[go: up one dir, main page]

Next Issue
Volume 6, December
Previous Issue
Volume 6, October
 
 
applsci-logo

Journal Browser

Journal Browser

Appl. Sci., Volume 6, Issue 11 (November 2016) – 61 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
6971 KiB  
Article
Digital Controller Design Based on Active Damping Method of Capacitor Current Feedback for Auxiliary Resonant Snubber Inverter with LC Filter
by Hailin Zhang, Baoquan Kou, Lu Zhang and Yinxi Jin
Appl. Sci. 2016, 6(11), 377; https://doi.org/10.3390/app6110377 - 22 Nov 2016
Cited by 5 | Viewed by 6617
Abstract
In some high-performance applications, an LC filter must be added to the auxiliary resonant snubber inverter (ARSI) to reduce the output current ripple. However, resonance occurs due to the additional LC filter, which makes the traditional closed-loop control not suitable to be used [...] Read more.
In some high-performance applications, an LC filter must be added to the auxiliary resonant snubber inverter (ARSI) to reduce the output current ripple. However, resonance occurs due to the additional LC filter, which makes the traditional closed-loop control not suitable to be used directly. Therefore, this paper presents a double-loop digital control based on the active damping method of capacitor current feedback to stabilize the system. Most of the studies on active damping methods are focused on the grid in consideration of zero resistance. However, the load resistance should not be neglected in the drive system. Therefore, the load resistance and digital control delays are considered in this paper. Moreover, an improved loading method is proposed to improve the duty ratio range. In order to verify the effectiveness of the controller, a prototype was developed. The simulation and experimental results demonstrate that soft-switching can be realized for the entire load range. The maximum duty ratio is improved by 0.01 by using the proposed loading method. The resonance can be eliminated by using the proposed control method. Full article
Show Figures

Figure 1

Figure 1
<p>Circuit of the single-phase auxiliary resonant snubber inverter (ARSI) with LC filter.</p>
Full article ">Figure 2
<p>Control diagram of the ARSI.</p>
Full article ">Figure 3
<p>Key waveforms to realize the zero-voltage switching (ZVS) of S<sub>1</sub> and S<sub>4</sub> (<b>a</b>) <span class="html-italic">i<sub>Lf_l</sub></span> &lt; −<span class="html-italic">I<sub>r_</sub></span><sub>min</sub>; (<b>b</b>) <span class="html-italic">i<sub>Lf_l</sub></span> &gt; −<span class="html-italic">I<sub>r_</sub></span><sub>min</sub>.</p>
Full article ">Figure 4
<p>Digital pulse-width-modulation (DPWM) diagram of the ARSI.</p>
Full article ">Figure 5
<p>DPWM diagram at the condition of <span class="html-italic">I<sub>o_</sub></span><sub>max</sub> and <span class="html-italic">D</span><sub>max</sub>: (<b>a</b>) conventional loading scheme; (<b>b</b>) improved loading scheme.</p>
Full article ">Figure 6
<p>Digital control model of the output current controller.</p>
Full article ">Figure 7
<p>Output current controller model in the s-domain.</p>
Full article ">Figure 8
<p>Bode plot of the approximated model and the precise model.</p>
Full article ">Figure 9
<p>Bode plot of the ARSI with different PI parameters: (<b>a</b>) different <span class="html-italic">K<sub>p</sub></span>; (<b>b</b>) different <span class="html-italic">K<sub>i</sub></span>.</p>
Full article ">Figure 10
<p>Model of ARSI in digital control.</p>
Full article ">Figure 11
<p>Root locus of variation in active damping gain <span class="html-italic">K<sub>cf</sub></span> using a dual-loop controller.</p>
Full article ">Figure 12
<p>Open-loop Bode plot with different active damping gain <span class="html-italic">K<sub>cf</sub></span>.</p>
Full article ">Figure 13
<p>Bode plot of the single loop and double loop.</p>
Full article ">Figure 14
<p>Photograph of the prototype.</p>
Full article ">Figure 15
<p>Simulation results of the current and voltage of the main switches when <span class="html-italic">i<sub>o</sub></span> = 8 A. (<b>a</b>) S<sub>3</sub>; (<b>b</b>) S<sub>4</sub>.</p>
Full article ">Figure 16
<p>Experimental results of the current and voltage of the main switches when <span class="html-italic">i<sub>o</sub></span> = 8 A. (<b>a</b>) S<sub>3</sub>; (<b>b</b>) S<sub>4</sub>.</p>
Full article ">Figure 17
<p>Simulation waveforms of the auxiliary current with an 8 A, 100 Hz sinusoidal output current.</p>
Full article ">Figure 18
<p>Experimental waveforms of the auxiliary current with an 8 A, 100 Hz sinusoidal output current.</p>
Full article ">Figure 19
<p>Simulation results of the output current with and without active damping method: (<b>a</b>) DC output current; (<b>b</b>) sinusoidal output current.</p>
Full article ">Figure 20
<p>Experimental results of the output current (<b>a</b>) without and (<b>b</b>) with active damping method.</p>
Full article ">Figure 21
<p>Simulation results of the load dynamic response: (<b>a</b>) a step change from 12.5% to 75% rated output power; (<b>b</b>) a step change from 75% to 12.5% rated output power.</p>
Full article ">Figure 22
<p>Experimental results of the load dynamic response: (<b>a</b>) a step change from 12.5% to 62.5% rated output power; (<b>b</b>) a step change from 62.5% to 12.5% rated output power.</p>
Full article ">
2226 KiB  
Article
Ammonium Removal from Landfill Leachate by Means of Multiple Recycling of Struvite Residues Obtained through Acid Decomposition
by Alessio Siciliano, Maria Assuntina Stillitano, Carlo Limonti and Francesco Marchio
Appl. Sci. 2016, 6(11), 375; https://doi.org/10.3390/app6110375 - 22 Nov 2016
Cited by 16 | Viewed by 5629
Abstract
The treatment of landfill leachate, due to its great polluting load, is a very difficult task. In particular, the abatement of high ammonium concentrations represents one of the main issues. Among the available techniques, struvite precipitation is an effective method for the removal [...] Read more.
The treatment of landfill leachate, due to its great polluting load, is a very difficult task. In particular, the abatement of high ammonium concentrations represents one of the main issues. Among the available techniques, struvite precipitation is an effective method for the removal and recovery of NH4+ load. However, due to the lack of phosphorus and magnesium amounts, the struvite formation results in an expensive process in the leachate treatment. To overcome this issue, in the present work, we developed a simple and suitable method for ammonium removal by the multiple recycling of struvite decomposition residues. In this regard, a procedure for acid dissolution of struvite, produced by using industrial grade reagents, was initially defined. The effect of pH, temperature, and acid type was investigated. The experimental results proved the effectiveness of both hydrochloric and acetic acid, which allow a high and selective release of ammonium at T = 50 °C and pH = 5.5. The multiple reuse of decomposition products, combined with the supplementation of a small quantity of phosphorus and magnesium at molar ratios of n(N):n(Mg):n(P) = 1:0.05:0.05, guarantees stable NH4+ abatement of about 82%. The proposed process allows a cost saving of around to 74% and can be easily applied in industrial treatment plants. Full article
Show Figures

Figure 1

Figure 1
<p>Ammonium removal during the tests conducted by using industrial grade reagents.</p>
Full article ">Figure 2
<p>Phosphorus recovery during the tests conducted by using industrial grade reagents.</p>
Full article ">Figure 3
<p>Ammonium removal during the tests conducted with the simultaneous dosage of reagents.</p>
Full article ">Figure 4
<p>Phosphorus recovery during the tests conducted with the simultaneous dosage of reagents.</p>
Full article ">Figure 5
<p>Diffractogram of solid produced from the leachate treatment using industrial-grade reagents, simultaneously dosed.</p>
Full article ">Figure 6
<p>N-NH<sub>4</sub><sup>+</sup> release (millimoles per gram of decomposed solids) detected during the struvite decomposition tests.</p>
Full article ">Figure 7
<p>P-PO<sub>4</sub><sup>3−</sup> release (millimoles per gram of decomposed solid) detected during the struvite decomposition tests.</p>
Full article ">Figure 8
<p>N:P molar ratio of dissolved ammonium and phosphorus, detected during the struvite decomposition tests.</p>
Full article ">Figure 9
<p>Diffractogram of struvite residues obtained by using HCl at 50 °C and pH = 5.5.</p>
Full article ">Figure 10
<p>N-NH<sub>4</sub><sup>+</sup> removal detected by changing the dosage of struvite residues for the treatment of raw leachate.</p>
Full article ">Figure 11
<p>Diffractogram of precipitate produced by reusing the struvite decomposition residues for the treatment of raw leachate.</p>
Full article ">Figure 12
<p>Ammonium removal during the repeated cycles conducted by using the struvite decomposition residues.</p>
Full article ">
6667 KiB  
Article
Field Measurements of Water Supply and Drainage Noise in the Bathrooms of Korea’s Multi-Residential Buildings
by Hong-Seok Yang, Hyun-Min Cho and Myung-Jun Kim
Appl. Sci. 2016, 6(11), 372; https://doi.org/10.3390/app6110372 - 22 Nov 2016
Cited by 6 | Viewed by 6262
Abstract
In Korea, water supply and drainage noises result in one of the main noise complaints because more than 50% of people reside in multi-residential buildings. In this study, a series of field measurements were therefore carried out to examine the current noise situation. [...] Read more.
In Korea, water supply and drainage noises result in one of the main noise complaints because more than 50% of people reside in multi-residential buildings. In this study, a series of field measurements were therefore carried out to examine the current noise situation. The noise levels were measured in the bathrooms of the upper and lower floors, as well as in habitable rooms. The measurement results for the bathrooms of the lower floor (N = 113) are 47.8 dBA (water closet), 42.7 dBA (basin), and 33.9 dBA (bathtub) for water drainage, while values vary between 33.7 dBA and 37.0 dBA for the water supply. The results suggest that the water drainage noise needs to be controlled first. The system bathroom (42.8 dBA) produced lower noise levels than the wet construction method (48.2 dBA) for all of the sanitary wares. The highest noise levels in the living rooms (N = 11) and bedrooms (N = 8) of the lower floor are 34.3 dBA and 39.1 dBA, respectively. The average noise level in the rooms (N = 19) is 37.8 dBA. The overall result suggests that it is necessary to develop an acoustic guideline to satisfy the higher Class of the 2nd ISO/CD 19488, although the current noise level satisfies Class C (living room) and Class D (bedroom). Full article
(This article belongs to the Special Issue Noise and Vibration Control in the Built Environment)
Show Figures

Figure 1

Figure 1
<p>The 14 floor plans of the studied housing units with different floor areas: (<b>a</b>) 33 type; (<b>b</b>) 36 type; (<b>c</b>) 46 type; (<b>d</b>) 59A type; (<b>e</b>) 59B type; (<b>f</b>) 59C type; (<b>g</b>) 74A type; (<b>h</b>) 74B type; (<b>i</b>) 74C type; (<b>j</b>) 84A type; (<b>k</b>) 84B1 type; (<b>l</b>) 84B3 type; (<b>m</b>) 84C type; (<b>n</b>) 84D type.</p>
Full article ">Figure 1 Cont.
<p>The 14 floor plans of the studied housing units with different floor areas: (<b>a</b>) 33 type; (<b>b</b>) 36 type; (<b>c</b>) 46 type; (<b>d</b>) 59A type; (<b>e</b>) 59B type; (<b>f</b>) 59C type; (<b>g</b>) 74A type; (<b>h</b>) 74B type; (<b>i</b>) 74C type; (<b>j</b>) 84A type; (<b>k</b>) 84B1 type; (<b>l</b>) 84B3 type; (<b>m</b>) 84C type; (<b>n</b>) 84D type.</p>
Full article ">Figure 2
<p>Cross-sections of bathrooms for which the (<b>a</b>) UBR system and (<b>b</b>) wet construction method had been applied.</p>
Full article ">Figure 3
<p>Illustration of the experimental setup for the measurement in the bathroom and adjacent rooms of the lower floor (59A type).</p>
Full article ">Figure 4
<p>Views of the experimental setups in (<b>a</b>) the bathroom and (<b>b</b>) the living room.</p>
Full article ">Figure 5
<p>Time history of water supply and drainage noises from the use of sanitary wares including the (<b>a</b>) water closet, (<b>b</b>) basin, and (<b>c</b>) bathtub measured at different locations (only a part of the time history has been shown due to long-time operation).</p>
Full article ">Figure 6
<p>Time history of the noise from the use of the water closet installed in 19 bathrooms of 11 housings with different floor plans (longest time with red dot: bathroom attached to the living room of the 59A type; shortest time with green dot: bathroom attached to the bedroom of the 84A type).</p>
Full article ">Figure 7
<p>Frequency spectrum of the water supply and drainage noises (L<sub>AFmax</sub>) from the use of the sanitary wares in the bathrooms attached to the living room of the upper and lower floors for the 59A type: (<b>a</b>) water closet; (<b>b</b>) basin; (<b>c</b>) bathtub.</p>
Full article ">Figure 8
<p>Average noise level for each sanitary ware measured in the bathrooms of the lower floor attached to the living room (<span class="html-italic">N</span> = 64) and bedroom (<span class="html-italic">N</span> = 49). The deviation bar indicates the range between the maximum and minimum noise levels measured in the different bathrooms.</p>
Full article ">Figure 9
<p>Frequency distribution and cumulative percentages of water supply and drainage noises (L<sub>AFmax</sub>) in the bathrooms of the lower floor from the use of the sanitary wares (<span class="html-italic">N</span> = 113).</p>
Full article ">Figure 10
<p>Average noise level for each sanitary ware according to the construction methods including the UBR system (<span class="html-italic">N</span> = 15) and wet-construction method (<span class="html-italic">N</span> = 97). The deviation bar indicates the range between the maximum and minimum noise levels measured in the different bathrooms.</p>
Full article ">Figure 11
<p>Water supply and drainage noises (L<sub>AFmax</sub>) according to the groups of low (<span class="html-italic">N</span> = 60) and high (<span class="html-italic">N</span> = 53) floors.</p>
Full article ">Figure 12
<p>Frequency spectrum of water supply and drainage noises from the use of the water closet measured in the (<b>a</b>) living room and (<b>b</b>) bedroom of the lower floor for the 59B type.</p>
Full article ">Figure 13
<p>Noise levels measured in the living room (<span class="html-italic">N</span> = 11) and bedroom (<span class="html-italic">N</span> = 8) according to the different operational conditions of each sanitary ware in 11 different floor plans: (<b>a</b>) living room; (<b>b</b>) bedroom.</p>
Full article ">Figure 14
<p>Frequency distribution and cumulative percentages of water supply and drainage noises (L<sub>AFmax</sub>) in the living room (<span class="html-italic">N</span> = 11) and bedroom (<span class="html-italic">N</span> = 8) of the lower floor from the use of the sanitary wares.</p>
Full article ">
10210 KiB  
Article
The Machining of Hard Mold Steel by Ultrasonic Assisted End Milling
by Ming Yi Tsai, Chia Tai Chang and Jihng Kuo Ho
Appl. Sci. 2016, 6(11), 373; https://doi.org/10.3390/app6110373 - 21 Nov 2016
Cited by 22 | Viewed by 8266
Abstract
This study describes the use of ultrasonic-assisted end milling to improve the quality of the machined surface of hard Stavax (modified AISI 420) mold steel and to reduce the amount of work involved in the final polishing process. The effects of input voltage, [...] Read more.
This study describes the use of ultrasonic-assisted end milling to improve the quality of the machined surface of hard Stavax (modified AISI 420) mold steel and to reduce the amount of work involved in the final polishing process. The effects of input voltage, the stretch length and cutter holding force on the amplitude of the ultrasonic vibration used were measured. The effect of ultrasonic frequency (25 and 50 kHz) and amplitude (0, 2.20 and 3.68 μm) as well as the effect of the rake angle (6° and −6°) and the cutter helix angle (25°, 35° and 45°) on tool wear and quality of the workpiece surface finish were also investigated. It was found that the ultrasonic amplitude increased with cutter stretch length and input voltage, as expected. The amplitude remained constant when the cutter holding force exceeded 15 N. The experimental results showed that the ultrasonic amplitude had an optimum value with respect to surface finish. However, large amplitude ultrasonics did not necessarily improve quality. Furthermore, the cutters used for ultrasonic-assisted milling show less wear than those used for normal milling. It was also found that a positive rake angle and cutters with a large helix angle gave a better surface finish. Full article
(This article belongs to the Special Issue Selected Papers from the 2016 International Conference on Inventions)
Show Figures

