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Keywords = straight wing aircraft

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26 pages, 11593 KiB  
Article
Experimental Parameter Identification and an Evaluation of the Impact of Tire Models on the Dynamics of Fixed-Wing Unmanned Aerial Vehicles
by Hikaru Eguchi and Daisuke Nakata
Aerospace 2024, 11(8), 620; https://doi.org/10.3390/aerospace11080620 - 29 Jul 2024
Viewed by 630
Abstract
Because fixed-wing unmanned aerial vehicles (UAVs) require high-speed taxiing for takeoff and landing, the aircraft’s stability during taxiing is critical. However, despite research on the taxiing stability of fixed-wing UAVs conducted in taxiing motion simulations employing various tire models, the applicability of the [...] Read more.
Because fixed-wing unmanned aerial vehicles (UAVs) require high-speed taxiing for takeoff and landing, the aircraft’s stability during taxiing is critical. However, despite research on the taxiing stability of fixed-wing UAVs conducted in taxiing motion simulations employing various tire models, the applicability of the models to fixed-wing UAV taxiing simulations remains unclear, as does the rationale behind the parameter settings in the models. Therefore, in our study, we measured the forces acting on the tires of a fixed-wing UAV under various conditions, including tire loads of 1.6–3.6 kg and tire slip angles of 0–40 deg. Based on the results, we modified conventional tire models and assessed their applicability in taxiing simulations. Among our findings, the parameter values of the models significantly differed from those used in crewed aircraft taxiing simulations, and the presence or absence of load parameters in the lateral force tire models significantly affected the dynamics. Furthermore, the aerodynamics acting on the aircraft enhanced the straight-line stability during taxiing, resulting in reduced forces on the tires. Full article
(This article belongs to the Special Issue Aircraft Design and System Optimization)
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Figure 1
<p>The definition of the coordinate system and forces acting on the tire.</p>
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<p>(<b>a</b>) Schematic of tire force measurement device and (<b>b</b>) measurement part.</p>
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<p>(<b>a</b>) Constructed tire force measurement device and (<b>b</b>) specimen tire.</p>
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<p>Results of measuring longitudinal force <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Results of measuring lateral force <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Results of measuring vertical reaction force <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Slope of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math> in relation to <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math> at <math display="inline"><semantics> <mrow> <mi>β</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> deg. S.E. = standard error.</p>
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<p>Results of fitting <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>x</mi> <mi>β</mi> </mrow> </msub> </mrow> </semantics></math> for each load.</p>
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<p>Comparison of lateral force <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math> calculated using Equation (6) and experimental results. S.E. = standard error.</p>
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<p>A quadratic approximation of the peak value of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Fitting of the slope <math display="inline"><semantics> <mrow> <mi>B</mi> <mi>C</mi> <mi>D</mi> </mrow> </semantics></math> as a function of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Quadratic approximation of <math display="inline"><semantics> <mrow> <mi>E</mi> </mrow> </semantics></math>.</p>
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<p>Comparison of longitudinal force <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>x</mi> </mrow> </msub> </mrow> </semantics></math> calculated using Equation (12) and experimental results.</p>
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<p>Comparison of lateral force <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math> calculated with Magic Formula tire model and experimental results.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math> calculated with the Magic Formula tire model for changes in <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Comparison of lateral force <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math> calculated using Equation (9) and experimental results.</p>
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<p><math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>y</mi> </mrow> </msub> </mrow> </semantics></math> calculated with Equation (9) for changes in <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>F</mi> </mrow> <mrow> <mi>z</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>(<b>a</b>) One-third-scale Oowashi and (<b>b</b>) dimensions of one-third-scale Oowashi.</p>
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<p>A force diagram and parameters for a dynamic model of a UAV.</p>
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<p>(<b>a</b>) Trajectories of LT and NT1, and (<b>b</b>) velocities and yaw angles of LT and NT1.</p>
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<p>Comparison of slip angle <math display="inline"><semantics> <mrow> <mi>β</mi> </mrow> </semantics></math> and tire forces between LT and NT1 under steering input of 5 deg.: (<b>a</b>) nose tire, (<b>b</b>) right main tire, and (<b>c</b>) left main tire.</p>
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<p>(<b>a</b>) Trajectories of NT1 and NT2 and (<b>b</b>) velocities and yaw angles of NT1 and NT2.</p>
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<p>Comparison of slip angle <math display="inline"><semantics> <mrow> <mi>β</mi> </mrow> </semantics></math> and tire forces between NT1 and NT2 under steering input of 5 deg.: (<b>a</b>) nose tire, (<b>b</b>) right main tire, and (<b>c</b>) left main tire.</p>
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<p>(<b>a</b>) Trajectories of LT considering aerodynamics, NT1 considering aerodynamics, and NT1; (<b>b</b>) velocities and yaw angles of LT considering aerodynamics, NT1 considering aerodynamics, and NT1; and (<b>c</b>) rolling and yawing moments of LT considering aerodynamics, NT1 considering aerodynamics, and NT1.</p>
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<p>Comparison of slip angle <math display="inline"><semantics> <mrow> <mi>β</mi> </mrow> </semantics></math> and tire forces between NT1 aero, NT2 aero, and NT2.: (<b>a</b>) nose tire, (<b>b</b>) right main tire, and (<b>c</b>) left main tire.</p>
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21 pages, 6712 KiB  
Article
Design and Flight Simulation Verification of the Dragonfly eVTOL Aircraft
by Wen Zhao, Yingqi Wang, Liqiao Li, Fenghua Huang, Hanwen Zhan, Yiqi Fu and Yunfei Song
Drones 2024, 8(7), 311; https://doi.org/10.3390/drones8070311 - 9 Jul 2024
Viewed by 803
Abstract
Recently, electric vertical take-off and landing (eVTOL) aircraft have become a top priority for urban air transportation due to their ability to overcome urban ground traffic congestion. In this research, a new type of scaled lift–cruise ‘Dragonfly’ has been designed. The ‘Dragonfly’ combines [...] Read more.
