ">Figure 5
<p>Hardening curve for ice material model.</p> Full article ">Figure 6
<p>Side view of ice model: (<b>a</b>) mesh size of 0.2 m (<b>b</b>) mesh size of 0.8 m.</p> Full article ">Figure 7
<p>Ice force histories from the simulations with different mesh sizes.</p> Full article ">Figure 8
<p>The mean, std. and maximum forces varying with the mesh size.</p> Full article ">Figure 9
<p>Ice force histories from the simulations with different failure strains.</p> Full article ">Figure 10
<p>The mean, standard deviation, and maximum forces varying with the failure strain.</p> Full article ">Figure 11
<p>Relationship between failure strain and size ratio.</p> Full article ">Figure 12
<p>Ice force histories from the simulation with mesh size of 0.2 m and measurement for test #306.</p> Full article ">Figure 13
<p>Ice force histories from the simulation with mesh size of 0.4 m and measurement for test #306.</p> Full article ">Figure 14
<p>Ice force histories from the simulation with mesh size of 0.6 m and measurement for test #306.</p> Full article ">Figure 15
<p>Ice force histories from the simulation with mesh size of 0.8 m and measurement for test #306.</p> Full article ">Figure 16
<p>An image extracted from the simulation with mesh size of 0.2 m at t = 10 s.</p> Full article ">Figure 17
<p>An image extracted from the simulation with mesh size of 0.8 m at t = 10 s.</p> Full article ">Figure 18
<p>An image extracted from test #306.</p> Full article ">Figure 19
<p>Spectrum of ice force from the simulation with mesh size of 0.2 m and measurement for test #306.</p> Full article ">Figure 20
<p>Spectrum of ice force from the simulation with mesh size of 0.4 m and measurement for test #306.</p> Full article ">Figure 21
<p>Spectrum of ice force from the simulation with mesh size of 0.6 m and measurement for test #306.</p> Full article ">Figure 22
<p>Spectrum of ice force from the simulation with mesh size of 0.8 m and measurement for test #306.</p> Full article ">Figure A1
<p>Ice force histories from the simulation with mesh size of 0.2 m and measurement for test #304.</p> Full article ">Figure A2
<p>Ice force histories from the simulation with mesh size of 0.4 m and measurement for test #304.</p> Full article ">Figure A3
<p>Ice force histories from the simulation with mesh size of 0.6 m and measurement for test #304.</p> Full article ">Figure A4
<p>Ice force histories from the simulation with mesh size of 0.8 m and measurement for test #304.</p> Full article ">Figure A5
<p>Comparison of the maximum ice force between the simulated and measured results for all tests.</p> Full article ">Figure A6
<p>Comparison of the mean ice force between the simulated and measured results for all tests.</p> Full article ">Figure A7
<p>Comparison of the standard deviation between the simulated and measured results for all tests.</p> Full article ">
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