Figure 1

Figure 1
<p>The ultrasonic-assisted milling system.</p>
Full article ">Figure 2
<p>Detailed procedure flow chart.</p>
Full article ">Figure 3
<p>Variation in amplitude with input voltage for cutter stretch length of 25 and 40 mm.</p>
Full article ">Figure 4
<p>Variation in amplitude with input voltage for cutter holding force of 10, 15, 20 and 25 N.</p>
Full article ">Figure 5
<p>Variations in surface roughness (<span class="html-italic">R</span>a) for conventional milling and ultrasonic-assisted milling (amplitudes 2.20 and 3.68 μm) at frequencies of 20 and 50 kHz.</p>
Full article ">Figure 6
<p>Optical micrographs (400×) of milled sample surfaces: (<b>a</b>) Conventional milling; (<b>b</b>) with ultrasonic assistance at 20 kHz and (<b>c</b>) at 50 kHz.</p>
Full article ">Figure 6 Cont.
<p>Optical micrographs (400×) of milled sample surfaces: (<b>a</b>) Conventional milling; (<b>b</b>) with ultrasonic assistance at 20 kHz and (<b>c</b>) at 50 kHz.</p>
Full article ">Figure 7
<p>Variations in the average surface roughness (<span class="html-italic">R</span>a) of Stavax (modified AISI 420) milled with and without ultrasonic vibration using cutters with a helix angle of 25°, 35° and 45°.</p>
Full article ">Figure 8
<p>Milled surface quality: (<b>a</b>) conventional milling; (<b>b</b>) helix angle of 25°; (<b>c</b>) helix angle of 35° and (<b>d</b>) helix angle of 45° (all 500×).</p>
Full article ">Figure 9
<p>25° helix cutter surface: (<b>a</b>) unused tool; (<b>b</b>) tool after conventional milling; and (<b>c</b>) tool after ultrasonic-assisted milling (all 500×).</p>
Full article ">Figure 10
<p>35° helix cutter surface: (<b>a</b>) unused tool; (<b>b</b>) tool after conventional milling; and (<b>c</b>) tool after ultrasonic-assisted milling (all 500×).</p>
Full article ">Figure 11
<p>45° helix cutter surface: (<b>a</b>) unused tool (200×); (<b>b</b>) tool after unassisted milling (500×); and (<b>c</b>) tool after ultrasonic-assisted milling (500×).</p>
Full article ">Figure 12
<p>Variation in the average surface roughness (<span class="html-italic">R</span>a) of Stavax (modified AISI 420) machined with and without ultrasonics at cutter rake angles of 6° and −6°.</p>
Full article ">Figure 13
<p>Milled surface quality of (<b>a</b>) unassisted; (<b>b</b>) ultrasonic-assisted milling with rake angle −6°; and (<b>c</b>) cutter helix angle 45° (500×).</p>
Full article ">Figure 14
<p>Cutter surface after (<b>a</b>) unassisted milling and (<b>b</b>) ultrasonic-assisted milling with a rake angle of 6° (600×).</p>
Full article ">Figure 15
<p>Cutter surface after (<b>a</b>) unassisted milling and (<b>b</b>) ultrasonic-assisted milling with a rake angle of −6° (600×).</p>
Full article ">
15451 KiB  
Article
Land Cover Classification Using a KOMPSAT-3A Multi-Spectral Satellite Image
by Tri Dev Acharya, In Tae Yang and Dong Ha Lee
Appl. Sci. 2016, 6(11), 371; https://doi.org/10.3390/app6110371 - 21 Nov 2016
Cited by 17 | Viewed by 6834
Abstract
New sets of satellite sensors are frequently being added to the constellation of remote sensing satellites. These new sets offer improved specification to collect imagery on-demand over specific locations and for specific purposes. The Korea Multi-Purpose Satellite (KOMPSAT) series of satellites is a [...] Read more.
New sets of satellite sensors are frequently being added to the constellation of remote sensing satellites. These new sets offer improved specification to collect imagery on-demand over specific locations and for specific purposes. The Korea Multi-Purpose Satellite (KOMPSAT) series of satellites is a multi-purposed satellite system developed by Korea Aerospace Research Institute (KARI). The recent satellite of the KOMPSAT series, KOMPSAT-3A, demonstrates high resolution multi-spectral imagery with infrared and high resolution electro-optical bands for geographical information systems applications in environmental, agricultural and oceanographic sciences as well as natural disasters. In this study, land cover classification of multispectral data was performed using four supervised classification methods: Mahalanobis Distance (MahD), Minimum Distance (MinD), Maximum Likelihood (ML) and Support Vector Machine (SVM), using a KOMPSAT-3A multi-spectral imagery with 2.2 m spatial resolution. The study area for this study was selected from southwestern region of South Korea, around Buan city. The training data for supervised classification was carefully selected by visual interpretation of KOMPSAT-3A imagery and field investigation. After classification, the results were then analyzed for the validation of classification accuracy by comparison with those of field investigation. For the validation, we calculated the User’s Accuracy (UA), Producer’s Accuracy (PA), Overall Accuracy (OA) and Kappa statistics from the error matrix to check the classification accuracy for each class obtained individually from different methods. Finally, the comparative analysis was done for the study area for various results of land cover classification using a KOMPSAT-3A multi-spectral imagery. Full article
Show Figures

Figure 1

Figure 1
<p>Overall process adopted in this study where land cover classification of Korea Multi-Purpose Satellite (KOMPSAT)-3A image was done using four supervised methods i.e. Mahalanobis Distance (MahD), Minimum Distance (MinD), Maximum Likelihood (ML) and Support Vector Machine (SVM).</p>
Full article ">Figure 2
<p>Location of the study area in Korea: (<b>a</b>) Full KOMPSAT-3A scene in a natural color composite image taken on 17 June 2016; (<b>b</b>) False color composite of study area.</p>
Full article ">Figure 2 Cont.
<p>Location of the study area in Korea: (<b>a</b>) Full KOMPSAT-3A scene in a natural color composite image taken on 17 June 2016; (<b>b</b>) False color composite of study area.</p>
Full article ">Figure 3
<p>Sampling for training and validation: (<b>a</b>) Sampled polygons in the study area; (<b>b</b>) Zoomed view of a water polygon (white box on left-bottom of <a href="#applsci-06-00371-f003" class="html-fig">Figure 3</a>a); (<b>c</b>) Zoomed area with training (<b>red</b>) and validation (<b>blue</b>) pixels.</p>
Full article ">Figure 4
<p>Example of derived ratio and indices from KOMPSAT-3A bands in the study area: (<b>a</b>) Blue/Green; (<b>b</b>) Green/Red; (<b>c</b>) Normalized Difference Vegetation Index (NDVI); and (<b>d</b>) Normalized Difference Water Index (NDWI). Compositing these bands could provide better classification information for original bands.</p>
Full article ">Figure 5
<p>Land cover classification of the test site using original four bands composite: (<b>a</b>) Mahalanobis Distance (MahD); (<b>b</b>) Minimum Distance (MinD); (<b>c</b>) Maximum Likelihood (ML); and (<b>d</b>) Support Vector Machine (SVM).</p>
Full article ">Figure 6
<p>Land cover classification of the test site using ratio and indices bands composite: (<b>a</b>) MahD; (<b>b</b>) MinD; (<b>c</b>) ML; and (<b>d</b>) SVM.</p>
Full article ">
2586 KiB  
Review
Advanced Microbubbles as a Multifunctional Platform Combining Imaging and Therapy
by Xianwei Ni, Jinmin Ye, Liping Wang, Shunlong Xu, Chunpeng Zou, Yan Yang and Zhe Liu
Appl. Sci. 2016, 6(11), 365; https://doi.org/10.3390/app6110365 - 21 Nov 2016
Cited by 7 | Viewed by 5943
Abstract
Microbubbles as traditional ultrasound contrast agents have seen tremendous developments and bio-applications in the past decades. Due to their outstanding performance, advanced microbubbles as a multifunctional platform combining both imaging and therapy have been increasingly attracting attention. Associated with ultrasound-mediated stimuli, targeting drug [...] Read more.
Microbubbles as traditional ultrasound contrast agents have seen tremendous developments and bio-applications in the past decades. Due to their outstanding performance, advanced microbubbles as a multifunctional platform combining both imaging and therapy have been increasingly attracting attention. Associated with ultrasound-mediated stimuli, targeting drug transportation with high precision can be established and, as a consequence, a synergistic treatment strategy may prevail, which implies a bright perspective for this brand-new technology. This perspective article will summarize the latest developments on the advanced microbubbles, and review their emerging biomedical applications for the vast community of both applied ultrasound and functional ultrasound-based materials. Full article
(This article belongs to the Special Issue Biomedical Ultrasound)
Show Figures