Recently, electric vertical take-off and landing (eVTOL) aircraft have become a top priority for urban air transportation due to their ability to overcome urban ground traffic congestion. In this research, a new type of scaled lift–cruise ‘Dragonfly’ has been designed. The ‘Dragonfly’ combines the characteristics of an octocopter and a fixed-wing aircraft. Compared with the same type of eVTOL aircraft, it has a longer wingspan and a more stable aircraft structure, it can not only take off and land vertically without the need for a runway, but also fly quickly in a straight line and hover in mid-air. In order to ensure the success of the flight test, it was also simulated in this paper. A simulation scenario highly fitting with the flight test environment of eVTOL is designed in the Gazebo simulation platform, and then combined with the PX4 flight control platform, the system SITL of the constructed aircraft simulation model is carried out on the Gazebo platform, Finally, simulation flight test data for accurate analysis are obtained, the accuracy and stability of the control algorithm are fed back, and scientific support for the follow-up ‘Dragonfly’ aircraft hardware-in-the-loop simulation and physical flight test is provided. Full article
(This article belongs to the Section Drone Design and Development)
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<p>(<b>a</b>) ‘Vahana’ (Airbus), (<b>b</b>) ‘E20’ (Tcab Tech. Co., Ltd.), (<b>c</b>) ‘VoloCity’ (Volocopter), (<b>d</b>) ‘ehang-216’ (NASDAQ/EH), (<b>e</b>) ‘Boeing-PAV’ (Boeing), (<b>f</b>) ‘V1500M’ (Autoflight).</p>
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<p>(<b>a</b>) The prototype design of the ‘Dragonfly’ eVTOL; (<b>b</b>) the prototype design of the ‘Dragonfly’ eVTOL.</p>
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<p>Three-dimensional model diagram of ‘Dragonfly’ aircraft.</p>
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<p>Structural components of simplified aircraft model.</p>
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<p>Overall structure diagram of aircraft URDF model.</p>
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<p>‘base_ link’ and ‘lf1_ prop_ link’ connection diagram.</p>
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<p>URDF model label hierarchy of aircraft.</p>
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<p>Display interface of aircraft simulation model in Gazebo.</p>
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<p>Diagram of the angle of attack and coefficient of lift.</p>
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<p>Schematic diagram of the principal architecture of the “Dragonfly” flight control system.</p>
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<p>Add sensors by using &lt;gazebo&gt; and &lt;plugin&gt; labels.</p>
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<p>The architecture of system software-in-the-loop simulation.</p>
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<p>Diagram of ROS nodes.</p>
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<p>The planned flight path.</p>
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<p>The flight simulation test diagram in the whole flight profile.</p>
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<p>The flight simulation diagram at each stage: (<b>a</b>) climb, (<b>b</b>) cruise, (<b>c</b>) glide, (<b>d</b>) landing.</p>
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<p>The raw data output by IMU and magnetometer sensors.</p>
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<p>The change in flight attitude: (<b>a</b>) roll, (<b>b</b>) pitch, (<b>c</b>) yaw, (<b>d</b>) three-axis attitude angle.</p>
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<p>(<b>a</b>) The changes in barometric/absolute altitude; (<b>b</b>) the changes in indicated/vacuum airspeed.</p>
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21 pages, 1001 KiB  
Article
Clothoid-Based Path Planning for a Formation of Fixed-Wing UAVs
by Luciano Blasi, Egidio D’Amato, Immacolata Notaro and Gennaro Raspaolo
Electronics 2023, 12(10), 2204; https://doi.org/10.3390/electronics12102204 - 12 May 2023
Cited by 7 | Viewed by 1849
Abstract
Unmanned aerial vehicles (UAVs) are playing an increasingly crucial role in many applications such as search and rescue, delivery services, and military operations. However, one of the significant challenges in this area is to plan efficient and safe trajectories for UAV formations. This [...] Read more.
Unmanned aerial vehicles (UAVs) are playing an increasingly crucial role in many applications such as search and rescue, delivery services, and military operations. However, one of the significant challenges in this area is to plan efficient and safe trajectories for UAV formations. This paper presents an optimization procedure for trajectory planning for fixed-wing UAV formations using graph theory and clothoid curves. The proposed planning strategy consists of two main steps. Firstly, the geometric optimization of paths is carried out using graphs for each UAV, providing piece-wise linear paths whose smooth connections are made with clothoids. Secondly, the geometric paths are transformed into time-dependent trajectories, optimizing the assigned aircraft speeds to avoid collisions by solving a mixed-integer optimal control problem for each UAV of the flight formation. The proposed method is effective in achieving suboptimal paths while ensuring collision avoidance between aircraft. A sensitivity analysis of the main parameters of the algorithm was conducted in ideal conditions, highlighting the possibility of decreasing the length of the optimal path by about 4.19%, increasing the number of points used in the discretization and showing a maximum path length reduction of about 10% compared with the average solution obtained with a similar algorithm using a graph based on random directions. Furthermore, the use of clothoids, whose parameters depend on the UAV performance constraints, provides smoother connections, giving a significant improvement over traditional straight-line or circular trajectories in terms of flight dynamics compliance and trajectory tracking capabilities. The method can be applied to various UAV formation scenarios, making it a versatile and practical tool for mission planning. Full article
(This article belongs to the Section Networks)
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<p>Intersection between the paths of the <span class="html-italic">i</span>th and <span class="html-italic">j</span>th UAV.</p>
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<p>Test case #1: Path planning considering several configuration parameters as shown in <a href="#electronics-12-02204-t002" class="html-table">Table 2</a>. (<b>a</b>) Minimum (<span class="html-italic">rand min</span>) and average (<span class="html-italic">rand mean</span>) path length found with the random-based graph compared with the minimum path length found with the fixed-based graph; (<b>b</b>) computational time, obtained with an Intel i5-8250u based laptop.</p>
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<p>Test case #1: Optimum paths with different grid configurations.</p>
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<p>Test case #2: Path planning considering several configuration parameters, as shown in <a href="#electronics-12-02204-t002" class="html-table">Table 2</a>. (<b>a</b>) Path length and (<b>b</b>) computational time, obtained with an Intel i5-8520u based laptop.</p>
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<p>Test case #2: Optimum paths with different grid configurations.</p>
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<p>Test case #3: Results. (<b>a</b>) Optimal fleet paths to avoid obstacles and reach target points; (<b>b</b>) UAVs mutual distances during flight.</p>
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<p>Test case #3: Planned optimal speeds (<b>a</b>) and accelerations (<b>b</b>) during flight to avoid collisions in path intersections.</p>
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<p>Test case #4: Optimal fleet paths to avoid obstacles and reach target points. Coloured lines show the planned trajectories for each UAV.</p>
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<p>Test case #5: Fleet optimal paths to avoid obstacles and reach target points.</p>
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18 pages, 6449 KiB  
Article
Simulation of and Experimental Research on Rivulet Model on Airfoil Surface
by Yanxia Lou, Xueqin Bu, Xiaobin Shen, Guiping Lin, Ruchen Zhang, Feixiong Zeng, Haichuan Jin, Kuiyuan Ma and Dongsheng Wen
Aerospace 2022, 9(10), 570; https://doi.org/10.3390/aerospace9100570 - 29 Sep 2022
Cited by 3 | Viewed by 2143
Abstract
The occurrence of aircraft icing can significantly affect flight performance. One of the most important aspects in the study of anti-icing technology for aircraft is the distribution of overflow water. Owing to the external airflow pressure, shear stress, and surface tension, the water [...] Read more.