Figure 1

Figure 1
<p>Arena of UCAs (ultrasound contrast agents) as a multifunctional platform combining imaging and therapy.</p>
Full article ">Figure 2
<p>Ultrasound images of MAT B III tumors in CPS (Contrast Pulse Sequencing)mode. Green outline implied tumor; red outline implied nontumoral vasculature. (<b>A</b>) Before injection of the VEGFR2-targeted microbubbles (BR55); (<b>B</b>) At 20 s after injection of BR55 (peak intensity), the tumor vasculature and nontumoral vasculature shows hyperechoic; (<b>C</b>) At 10 min after injection of BR55, only the VEGFR2-targeted microbubbles are adherent to the tumor vasculature; (<b>D</b>) At 11 min, the microbubbles in the tumor were cleared and residual circulating bubbles were waiting for refilling of the tumor. <b>Note:</b> Copyright 2010, American Chemical Society.</p>
Full article ">Figure 3
<p>Comparison of before and after i.v (intravenously) injection of (<b>A</b>) AlgNC; and (<b>B</b>) CaCO<sub>3</sub>-AlgNC in vivo ultrasound imaging of tumors showed in the red outline; (<b>C</b>) Significant differences between contrast-enhanced ratio of CaCO<sub>3</sub>-AlgNC and AlgNC post-injection. *, <span class="html-italic">p</span> &lt; 0.05, and #, <span class="html-italic">p</span> &gt; 0.05. <b>Note:</b> Copyright 2016, American Chemical Society. Abbrevation: NC: nanocarrier.</p>
Full article ">Figure 4
<p>BBB (blood-brain barrier) disruption in MRI (magnetic resonance imaging). (<b>A</b>) Four spots in the dorsal hippocampus were chosen marked with × in T2-weighted images. (<b>B</b>) Following sonication, in T1-weighted images, four hyperintense spots (marked with red arrow) illustrated BBB disruption with injection of gadolinium contrast agents (0.2 mL/kg; Omniscan, GE Healthcare, Milwaukee, WI, USA). <b>Notes:</b> Copyright 2013, American Chemical Society. Abbrevation: BBB: blood-brain barrier.</p>
Full article ">Figure 5
<p>Intravenous administration of DNAlipHep and DNAlipPEG in tumor bearing mice with UTMD (ultrasound-targeted microbubble destruction). <b>Notes:</b> Copyright 2016, American Chemical Society.</p>
Full article ">Figure 6
<p>Using focus ultrasound the tumor uptake of <sup>68</sup>Ga-A2B1 was significantly higher compared with control. <b>Notes:</b> Copyright 2014, American Chemical Society. Abbrevation: Glioblastoma, integrin α2β1, PET imaging, focus ultrasound.</p>
Full article ">
5383 KiB  
Article
Design and Implementation of an Optimal Energy Control System for Fixed-Wing Unmanned Aerial Vehicles
by Ying-Chih Lai and Wen Ong Ting
Appl. Sci. 2016, 6(11), 369; https://doi.org/10.3390/app6110369 - 19 Nov 2016
Cited by 17 | Viewed by 7758
Abstract
In conventional flight control design, the autopilot and the autothrottle systems are usually considered separately, resulting in a complex system and inefficient integration of functions. Therefore, the concept of aircraft energy control is brought up to solve the problem of coordinated control using [...] Read more.
In conventional flight control design, the autopilot and the autothrottle systems are usually considered separately, resulting in a complex system and inefficient integration of functions. Therefore, the concept of aircraft energy control is brought up to solve the problem of coordinated control using elevator and throttle. The goal of this study is to develop an optimal energy control system (OECS), based on the concept of optimal energy for fixed-wing unmanned aerial vehicles (UAVs). The energy of an aircraft is characterized by two parameters, which are specific energy distribution rate, driven by elevator, and total specific energy rate, driven by throttle. In this study, a system identification method was employed to obtain the energy model of a small UAV. The proposed approach consists of energy distribution loop and total energy loop. Energy distribution loop is designed based on linear-quadratic-Gaussian (LQG) regulator and is responsible for regulating specific energy distribution rate to zero. On the other hand, the total energy loop, based on simple gain scheduling method, is responsible for driving the error of total specific energy rate to zero. The implementation of OECS was successfully validated in the hard-in-the-loop (HIL) simulation of the applied UAV. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Flow chart of system identification process.</p>
Full article ">Figure 2
<p>Doublet input with different time steps.</p>
Full article ">Figure 3
<p>Elevator doublet with time step of 1 s as input.</p>
Full article ">Figure 4
<p>Thrust pulse with time step of 3 s as input.</p>
Full article ">Figure 5
<p>An example of identified model <span class="html-italic">ft11run10</span>.</p>
Full article ">Figure 6
<p>Model <span class="html-italic">ft10run07</span> cross-validated with data <span class="html-italic">ft10run15</span>.</p>
Full article ">Figure 7
<p>The response of the <math display="inline"> <semantics> <mrow> <mo>∆</mo> <mover> <mrow> <msub> <mi>E</mi> <mi mathvariant="normal">s</mi> </msub> </mrow> <mo>˙</mo> </mover> </mrow> </semantics> </math> with an increment of throttle input.</p>
Full article ">Figure 8
<p>Curve fit relation of <math display="inline"> <semantics> <mrow> <mo>∆</mo> <mover> <mrow> <msub> <mi>E</mi> <mi mathvariant="normal">s</mi> </msub> </mrow> <mo>˙</mo> </mover> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mo>∆</mo> <msub> <mi mathvariant="sans-serif">δ</mi> <mi mathvariant="normal">T</mi> </msub> </mrow> </semantics> </math>.</p>
Full article ">Figure 9
<p>The block diagram of the proposed OECS. OECS, optimal energy control system; LQG, linear-quadratic-Gaussian.</p>
Full article ">Figure 10
<p>Spoonbill unmanned aerial vehicle (UAV) in X-Plane flight simulator.</p>
Full article ">Figure 11
<p>Architecture of Spoonbill HIL system. HIL, hard-in-the-loop; COM, communication port; PWM, Pulse Width Modulation; RC, radio control; AHRS, attitude and heading reference system; GPS, Global Positioning System; UDP, User Datagram Protocol.</p>
Full article ">Figure 12
<p>Communication between X-Plane and onboard computer with the help of GUI program. GUI, graphic user interface.</p>
Full article ">Figure 13
<p>Simulation results of level flight without the presence of wind.</p>
Full article ">Figure 14
<p>Simulation results of level flight with the presence of wind.</p>
Full article ">Figure 15
<p>Simulation results of climbing without the presence of wind.</p>
Full article ">Figure 16
<p>Simulation results of climbing with the presence of wind.</p>
Full article ">Figure 17
<p>Simulation results of descending without the presence of wind.</p>
Full article ">Figure 18
<p>Simulation results of descending with the presence of wind.</p>
Full article ">Figure 19
<p>Fuzzy logic control (FLC) simulation results of climbing without the presence of wind.</p>
Full article ">Figure 20
<p>FLC simulation results of descending without the presence of wind.</p>
Full article ">Figure 20 Cont.
<p>FLC simulation results of descending without the presence of wind.</p>
Full article ">
689 KiB  
Article
Spectral Envelope Transformation in Singing Voice for Advanced Pitch Shifting
by José L. Santacruz, Lorenzo J. Tardón, Isabel Barbancho and Ana M. Barbancho
Appl. Sci. 2016, 6(11), 368; https://doi.org/10.3390/app6110368 - 19 Nov 2016
Cited by 3 | Viewed by 6617
Abstract
The aim of the present work is to perform a step towards more natural pitch shifting techniques in singing voice for its application in music production and entertainment systems. In this paper, we present an advanced method to achieve natural modifications when applying [...] Read more.
The aim of the present work is to perform a step towards more natural pitch shifting techniques in singing voice for its application in music production and entertainment systems. In this paper, we present an advanced method to achieve natural modifications when applying a pitch shifting process to singing voice by modifying the spectral envelope of the audio excerpt. To this end, an all-pole model has been selected to model the spectral envelope, which is estimated using a constrained non-linear optimization. The analysis of the global variations of the spectral envelope was carried out by identifying changes of the parameters of the model along with the changes of the pitch. With the obtained spectral envelope transformation functions, we applied our pitch shifting scheme to some sustained vowels in order to compare results with the same transformation made by using the Flex Pitch plugin of Logic Pro X and pitch synchronous overlap and add technique (PSOLA). This comparison has been carried out by means of both an objective and a subjective evaluation. The latter was done with a survey open to volunteers on our website. Full article
(This article belongs to the Section Acoustics and Vibrations)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Diagram of the analysis of the envelope behavior and our pitch shifting scheme with spectral envelope transformation.</p>
Full article ">Figure 2
<p>Estimation of the parameters of the spectral envelope. Harmonic component.</p>
Full article ">Figure 3
<p><math display="inline"> <semantics> <mrow> <mi>F</mi> <mn>1</mn> </mrow> </semantics> </math> evolution with pitch (<math display="inline"> <semantics> <mrow> <mi>f</mi> <mn>0</mn> </mrow> </semantics> </math>), harmonic component.</p>
Full article ">Figure 4
<p><math display="inline"> <semantics> <mrow> <mi>F</mi> <mn>2</mn> </mrow> </semantics> </math> evolution with pitch, harmonic component.</p>
Full article ">Figure 5
<p><math display="inline"> <semantics> <mrow> <mi>F</mi> <mn>3</mn> </mrow> </semantics> </math> evolution with pitch, harmonic component.</p>
Full article ">Figure 6
<p>Pitch shifting scheme with envelope transformation.</p>
Full article ">Figure 7
<p>Pitch marking using two different methods. MBS achieves smaller differences between consecutive pitch marks than the glottal closure instant (GCI).</p>
Full article ">Figure 8
<p>Magnitude of the <math display="inline"> <semantics> <mfrac> <msub> <mi>H</mi> <mn>2</mn> </msub> <msub> <mi>H</mi> <mn>1</mn> </msub> </mfrac> </semantics> </math> filter response of the harmonic component of an <math display="inline"> <semantics> <mrow> <mi>F</mi> <mn>3</mn> </mrow> </semantics> </math> note (172.6 Hz) of a male singer to be pitch shifted a fifth above.</p>
Full article ">Figure 9
<p>Magnitude of the compensation filter for pitch shifting an <math display="inline"> <semantics> <mrow> <mi>F</mi> <mn>3</mn> </mrow> </semantics> </math> note (172.6 Hz) of a male singer to be pitch shifted a fifth above.</p>
Full article ">Figure 10
<p>Continuous quality scale provided for the subjective evaluation.</p>
Full article ">Figure 11
<p>Normalized similarity (NS) of the 10 first harmonic peaks. (<b>a</b>) Magnitude of the peaks; (<b>b</b>) phase of the harmonic peaks.</p>
Full article ">Figure 12
<p>Normalized similarity of the central frequency of the first three formants. (<b>a</b>) Harmonic component; (<b>b</b>) residual component.</p>
Full article ">Figure 13
<p>Normalized similarity of the bandwidth of the first three formants. (<b>a</b>) Harmonic component; (<b>b</b>) residual component.</p>
Full article ">Figure 14
<p>Quality score. Distributions obtained with the survey for isolated notes and melodies. (<b>a</b>) Global results including all participants; (<b>b</b>) participants using headphones for the test; (<b>c</b>) participants with professional music studies or a professional music production background using headphones; (<b>d</b>) participants using headphones for the test with elementary music studies or an elementary music production background; (<b>e</b>) participants using speakers during the test.</p>
Full article ">
4704 KiB  
Article
Longitudinal Jitter Analysis of a Linear Accelerator Electron Gun
by MingShan Liu and Munawar Iqbal
Appl. Sci. 2016, 6(11), 350; https://doi.org/10.3390/app6110350 - 19 Nov 2016
Cited by 1 | Viewed by 4141
Abstract
We present measurements and analysis of the longitudinal timing jitter of a Beijing Electron Positron Collider (BEPCII) linear accelerator electron gun. We simulated the longitudinal jitter effect of the gun using PARMELA to evaluate beam performance, including: beam profile, average energy, energy spread, [...] Read more.
We present measurements and analysis of the longitudinal timing jitter of a Beijing Electron Positron Collider (BEPCII) linear accelerator electron gun. We simulated the longitudinal jitter effect of the gun using PARMELA to evaluate beam performance, including: beam profile, average energy, energy spread, and XY emittances. The maximum percentage difference of the beam parameters is calculated to be 100%, 13.27%, 42.24% and 65.01%, 86.81%, respectively. Due to this, the bunching efficiency is reduced to 54%. However, the longitudinal phase difference of the reference particle was 9.89°. The simulation results are in agreement with tests and are helpful to optimize the beam parameters by tuning the trigger timing of the gun during the bunching process. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic of the pre-injector.</p>
Full article ">Figure 2
<p>Beam current and timing measurement scheme in the pre-injector.</p>
Full article ">Figure 3
<p>Single waveform picked up by a BPM with an oscilloscope.</p>
Full article ">Figure 4
<p>Beam profile image measured by a profile monitor.</p>
Full article ">Figure 5
<p>Signal waveforms measured by the Beam Current Transformers (BCTs).</p>
Full article ">Figure 6
<p>Persistently stored waveforms measured by the BCT1 and BCT2 under the condition with certain timing jitters.</p>
Full article ">Figure 7
<p>Nominal beam parameters at the A0 exit without any timing jitter.</p>
Full article ">Figure 8
<p>Beam parameters at A0 exit with 30 ps longitudinal jitter.</p>
Full article ">Figure 9
<p>Variations in the beam energy, energy spread, and phase as a function of the gun timing.</p>
Full article ">Figure 10
<p>Variations in the <span class="html-italic">x</span> and <span class="html-italic">y</span> normalized emittance as a function of the gun timing.</p>
Full article ">Figure 11
<p>Variations in the bunching efficiency as a function of the gun timing.</p>
Full article ">
1099 KiB  
Communication
Feasibility Study of a Gripper with Thermally Controlled Stiffness of Compliant Jaws
by Guangbo Hao and Mehdi Riza
Appl. Sci. 2016, 6(11), 367; https://doi.org/10.3390/app6110367 - 18 Nov 2016
Cited by 7 | Viewed by 4231
Abstract
This paper proposes a simple and compact compliant gripper, whose gripping stiffness can be thermally controlled to accommodate the actuation inaccuracy to avoid or reduce the risk of breaking objects. The principle of reducing jaw stiffness is that thermal change can cause an [...] Read more.
This paper proposes a simple and compact compliant gripper, whose gripping stiffness can be thermally controlled to accommodate the actuation inaccuracy to avoid or reduce the risk of breaking objects. The principle of reducing jaw stiffness is that thermal change can cause an initial internal compressive force along each compliant beam. A prototype is fabricated with physical testing to verify the feasibility. It has been shown that when a voltage is applied, the gripping stiffness effectively reduces to accommodate more inaccuracy of actuation, which allows delicate or small-scale objects to be gripped. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic design of the proposed monolithic symmetrical gripper.</p>
Full article ">Figure 2
<p>Fully assembled asymmetrical gripper shown next to a hand for reference (<b>above</b>); top plate removed, revealing the heating coil (<b>below</b>).</p>
Full article ">Figure 3
<p>Testing results of the jaw mechanism with and without heat.</p>
Full article ">
925 KiB  
Article
Validation of a Numerical Model for the Prediction of the Annoyance Condition at the Operator Station of Construction Machines
by Eleonora Carletti and Francesca Pedrielli
Appl. Sci. 2016, 6(11), 363; https://doi.org/10.3390/app6110363 - 18 Nov 2016
Cited by 4 | Viewed by 3864
Abstract
It is well-known that the reduction of noise levels is not strictly linked to the reduction of noise annoyance. Even earthmoving machine manufacturers are facing the problem of customer complaints concerning the noise quality of their machines with increasing frequency. Unfortunately, all the [...] Read more.
It is well-known that the reduction of noise levels is not strictly linked to the reduction of noise annoyance. Even earthmoving machine manufacturers are facing the problem of customer complaints concerning the noise quality of their machines with increasing frequency. Unfortunately, all the studies geared to the understanding of the relationship between multidimensional characteristics of noise signals and the auditory perception of annoyance require repeated sessions of jury listening tests, which are time-consuming. In this respect, an annoyance prediction model was developed for compact loaders to assess the annoyance sensation perceived by operators at their workplaces without repeating the full sound quality assessment but using objective parameters only. This paper aims at verifying the feasibility of the developed annoyance prediction model when applied to other kinds of earthmoving machines. For this purpose, an experimental investigation was performed on five earthmoving machines, different in type, dimension, and engine mechanical power, and the annoyance predicted by the numerical model was compared to the annoyance given by subjective listening tests. The results were evaluated by means of the squared value of the correlation coefficient, R2, and they confirm the possible applicability of the model to other kinds of machines. Full article
(This article belongs to the Special Issue Noise and Vibration Control in the Built Environment)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Sound pressure levels for all the six sound stimuli recorded at the right ear.</p>
Full article ">Figure 2
<p>Comparison of the predicted and observed values of annoyance with different numerical regression models.</p>
Full article ">Figure 3
<p>Comparison between the regressions obtained with and without Stimulus F, for each prediction model (<b>a</b>) <span class="html-italic">Y</span><sub>1</sub>; (<b>b</b>) <span class="html-italic">Y</span><sub>2</sub>; (<b>c</b>) <span class="html-italic">Y</span><sub>3</sub>; (<b>d</b>) <span class="html-italic">Y</span><sub>4</sub>; (<b>e</b>) <span class="html-italic">Y</span><sub>5</sub>; (<b>f</b>) <span class="html-italic">Y</span><sub>6</sub>.</p>
Full article ">Figure 3 Cont.
<p>Comparison between the regressions obtained with and without Stimulus F, for each prediction model (<b>a</b>) <span class="html-italic">Y</span><sub>1</sub>; (<b>b</b>) <span class="html-italic">Y</span><sub>2</sub>; (<b>c</b>) <span class="html-italic">Y</span><sub>3</sub>; (<b>d</b>) <span class="html-italic">Y</span><sub>4</sub>; (<b>e</b>) <span class="html-italic">Y</span><sub>5</sub>; (<b>f</b>) <span class="html-italic">Y</span><sub>6</sub>.</p>
Full article ">Figure 4
<p>Comparison between the annoyance values predicted by <span class="html-italic">Y</span><sub>3</sub> and those obtained by subjective listening tests.</p>
Full article ">
804 KiB  
Article
A Calibration Method for Nonlinear Mismatches in M-Channel Time-Interleaved Analog-to-Digital Converters Based on Hadamard Sequences
by Husheng Liu, Yinan Wang, Nan Li and Hui Xu
Appl. Sci. 2016, 6(11), 362; https://doi.org/10.3390/app6110362 - 18 Nov 2016
Cited by 5 | Viewed by 4667
Abstract
The time-interleaved analog-to-digital converter (TIADC) is an architecture used to achieve a high sampling rate and high dynamic performance. However, estimation and compensation methods are required to maintain the dynamic performance of the constituent analog-to-digital converters (ADCs) due to channel mismatches. This paper [...] Read more.
The time-interleaved analog-to-digital converter (TIADC) is an architecture used to achieve a high sampling rate and high dynamic performance. However, estimation and compensation methods are required to maintain the dynamic performance of the constituent analog-to-digital converters (ADCs) due to channel mismatches. This paper proposes a blind adaptive method to calibrate the nonlinear mismatches in M-channel TIADCs (M-TIADCs). The nonlinearity-induced error signal is reconstructed by the proposed multiplier Hadamard transform (MHT) structure, and the nonlinear parameters are estimated by the filtered-X least-mean square (FxLMS) algorithm. The performance of cascade calibration is also analyzed. The numerical simulation results show that the proposed method consumes much less hardware resources while maintaining the calibration performance. Full article
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) A time-interleaved analog-to-digital converter (ADC) consists of <span class="html-italic">M</span> sub-ADCs; (<b>b</b>) timing diagram of the sampling clocks. MUX, Multiplexer; CLK, Clock.</p>
Full article ">Figure 2
<p>Nonlinear mismatches in the <span class="html-italic">M</span>-time-interleaved analog-to-digital converter (TIADC) are interpreted as the sum of a series of gain-mismatched <span class="html-italic">M</span>-TIADCs.</p>
Full article ">Figure 3
<p>(<b>a</b>) Model of <span class="html-italic">M</span>-TIADC with nonlinear mismatches; (<b>b</b>) the detail of the Hadamard transform (HT) block.</p>
Full article ">Figure 4
<p>Calibration structure for nonlinear mismatches in <span class="html-italic">M</span>-TIADCs. The HT block is the same as <a href="#applsci-06-00362-f003" class="html-fig">Figure 3</a>b, where the parameters <math display="inline"> <semantics> <msub> <mi>c</mi> <mrow> <mi>k</mi> <mo>,</mo> <mi>l</mi> </mrow> </msub> </semantics> </math> are replaced by the estimated parameters <math display="inline"> <semantics> <mrow> <msub> <mover accent="true"> <mi>c</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <mi>l</mi> </mrow> </msub> <mrow> <mo>[</mo> <mi>n</mi> <mo>]</mo> </mrow> </mrow> </semantics> </math>.</p>
Full article ">Figure 5
<p>Adaptive calibration structure exploiting the filtered-X least mean square (FxLMS) algorithm.</p>
Full article ">Figure 6
<p>The structure of the <span class="html-italic">i</span>-th stage calibration structure.</p>
Full article ">Figure 7
<p>The spectra of 4-TIADC output (<b>a</b>) before and (<b>b</b>) after calibration.</p>
Full article ">Figure 8
<p>The convergence behavior of the estimated parameters <math display="inline"> <semantics> <mrow> <msub> <mover accent="true"> <mi>c</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <mi>l</mi> </mrow> </msub> <mrow> <mo>[</mo> <mi>n</mi> <mo>]</mo> </mrow> </mrow> </semantics> </math>. (<b>a</b>) Second order nonlinear parameters; (<b>b</b>) third order nonlinear parameters.</p>
Full article ">Figure 9
<p>The spectra of 8-TIADC (<b>a</b>) before and (<b>b</b>) after calibration.</p>
Full article ">Figure 10
<p>The spectra of 4-TIADC output with and without calibration for dual band noise input.</p>
Full article ">Figure 11
<p>The convergence behavior of the estimated parameters <math display="inline"> <semantics> <mrow> <msub> <mover accent="true"> <mi>c</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <mi>l</mi> </mrow> </msub> <mrow> <mo>[</mo> <mi>n</mi> <mo>]</mo> </mrow> </mrow> </semantics> </math> for dual band noise input. (<b>a</b>) Second order nonlinear parameters; (<b>b</b>) third order nonlinear parameters.</p>
Full article ">Figure 12
<p>The spectra of 4-TIADC output (<b>a</b>) before and (<b>b</b>) after calibration for bandpass multi-tone sinusoidal signal input.</p>
Full article ">Figure 13
<p>(<b>a</b>) Complexity and (<b>b</b>) complexity ratio under different numbers of channels and orders of the nonlinearity. BWE, bandwidth efficient.</p>
Full article ">Figure 14
<p>Performance (signal to noise and distortion ratio (SNDR) and spurious-free dynamic range (SFDR)) improvement under different orders of the high pass filter.</p>
Full article ">Figure 15
<p>The spectra of 4-TIADC output. (<b>a</b>) Without calibration; (<b>b</b>) one-stage calibration; (<b>c</b>) two-stage calibration.</p>
Full article ">Figure 16
<p>The mean square deviation (MSD) of one-stage calibration and two-stage calibration.</p>
Full article ">Figure 17
<p>The SNDR of calibrated 4-TIADC output with different strengths of nonlinear mismatches.</p>
Full article ">
7703 KiB  
Article
Harmonic Differential Quadrature Analysis of Soft-Core Sandwich Panels under Locally Distributed Loads
by Xinwei Wang and Zhangxian Yuan
Appl. Sci. 2016, 6(11), 361; https://doi.org/10.3390/app6110361 - 18 Nov 2016
Cited by 5 | Viewed by 4800
Abstract
Sandwich structures are widely used in practice and thus various engineering theories adopting simplifying assumptions are available. However, most engineering theories of beams, plates and shells cannot recover all stresses accurately through their constitutive equations. Therefore, the soft-core is directly modeled by two-dimensional [...] Read more.
Sandwich structures are widely used in practice and thus various engineering theories adopting simplifying assumptions are available. However, most engineering theories of beams, plates and shells cannot recover all stresses accurately through their constitutive equations. Therefore, the soft-core is directly modeled by two-dimensional (2D) elasticity theory without any pre-assumption on the displacement field. The top and bottom faces act like the elastic supports on the top and bottom edges of the core. The differential equations of the 2D core are then solved by the harmonic differential quadrature method (HDQM). To circumvent the difficulties in dealing with the locally distributed load by point discrete methods such as the HDQM, a general and rigorous way is proposed to treat the locally distributed load. Detailed formulations are provided. The static behavior of sandwich panels under different locally distributed loads is investigated. For verification, results are compared with data obtained by ABAQUS with very fine meshes. A high degree of accuracy on both displacement and stress has been observed. Full article
Show Figures