The occurrence of aircraft icing can significantly affect flight performance. One of the most important aspects in the study of anti-icing technology for aircraft is the distribution of overflow water. Owing to the external airflow pressure, shear stress, and surface tension, the water film breaks up to form steady rivulets. Experiments on NACA0012 airfoil surfaces were conducted based on an open straight-flow and low-speed wind tunnel. Simultaneously, an engineered three-dimensional rivulet model considering the surface roughness was established based on the energy-minimum principle. A comparison between the simulation and experimental results shows that the errors in the water film breakup location and the flow velocity of rivulets are less than 20%, and the errors in the spacing and width of rivulets are less than 40%. In addition, the effects of surface temperature and uniform roughness on water film breakup were investigated. Furthermore, the rivulet model was applied to the numerical calculation of the thermal performance of hot-air anti-icing systems. The simulations reveal that the uniform roughness of the wing surface causes the water film to break earlier. As the surface roughness increases, the thickness, spacing, and width of the rivulets increase, and the rivulet flow velocity decreases. Full article
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<p>Schematic diagram of water film breakup.</p>
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<p>Rivulet model.</p>
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<p>Schematic diagram of a three-dimensional control volume.</p>
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<p>Relationships between the Reynolds number of water film and the average thickness and interfacial shear coefficient under different roughness values: (<b>a</b>) Relationship between the Reynolds number of water film and the average thickness of water film [<a href="#B23-aerospace-09-00570" class="html-bibr">23</a>]; (<b>b</b>) Relationship between the Reynolds number of water film and the interfacial shear coefficient.</p>
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<p>Water film breakup experimental system.</p>
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<p>Calibration of air speed in the test section of the wind tunnel.</p>
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<p>Experimental samples: (<b>a</b>) Straight wing; (<b>b</b>) Sweptback wing.</p>
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<p>Static contact angle measurement: (<b>a</b>) Equipment; (<b>b</b>) Captured image.</p>
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<p>Local collection efficiencies at different air speeds.</p>
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<p>The experimental phenomenon captured at an air speed of 20 m/s.</p>
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<p>Comparison of experiment and simulation results for a straight wing: (<b>a</b>) The spacing between rivulets; (<b>b</b>) The width of the rivulets; (<b>c</b>) Water film breakup location as a percentage of the total chord; (<b>d</b>) Rivulet velocity at 1/2 chord position.</p>
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<p>Comparison of experiment and simulation results of a sweptback wing: (<b>a</b>) The spacing between rivulets; (<b>b</b>) The width of the rivulets; (<b>c</b>) Water film breakup location as a percentage of the total chord; (<b>d</b>) Rivulet velocity at 1/2 chord position.</p>
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<p>Location of water film breakup.</p>
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<p>Flow chart of heat transfer coupling calculation.</p>
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<p>Heated area of the anti-ice system.</p>
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<p>Contour of the water mass flow rate (kg/s): (<b>a</b>) Water film model; (<b>b</b>) Rivulet model.</p>
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<p>Distribution of the water flow rate along the chord.</p>
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18 pages, 4817 KiB  
Article
Shape Sensing for an UAV Composite Half-Wing: Numerical Comparison between Modal Method and Ko’s Displacement Theory
by Filippo Valoriani, Marco Esposito and Marco Gherlone
Aerospace 2022, 9(9), 509; https://doi.org/10.3390/aerospace9090509 - 13 Sep 2022
Cited by 6 | Viewed by 1901
Abstract
Shape sensing is the reconstruction of the displacement field of a structure from some discrete surface strain measurements and is a key technology for structural health monitoring. The aim of this paper is to compare two approaches to shape sensing that have been [...] Read more.
Shape sensing is the reconstruction of the displacement field of a structure from some discrete surface strain measurements and is a key technology for structural health monitoring. The aim of this paper is to compare two approaches to shape sensing that have been shown to be more efficient, especially for aircraft structures applications, in terms of required input strain measurements: the Ko’s Displacement Theory and the Modal Method. An object of the shape-sensing analysis is the half-wing of a multirotor UAV. The approaches are summarized in order to set the framework for the numerical comparative investigation. Then, the multirotor UAV is presented and a finite element model of its half-wing is used to simulate the static response to straight-and-level flight conditions. For a given common set of surface strain measurement points, Ko’s Displacement Theory and the Modal Method are compared in terms of accuracy of the reconstructed half-wing deflection and twist angle. The Modal Method is shown to be more accurate than Ko’s Displacement Theory, especially for the evaluation of the deflection field. Further numerical analyses show that the Modal Method is influenced by the set of mode shapes included in the analysis and that excellent reconstructed deflections can be obtained with a reduced number of sensors, thus assessing the approach as an efficient shape-sensing tool for aircraft structures real applications. Full article
(This article belongs to the Section Aeronautics)
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<p>Half-wing with reference system and sensor markers.</p>
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<p>Multirotor ICON V2, PROS3. (<b>a</b>) Back view of the aircraft, not operative at ground, (<b>b</b>) front view of the UAV during take-off, the rear propeller is switched off during this phase.</p>
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<p>Geometry of the half-wing, dimensions reported in millimeters. (<b>a</b>) ICON V2 disassembled half-wing (tape is attached on the external surface as a guide to indicate the position of ribs and spars), (<b>b</b>) drafting with quotations, TOP view, (<b>c</b>) axonometry with quotations, ribs height, (<b>d</b>) axonometry with quotations, ribs length, (<b>e</b>) wing airfoil (for confidentiality reasons, the airfoil type is not specified and its geometry has been directly taken from the CAD model provided by the PROS3 company).</p>
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<p>Geometry of the half-wing, dimensions reported in millimeters. (<b>a</b>) ICON V2 disassembled half-wing (tape is attached on the external surface as a guide to indicate the position of ribs and spars), (<b>b</b>) drafting with quotations, TOP view, (<b>c</b>) axonometry with quotations, ribs height, (<b>d</b>) axonometry with quotations, ribs length, (<b>e</b>) wing airfoil (for confidentiality reasons, the airfoil type is not specified and its geometry has been directly taken from the CAD model provided by the PROS3 company).</p>
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<p>Finite elements Half-wing model. (<b>a</b>) Half wing FE model, (<b>b</b>) Half-wing FE model with associated properties: Balsa (green) for ribs and spars, Foam + CFRP (red) for the tubular spars, GFRP (blue) for the upper and lower panels, (<b>c</b>) Tubular spars discretization: BAR2 elements (yellow) for the CFRP spars and QUAD4 elements (white) for the connection with the skin, (<b>d</b>) 3D visualization of tubular spars.</p>
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<p>Finite elements Half-wing model. (<b>a</b>) Half wing FE model, (<b>b</b>) Half-wing FE model with associated properties: Balsa (green) for ribs and spars, Foam + CFRP (red) for the tubular spars, GFRP (blue) for the upper and lower panels, (<b>c</b>) Tubular spars discretization: BAR2 elements (yellow) for the CFRP spars and QUAD4 elements (white) for the connection with the skin, (<b>d</b>) 3D visualization of tubular spars.</p>