Figure 1

Figure 1
<p>Sketch of a sandwich panel with a soft core.</p>
Full article ">Figure 2
<p>Sketch of the top face, bottom face and the core of a sandwich panel. (<b>a</b>) top face; (<b>b</b>) core; (<b>c</b>) bottom face.</p>
Full article ">Figure 3
<p>Comparisons of iso-displacement (<math display="inline"> <semantics> <mrow> <mi>u</mi> <mo>/</mo> <msub> <mi>w</mi> <mi>n</mi> </msub> </mrow> </semantics> </math>) diagram for sandwich panels under locally distributed loads (<span class="html-italic">Lp</span> = 0.1<span class="html-italic">L</span>): (<b>a</b>) HDQM (harmonic differential quadrature method); and (<b>b</b>) ABAQUS.</p>
Full article ">Figure 4
<p>Comparisons of iso-displacement (<math display="inline"> <semantics> <mrow> <mi>w</mi> <mo>/</mo> <msub> <mi>w</mi> <mi>n</mi> </msub> </mrow> </semantics> </math>) diagram for sandwich panels under locally distributed loads (<span class="html-italic">L<sub>p</sub></span> = 0.1<span class="html-italic">L</span>): (<b>a</b>) HDQM; and (<b>b</b>) ABAQUS.</p>
Full article ">Figure 5
<p>Comparisons of iso-stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">σ</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) diagram for sandwich panels under locally distributed loads (<span class="html-italic">L<sub>p</sub></span> = 0.1<span class="html-italic">L</span>): (<b>a</b>) HDQM; and (<b>b</b>) ABAQUS.</p>
Full article ">Figure 6
<p>Comparisons of iso-stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">σ</mi> <mrow> <mi>z</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) diagram for sandwich panels under locally distributed loads (<span class="html-italic">L<sub>p</sub></span> = 0.1<span class="html-italic">L</span>): (<b>a</b>) HDQM; and (<b>b</b>) ABAQUS.</p>
Full article ">Figure 7
<p>Comparisons of iso-displacement (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) diagram for sandwich panels under locally distributed loads (<span class="html-italic">L<sub>p</sub></span> = 0.1<span class="html-italic">L</span>): (<b>a</b>) HDQM; and (<b>b</b>) ABAQUS.</p>
Full article ">Figure 8
<p>Comparison of stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">σ</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) of sandwich panels at <span class="html-italic">x</span> = −0.0464<span class="html-italic">L</span>.</p>
Full article ">Figure 9
<p>Comparison of stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">σ</mi> <mrow> <mi>z</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) of sandwich panels at <span class="html-italic">x</span> = −0.0464<span class="html-italic">L</span>.</p>
Full article ">Figure 10
<p>Comparison of shear stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) of sandwich panels at <span class="html-italic">x</span> = −0.0464<span class="html-italic">L</span>.</p>
Full article ">Figure 11
<p>Through-thickness distribution of the shear stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) for sandwich panels under different loadings (<span class="html-italic">x</span> = −0.0464<span class="html-italic">L</span>).</p>
Full article ">Figure 12
<p>Through-thickness distribution of the shear stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) for sandwich panels under different loadings (<span class="html-italic">x</span> = −0.4726<span class="html-italic">L</span>).</p>
Full article ">Figure 13
<p>Iso-stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">σ</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) diagrams for sandwich panels under various locally distributed loads: (<b>a</b>) <span class="html-italic">L<sub>p</sub></span> = <span class="html-italic">L</span>; (<b>b</b>) <span class="html-italic">L<sub>p</sub></span> = 0.5<span class="html-italic">L</span>; (<b>c</b>) <span class="html-italic">L<sub>p</sub></span> = 0.2<span class="html-italic">L</span>; (<b>d</b>) <span class="html-italic">L<sub>p</sub></span> = 0.01<span class="html-italic">L</span>; and (<b>e</b>) <span class="html-italic">L<sub>p</sub></span> = 0.001.</p>
Full article ">Figure 13 Cont.
<p>Iso-stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">σ</mi> <mrow> <mi>x</mi> <mi>x</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) diagrams for sandwich panels under various locally distributed loads: (<b>a</b>) <span class="html-italic">L<sub>p</sub></span> = <span class="html-italic">L</span>; (<b>b</b>) <span class="html-italic">L<sub>p</sub></span> = 0.5<span class="html-italic">L</span>; (<b>c</b>) <span class="html-italic">L<sub>p</sub></span> = 0.2<span class="html-italic">L</span>; (<b>d</b>) <span class="html-italic">L<sub>p</sub></span> = 0.01<span class="html-italic">L</span>; and (<b>e</b>) <span class="html-italic">L<sub>p</sub></span> = 0.001.</p>
Full article ">Figure 14
<p>Iso-stress (<math display="inline"> <semantics> <mrow> <msub> <mi>σ</mi> <mrow> <mi>z</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) diagrams for sandwich panels under various locally distributed loads: (<b>a</b>) <span class="html-italic">L<sub>p</sub></span> = <span class="html-italic">L</span>; (<b>b</b>) <span class="html-italic">L<sub>p</sub></span> = 0.5<span class="html-italic">L</span>; (<b>c</b>) <span class="html-italic">L<sub>p</sub></span> = 0.2<span class="html-italic">L</span>; (<b>d</b>) <span class="html-italic">L<sub>p</sub></span> = 0.01<span class="html-italic">L</span>; and (<b>e</b>) <span class="html-italic">L<sub>p</sub></span> = 0.001.</p>
Full article ">Figure 15
<p>Iso-stress (<math display="inline"> <semantics> <mrow> <msub> <mi mathvariant="sans-serif">τ</mi> <mrow> <mi>x</mi> <mi>z</mi> </mrow> </msub> <mo>/</mo> <mi>q</mi> </mrow> </semantics> </math>) diagrams for sandwich panels under various locally distributed loads: (<b>a</b>) <span class="html-italic">L<sub>p</sub></span> = <span class="html-italic">L</span>; (<b>b</b>) <span class="html-italic">L<sub>p</sub></span> = 0.5<span class="html-italic">L</span>; (<b>c</b>) <span class="html-italic">L<sub>p</sub></span> = 0.2<span class="html-italic">L</span>; (<b>d</b>) <span class="html-italic">L<sub>p</sub></span> = 0.01<span class="html-italic">L</span>; and (<b>e</b>) <span class="html-italic">L<sub>p</sub></span> = 0.001.</p>
Full article ">
3256 KiB  
Article
Extending the Effective Ranging Depth of Spectral Domain Optical Coherence Tomography by Spatial Frequency Domain Multiplexing
by Tong Wu, Qingqing Wang, Youwen Liu, Jiming Wang, Chongjun He and Xiaorong Gu
Appl. Sci. 2016, 6(11), 360; https://doi.org/10.3390/app6110360 - 17 Nov 2016
Cited by 5 | Viewed by 7282
Abstract
We present a spatial frequency domain multiplexing method for extending the imaging depth range of a spectral domain optical coherence tomography (SDOCT) system without any expensive device. This method uses two galvo scanners with different pivot-offset distances in two independent reference arms for [...] Read more.
We present a spatial frequency domain multiplexing method for extending the imaging depth range of a spectral domain optical coherence tomography (SDOCT) system without any expensive device. This method uses two galvo scanners with different pivot-offset distances in two independent reference arms for spatial frequency modulation and multiplexing. The spatial frequency contents corresponding to different depth regions of the sample can be shifted to different frequency bands. The spatial frequency domain multiplexing SDOCT system provides an approximately 1.9-fold increase in the effective ranging depth compared with that of a conventional full-range SDOCT system. The reconstructed images of phantom and biological tissue demonstrate the expected increase in ranging depth. The parameters choice criterion for this method is discussed. Full article
(This article belongs to the Special Issue Development and Application of Optical Coherence Tomography (OCT))
Show Figures

Figure 1

Figure 1
<p>Schematic of the spatial frequency domain multiplexing spectral domain optical coherence tomography (SDOCT) system. SLD: super luminescent diode; FC: fiber coupler; NPBS: non-polarizing beam splitter; M: reference mirror; GS: galvanometer scanner; L: lens; SMP: sample; COL: collimator; PC: polarization controller; DG: diffraction grating; COMP: computer; CMOS: complementary metal oxide semiconductor.</p>
Full article ">Figure 2
<p>Data processing flowchart of the spatial frequency domain multiplexing SDOCT system. FT: Fourier Transform.</p>
Full article ">Figure 3
<p>Sketch of the two reference arms in the spatial frequency domain multiplexing SDOCT system. <span class="html-italic">s</span><sub>1</sub> and <span class="html-italic">s</span><sub>2</sub>: the pivot-offset distances; L1 and L2: the focal lens in the reference arms; M1 and M2: the plane mirrors; f: focal length of the focal lens.</p>
Full article ">Figure 4
<p>Schematic of the choice of the center spatial carrier frequencies. Crosstalk between the spatial spectra occurs in (<b>a</b>), and the two spatial spectra can be well separated through parameters design as shown in (<b>b</b>).</p>
Full article ">Figure 5
<p>The measured sensitivity curves corresponding to the Reference Arm I and Reference Arm II.</p>
Full article ">Figure 6
<p>(<b>a</b>) The photograph of the artificial phantom of a step comprised of two blocks of sellotape. The red line is the lateral scan position on the phantom; (<b>b</b>,<b>c</b>) the cross-sectional optical coherence tomography (OCT) image of the phantom acquired with the conventional single-reference-arm approach; (<b>d</b>) the extended range OCT image acquired with the proposed two-reference-arm spatial frequency domain multiplexing approach. The blurry horizontal white line is the residual direct current (DC) term.</p>
Full article ">Figure 7
<p>Cross-sectionalOCT image of the swine adipose tissue, (<b>a</b>,<b>b</b>) acquired with the conventional single-reference-arm approach. (<b>c</b>) The extended range OCT image is obtained with the two-reference–arm spatial frequency domain multiplexing approach. The blurry horizontal white line is the residual DC terms. (<b>d</b>) A-scans at the position marked by the red arrows in (<b>a</b>,<b>b</b>) demonstrate the advantage of the ranging depth extension.</p>
Full article ">
5379 KiB  
Article
A Sibelobe Suppressing Beamformer for Coherent Plane Wave Compounding
by Wei Guo, Yuanyuan Wang and Jinhua Yu
Appl. Sci. 2016, 6(11), 359; https://doi.org/10.3390/app6110359 - 17 Nov 2016
Cited by 16 | Viewed by 5806
Abstract
Contrast degradation is a critical problem in ultrasound plane wave imaging (PWI) resulting from signals leakage from the sidelobes. An ideal sidelobe reduction method may enhance the contrast without remarkably increasing computational load. To this end, we introduce a new singular value decomposition [...] Read more.
Contrast degradation is a critical problem in ultrasound plane wave imaging (PWI) resulting from signals leakage from the sidelobes. An ideal sidelobe reduction method may enhance the contrast without remarkably increasing computational load. To this end, we introduce a new singular value decomposition (SVD) sidelobe reduction beamformer for coherent plane wave compounding (CPWC) based on a previous work. The SVD takes advantage of the benefits of the different features of the mainlobe and sibelobe in terms of spatio-angular coherence and removes the sidelobes before the final coherent summation. This SVD-based method provides a three-dimensional approach (2D in the space and 1D in the angle) while the computation load is kept satisfactory by a dimension-reduced operation before the SVD. To directly observe the sidelobe level, we demonstrate the performance of our SVD method with a point spread function (PSF) simulation. Compared to CPWC, our method shows a 6.2 dB reduction in the peak sidelobe level (PSL). We also applied our method to the anechoic cyst inside the speckle for the imaging contrast. Both in the simulation and phantom studies, our method enhances the contrast-to-noise ratio (CNR) by more than 10%. Therefore, this new beamformer can be an efficient way to suppress sidelobes in PWI. Full article
(This article belongs to the Special Issue Biomedical Ultrasound)
Show Figures

Figure 1

Figure 1
<p>Sidelobe and mainlobe for a simulated point target.</p>
Full article ">Figure 2
<p>Plane wave firings with different steering angles for coherent plane wave compounding (CPWC). The cyst target is within the overlapped region of all plane waves.</p>
Full article ">Figure 3
<p>The CPWC acquisitions form a 3D stack of images with two spatial dimensions (<span class="html-italic">n<sub>x</sub></span>, <span class="html-italic">n<sub>z</sub></span>) and one angular dimension (<span class="html-italic">n<sub>a</sub></span>). It is reshaped in a 2D spatio-angular representation (<span class="html-italic">P</span>) where all pixels at one angle are arranged in one column (<span class="html-italic">n<sub>x</sub></span>.<span class="html-italic">n<sub>z</sub></span>). As a consequence, all angle points for one pixel are arranged in one row (<span class="html-italic">n<sub>a</sub></span>).</p>
Full article ">Figure 4
<p>The graphical explanation of the proposed singular value decomposition (SVD) filter (<b><span class="html-italic">N</span></b> represents the rank of matrix <b><span class="html-italic">P</span></b>).</p>
Full article ">Figure 5
<p>The covariance matrix of dimension <math display="inline"> <semantics> <mrow> <msub> <mi>n</mi> <mi>a</mi> </msub> <mo>×</mo> <msub> <mi>n</mi> <mi>a</mi> </msub> </mrow> </semantics> </math> is presented here.</p>
Full article ">Figure 6
<p>Beamformed responses of the simulated point spread function (PSF): (<b>a</b>) CPWC; (<b>b</b>) CPWC with Hamming window; and (<b>c</b>) CPWC + SVD. All images are shown with a dynamic range of 60 dB.</p>
Full article ">Figure 7
<p>The lateral variation of CPWC, CPWC + Hamming window and CPWC + SVD at the depth of 20 mm.</p>
Full article ">Figure 8
<p>Beamformed images of simulated cyst phantom: (<b>a</b>) CPWC; (<b>b</b>) CPWC with Hamming window; and (<b>c</b>) CPWC + SVD. All images are shown with a dynamic range of 60 dB.</p>
Full article ">Figure 9
<p>Beamformed images of a point and a hyperechoic region phantom: (<b>a</b>) CPWC; (<b>b</b>) CPWC with Hamming window; and (<b>c</b>) CPWC + SVD. All images are shown with a dynamic range of 60 dB.</p>
Full article ">Figure 10
<p>Beamformed images of cyst phantom: (<b>a</b>) CPWC; (<b>b</b>) CPWC with Hamming window; and (<b>c</b>) CPWC + SVD. All images are shown with a dynamic range of 60 dB.</p>
Full article ">Figure 11
<p>Beamformed responses of the simulated PSF: (<b>a</b>) CPWC using five angles; (<b>b</b>) CPWC using 11 angles; (<b>c</b>) CPWC using 21 angles; (<b>d</b>) CPWC + SVD using five angles; (<b>e</b>) CPWC + SVD using 11 angles; and (<b>f</b>) CPWC + SVD using 21 angles. All images are shown with a dynamic range of 60 dB.</p>
Full article ">
2053 KiB  
Article
TRAP: A Three-Way Handshake Server for TCP Connection Establishment
by Fu-Hau Hsu, Yan-Ling Hwang, Cheng-Yu Tsai, Wei-Tai Cai, Chia-Hao Lee and KaiWei Chang
Appl. Sci. 2016, 6(11), 358; https://doi.org/10.3390/app6110358 - 16 Nov 2016
Cited by 16 | Viewed by 32702
Abstract
Distributed denial of service attacks have become more and more frequent nowadays. In 2013, a massive distributed denial of service (DDoS) attack was launched against Spamhaus causing the service to shut down. In this paper, we present a three-way handshaking server for Transmission [...] Read more.
Distributed denial of service attacks have become more and more frequent nowadays. In 2013, a massive distributed denial of service (DDoS) attack was launched against Spamhaus causing the service to shut down. In this paper, we present a three-way handshaking server for Transmission Control Protocol (TCP) connection redirection utilizing TCP header options. When a legitimate client attempted to connect to a server undergoing an SYN-flood DDoS attack, it will try to initiate a three-way handshake. After it has successfully established a connection, the server will reply with a reset (RST) packet, in which a new server address and a secret is embedded. The client can, thus, connect to the new server that only accepts SYN packets with the corrected secret using the supplied secret. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>TCP three-way handshake diagram. TCP, Transmission Control Protocol; SYN, Synchronize; ACK, Acknowledgement.</p>
Full article ">Figure 2
<p>Illustration of SYN flood attacks.</p>
Full article ">Figure 3
<p>TCP header format (reference source: RFC-793) [<a href="#B6-applsci-06-00358" class="html-bibr">6</a>].</p>
Full article ">Figure 4
<p>Netfilter hooks diagram (reference source: netfilter.org) [<a href="#B11-applsci-06-00358" class="html-bibr">11</a>].</p>
Full article ">Figure 5
<p>Illustration of TCP Cookies.</p>
Full article ">Figure 6
<p>System overview.</p>
Full article ">Figure 7
<p>System design.</p>
Full article ">Figure 8
<p>Acquiring packet buffer using libpcap.</p>
Full article ">Figure 9
<p>Example code of acquiring packets using Netfilter hooks.</p>
Full article ">Figure 10
<p>Packet dump viewed by Wireshark.</p>
Full article ">
557 KiB  
Article
Energy-Efficient On–Off Power Control of Femto-Cell Base Stations for Cooperative Cellular Networks
by Woongsup Lee and Bang Chul Jung
Appl. Sci. 2016, 6(11), 356; https://doi.org/10.3390/app6110356 - 16 Nov 2016
Cited by 2 | Viewed by 4154
Abstract
Improving energy efficiency (EE) of mobile communication systems (MCSs) has been considered a key aim in recent years, and has been the subject of intense research interest. One of the simplest yet most powerful ways to increase the EE is to turn off [...] Read more.
Improving energy efficiency (EE) of mobile communication systems (MCSs) has been considered a key aim in recent years, and has been the subject of intense research interest. One of the simplest yet most powerful ways to increase the EE is to turn off redundant communication entities whose operation does not greatly affect the overall performance of the MCS. In this paper, we propose a novel on–off power control scheme for femto-cell base stations (FBSs) considering cooperative transmission in which multiple FBSs collaborate on the same data transmission. In the proposed scheme, the operation of the redundant FBSs is halted in an adaptive manner. For the proper determination of redundant FBSs with low computational complexity, we propose using the level of contribution (LOC), which specifies the importance of a given FBS in the cooperative transmission. Redundant FBSs are chosen based on their LOC value, and these FBSs are turned off in order to reduce the power consumption of MCSs while minimizing the degradation of the overall throughput of cooperative transmissions. The performance of the proposed scheme is verified through extensive simulations, which shows that near-optimal performance can be achieved without excessive computations. Full article
Show Figures