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<p>Half-wing boundary and loading conditions (concentrated forces have both <span class="html-italic">y</span>-axis and a <span class="html-italic">z</span>-axis component, then are applied to each rib by means of rigid connections and correspond to the aerodynamic loads experienced during a straight-and-level flight).</p>
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<p>Half-wing deformed shape and displacements (magnitude) distribution (mm).</p>
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<p>Half-wing with strain measuring lines on the upper panel for the application of the Ko’s Displacement Theory.</p>
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<p>Neutral planes and measuring lines for Ko’s Displacement Theory. Cross-sections considered for neutral axis calculation are represented in purple color.</p>
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<p>Percent strain energy of the first 20 mode shapes (and of the first residual vector, 21st among the calculated ones).</p>
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<p>FEM modal analysis, deformed shape, and displacements (magnitude) distribution (mm): (<b>a</b>) first mode shape; (<b>b</b>) second mode shape; (<b>c</b>) residual vector.</p>
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<p>FEM modal analysis, deformed shape, and displacements (magnitude) distribution (mm): (<b>a</b>) first mode shape; (<b>b</b>) second mode shape; (<b>c</b>) residual vector.</p>
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<p>Result comparison between Modal Method (MM), Ko’s Displacement Theory (Ko), and FEM static analysis (FEM): (<b>a</b>) deflection along the first sensing line; (<b>b</b>) deflection along the second sensing line; (<b>c</b>) twist computed through the lines deflection.</p>
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<p>Result comparison between Modal Method (MM), Ko’s Displacement Theory (Ko), and FEM static analysis (FEM): (<b>a</b>) deflection along the first sensing line; (<b>b</b>) deflection along the second sensing line; (<b>c</b>) twist computed through the lines deflection.</p>
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<p>Optimal strain gauges configuration.</p>
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18 pages, 3017 KiB  
Article
Energy Acquisition of Solar-Powered Joint-Wing Aircraft Considering Mismatch Power Loss
by Xinzhe Ji, Kangwen Sun, Xiao Guo and Mou Sun
Energies 2022, 15(1), 157; https://doi.org/10.3390/en15010157 - 27 Dec 2021
Cited by 1 | Viewed by 2345
Abstract
Solar-powered aircraft can perform long-term flights with clean solar energy. However, the energy derived from solar irradiation is influenced by the time of year and latitude, which limits the energy acquisition ability of solar aircraft with a straight-wing configuration. Hence, unconventional configurations based [...] Read more.
Solar-powered aircraft can perform long-term flights with clean solar energy. However, the energy derived from solar irradiation is influenced by the time of year and latitude, which limits the energy acquisition ability of solar aircraft with a straight-wing configuration. Hence, unconventional configurations based on increasing wing dihedral to track the sun are proposed to improve energy acquisition at high-latitude regions in winter, which may involve power loss caused by mismatch in the photovoltaic system. However, mismatch loss is seldom considered and may cause energy to be overestimated. In this paper, the energy acquisition characteristics of a joint-wing configuration are presented based on the simulation of an energy system to investigate the mismatch power loss. The results indicate a 4~15% deviation from the frequently used estimation method and show that the mismatch loss is influenced by the curved upper surface, the severity of shading and the circuit configuration. Then, the configuration energy acquisition factor is proposed to represent the energy acquisition ability of the joint-wing configuration. Finally, the matching between the aircraft configuration and flight trajectory is analyzed, demonstrating that the solar-powered aircraft with an unconventional wing configuration is more sensitive to the coupling between configuration and trajectory. Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
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<p>Energy acquisition estimation of solar-powered aircraft.</p>
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<p>MPPT model based on modified hill-climbing algorithm.</p>
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<p>Wing sections and parameters of joint-wing layout.</p>
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<p>Shading states of P.</p>
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<p>Model of energy system.</p>
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<p>PV circuit configuration of a wing section.</p>
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<p>Output power of different wing sections over a period of 24 h. (<b>a</b>) Output power of wing section 3. (<b>b</b>) Output power of wing section 4.</p>
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<p>Irradiation inputs to PV modules. (<b>a</b>) PV modules on airfoil curve. (<b>b</b>) Irradiation inputs of wing section 4.</p>
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<p>Proportion of overlapping area.</p>
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<p>Output powers of different overlapping areas in 24 h. (<b>a</b>) Output power of wing section 3. (<b>b</b>) Output power of wing section 4.</p>
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<p>Energy acquisition of different overlapping areas. (<b>a</b>) Total energy of wing section 3. (<b>b</b>) Total energy of wing section 4.</p>
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<p>Models of different PV configurations. (<b>a</b>) SP circuit configuration. (<b>b</b>) BL circuit configuration. (<b>c</b>) TCT circuit configuration.</p>
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<p>Energy acquisition of different circuit configurations. (<b>a</b>) Output power of wing section 3. (<b>b</b>) Output power of wing section 3.</p>
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<p>Output characteristics of different circuit configurations. (<b>a</b>) Partial shading conditions. (<b>b</b>) I–V curve.</p>
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<p>Energy acquisition ability in aircraft body-fixed coordinate system. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mrow> <mi>C</mi> <mi>E</mi> <mi>A</mi> </mrow> </msub> </mrow> </semantics></math> of straight-wing layout. (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mrow> <mi>C</mi> <mi>E</mi> <mi>A</mi> </mrow> </msub> </mrow> </semantics></math> of joint-wing layout.</p>
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<p>Energy acquisition factor versus <math display="inline"><semantics> <mrow> <msub> <mi>α</mi> <mi>B</mi> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mi>B</mi> </msub> </mrow> </semantics></math>.</p>
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<p>Energy acquisition estimation based on <math display="inline"><semantics> <mrow> <msub> <mi>F</mi> <mrow> <mi>C</mi> <mi>E</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Optimal <math display="inline"><semantics> <mrow> <msub> <mi>ψ</mi> <mi>B</mi> </msub> </mrow> </semantics></math> with the value of <math display="inline"><semantics> <mrow> <msub> <mi>μ</mi> <mrow> <mi>C</mi> <mi>E</mi> <mi>A</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Output power of different configurations with different flight strategies.</p>
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20 pages, 11442 KiB  
Article
Sol–Gel Waveguide-Based Sensor for Structural Health Monitoring on Large Surfaces in Aerospace Domain
by Maxime Royon, Damien Jamon, Thomas Blanchet, François Royer, Francis Vocanson, Emmanuel Marin, Adriana Morana, Aziz Boukenter, Youcef Ouerdane, Yves Jourlin, Rolf Evenblij, Thijs Van Leest, Marie-Anne de Smet and Sylvain Girard
Aerospace 2021, 8(4), 109; https://doi.org/10.3390/aerospace8040109 - 14 Apr 2021
Cited by 9 | Viewed by 3693
Abstract
The potential of sol–gel-based optical sensors is investigated for applications in the aerospace domain. To this aim, a low-cost and non-intrusive sol–gel sensor based on waveguides, arranged as a 2D matrix structure, is fabricated by UV photolithography for delamination and damage detection. Two [...] Read more.
The potential of sol–gel-based optical sensors is investigated for applications in the aerospace domain. To this aim, a low-cost and non-intrusive sol–gel sensor based on waveguides, arranged as a 2D matrix structure, is fabricated by UV photolithography for delamination and damage detection. Two different organic–inorganic sol–gels were selected to fabricate the photonic device: TiO2–SiO2 and ZrO2–SiO2, acting as the waveguide core and the cladding, respectively. A systematic study was performed to determine the manufacturing parameters controlling their properties. The results show that large surfaces can be functionalized via sol–gel methods using the direct laser-writing approach. The structures are characterized in terms of refractive index, and the guiding properties were investigated through simulations and experiments, indicating an excellent behavior regarding the light guidance in a straight waveguide or in the 2D matrix structure grid. Additionally, preliminary tests show that the presence of impact can be easily detected after damage through the induced optical losses on large surfaces. This proof of concept sensor is a promising tool for structural health monitoring. To achieve the ultimate goal, the integration of this photonic sensor will be later performed on aircraft wings. Full article
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<p>Final architecture of the 2D sol–gel matrix sensor for damage detection. The sensor is based on a grid of optical waveguides. An impact on the plane leads to the degradation or the rupture of one or more waveguides. Thanks to the particular 2D structure of the sensing material, the identification of the impacted damage allows the damage localization.</p>
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<p>Preparation of the different organic–inorganic sol–gel solutions. Material synthesis of (<b>a</b>) TiO<sub>2</sub>–SiO<sub>2</sub> and (<b>b</b>) ZrO<sub>2</sub>–SiO<sub>2</sub> sols. In both cases, a photoinitiator (DMPA) is added to induce the start of UV-polymerization reactions.</p>
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<p>Example of the photolithography processes used for the layer structuration. (<b>a</b>) Photolithography by photomask on an organic–inorganic layer. (<b>b</b>) Principle of the direct writing technique (Dilase 750 from Kloé company, Montpellier, France). A laser beam is focused on the hybrid thin films. The structures are created by the translation of the stages in the X and Y directions while the laser beam is fixed. The black lines on the layer represent the UV photopolymerized exposed regions.</p>
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<p>TiO<sub>2</sub>–SiO<sub>2</sub> patterns obtained using the amplitude mask with different slits at 15 µm, 8 µm and 3 µm. Microscope observations (reflection x20) of (<b>a</b>) line obtained with a slit of 15 µm in width, (<b>b</b>) line obtained with a slit of 8 µm and (<b>c</b>) line obtained with a slit of 3 µm. (<b>d</b>) Profilometer measurement of (<b>a</b>).</p>
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<p>Investigation of TiO<sub>2</sub>–SiO<sub>2</sub> (red squared curve) and ZrO<sub>2</sub>–SiO<sub>2</sub> (black dotted curve) thicknesses using the spin coating (<b>a</b>) and the dip coating (<b>b</b>) methods.</p>
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<p>TiO<sub>2</sub>–SiO<sub>2</sub> grid observed using an optical microscope in a reflection mode (×20). The crossed TiO<sub>2</sub>–SiO<sub>2</sub> area is not affected by the double exposure (360 J/cm<sup>2</sup>).</p>
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<p>Structures obtained by the direct writing technique showing (<b>a</b>) lines obtained at 10% and for different scanning speed (200 µm/s, 1 and 10 mm/s), (<b>b</b>) calcinated trace induced at 30% and 200 µm/s and (<b>c</b>) Jean Monnet University logo with a 420 µm size in height.</p>
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<p>Characterization of the photo-induced patterns using the Dilase 750 facility. (<b>a</b>) Width of the structures as a function of the scanning speed for powers ranging from 1% and 15% and (<b>b</b>) profile obtained for a line written at 10% and 200 µm/s.</p>
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<p>TiO<sub>2</sub>–SiO<sub>2</sub> grid architecture on a large substrate composed of 62 guides. (<b>a</b>) Overview of the sensor, (<b>b</b>) corresponding zoom showing the 1 cm separation between two consecutive lines and (<b>c</b>) microscope image of the doubled exposed zone.</p>
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<p>Two configurations of the photonic device deposited on soda-lime glass. (<b>a</b>) TiO<sub>2</sub>–SiO<sub>2</sub> core without cladding and surrounded by air. (<b>b</b>) TiO<sub>2</sub>–SiO<sub>2</sub> core buried in a ZrO<sub>2</sub>–SiO<sub>2</sub> coating and (<b>c</b>) output light of the TiO<sub>2</sub>–SiO<sub>2</sub> core waveguide with ZrO<sub>2</sub>–SiO<sub>2</sub> cladding obtained experimentally.</p>
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<p>Refractive index of TiO<sub>2</sub>–SiO<sub>2</sub> (red line) and ZrO<sub>2</sub>–SiO<sub>2</sub> (black line) obtained by the ellipsometry technique. The layers were insolated by UV photons and thermally treated.</p>
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<p>Simulated transverse electric TE<sub>00</sub> mode of a TiO<sub>2</sub>–SiO<sub>2</sub> waveguide deposited on a soda-lime glass surrounded by air and operating at (<b>a</b>) 630 nm, (<b>b</b>) 810 nm and (<b>c</b>) 1550 nm. The thicknesses and widths are 5 µm and 10 µm, respectively.</p>
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<p>Simulated TE<sub>00</sub> mode of a TiO<sub>2</sub>–SiO<sub>2</sub> waveguide deposited on soda-lime glass and surrounded by the ZrO<sub>2</sub>–SiO<sub>2</sub> cladding and operating at (<b>a</b>) 630 nm, (<b>b</b>) 810 nm and (<b>c</b>) 1550 nm. The thicknesses and widths are 5 µm and 10 µm, respectively.</p>