Figure 1

Figure 1
<p>Toy example that depicts the limitation of conventional on–off power control scheme.</p>
Full article ">Figure 2
<p>System model which depicts femto-cell base stations (FBSs) with cooperative transmission, MS: mobile station.</p>
Full article ">Figure 3
<p>Procedure of proposed on–off power control scheme, LOC: level of contribution.</p>
Full article ">Figure 4
<p>Number of active FBSs vs. <span class="html-italic">ϵ</span> by varying <span class="html-italic">N</span>.</p>
Full article ">Figure 5
<p>Spectral efficiency vs. <span class="html-italic">ϵ</span> by varying <span class="html-italic">N</span>.</p>
Full article ">Figure 6
<p>Relative power consumption of FBSs vs. <span class="html-italic">σ</span> by varying <span class="html-italic">N</span>.</p>
Full article ">Figure 7
<p>Spectral efficiency vs. <span class="html-italic">σ</span> by varying <span class="html-italic">N</span>.</p>
Full article ">Figure 8
<p>Computation time vs. <span class="html-italic">N</span>.</p>
Full article ">
1240 KiB  
Article
Compact Aberration-Free Relay-Imaging Multi-Pass Layouts for High-Energy Laser Amplifiers
by Jörg Körner, Joachim Hein and Malte Christoph Kaluza
Appl. Sci. 2016, 6(11), 353; https://doi.org/10.3390/app6110353 - 16 Nov 2016
Cited by 12 | Viewed by 5580
Abstract
We present the results from a theoretical investigation of laser beam propagation in relay imaging multi-pass layouts, which recently found application in high-energy laser amplifiers. Using a method based on the well-known ABCD-matrix formalism and proven by ray tracing, it was possible to [...] Read more.
We present the results from a theoretical investigation of laser beam propagation in relay imaging multi-pass layouts, which recently found application in high-energy laser amplifiers. Using a method based on the well-known ABCD-matrix formalism and proven by ray tracing, it was possible to derive a categorization of such systems. Furthermore, basic rules for the setup of such systems and the compensation for low order aberrations are derived. Due to the introduced generalization and parametrization, the presented results can immediately be applied to any system of the investigated kinds for a wide range of parameters, such as number of round-trips, focal lengths and optics sizes. It is shown that appropriate setups allow a close-to-perfect compensation of defocus caused by a thermal lens and astigmatism caused by non-normal incidence on the imaging optics, as well. Both are important to avoid intensity spikes leading to damages of optics in multi-pass laser amplifiers. Full article
(This article belongs to the Section Optics and Lasers)
Show Figures

Figure 1

Figure 1
<p>Schematic drawings of Type I systems with three round-trips based on lenses (<b>a</b>) and on mirrors (<b>b</b>) as imaging elements. The numbers in the arrows denote the sequence of passing beams.</p>
Full article ">Figure 2
<p>Schematic drawings of Type II systems with three round-trips based on lenses (<b>a</b>) and on mirrors (<b>b</b>) as imaging elements. The numbers in the arrows denote the sequence of passing beams.</p>
Full article ">Figure 3
<p>Inverse absolute value of the radius <math display="inline"> <semantics> <msub> <mi>R</mi> <mi>o</mi> </msub> </semantics> </math> as a function of the focal width of a thermal lens <math display="inline"> <semantics> <msub> <mi>f</mi> <mi>t</mi> </msub> </semantics> </math> for compensated and uncompensated relay imaging systems with 5 round-trips. Results were derived from ray-tracing simulation. Values small than 10<math display="inline"> <semantics> <mrow> <msup> <mrow/> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mspace width="0.166667em"/> <mfrac bevelled="true"> <mrow> <mn>1</mn> <mspace width="-1.111pt"/> </mrow> <mrow> <mspace width="-0.55542pt"/> <mi mathvariant="normal">m</mi> </mrow> </mfrac> </mrow> </semantics> </math> can be considered as numerical noise.</p>
Full article ">Figure 4
<p>Three dimensional setup of the basic layouts for Type I (<b>a</b>) and Type II (<b>b</b>) systems in FRED. Both layouts have a half folding angle of <span class="html-italic">θ</span> = 5° and five passes.</p>
Full article ">Figure 5
<p>Change in beam diameter in the tangential and sagittal plane as a function of the folding angle <span class="html-italic">θ</span> for Type I and Type II systems for up to five round-trips.</p>
Full article ">Figure 6
<p>Absolute astigmatic deformation of the wavefront as a function of the incidence angle on optic <math display="inline"> <semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics> </math> for Type I and Type II systems. Lines are calculated by the matrix method, and single data points originate from FRED ray tracings.</p>
Full article ">Figure 7
<p>Upper image: arrangement of passes on optic <math display="inline"> <semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics> </math> for different numbers of round-trips. The numbers denote the sequence of hits on the optic <math display="inline"> <semantics> <msub> <mi>L</mi> <mn>2</mn> </msub> </semantics> </math>. Center image: parameters for folding angles on <math display="inline"> <semantics> <msub> <mi>L</mi> <mn>2</mn> </msub> </semantics> </math> due to the round-trips in a Type II system with four round-trips. Lower image: parameters for folding angles on <math display="inline"> <semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics> </math> due to the round-trips in a Type I system with four round-trips.</p>
Full article ">Figure 8
<p>Absolute astigmatic deformation of the wavefront as a function of the ratio between the diameter <span class="html-italic">D</span> of optic <math display="inline"> <semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics> </math> and its focal width <span class="html-italic">f</span> for Type I and Type II systems. Lines are calculated by the matrix method, and single data points originate from FRED ray tracings.</p>
Full article ">Figure 9
<p>Evolution of the astigmatic deformation of the wavefront for 5 round-trips (<b>a</b>) and for 10 round-trips (<b>b</b>). Lines are only for illustration purposes.</p>
Full article ">Figure 10
<p>Different views of a compensated Type I system with five round-trips and <math display="inline"> <semantics> <mrow> <mi>θ</mi> <mo>=</mo> <msup> <mn>10</mn> <mo>∘</mo> </msup> </mrow> </semantics> </math>.</p>
Full article ">Figure 11
<p>Compensated Type II system with <span class="html-italic">d</span> = 200 mm and <span class="html-italic">f</span> = 500 mm for 10 round-trips. (<b>a</b>) Astigmatic wavefront deformation as a function of round-trip number as a result of a ray-tracing calculation; (<b>b</b>) different views of the compensated Type II system.</p>
Full article ">Figure 12
<p>Analysis of ray-tracing results from the compensated Type I system with five round-trips and the compensated Type II system with 10 round-trips. The upper diagrams show the Zernike coefficients of the output wave front (numbering according to Noll et al. [<a href="#B9-applsci-06-00353" class="html-bibr">9</a>]) for a wavelength corresponding to 1 µm. The lower images show the corresponding residual wavefront after subtracting all terms lower than seven.</p>
Full article ">
2027 KiB  
Article
Mathematical Models of Androgen Resistance in Prostate Cancer Patients under Intermittent Androgen Suppression Therapy
by Javier Baez and Yang Kuang
Appl. Sci. 2016, 6(11), 352; https://doi.org/10.3390/app6110352 - 16 Nov 2016
Cited by 27 | Viewed by 6757
Abstract
Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen [...] Read more.
Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). We accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). While these models are simplifications of a previously published model, they fit data with similar accuracy and improve forecasting results. Both models describe the progression of androgen resistance. Although Model 1 is simpler than the more realistic Model 2, it can fit clinical data to a greater precision. However, we found that Model 2 can forecast future PSA levels more accurately. These findings suggest that including more realistic mechanisms of androgen dynamics in a two population model may help androgen resistance timing prediction. Full article
(This article belongs to the Special Issue Dynamical Models of Biology and Medicine)
Show Figures

Figure 1

Figure 1
<p>Sample data for prostate-specific antigen (PSA) and androgen data for a patient in a clinical trial.</p>
Full article ">Figure 2
<p>Bifurcation diagram displaying <math display="inline"> <semantics> <msub> <mi>x</mi> <mn>1</mn> </msub> </semantics> </math> cell population vs. parameters <span class="html-italic">μ</span> and <span class="html-italic">γ</span> (<b>left</b>) and <span class="html-italic">γ</span> and <math display="inline"> <semantics> <msub> <mi>d</mi> <mn>1</mn> </msub> </semantics> </math> (<b>right</b>). This figure depicts the regions in which <math display="inline"> <semantics> <msub> <mi>x</mi> <mn>1</mn> </msub> </semantics> </math> can go extinct. This happens when androgen levels <span class="html-italic">γ</span> are very low, or cancer cells’ proliferation rate <span class="html-italic">μ</span> is very low, or cancer cells’ death rate <math display="inline"> <semantics> <msub> <mi>d</mi> <mn>1</mn> </msub> </semantics> </math> is very high.</p>
Full article ">Figure 3
<p>Normalized sensitivities of Model 1.</p>
Full article ">Figure 4
<p>Normalized sensitivities of Model 2.</p>
Full article ">Figure 5
<p>Simulations of fittings for every model for 1.5 cycles of treatment (<b>left</b> of gray line), and one cycle of forecast (<b>right</b> of gray line). For these four patients, we can see that models fit data at comparable accuracy but Model 2 perform much better in PSA forecasting.</p>
Full article ">Figure 6
<p>Simulations of fittings of androgen levels for Models 1 and 2. These two models have comparable goodness in fitting androgen data as their derivations are very similar.</p>
Full article ">Figure 7
<p>Cancer cells in resistant and non-resistant patient for Model 1. For the non-resistant patient we see a slight increase in volume over the course of several cycles. In the resistant patient we see that cancer volume has grown substantially.</p>
Full article ">Figure 8
<p>Cancer cells in resistant and non-resistant patients for Model 2. For the non-resistant patient, we see an increase in the volume of CR cells, but the original volume is about the same. In the resistant patient, we see that cancer volume has grown to double the volume compared to the non resistant patient.</p>
Full article ">
5087 KiB  
Article
Investigating the Influence of Plasma-Treated SiO2 Nanofillers on the Electrical Treeing Performance of Silicone-Rubber
by Fatin Nabilah Musa, Nouruddeen Bashir, Mohd Hafizi Ahmad, Zolkafle Buntat and Mohamed Afendi Mohamed Piah
Appl. Sci. 2016, 6(11), 348; https://doi.org/10.3390/app6110348 - 16 Nov 2016
Cited by 16 | Viewed by 4254
Abstract
This study presents an investigation of electrical tree performance as well as the effect of filler concentration of silicone rubber (SiR) filled with atmospheric-pressure plasma-treated silicon dioxide (SiO2) nanofiller. Atmospheric-pressure plasma was used to treat the SiO2 nanofiller surfaces to [...] Read more.
This study presents an investigation of electrical tree performance as well as the effect of filler concentration of silicone rubber (SiR) filled with atmospheric-pressure plasma-treated silicon dioxide (SiO2) nanofiller. Atmospheric-pressure plasma was used to treat the SiO2 nanofiller surfaces to enhance compatibility with SiR matrices. A fixed AC voltage of 10 kV, 50 Hz was applied to untreated, silane-treated, and plasma-treated nanocomposites with filler concentrations of 1, 3, and 5 wt % to investigate their electrical performance during electrical treeing. The result showed that plasma-treated SiO2 nanoparticles were uniformly well dispersed and formed strong covalent bonds with the molecules of the SiR polymer matrix. The plasma-treated nanocomposites were able to resist the electrical treeing better than the untreated or silane-treated nanocomposites. The increase in filler concentration enhanced the electrical tree performances of the nanocomposites. The result from this study reveals that the plasma-treated nanocomposites exhibited the best result in inhibiting the growth of electrical treeing compared to the existing surface treatment methods used in this study. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of atmospheric pressure plasma test cell (<b>a</b>) 3D; (<b>b</b>) 2D.</p>
Full article ">Figure 2
<p>Experimental setup for the plasma treatment.</p>
Full article ">Figure 3
<p>Experimental setup for electrical tree growth monitoring.</p>
Full article ">Figure 4
<p>Surface composition of nanoparticles: untreated, silane-treated, and plasma-treated.</p>
Full article ">Figure 5
<p>Morphology images of silicon dioxide nanoparticles: (<b>a</b>) untreated; (<b>b</b>) silane-treated; and (<b>c</b>) plasma-treated.</p>
Full article ">Figure 6
<p>Tree initiation time for directly mixed nanocomposites (DMNC), silane-treated nanocomposites (STNC), and plasma-treated nanocomposites (PTNC).</p>
Full article ">Figure 7
<p>Electrical tree performance (<b>a</b>) DMNC; (<b>b</b>) STNC; (<b>c</b>) PTNC.</p>
Full article ">Figure 8
<p>Growth rates for DMNC, STNC, and PTNC.</p>
Full article ">Figure 9
<p>Tree bridging times for DMNC, STNC, and PTNC.</p>
Full article ">Figure 10
<p>Field emission scanning electron microscopy (FESEM) images at 5 wt % for (<b>a</b>) DMNC; (<b>b</b>) STNC; and (<b>c</b>) PTNC.</p>
Full article ">
2444 KiB  
Article
Numerical Study of Photoacoustic Pressure for Cancer Therapy
by Thomas Grosges and Dominique Barchiesi
Appl. Sci. 2016, 6(11), 357; https://doi.org/10.3390/app6110357 - 15 Nov 2016
Cited by 8 | Viewed by 3806
Abstract
A commonly used therapy for cancer is based on the necrosis of cells induced by heating through the illumination of nanoparticles embedded in cells. Recently, the photoacoustic pressure shock induced by the illumination pulse was proved and this points to another means of [...] Read more.
A commonly used therapy for cancer is based on the necrosis of cells induced by heating through the illumination of nanoparticles embedded in cells. Recently, the photoacoustic pressure shock induced by the illumination pulse was proved and this points to another means of cell destruction. The purpose of this study is to propose a model of the photoacoustic pressure in cells. The numerical resolution of the problem requires the accurate computation of the electromagnetism, the temperature and the pressure around the nanostructures embedded in a cell. Here, the problem of the interaction between an electromagnetic excitation and a gold nanoparticle embedded in a cell domain is solved. The variations of the thermal and photoacoustic pressures are studied in order to analyze the pressure shock wave inducing the collapse of the cell’s membrane in cancer therapy. Full article
(This article belongs to the Section Nanotechnology and Applied Nanosciences)
Show Figures

Figure 1

Figure 1
<p>Geometry (<b>a</b>) and associated mesh (<b>b</b>) of the 3D water domain including the cell; Zoomed-in view in the xy plane on the cell (<b>c</b>) including the gold nanoparticle and (<b>d</b>) the associated mesh.</p>
Full article ">Figure 2
<p>Time evolution of the variations of the acoustic pressure (in Pa) computed at (<b>a</b>) 0.5 ns; (<b>b</b>) 1.5 ns; (<b>c</b>) 2.5 ns; (<b>d</b>) 4.5 ns; (<b>e</b>) 14.5 ns and (<b>f</b>) 40.0 ns after the initial shock in the whole computationnal domain. The size of the cell’s membrane is also illustrated at the beginning and the end of the wave propagation (<b>a</b>–<b>f</b>). The radii of the nanoparticle, the cell and the computationnal domain are: 50 nm, 1 <math display="inline"> <semantics> <mi mathvariant="sans-serif">μ</mi> </semantics> </math>m and 22 <math display="inline"> <semantics> <mi mathvariant="sans-serif">μ</mi> </semantics> </math>m, respectively.</p>
Full article ">Figure 3
<p>(<b>a</b>) Time evolution of the temperature (in °C) in the cell (i.e., <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>y</mi> <mo>|</mo> <mo>≤</mo> <mn>1000</mn> </mrow> </semantics> </math> nm) and in the water (i.e., <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>y</mi> <mo>|</mo> <mo>≥</mo> <mn>1000</mn> </mrow> </semantics> </math> nm); (<b>b</b>) The spatial distribution of the temperature stays located in the near vicinity of the nanoparticle (i.e., at <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>y</mi> <mo>|</mo> <mo>≈</mo> <mn>50</mn> </mrow> </semantics> </math> nm).</p>
Full article ">Figure 4
<p>(<b>a</b>) Time evolution of the variation of the pressure (in Pa) in the cell (i.e., <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>y</mi> <mo>|</mo> <mo>≤</mo> <mn>1000</mn> </mrow> </semantics> </math> nm) and in the water (i.e., <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>y</mi> <mo>|</mo> <mo>≥</mo> <mn>1000</mn> </mrow> </semantics> </math> nm); (<b>b</b>) The spatial distribution of the pressure variation is computed from the center of the nanoparticle (i.e., at <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>y</mi> <mo>|</mo> <mo>≈</mo> <mn>0</mn> </mrow> </semantics> </math> nm) and propagated to the cell membrane (i.e., at <math display="inline"> <semantics> <mrow> <mo>|</mo> <mi>y</mi> <mo>|</mo> <mo>≈</mo> <mn>1</mn> <mspace width="3.33333pt"/> <mi mathvariant="sans-serif">μ</mi> </mrow> </semantics> </math>m).</p>
Full article ">Figure 5
<p>Evolution of the variation of pressure at the limit of the cell membrane as a function of time, along the <span class="html-italic">y</span>-axis for two nanoparticle shapes (spheroide of radius R = 50 nm illuminated at <math display="inline"> <semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mn>532</mn> </mrow> </semantics> </math> nm and <math display="inline"> <semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mn>800</mn> </mrow> </semantics> </math> nm, and an ellipsoide of semi-axis a = 100 nm, b = 50 nm illuminated at <math display="inline"> <semantics> <mrow> <mi>λ</mi> <mo>=</mo> <mn>532</mn> </mrow> </semantics> </math> nm).</p>
Full article ">
3341 KiB  
Article
Analysis of the Numerical Diffusion in Anisotropic Mediums: Benchmarks for Magnetic Field Aligned Meshes in Space Propulsion Simulations
by Daniel Pérez-Grande, Oscar Gonzalez-Martinez, Pablo Fajardo and Eduardo Ahedo
Appl. Sci. 2016, 6(11), 354; https://doi.org/10.3390/app6110354 - 15 Nov 2016
Cited by 11 | Viewed by 7020
Abstract
This manuscript explores numerical errors in highly anisotropic diffusion problems. First, the paper addresses the use of regular structured meshes in numerical solutions versus meshes aligned with the preferential directions of the problem. Numerical diffusion in structured meshes is quantified by solving the [...] Read more.
This manuscript explores numerical errors in highly anisotropic diffusion problems. First, the paper addresses the use of regular structured meshes in numerical solutions versus meshes aligned with the preferential directions of the problem. Numerical diffusion in structured meshes is quantified by solving the classical anisotropic diffusion problem; the analysis is exemplified with the application to a numerical model of conducting fluids under magnetic confinement, where rates of transport in directions parallel and perpendicular to a magnetic field are quite different. Numerical diffusion errors in this problem promote the use of magnetic field aligned meshes (MFAM). The generation of this type of meshes presents some challenges; several meshing strategies are implemented and analyzed in order to provide insight into achieving acceptable mesh regularity. Second, Gradient Reconstruction methods for magnetically aligned meshes are addressed and numerical errors are compared for the structured and magnetically aligned meshes. It is concluded that using the latter provides a more correct and straightforward approach to solving problems where anisotropicity is present, especially, if the anisotropicity level is high or difficult to quantify. The conclusions of the study may be extrapolated to the study of anisotropic flows different from conducting fluids. Full article
(This article belongs to the Special Issue Applications of Complex Fluids)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) The marked region represents a typical axisymmetric simulation domain for a Hall Effect Thruster geometry; (<b>b</b>) Magnetic Field Aligned Mesh for the SPT-100 Hall Effect Thruster magnetic topology; (<b>c</b>) Detail of a mesh element.</p>
Full article ">Figure 2
<p>Regular structured mesh with tilted Magnetic field. Blue lines are aligned with the magnetic field <math display="inline"> <semantics> <mover accent="true"> <mi>B</mi> <mo stretchy="false">→</mo> </mover> </semantics> </math>. The variables <span class="html-italic">x</span> and <span class="html-italic">y</span> are the Cartesian coordinates (reference) and <math display="inline"> <semantics> <msup> <mi>x</mi> <mo>′</mo> </msup> </semantics> </math> and <math display="inline"> <semantics> <msup> <mi>y</mi> <mo>′</mo> </msup> </semantics> </math> are the coordinates aligned with the magnetic field.</p>
Full article ">Figure 3
<p>Sketch illustrating the numerical diffusion, because of the iterative nature of numerical algorithms, after one iteration, the cross-diffusion term allows for permeability across the magnetic field line at a higher rate than would normally be allowed for perpendicular diffusivity; (<b>a</b>) numerical diffusion in the vertical, <span class="html-italic">y</span>, direction; (<b>b</b>) <span class="html-italic">x</span>-directed numerical diffusion.</p>
Full article ">Figure 4
<p>Schematic of central differences in a cartesian mesh. The central node on each volume are indicated, <math display="inline"> <semantics> <msub> <mi>n</mi> <mi>i</mi> </msub> </semantics> </math>, for the six cells considered. The derivative at the faces are computed using the nearest nodes.</p>
Full article ">Figure 5
<p>Time evolution for a simple diffusion problem on a Cartesian mesh for the case <math display="inline"> <semantics> <mrow> <mi mathvariant="normal">Θ</mi> <mo>=</mo> <msub> <mi>D</mi> <mo>∥</mo> </msub> <mspace width="-1.111pt"/> <mo>/</mo> <mspace width="-0.55542pt"/> <msub> <mi>D</mi> <mo>⊥</mo> </msub> </mrow> </semantics> </math> and <math display="inline"> <semantics> <mrow> <mi>α</mi> <mo>=</mo> <mo>−</mo> <msup> <mn>45</mn> <mo>∘</mo> </msup> </mrow> </semantics> </math>. Non-dimensionalized variables are used.</p>
Full article ">Figure 6
<p>(<b>a</b>) Error, computed as defined in Equation (<a href="#FD9-applsci-06-00354" class="html-disp-formula">9</a>) vs. time for an infinite diffusion ratio and various inclinations of the magnetic field for a mesh resolution of 5000 elements; (<b>b</b>) Error vs. time for a diffusion ratio equal to infinite for various mesh resolutions; the inclination is fixed at 45 degrees.</p>
Full article ">Figure 7
<p>Example of evenly distributed Magnetic Field Aligned Mesh (MFAM) coordinates, <span class="html-italic">λ</span> and <span class="html-italic">σ</span>, using the Smoothing method used for initial contour selection.</p>
Full article ">Figure 8
<p>Meshing example illustrating the Expanded Exponential Stretching method with posterior manual correction in a magnetic field topology with a singular point. A zoom close to the domain’s boundary is included in the top part of the figure.</p>
Full article ">Figure 9
<p>Meshing examples obtained with two methods for an initial number of <span class="html-italic">λ</span> and <span class="html-italic">σ</span> isolines equal to 50: (<b>a</b>) Smoothing method; (<b>b</b>) Expanded Exponential Stretching method &amp; manual correction.</p>
Full article ">Figure 10
<p>Mesh quality for different meshing examples: (<b>a</b>) Aspect Ratios, (<b>b</b>) Smoothness, (<b>c</b>) Skewness; (top) 2D contours in the mesh and (bottom) Comparison for mesh quality statistics between Exponential-Stretching method mesh presented in <a href="#applsci-06-00354-f009" class="html-fig">Figure 9</a> and Smoothing method mesh. Diferent values (min., max., mean, most likely, 80% cumulative, 90% cumulative, 95% cumulative) are used for the evaluation.</p>
Full article ">Figure 11
<p>Gradient reconstruction (GR) errors for various functions: log10 of relative errors in the WLSQR method -9 stencil points, inverse-distance weighting for (<b>a</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>∼</mo> <msup> <mi>λ</mi> <mn>2</mn> </msup> <mo>+</mo> <msup> <mi>σ</mi> <mn>2</mn> </msup> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>∼</mo> <msup> <mi>λ</mi> <mn>3</mn> </msup> <mo>×</mo> <msup> <mi>σ</mi> <mn>3</mn> </msup> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>∼</mo> <mo form="prefix">sin</mo> <mi>λ</mi> <mo>×</mo> <mo form="prefix">cos</mo> <mi>σ</mi> </mrow> </semantics> </math> (elements are colored according to the worst GR error for their respective facets).</p>
Full article ">Figure 12
<p>Comparison of GR errors for various Weighted Least Squares (WLSQR) method parameters (Taylor order = 2 &amp; inverse-distance weighting; Taylor order = 2 &amp; unweighted; Taylor order = 3 (16 stencil points) &amp; inverse-distance×area weighting) for functions (<b>a</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>ϕ</mi> <mn>1</mn> </msub> <mo>∼</mo> <msup> <mi>λ</mi> <mn>2</mn> </msup> <mo>+</mo> <msup> <mi>σ</mi> <mn>2</mn> </msup> </mrow> </semantics> </math>; (<b>b</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>ϕ</mi> <mn>2</mn> </msub> <mo>∼</mo> <msup> <mi>λ</mi> <mn>3</mn> </msup> <mo>×</mo> <msup> <mi>σ</mi> <mn>3</mn> </msup> </mrow> </semantics> </math>; (<b>c</b>) <math display="inline"> <semantics> <mrow> <msub> <mi>ϕ</mi> <mn>3</mn> </msub> <mo>∼</mo> <mo form="prefix">sin</mo> <mi>λ</mi> <mo>×</mo> <mo form="prefix">cos</mo> <mi>σ</mi> </mrow> </semantics> </math>.</p>
Full article ">Figure 13
<p>Temporal evolution of the anisotropic diffusion problem solution in Cartesian (<b>a</b>) and MFAM (<b>b</b>) meshes. Variables are non-dimensionalized.</p>
Full article ">Figure 14
<p>Evolution of average density due to diffusion for the low density region of the domain (marked in blue in <a href="#applsci-06-00354-f013" class="html-fig">Figure 13</a>) at <math display="inline"> <semantics> <mrow> <msup> <mi>t</mi> <mo>′</mo> </msup> <mo>=</mo> <mn>0</mn> </mrow> </semantics> </math> for simulations performed in Cartesian and MFAM meshes for two different Θ values.</p>
Full article ">
2818 KiB  
Article
Quantum Control of Population Transfer and Vibrational States via Chirped Pulses in Four Level Density Matrix Equations
by Iduabo John Afa and Carles Serrat
Appl. Sci. 2016, 6(11), 351; https://doi.org/10.3390/app6110351 - 15 Nov 2016
Cited by 3 | Viewed by 5161
Abstract
We investigate the effect of chirped excitation and the excitation detuning on the coherent control of population transfer and vibrational states in a four-level system. Density matrix equations are studied for optimally enhanced processes by considering specific parameters typical of oxazine systems. Our [...] Read more.
We investigate the effect of chirped excitation and the excitation detuning on the coherent control of population transfer and vibrational states in a four-level system. Density matrix equations are studied for optimally enhanced processes by considering specific parameters typical of oxazine systems. Our simulations show a strong dependence on the interplay between chirp and excitation detuning and predict enhancement factors up to 3.2 for population transfer and up to 38.5 for vibrational coherences of electronic excited states. The study of the dynamics of the populations and vibrational coherences involved in the four-level system allows an interpretation of the different enhancement/suppression processes observed. Full article
(This article belongs to the Special Issue Ultrashort Optical Pulses)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic of the four level system showing the transition wavenumbers considered and different excitation frequencies.</p>
Full article ">Figure 2
<p>Enhancement/suppression factor of (<b>a</b>) population in the ground state; (<b>b</b>) vibrational coherence in the ground state; (<b>c</b>) population in the upper state; and (<b>d</b>) vibrational coherence in the upper state. Dashed lines indicate the position of the excited states (see <a href="#applsci-06-00351-f001" class="html-fig">Figure 1</a>).</p>
Full article ">Figure 3
<p>Time evolution of the populations in the ground state (<b>a</b>–<b>c</b>); and in the upper states (<b>d</b>–<b>f</b>); for specific parameter values, as indicated. Note that the lines, which are named with letters, correspond to the parameter values detailed in <a href="#applsci-06-00351-f005" class="html-fig">Figure 5</a>a,e.</p>
Full article ">Figure 4
<p>Time evolution of the vibrational coherences in the ground state (<b>a</b>); and in the upper states (<b>b</b>), for the indicated parameter values.</p>
Full article ">Figure 5
<p>Enhancement/suppression factors of (<b>a</b>,<b>b</b>) population in the ground state; (<b>c</b>,<b>d</b>) vibrational coherence in the ground state; (<b>e</b>,<b>f</b>) population in the upper state; and (<b>g</b>,<b>h</b>) vibrational coherence in the upper state. The right hand panels are for a laser pulse of 30 fs and the right hand panels for 17 fs, as indicated. The colored lines represent the different excitation frequencies: 18,800 cm<sup>−1</sup> (black line), 19,400 cm<sup>−1</sup> (red line), 19,700 cm<sup>−1</sup> (blue line), 20,000 cm<sup>−1</sup> (dark cyan line), and 20,600 cm<sup>−1</sup> (magenta line). The electronic dephasing time is 100 fs for all cases. A bold (blue) line has been chosen for the excitation wavenumber of 19,700 cm<sup>−1</sup>, in order to clarify the comparisons with <a href="#applsci-06-00351-f007" class="html-fig">Figure 7</a>.</p>
Full article ">Figure 6
<p>Enhancement of in |ρ<sub>34</sub>| with <math display="inline"> <semantics> <mover accent="true"> <mi>ν</mi> <mo stretchy="false">˜</mo> </mover> </semantics> </math> ≃ 19,365 cm<sup>−1</sup> and for pulse durations of 30 fs and 17 fs, as indicated.</p>
Full article ">Figure 7
<p>Influence of electronic dephasing (<span class="html-italic">T</span><sub>2,elec</sub> = 5 fs, 25 fs, 50 fs, 100 fs and 200 fs, as indicated) on the enhancement of (<b>a</b>) population in the ground state; (<b>b</b>) vibrational coherence in the ground state; (<b>c</b>) population in the upper state; and (<b>d</b>) vibrational coherence in the upper state, considering an excitation frequency of 19,700 cm<sup>−1</sup>. The bold blue lines show the electronic dephasing time <span class="html-italic">T</span><sub>2,elec</sub> = 100 fs for a clearer comparison with <a href="#applsci-06-00351-f005" class="html-fig">Figure 5</a>.</p>
Full article ">
5468 KiB  
Article
Thin Film Williamson Nanofluid Flow with Varying Viscosity and Thermal Conductivity on a Time-Dependent Stretching Sheet
by Waris Khan, Taza Gul, Muhammad Idrees, Saeed Islam, Ilyas Khan and L.C.C. Dennis
Appl. Sci. 2016, 6(11), 334; https://doi.org/10.3390/app6110334 - 15 Nov 2016
Cited by 42 | Viewed by 5719
Abstract
This article describes the effect of thermal radiation on the thin film nanofluid flow of a Williamson fluid over an unsteady stretching surface with variable fluid properties. The basic governing equations of continuity, momentum, energy, and concentration are incorporated. The effect of thermal [...] Read more.
This article describes the effect of thermal radiation on the thin film nanofluid flow of a Williamson fluid over an unsteady stretching surface with variable fluid properties. The basic governing equations of continuity, momentum, energy, and concentration are incorporated. The effect of thermal radiation and viscous dissipation terms are included in the energy equation. The energy and concentration fields are also coupled with the effect of Dufour and Soret. The transformations are used to reduce the unsteady equations of velocity, temperature and concentration in the set of nonlinear differential equations and these equations are tackled through the Homotopy Analysis Method (HAM). For the sake of comparison, numerical (ND-Solve Method) solutions are also obtained. Special attention has been given to the variable fluid properties’ effects on the flow of a Williamson nanofluid. Finally, the effect of non-dimensional physical parameters like thermal conductivity, Schmidt number, Williamson parameter, Brinkman number, radiation parameter, and Prandtl number has been thoroughly demonstrated and discussed. Full article
(This article belongs to the Special Issue Recent Developments of Nanofluids)
Show Figures