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<p>Characterization of TiO<sub>2</sub>–SiO<sub>2</sub> waveguides (surrounded by air). The figure illustrates: (<b>a</b>) top-view of the waveguide injection at 638 nm, (<b>b</b>) output optical guided mode at 638 nm and (<b>c</b>) guided mode at 1550 nm.</p>
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<p>Injection of visible light (638 nm) in the architecture composed of the TiO<sub>2</sub>–SiO<sub>2</sub> core deposited on soda-lime glass and surrounded by the ZrO<sub>2</sub>–SiO<sub>2</sub> cladding. (<b>a</b>) Diagram of the SMF28 misaligned with the core, (<b>b</b>) corresponding output, (<b>c</b>) diagram of SMF28 aligned with the core and (<b>d</b>) corresponding guided mode. The SMF28 is schematized by black circles.</p>
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<p>Damage detection with a TiO<sub>2</sub>–SiO<sub>2</sub> waveguide operating at 638 nm showing: (<b>a</b>) top-view of the unaffected guide before the impact, (<b>b</b>) corresponding microscope image and (<b>c</b>) guided mode. After the impact: (<b>d</b>) top-view, (<b>e</b>) microscope image and (<b>f</b>) absence mode observation.</p>
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<p>Top-view of TiO<sub>2</sub>–SiO<sub>2</sub> waveguide grid after signal injection at 638 nm for (<b>a</b>) 6 perpendicular waveguides spaced by 3 mm and (<b>b</b>) 12 perpendicular waveguides spaced by 1 mm. In both cases, the corresponding inset illustrates the guided mode at 638 nm, and the waveguides are surrounded by air.</p>
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<p>Thermal cycling performed on a 10 cm × 10 cm TiO<sub>2</sub>–SiO<sub>2</sub> grid architecture divided into three steps: a first increase from 20 °C to 80 °C followed by a decrease down to −40 °C, while the last increase is performed to reach 20 °C. Each temperature level lasts 1 h.</p>
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<p>Thermal cycling (TC) effect on a TiO<sub>2</sub>–SiO<sub>2</sub> grid architecture. Microscope images of the grid area are given (<b>a</b>) before the thermal cycling, (<b>b</b>) after being thermally treated at 80 °C, (<b>c</b>) −40 °C and (<b>d</b>) after all the consecutive thermal treatments. (<b>e</b>) Corresponding profilometer measurements (SF = 10 mg) and (<b>f</b>) profilometer measurements of the structure submitted to the full thermal cycling with SF of 10 mg (black and red lines) and 15 mg (blue line).</p>
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18 pages, 7944 KiB  
Article
Geometric Effects Analysis and Verification of V-Shaped Support Interference on Blended Wing Body Aircraft
by Xin Xu, Qiang Li, Dawei Liu, Keming Cheng and Dehua Chen
Appl. Sci. 2020, 10(5), 1596; https://doi.org/10.3390/app10051596 - 28 Feb 2020
Cited by 2 | Viewed by 2108
Abstract
A special V-shaped support for blended wing body aircraft was designed and applied in high-speed wind tunnel tests. In order to reduce the support interference and explore the design criteria of the V-shaped support, interference characteristics and geometric parameter effects of V-shaped support [...] Read more.
A special V-shaped support for blended wing body aircraft was designed and applied in high-speed wind tunnel tests. In order to reduce the support interference and explore the design criteria of the V-shaped support, interference characteristics and geometric parameter effects of V-shaped support on blended wing body aircraft were numerically studied. According to the numerical results, the corresponding dummy V-shaped supports were designed and manufactured, and verification tests was conducted in a 2.4 m × 2.4 m transonic wind tunnel. The test results were in good agreement with the numerical simulation. Results indicated that pitching moment of blended wing body aircraft is quite sensitive to the V-shaped support geometric parameters, and the influence of the inflection angle is the most serious. To minimize the pitching moment interference, the straight-section diameter and inflection angle should be increased while the straight-section length should be shortened. The results could be used to design special V-shaped support for blended wing body aircraft in wind tunnel tests, reduce support interference, and improve the accuracy of test results. Full article
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<p>Geometric outline of the blended wing body (BWB) aircraft model used in the current research.</p>
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<p>Geometric outline and parameters of the V-shaped support: (<b>a</b>) different sections of the V-shaped support; (<b>b</b>) outline of a BWB model with the V-shaped support; (<b>c</b>) geometric parameters of the V-shaped support.</p>
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<p>The grid of V-shaped support with different parameters (the straight-section diameter D = 44 mm/52 mm/55 mm, the straight-section length L = 200 mm/300 mm/400 mm, the first-section length H = L2 – 100 mm/L2/L2 + 100 mm, the inflection angle P = 13°/15°/17°/20°, and multiple variable parameters L = 400 mm/H = L2 + 100 mm).</p>
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<p>Computational fluid dynamics (CFD) and European Transonic Windtunnel (ETW)/ China Aerodynamics Research and Development Center (CARDC) test results comparison for the CHN-T1 aircraft (<span class="html-italic">Ma</span> = 0.78, <span class="html-italic">Re</span> = 3 × 10<sup>6</sup>): (<b>a</b>) <span class="html-italic">C<sub>L</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) <span class="html-italic">C<sub>L</sub></span>-<span class="html-italic">C<sub>D</sub></span> curves.</p>
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<p>Aerodynamic characteristics of the BWB aircraft with and without the V-shaped support (<span class="html-italic">Ma</span> = 0.75): (<b>a</b>) <span class="html-italic">C<sub>L</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) <span class="html-italic">C<sub>D</sub></span>-<span class="html-italic">α</span> curves; (<b>c</b>) <span class="html-italic">C<sub>m</sub></span>-<span class="html-italic">α</span> curves.</p>