Figure 1

Figure 1
<p>Geometry of the problem</p>
Full article ">Figure 2
<p>The combined graph of <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math>-curves <span class="html-italic">f</span>”(0) θ’(0), <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">B<sub>r</sub></span> = 0.8, <span class="html-italic">N<sub>r</sub></span> = 0.8, <span class="html-italic">D<sub>u</sub></span> = 0.8, <span class="html-italic">S<sub>c</sub></span> = 0.4, ε = 0.8, <span class="html-italic">S<sub>r</sub></span> = 0.4, λ = 0.8, Λ = 1, β = 1, <span class="html-italic">S</span> = 0.3.</p>
Full article ">Figure 3
<p>The graph of <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math>-curve <math display="inline"> <semantics> <mrow> <msup> <mi mathvariant="sans-serif">φ</mi> <mo>′</mo> </msup> <mo>(</mo> <mn>0</mn> <mo>)</mo> </mrow> </semantics> </math>, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">B<sub>r</sub></span> = 0.8, <span class="html-italic">N<sub>r</sub></span> = 0.8, <span class="html-italic">D<sub>u</sub></span> = 0.8, <span class="html-italic">S<sub>c</sub></span> = 0.4, ε = 0.8, <span class="html-italic">S<sub>r</sub></span> = 0.4, λ = 0.8, Λ = 1, β = 1, <span class="html-italic">S</span> = 0.3.</p>
Full article ">Figure 4
<p>The comparison between HAM and numerical solutions for velocity profile <math display="inline"> <semantics> <mrow> <mi>f</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.28, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">B<sub>r</sub></span> = 0.1, <span class="html-italic">N<sub>r</sub></span> = 0.1, <span class="html-italic">D<sub>u</sub></span> = 0.1, <span class="html-italic">S<sub>c</sub></span> = 0.1, ε = 0.1, <span class="html-italic">S<sub>r</sub></span> = 0.1, λ = 0.1, Λ = 0.1, β = 1, <span class="html-italic">S</span> = 0.1.</p>
Full article ">Figure 5
<p>The comparison between HAM and numerical solutions for temperature fields <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.45, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.3, <span class="html-italic">D<sub>u</sub></span> = 0.3, <span class="html-italic">S<sub>c</sub></span> = 0.9, ε = 0.9, <span class="html-italic">S<sub>r</sub></span> = 0.1, λ = 0.1, Λ = 0.1, β = 1, <span class="html-italic">S</span> = 0.2.</p>
Full article ">Figure 6
<p>The comparison between HAM and numerical solutions for concentration fields <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">B<sub>r</sub></span> = 0.1, <span class="html-italic">N<sub>r</sub></span> = 0.1, <span class="html-italic">D<sub>u</sub></span> = 0.1, <span class="html-italic">S<sub>c</sub></span> = 0.1, ε = 0.1, <span class="html-italic">S<sub>r</sub></span> = 0.1, λ = 0.1, Λ = 0.1, β = 1, <span class="html-italic">S</span> = 0.1.</p>
Full article ">Figure 7
<p>Variants in velocity field <math display="inline"> <semantics> <mrow> <mi>f</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for various values of <span class="html-italic">S</span>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">D<sub>u</sub></span> = 0.7, <span class="html-italic">S<sub>c</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 8
<p>The variation of temperature scale gradient <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for different quantities of <span class="html-italic">S</span>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, <span class="html-italic">S<sub>c</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 9
<p>Variations in concentration field <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> occur for different numbers of <span class="html-italic">S</span>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, <span class="html-italic">S<sub>c</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 10
<p>Variation in velocity field <math display="inline"> <semantics> <mrow> <mi>f</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for various values of <span class="html-italic">P<sub>r</sub></span>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">D<sub>u</sub></span> = 0.7, <span class="html-italic">S<sub>c</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1, <span class="html-italic">S</span> = 0.7.</p>
Full article ">Figure 11
<p>The variation of temperature scale gradient <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for different values of <span class="html-italic">P<sub>r</sub></span>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, <span class="html-italic">S<sub>c</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 12
<p>Variations in concentration field <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> occur for different values of <math display="inline"> <semantics> <mrow> <mi>P</mi> <mi>r</mi> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, <span class="html-italic">S<sub>c</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 13
<p>Variations in velocity field <math display="inline"> <semantics> <mrow> <mi>f</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for various values of <math display="inline"> <semantics> <mrow> <msub> <mi>D</mi> <mi>u</mi> </msub> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">S<sub>c</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1, <span class="html-italic">S</span> = 0.7.</p>
Full article ">Figure 14
<p>The variation of temperature scale gradient <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for different values of <math display="inline"> <semantics> <mrow> <msub> <mi>D</mi> <mi>u</mi> </msub> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">S<sub>c</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 15
<p>Variations in concentration field <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> occur for different values of <math display="inline"> <semantics> <mrow> <msub> <mi>D</mi> <mi>u</mi> </msub> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">S<sub>c</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 16
<p>Variations in concentration field <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> occur for different values of <span class="html-italic">S<sub>r</sub></span>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">S<sub>c</sub></span> = 0.7, ε = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 17
<p>The variation of temperature scale gradient <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for different values of <span class="html-italic">S<sub>c</sub></span>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">D<sub>u</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 18
<p>Variations in concentration field <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">φ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> occur for different values of <math display="inline"> <semantics> <mrow> <msub> <mi>S</mi> <mi>c</mi> </msub> </mrow> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">S<sub>r</sub></span> = 0.7, ε = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, λ = 0.7, Λ = 0.7, β = 1.</p>
Full article ">Figure 19
<p>Variations in velocity field <math display="inline"> <semantics> <mrow> <msup> <mi>f</mi> <mo>′</mo> </msup> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for various values of <math display="inline"> <semantics> <mi mathvariant="sans-serif">Λ</mi> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">S<sub>c</sub></span> = 0.7, λ = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, β = 1, <span class="html-italic">S</span> = 0.7.</p>
Full article ">Figure 20
<p>The variation of temperature scale gradient <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for different values of <math display="inline"> <semantics> <mi mathvariant="sans-serif">Λ</mi> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">S</span> = 0.7, <span class="html-italic">B<sub>r</sub></span> = 0.7, <span class="html-italic">N<sub>r</sub></span> = 0.7, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">D<sub>u</sub></span> = 0.7, ε = 0.7, <span class="html-italic">S<sub>r</sub></span> = 0.7, λ = 0.7, <span class="html-italic">S<sub>c</sub></span> = 0.7, β = 1.</p>
Full article ">Figure 21
<p>Variations in velocity field <math display="inline"> <semantics> <mrow> <msup> <mi>f</mi> <mo>′</mo> </msup> <mo stretchy="false">(</mo> <mi mathvariant="sans-serif">η</mi> <mo stretchy="false">)</mo> </mrow> </semantics> </math> for various values of <math display="inline"> <semantics> <mi mathvariant="sans-serif">λ</mi> </semantics> </math>, when <math display="inline"> <semantics> <mi>ℏ</mi> </semantics> </math> = −0.25, <span class="html-italic">P<sub>r</sub></span> = 10, <span class="html-italic">S<sub>c</sub></span> = 0.7, Λ = 0.7, <span class="html-italic">D<sub>u</sub></span> = 0.7, β = 1, <span class="html-italic">S</span> = 0.7.</p>
Full article ">
15222 KiB  
Article
Moving Object Tracking and Its Application to an Indoor Dual-Robot Patrol
by Cheng-Han Shih and Jih-Gau Juang
Appl. Sci. 2016, 6(11), 349; https://doi.org/10.3390/app6110349 - 12 Nov 2016
Cited by 7 | Viewed by 5389
Abstract
This paper presents an application of image tracking using an omnidirectional wheeled mobile robot (WMR). The objective of this study is to integrate image processing of hue, saturation, and lightness (HSL) for fuzzy color space, and use mean shift tracking for object detection [...] Read more.
This paper presents an application of image tracking using an omnidirectional wheeled mobile robot (WMR). The objective of this study is to integrate image processing of hue, saturation, and lightness (HSL) for fuzzy color space, and use mean shift tracking for object detection and a Radio Frequency Identification (RFID) reader for confirming destination. Fuzzy control is applied to omnidirectional WMR for indoor patrol and intruder detection. Experimental results show that the proposed control scheme can make the WMRs perform indoor security service. Full article
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) RGB image and (<b>b</b>) hue, saturation, and lightness (HSL) image.</p>
Full article ">Figure 2
<p>Blocks in different colors.</p>
Full article ">Figure 3
<p>Fuzzy sets of color classification system.</p>
Full article ">Figure 4
<p>Fuzzy color classifications.</p>
Full article ">Figure 5
<p>Classifications of the background environment and object: (<b>a</b>) background environment; (<b>b</b>) training background color distribution; (<b>c</b>) add object in background environment; (<b>d</b>) classifications of the background environment and object.</p>
Full article ">Figure 6
<p>Steps for finding the highest density of color: (<b>a</b>) Search high color density; (<b>b</b>) search high color density again; (<b>c</b>) reach center of mass.</p>
Full article ">Figure 7
<p>Steps for mean shift tracking process against a static background: (<b>a</b>) Find the object; (<b>b</b>) the object moves to the right side; (<b>c</b>) search high color density; (<b>d</b>) catch the object; (<b>e</b>) the object moves forward; (<b>f</b>) keep tracking the object.</p>
Full article ">Figure 8
<p>Steps for tracking a moving object against a dynamic background: (<b>a</b>) Find the object; (<b>b</b>) scroll right; (<b>c</b>) the object moves forward; (<b>d</b>) the object moves; (<b>e</b>) keep tracking the object.</p>
Full article ">Figure 9
<p>Omnidirectional WMR.</p>
Full article ">Figure 10
<p>(<b>a</b>) MX—64; (<b>b</b>) MX—28.</p>
Full article ">Figure 11
<p>Omnidirectional WMR coordinate system.</p>
Full article ">Figure 12
<p>Simplified kinematic model of omnidirectional WMR.</p>
Full article ">Figure 13
<p>Ultrasonic sensors.</p>
Full article ">Figure 14
<p>Fuzzy sets.</p>
Full article ">Figure 15
<p>Flowchart of control sequence.</p>
Full article ">Figure 16
<p>(<b>a</b>) Ultra High Frequency (UHF) RFID reader MT-RF800-BT and (<b>b</b>) UHF tag.</p>
Full article ">Figure 17
<p>Initial setup and experimental environment.</p>
Full article ">Figure 18
<p>Target is not detected, thus the robot turns left to find the room color.</p>
Full article ">Figure 19
<p>The robot turns left; the DM detects the target; and the robot moves forward to the predefined door.</p>
Full article ">Figure 20
<p>Tag posted on the door.</p>
Full article ">Figure 21
<p>RFID verifies the destination at a specified distance.</p>
Full article ">Figure 22
<p>If the verification result is positive, the robot turns right.</p>
Full article ">Figure 23
<p>An ultrasonic sensor measures the distance between the robot and the door.</p>
Full article ">Figure 24
<p>If the verification result is positive, the second robot turns right.</p>
Full article ">Figure 25
<p>The second robot moves forward along the wall.</p>
Full article ">Figure 26
<p>The corridor environment diagram.</p>
Full article ">Figure 27
<p>Twin robots on an indoor patrol.</p>
Full article ">Figure 28
<p>The first robot finds an intruder.</p>
Full article ">Figure 29
<p>The first robot sends an alarm message to the remote control center and to the second robot.</p>
Full article ">Figure 30
<p>Security guards inspect the scene directly.</p>
Full article ">Figure 31
<p>Communication sequence.</p>
Full article ">Figure 32
<p>The first robot sends instant images to the control center and to the user’s smartphone. (<b>a</b>) Smartphone receives notification message about the intruder; (<b>b</b>) remote control center receives notification message about the intruder.</p>
Full article ">Figure 32 Cont.
<p>The first robot sends instant images to the control center and to the user’s smartphone. (<b>a</b>) Smartphone receives notification message about the intruder; (<b>b</b>) remote control center receives notification message about the intruder.</p>
Full article ">Figure 33
<p>First robot sends alarm message to the second robot. (<b>a</b>) Robot 1 initial signal indicators are off; (<b>b</b>) Robot 1 sends signal to Robot 2; (<b>c</b>) Robot 1 sends e-mail to control center; (<b>d</b>) Robot 2 receives alarm message; (<b>e</b>) Robot 2 sends e-mail to control center.</p>
Full article ">Figure 33 Cont.
<p>First robot sends alarm message to the second robot. (<b>a</b>) Robot 1 initial signal indicators are off; (<b>b</b>) Robot 1 sends signal to Robot 2; (<b>c</b>) Robot 1 sends e-mail to control center; (<b>d</b>) Robot 2 receives alarm message; (<b>e</b>) Robot 2 sends e-mail to control center.</p>
Full article ">Figure 34
<p>Experimental results of dual-robot patrol. (<b>a</b>) Starting position; (<b>b</b>) detecting doors; (<b>c</b>) moving forward to destination door; (<b>d</b>) when the robot approaches to the door, it will correct its position to aim at the room plate and door; (<b>e</b>) if it is the correct destination, the robot will approach the door and use RFID to verify the tag UID; (<b>f</b>) the robot turns right after verification is confirmed; (<b>g</b>) shifting path; (<b>h</b>) find moving object; (<b>i</b>) mean shift tracking and send message to the control center; (<b>j</b>) come to the end and rotate; (<b>k</b>) shifting path; (<b>l</b>) find the starting point of the elevator; (<b>m</b>) go straight to the elevator; (<b>n</b>) arrive back at the starting position.</p>
Full article ">Figure 34 Cont.
<p>Experimental results of dual-robot patrol. (<b>a</b>) Starting position; (<b>b</b>) detecting doors; (<b>c</b>) moving forward to destination door; (<b>d</b>) when the robot approaches to the door, it will correct its position to aim at the room plate and door; (<b>e</b>) if it is the correct destination, the robot will approach the door and use RFID to verify the tag UID; (<b>f</b>) the robot turns right after verification is confirmed; (<b>g</b>) shifting path; (<b>h</b>) find moving object; (<b>i</b>) mean shift tracking and send message to the control center; (<b>j</b>) come to the end and rotate; (<b>k</b>) shifting path; (<b>l</b>) find the starting point of the elevator; (<b>m</b>) go straight to the elevator; (<b>n</b>) arrive back at the starting position.</p>
Full article ">
3838 KiB  
Article
Oxygen Carrier Aided Combustion (OCAC) of Wood Chips in a Semi-Commercial Circulating Fluidized Bed Boiler Using Manganese Ore as Bed Material
by Magnus Rydén, Malin Hanning, Angelica Corcoran and Fredrik Lind
Appl. Sci. 2016, 6(11), 347; https://doi.org/10.3390/app6110347 - 12 Nov 2016
Cited by 53 | Viewed by 6982
Abstract
Oxygen Carrier Aided Combustion (OCAC) is realized by using an active oxygen-carrying bed material in fluidized bed boilers. The active material is reduced in fuel rich parts of the boiler and oxidized in air rich parts. Advantages could be achieved such as new [...] Read more.
Oxygen Carrier Aided Combustion (OCAC) is realized by using an active oxygen-carrying bed material in fluidized bed boilers. The active material is reduced in fuel rich parts of the boiler and oxidized in air rich parts. Advantages could be achieved such as new mechanisms for oxygen transport in space and time. Here calcined manganese ore has been used as active bed material in a 12 MWth circulating fluidized bed boiler. The fuel was wood chips and the campaign lasted more than two weeks. From an operational point of view, manganese ore worked excellently. From the temperature profile of the boiler it can be concluded that fuel conversion was facilitated, especially in the dense bottom bed. The effect did not always translate to reduced emissions, which suggests that final combustion in the cyclone outlet was also influenced. Substituting 10% of the sand bed with manganese ore made it possible to reduce the air to fuel ratio without generating large amounts of CO. The use of 100% manganese ore resulted in higher emissions of CO than the sand reference, but, when combined sulphur feeding, dramatic reductions in CO emissions, up to 90% compared to sand reference, was achieved. Full article
(This article belongs to the Section Energy Science and Technology)
Show Figures