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<p>Pressure contour of the BWB aircraft lower surface with and without the V-shaped support (<span class="html-italic">Ma</span> = 0.75, <span class="html-italic">α</span> = 0°): (<b>a</b>) pressure contour of the real model without support or cavity; (<b>b</b>) pressure contour of the test model with the V-shaped support (D52_L300_L2_P15) and cavity.</p>
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<p>Support interference results from the BWB aircraft with different straight-section diameters (D = 44 mm/52 mm/55 mm, <span class="html-italic">Ma</span> = 0.75): (<b>a</b>) <span class="html-italic">C<sub>L</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) <span class="html-italic">C<sub>D</sub></span>-<span class="html-italic">α</span> curves; (<b>c</b>) <span class="html-italic">C<sub>m</sub></span>-<span class="html-italic">α</span> curves.</p>
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<p>Pressure contour and distribution of the BWB aircraft with different straight-section diameters (D = 44 mm/52 mm/55 mm, <span class="html-italic">Ma</span> = 0.75, <span class="html-italic">α</span> = 0°): (<b>a</b>) pressure contour of the BWB aircraft under the D = 55 mm condition; (<b>b</b>) pressure distribution of profile F-F (position of F-F is shown in <a href="#applsci-10-01596-f008" class="html-fig">Figure 8</a>a).</p>
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<p>Support interference results of the BWB aircraft with different straight-section lengths (L = 200 mm/300 mm/400 mm, <span class="html-italic">Ma</span> = 0.75): (<b>a</b>) <span class="html-italic">C<sub>L</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) <span class="html-italic">C<sub>D</sub></span>-<span class="html-italic">α</span> curves; (<b>c</b>) <span class="html-italic">C<sub>m</sub></span>-<span class="html-italic">α</span> curves.</p>
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<p>Pressure contour and distribution of the BWB aircraft with different straight-section lengths (L = 200 mm/300 mm/400 mm, <span class="html-italic">Ma</span> = 0.75, <span class="html-italic">α</span> = 0°): (<b>a</b>) pressure contour of the BWB aircraft under the L = 200 mm condition; (<b>b</b>) pressure distribution of profile F-F (position of F-F is shown in <a href="#applsci-10-01596-f010" class="html-fig">Figure 10</a>a).</p>
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<p>Support interference results of the BWB aircraft with different first-section lengths (H = L2 − 100 mm/L2/L2 + 100 mm, <span class="html-italic">Ma</span> = 0.75): (<b>a</b>) <span class="html-italic">C<sub>L</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) <span class="html-italic">C<sub>D</sub></span>-<span class="html-italic">α</span> curves; (<b>c</b>) <span class="html-italic">C<sub>m</sub></span>-<span class="html-italic">α</span> curves.</p>
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<p>Support interference results of the BWB aircraft with different inflection angles (P = 13°/15°/17°/20°, <span class="html-italic">Ma</span> = 0.75): (<b>a</b>) <span class="html-italic">C<sub>L</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) <span class="html-italic">C<sub>D</sub></span>-<span class="html-italic">α</span> curves; (<b>c</b>) <span class="html-italic">C<sub>m</sub></span>-<span class="html-italic">α</span> curves.</p>
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<p>Pressure contour and distribution of the BWB aircraft with different inflection angles (P = 13°/15°/17°/20°, <span class="html-italic">Ma</span> = 0.75, <span class="html-italic">α</span> = 0°): (<b>a</b>) pressure contour of the BWB aircraft under the P = 13° condition; (<b>b</b>) pressure distribution of profile F-F (position of F-F is shown in <a href="#applsci-10-01596-f013" class="html-fig">Figure 13</a>a).</p>
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<p>Sensitivity comparison of Δ<span class="html-italic">C<sub>m</sub></span> with different geometric parameters (<span class="html-italic">Ma</span> = 0.75, α = 0°).</p>
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<p>Verification test equipment of the dummy V-shaped support with different inflection angles (P = 13°/15°/17°) and different straight-section diameters (D = 52 mm/44 mm): (<b>a</b>) dummy V-shaped supports with different inflection angles; (<b>b</b>) verification equipment in the wind tunnel; (<b>c</b>) straight section of the dummy V-shaped support with D = 52 mm, before the mechanical cutting; (<b>d</b>) straight section of dummy V-shaped support with D = 44 mm, after the mechanical cutting.</p>
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<p>Support interference test results of the BWB aircraft with different inflection angles (P = 13°/15°/17°, <span class="html-italic">Ma</span> = 0.75): (<b>a</b>) Δ<span class="html-italic">C<sub>D</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) Δ<span class="html-italic">C<sub>m</sub></span>-<span class="html-italic">α</span> curves.</p>
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<p>Support interference test results of the BWB aircraft with different straight-section diameters (D = 44 mm/52 mm, <span class="html-italic">Ma</span> = 0.75): (<b>a</b>) Δ<span class="html-italic">C<sub>D</sub></span>-<span class="html-italic">α</span> curves; (<b>b</b>) Δ<span class="html-italic">C<sub>m</sub></span>-<span class="html-italic">α</span> curves.</p>
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25 pages, 4206 KiB  
Article
Design and Analysis of a Robust UAV Flight Guidance and Control System Based on a Modified Nonlinear Dynamic Inversion
by Ehab Safwat, Weiguo Zhang, Ahmed Mohsen and Mohamed Kassem
Appl. Sci. 2019, 9(17), 3600; https://doi.org/10.3390/app9173600 - 2 Sep 2019
Cited by 6 | Viewed by 3820
Abstract
The work presented in this paper focuses on the design of a robust nonlinear flight control system for a small fixed-wing UAV against uncertainties and external disturbances. Toward this objective, an integrated UAV waypoints guidance scheme based on Carrot Chasing guidance law (CC) [...] Read more.