Figure 1

Figure 1
<p>Schematic illustration of Oxygen Carrier Aided Combustion (OCAC) in Circulating Fluidized Bed (CFB) boiler. Simplified bulk reactions in dense bed and freeboard have been included, with new significant reaction pathways in italic. OC–O = oxidized oxygen carrier, OC = reduced oxygen carrier.</p>
Full article ">Figure 2
<p>Schematic description of Chalmers Research Boiler/gasifier reactor system.</p>
Full article ">Figure 3
<p>Temperature profile over the boiler when operated on lower air-to-fuel-ratio (≈1.07). <span class="html-italic">T<sub>bottom</sub></span> was in the range 866–877 °C and have been used as reference.</p>
Full article ">Figure 4
<p>Temperature profile over the boiler when operated on higher air-to-fuel-ratio (≈1.17). Tbottom was in the range 855–875 °C and have been used as reference. For 50% Mn ore, data were for air-to-fuel ratio 1.13 since data for 1.17 are lacking.</p>
Full article ">Figure 5
<p>Measured concentrations of CO (mg/nm<sup>3</sup>, at 6% O<sub>2</sub>) at position kh2 in the convection path as a function of the air-to-fuel ratio for experiments with partial substitution of sand with manganese ore.</p>
Full article ">Figure 6
<p>Measured concentrations of CO (mg/nm<sup>3</sup>, at 6% O<sub>2</sub>) at position kh2 in the convection path as a function of the air-to-fuel ratio for experiments with 100% substitution of sand with manganese ore.</p>
Full article ">Figure 7
<p>Measured concentrations of NO (mg/nm<sup>3</sup>, at 6% O<sub>2</sub>) at position kh2 in the convection path as a function of the air-to-fuel ratio for experiments with partial substitution of sand with manganese ore.</p>
Full article ">Figure 8
<p>Measured concentrations of NO (mg/nm<sup>3</sup>, at 6% O<sub>2</sub>) at position kh2 in the convection path as a function of the air-to-fuel ratio for experiments with 100% manganese ore.</p>
Full article ">Figure 9
<p>High-resolution light microscope pictures of fresh manganese ore and three bed samples extracted during operation. The blue squares has a side measuring 1 mm. Note that the particles in <a href="#applsci-06-00347-f009" class="html-fig">Figure 9</a>d was extracted after the research campaign had been finished, during the replacement of ore with sand by plant personnel. (<b>a</b>) Fresh manganese ore; (<b>b</b>) 100% Mn ore after 20 h of operation; (<b>c</b>) 100% Mn ore after 172 h of operation; and (<b>d</b>) after &gt;300 h of operation (mixed with sand).</p>
Full article ">
598 KiB  
Article
On Squeezed Flow of Jeffrey Nanofluid between Two Parallel Disks
by Tasawar Hayat, Tehseen Abbas, Muhammad Ayub, Taseer Muhammad and Ahmed Alsaedi
Appl. Sci. 2016, 6(11), 346; https://doi.org/10.3390/app6110346 - 11 Nov 2016
Cited by 60 | Viewed by 5726
Abstract
The present communication examines the magnetohydrodynamic (MHD) squeezing flow of Jeffrey nanofluid between two parallel disks. Constitutive relations of Jeffrey fluid are employed in the problem development. Heat and mass transfer aspects are examined in the presence of thermophoresis and Brownian motion. Jeffrey [...] Read more.
The present communication examines the magnetohydrodynamic (MHD) squeezing flow of Jeffrey nanofluid between two parallel disks. Constitutive relations of Jeffrey fluid are employed in the problem development. Heat and mass transfer aspects are examined in the presence of thermophoresis and Brownian motion. Jeffrey fluid subject to time dependent applied magnetic field is conducted. Suitable variables lead to a strong nonlinear system. The resulting systems are computed via homotopic approach. The behaviors of several pertinent parameters are analyzed through graphs and numerical data. Skin friction coefficient and heat and mass transfer rates are numerically examined. Full article
(This article belongs to the Special Issue Recent Developments of Nanofluids)
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">ħ</span> -Curves for <span class="html-italic">f</span>, <math display="inline"> <semantics> <mi mathvariant="sans-serif">θ</mi> </semantics> </math> and <math display="inline"> <semantics> <mi mathvariant="sans-serif">ϕ</mi> </semantics> </math> at the lower disk.</p>
Full article ">Figure 2
<p><span class="html-italic">ቿ</span> -Curves for <span class="html-italic">f</span>, <math display="inline"> <semantics> <mi mathvariant="sans-serif">θ</mi> </semantics> </math> and <math display="inline"> <semantics> <mi mathvariant="sans-serif">ϕ</mi> </semantics> </math> at the upper disk.</p>
Full article ">Figure 3
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">β</mi> </mrow> </semantics> </math>.</p>
Full article ">Figure 4
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>N</mi> <mi>b</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 5
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>N</mi> <mi>t</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 6
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>P</mi> <mi>r</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 7
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">θ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>S</mi> <mi>q</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 8
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">ϕ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">β</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 9
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">ϕ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>N</mi> <mi>b</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 10
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">ϕ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>N</mi> <mi>t</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 11
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">ϕ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>L</mi> <mi>e</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 12
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">ϕ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <mi>P</mi> <mi>r</mi> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">Figure 13
<p>Plots of <math display="inline"> <semantics> <mrow> <mi mathvariant="sans-serif">ϕ</mi> <mo>(</mo> <mi mathvariant="sans-serif">η</mi> <mo>)</mo> </mrow> </semantics> </math> for <math display="inline"> <semantics> <mrow> <msub> <mi>S</mi> <mi>q</mi> </msub> <mo>.</mo> </mrow> </semantics> </math></p>
Full article ">
9651 KiB  
Article
Experimental Study on the Force-Bearing Performance of Masonry Structures with a Marble-Graphite Slide Seismic Isolator at the Foundation
by Suizi Jia, Yan Liu, Wanlin Cao, Wei Ye and Yuchen Zhang
Appl. Sci. 2016, 6(11), 345; https://doi.org/10.3390/app6110345 - 10 Nov 2016
Cited by 8 | Viewed by 4651
Abstract
As part of the search for a seismic isolator for low-rise buildings, this paper proposes a marble-graphite slide seismic isolation system composed of marble-graphite slides, an upper foundation beam, the lower counterpart of the upper beam, and the corresponding stop blocks, with the [...] Read more.
As part of the search for a seismic isolator for low-rise buildings, this paper proposes a marble-graphite slide seismic isolation system composed of marble-graphite slides, an upper foundation beam, the lower counterpart of the upper beam, and the corresponding stop blocks, with the stop blocks consisting of restrictive screws, positioning plates, nut connectors and stop holes linking the two foundation beams. To provide the desired isolation performance, plain mortar bars can be included at the beam interface to better control the initiating loads for foundation slippage. Tests of low-reversed cyclic loading were performed on four different masonry specimens: a recycled brick wall, a clay brick wall, an integrated recycled brick wall with flay ash blocks sandwiched between, and its clay brick counterpart. The four specimens were provided with marble-graphite slide isolators placed at the foundations. The isolator thickness was 20 mm, and the graphite and the marble served as a lubricant and a bearing, respectively. This paper then analyses all of the specimens in terms of the damage that occurred, the initiating load for slippage, the hysteretic performance, the bearing capacity and the performance of the stop blocks. The results indicate that mortar bars embedded in the marble-graphite slide isolator offer effective control of the initiating load, and the isolation system delivers good hysteretic performance. The stop blocks are capable of withstanding a large-magnitude earthquake and are a good choice for constraining the slippage displacement. Damage or failure of the specimens occurs only when the low-reversed cyclic loading continues after slippage takes place. The design is shown to be an outstanding and flexible seismic scheme for use in low-rise buildings. Full article
Show Figures

Figure 1

Figure 1
<p>The prototype structure (<b>a</b>) a plan view; (<b>b</b>) an elevation view; (<b>c</b>) a 3D prototype structure.</p>
Full article ">Figure 2
<p>Specimen Design, RC: reinforced concrete; MG: marble-graphite.</p>
Full article ">Figure 3
<p>Configuration of the Stop Block.</p>
Full article ">Figure 4
<p>Example specimen diagrams (<b>a</b>) Glass-Graphite –Base-Wall-1 (GGBW-1); (<b>b</b>) GGBW-4; (①- clay bricks; ②- concrete stem; ③- recycled bricks; ④- flay ash blocks).</p>
Full article ">Figure 5
<p>The making of the specimens: (<b>a</b>) stem making; (<b>b</b>) wall making; (<b>c</b>) completed specimen and its maintenance.</p>
Full article ">Figure 6
<p>Equipment and measurement: (<b>a</b>) loading devices and indicator arrangement; (<b>b</b>) test scene; (①- reaction wall; ②- loading frame; ③- 50t jack; ④- 50t sensor; ⑤- loading beam; ⑥- displacement sensor for loading beam; ⑦- wall; ⑧- marble-graphite isolator; ⑨- anchor block; ⑩- upper foundation beam; ⑪ - lower foundation beam; ⑫ - displacement sensor for upper foundation beam; ⑬ - dial indicator).</p>
Full article ">Figure 7
<p>The loading approach: (<b>a</b>) preliminary deformation stage; (<b>b</b>) isolator slippage stage; (<b>c</b>) seismic resistance of the wall stage.</p>
Full article ">Figure 8
<p>MG isolator: (<b>a</b>) MG mixture; (<b>b</b>) MG isolator in place.</p>
Full article ">Figure 9
<p>Mortar bar(s).</p>
Full article ">Figure 10
<p>Failure process of GGBW-1: (<b>a</b>) slide isolator; (<b>b</b>) preliminary cracking; (<b>c</b>) specimen failure.</p>
Full article ">Figure 11
<p>Failure process of GGBW-2: (<b>a</b>) slide isolator; (<b>b</b>) preliminary cracking; (<b>c</b>) specimen failure.</p>
Full article ">Figure 12
<p>Failure process of GGBW-3: (<b>a</b>) slide isolator; (<b>b</b>) preliminary cracking; (<b>c</b>) specimen failure.</p>
Full article ">Figure 13
<p>Failure process of GGBW-4: (<b>a</b>) slide isolator; (<b>b</b>) preliminary cracking; (<b>c</b>) specimen failure.</p>
Full article ">Figure 14
<p>MG slide and restrictive rebars upon failure of wall (<b>a</b>) buckled restrictive rebars; (<b>b</b>) MG slide upon failure of wall.</p>
Full article ">Figure 15
<p><span class="html-italic">F-U<sub>1</sub></span> hysteretic curves. (<b>a</b>) GGBW-1; (<b>b</b>) GGBW-2; (<b>c</b>) GGBW-3; (<b>d</b>) GGBW-4.</p>
Full article ">Figure 15 Cont.
<p><span class="html-italic">F-U<sub>1</sub></span> hysteretic curves. (<b>a</b>) GGBW-1; (<b>b</b>) GGBW-2; (<b>c</b>) GGBW-3; (<b>d</b>) GGBW-4.</p>
Full article ">Figure 16
<p><span class="html-italic">F-U<sub>2</sub></span> hysteretic Curves: (<b>a</b>) GGBW-1; (<b>b</b>) GGBW-3; (<b>c</b>) GGBW-4.</p>
Full article ">Figure 16 Cont.
<p><span class="html-italic">F-U<sub>2</sub></span> hysteretic Curves: (<b>a</b>) GGBW-1; (<b>b</b>) GGBW-3; (<b>c</b>) GGBW-4.</p>
Full article ">Figure 17
<p>Comparison of <span class="html-italic">F-U<sub>1</sub></span> and <span class="html-italic">F-U<sub>2</sub></span> Skeleton Curves: (<b>a</b>) GGBW-1; (<b>b</b>) GGBW-2; (<b>c</b>) GGBW-3; (<b>d</b>) GGBW-4.</p>
Full article ">Figure 18
<p>Force-bearing performance of mortar bars. (<b>a</b>) GGBW-1; (<b>b</b>) GGBW-2; (<b>c</b>) GGBW-3; (<b>d</b>) GGBW-4.</p>
Full article ">
5037 KiB  
Article
Analysis and Compensation of Dead-Time Effect of a ZVT PWM Inverter Considering the Rise- and Fall-Times
by Hailin Zhang, Baoquan Kou, Lu Zhang and He Zhang
Appl. Sci. 2016, 6(11), 344; https://doi.org/10.3390/app6110344 - 9 Nov 2016
Cited by 10 | Viewed by 7925
Abstract
The dead-time effect, as an intrinsic problem of the converters based on the half-bridge unit, leads to distortions in the converter output. Although several dead-time effect compensation or elimination methods have been proposed, they cannot fully remove the dead-time effect of blanking delay [...] Read more.
The dead-time effect, as an intrinsic problem of the converters based on the half-bridge unit, leads to distortions in the converter output. Although several dead-time effect compensation or elimination methods have been proposed, they cannot fully remove the dead-time effect of blanking delay error, because the output current polarity is difficult detect accurately. This paper utilizes the zero-voltage-switching (ZVT) technique to eliminate the blanking delay error, which is the main drawback of the hard-switching inverter, although the technique initially aims to improve the efficiency. A typical ZVT inverter—the auxiliary resonant snubber inverter (ARSI) is analyzed. The blanking delay error is completely eliminated in the ARSI. Another error source caused by the finite rise- and fall-times of the voltage is analyzed, which was not considered in the hard-switching inverter. A compensation method based on the voltage error estimation is proposed to compensate the rise- and fall-error. A prototype was developed to verify the effectiveness of the proposed control. Both the simulation and experimental results demonstrate that the qualities of the output current and voltage in the ARSI are better than that in the hard-switching inverter due to the elimination of the blanking delay error. The total harmonic distortion (THD) of the output is further reduced by using the proposed compensation method in the ARSI. Full article
Show Figures

Figure 1

Figure 1
<p>Circuit of auxiliary resonant snubber inverter.</p>
Full article ">Figure 2
<p>Key waveforms of the the auxiliary resonant snubber inverter (ARSI) in the heavy load condition.</p>
Full article ">Figure 3
<p>Key waveforms of the ARSI in the light load condition.</p>
Full article ">Figure 4
<p>Dead-time effect of the ARSI.</p>
Full article ">Figure 5
<p>Dead-time effect of hard-switching inverter with single pole (<b>a</b>) the operating stages when <span class="html-italic">i<sub>o</sub></span> &gt; 0; (<b>b</b>) the key waveforms when <span class="html-italic">i<sub>o</sub></span> &gt; 0; (<b>c</b>) the key waveforms when <span class="html-italic">i<sub>o</sub></span> &lt; 0.</p>
Full article ">Figure 6
<p>Transfer function of the ARSI.</p>
Full article ">Figure 7
<p>Transfer function of the ARSI with feedforward compensation.</p>
Full article ">Figure 8
<p>Photograph of the prototype.</p>
Full article ">Figure 9
<p>Open-loop control diagram of the ARSI with proposed dead-time effect compensation.</p>
Full article ">Figure 10
<p>Average voltage error vs. output current in the calculation.</p>
Full article ">Figure 11
<p>Resonant time vs. the switching current both in the calculation and simulation.</p>
Full article ">Figure 12
<p>Output voltage and current of the hard-switching inverter when the modulation index is 0.4 in an open-loop configuration. (<b>a</b>) simulation results; (<b>b</b>) experimental results.</p>
Full article ">Figure 13
<p>Simulation waveforms of ARSI without dead-time compensation when the modulation index is 0.4 in an open-loop configuration. (<b>a</b>) simulation results; (<b>b</b>) voltage error.</p>
Full article ">Figure 14
<p>Experimental waveforms of ARSI without dead-time compensation when the modulation index is 0.4 in an open-loop configuration.</p>
Full article ">Figure 15
<p>Simulation waveforms of ARSI with dead-time compensation when the modulation index is 0.4 in an open-loop configuration. (<b>a</b>) simulation results; (<b>b</b>) voltage error.</p>
Full article ">Figure 16
<p>Experimental waveforms of ARSI with dead-time compensation when the modulation index is 0.4 in an open-loop configuration.</p>
Full article ">Figure 17
<p>Magnitudes of the 2nd–10th harmonic components in respect to the fundamental component (<b>a</b>) output voltage; (<b>b</b>) output current.</p>
Full article ">Figure 18
<p>Experimental voltage and current THDs under different load condition (<b>a</b>) voltage THD; (<b>b</b>) current THD.</p>
Full article ">
1815 KiB  
Article
Optimization of One-Step In Situ Transesterification Method for Accurate Quantification of EPA in Nannochloropsis gaditana
by Yuting Tang, Yue Zhang, Julian N. Rosenberg, Michael J. Betenbaugh and Fei Wang
Appl. Sci. 2016, 6(11), 343; https://doi.org/10.3390/app6110343 - 8 Nov 2016
Cited by 18 | Viewed by 5486
Abstract
Microalgae are a valuable source of lipid feedstocks for biodiesel and valuable omega-3 fatty acids. Nannochloropsis gaditana has emerged as a promising producer of eicosapentaenoic acid (EPA) due to its fast growth rate and high EPA content. In the present study, the fatty [...] Read more.
Microalgae are a valuable source of lipid feedstocks for biodiesel and valuable omega-3 fatty acids. Nannochloropsis gaditana has emerged as a promising producer of eicosapentaenoic acid (EPA) due to its fast growth rate and high EPA content. In the present study, the fatty acid profile of Nannochloropsis gaditana was found to be naturally high in EPA and devoid of docosahexaenoic acid (DHA), thereby providing an opportunity to maximize the efficacy of EPA production. Using an optimized one-step in situ transesterification method (methanol:biomass = 90 mL/g; HCl 5% by vol.; 70 °C; 1.5 h), the maximum fatty acid methyl ester (FAME) yield of Nannochloropsis gaditana cultivated under rich condition was quantified as 10.04% ± 0.08% by weight with EPA-yields as high as 4.02% ± 0.17% based on dry biomass. The total FAME and EPA yields were 1.58- and 1.23-fold higher separately than that obtained using conventional two-step method (solvent system: methanol and chloroform). This one-step in situ method provides a fast and simple method to measure fatty acid methyl ester (FAME) yields and could serve as a promising method to generate eicosapentaenoic acid methyl ester from microalgae. Full article
(This article belongs to the Section Chemical and Molecular Sciences)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Effect of the ratio between methanol and biomass on the fatty acid methyl ester (FAME) yield. Reaction conditions: HCl/Methanol (5%, <span class="html-italic">v</span>/<span class="html-italic">v</span>), reaction temperature: 70 °C, reaction time: 1.5 h.</p>
Full article ">Figure 2
<p>Effect of acid concentration on the FAME yield. Reaction conditions: methanol-to-biomass ratio: 90 mL·g<sup>−1</sup>, reaction temperature: 70 °C, reaction time: 1.5 h.</p>
Full article ">Figure 3
<p>Effect of reaction time on the FAME yield. Reaction conditions: methanol-to-biomass ratio: 90 mL·g<sup>−1</sup>, HCl/Methanol (5%, <span class="html-italic">v</span>/<span class="html-italic">v</span>), reaction temperature: 70 °C.</p>
Full article ">Figure 4
<p>Effect of reaction temperature on the FAME yield. Reaction conditions: methanol-to-biomass ratio: 90 mL·g<sup>−1</sup>, HCl/Methanol (5%, <span class="html-italic">v</span>/<span class="html-italic">v</span>), reaction time: 1.5 h.</p>
Full article ">Figure 5
<p>(<b>a</b>) Extraction yield based on dry biomass; FAME yield based on total extract (%DW); (<b>b</b>) FAME yield of dry biomass (%DW).</p>
Full article ">
Previous Issue
Next Issue
Back to TopTop