The work presented in this paper focuses on the design of a robust nonlinear flight control system for a small fixed-wing UAV against uncertainties and external disturbances. Toward this objective, an integrated UAV waypoints guidance scheme based on Carrot Chasing guidance law (CC) in comparison with the pure pursuit and line of sight-based path following (PLOS) guidance law is analyzed. For path following based on CC, a Virtual Track Point (VTP) is introduced on the path to let the UAV chase the path. For PLOS, the pure pursuit guidance law directs the UAV to the next waypoint, while the LOS guidance law steers the vehicle toward the line of sight (LOS). Nonlinear Dynamic Inversion (NLDI) awards the flight control system researchers a straight forward method of deriving control laws for nonlinear systems. The control inputs are used to eliminate unwanted terms in the equations of motion using negative feedback of these terms. The two-time scale assumption is adopted here to separate the fast dynamics—three angular rates of aircraft—from the slow dynamics—the angle of attack, sideslip, and bank angles. However, precise dynamic models may not be available, therefore a modification of NLDI is presented to compensate the model uncertainties. Simulation results show that the modified NLDI flight control system is robust against wind disturbances and model mismatch. PLOS path-following technique more accurately follows the desired path than CC and also requires the least control effort. Full article
(This article belongs to the Special Issue Autonomous Micro Aerial Vehicles: Methods and Applications)
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<p>Nonlinear flight control system.</p>
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<p>Straight line path follower.</p>
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<p>Two-timescale dynamic inversion controller.</p>
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<p>Altitude control loop.</p>
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<p>Velocity control loop.</p>
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<p>Attitudes response with NLDI and MNLDI with pitch angle excitation without disturbances.</p>
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<p>Inner loop rate response for outer pitch angle excitation.</p>
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<p>Attitudes response with NLDI and MNLDI with pitch angle excitation with wind disturbances.</p>
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<p>Inner loop rate response for outer pitch angle excitation with wind.</p>
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<p>Moments coefficient perturbation.</p>
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<p>Attitudes response with NLDI and MNLDI with pitch angle excitation with wind disturbances and uncertainties.</p>
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<p>Inner loop rate response for outer pitch angle excitation with wind and uncertainties.</p>
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<p>Attitude angle error for outer pitch angle excitation with wind and uncertainties.</p>
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<p>Attitudes response with NLDI and MNLDI with roll angle excitation with wind disturbances and uncertainties.</p>
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<p>Attitude angle error for outer roll angle excitation with wind and uncertainties.</p>
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<p>Inner loop rate response for outer roll angle excitation with wind and uncertainties.</p>
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<p>Attitudes response with NLDI and MNLDI with roll angle excitation with wind disturbances and uncertainties.</p>
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<p>Attitude angle error for outer roll angle excitation with wind and uncertainties.</p>
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<p>Inner loop rate response for outer roll angle excitation with wind and uncertainties.</p>
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<p>Attitudes response with NLDI and MNLDI with side-slip angle excitation with wind disturbances and uncertainties.</p>
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<p>Inner loop rate response for outer side-slip angle excitation with wind and uncertainties.</p>
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<p>Attitude angle error for outer side-slip angle excitation with wind and uncertainties.</p>
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<p>Straight line path following without wind.</p>
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<p>Straight line path following with wind.</p>
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<p>Altituderesponse under sharply straight line path maneuvers.</p>
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<p>Velocity response under sharply straight line path maneuvers.</p>
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<p>Cross track error associated with both path following methods with wind.</p>
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<p>Mean of absolute cross-track error for carrot chasing and PLOS path following guidance methods.</p>
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20 pages, 5411 KiB  
Article
Pose Estimation for Straight Wing Aircraft Based on Consistent Line Clustering and Planes Intersection
by Xichao Teng, Qifeng Yu, Jing Luo, Xiaohu Zhang and Gang Wang
Sensors 2019, 19(2), 342; https://doi.org/10.3390/s19020342 - 16 Jan 2019
Cited by 8 | Viewed by 4399
Abstract
Aircraft pose estimation is a necessary technology in aerospace applications, and accurate pose parameters are the foundation for many aerospace tasks. In this paper, we propose a novel pose estimation method for straight wing aircraft without relying on 3D models or other datasets, [...] Read more.
Aircraft pose estimation is a necessary technology in aerospace applications, and accurate pose parameters are the foundation for many aerospace tasks. In this paper, we propose a novel pose estimation method for straight wing aircraft without relying on 3D models or other datasets, and two widely separated cameras are used to acquire the pose information. Because of the large baseline and long-distance imaging, feature point matching is difficult and inaccurate in this configuration. In our method, line features are extracted to describe the structure of straight wing aircraft in images, and pose estimation is performed based on the common geometry constraints of straight wing aircraft. The spatial and length consistency of the line features is used to exclude irrelevant line segments belonging to the background or other parts of the aircraft, and density-based parallel line clustering is utilized to extract the aircraft’s main structure. After identifying the orientation of the fuselage and wings in images, planes intersection is used to estimate the 3D localization and attitude of the aircraft. Experimental results show that our method estimates the aircraft pose accurately and robustly. Full article
(This article belongs to the Special Issue Visual Sensors)
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<p>Coordinate systems: (<b>a</b>) World frame; (<b>b</b>) Camera frame; (<b>c</b>) Body frame.</p>
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<p>The results of line feature extraction and line clustering based on spatial and length consistency: (<b>a</b>) Line feature extraction; (<b>b</b>) Spatially consistent line clustering; (<b>c</b>) Length-consistent line clustering.</p>
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<p>A comparison of the results of the methods: (<b>a</b>) Image moment method; (<b>b</b>) Mean shift algorithm.</p>
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<p>The explanation of the density-based spatial clustering of application with noise (DBSCAN) algorithm: the red points represent the core points, the yellow points represent the border points, and the blue points represent the noise points. The radius of the circle represents the distance threshold.</p>
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<p>The results of parallel line clustering. (<b>a</b>) The directions of the fuselage and the wings are extracted correctly; (<b>b</b>) The direction of the wings cannot be extracted for this extreme pose.</p>
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<p>Geometric constraint of plane–plane intersection.</p>
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<p>The flowchart of our pose estimation algorithm.</p>
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<p>Results of the structure extraction method.</p>
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<p>Some incorrect results from our structure extraction algorithm.</p>
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<p>Two aircraft models: (<b>a</b>) Model 1; (<b>b</b>) Model 2.</p>
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<p>Examples of simulated image pairs generated by the 3ds Max rendering engine: (<b>a</b>) Image pairs of Model 1; (<b>b</b>) Image pairs of Model 2.</p>
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<p>Structure extraction results on the simulated images: (<b>a</b>) Results on Model 1’s simulated image pairs; (<b>b</b>) Results on Model 2’s simulated image pairs.</p>
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<p>Pose estimation errors for the simulated images of Model 1: (<b>a</b>) Rotation errors; (<b>b</b>) Translation errors.</p>
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<p>Pose estimation errors for the simulated images of Model 2: (<b>a</b>) Rotation errors; (<b>b</b>) Translation errors.</p>
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965 KiB  
Article
CAROLS: A New Airborne L-Band Radiometer for Ocean Surface and Land Observations
by Mehrez Zribi, Mickael Pardé, Jacquline Boutin, Pascal Fanise, Daniele Hauser, Monique Dechambre, Yann Kerr, Marion Leduc-Leballeur, Gilles Reverdin, Niels Skou, Sten Søbjærg, Clement Albergel, Jean Christophe Calvet, Jean Pierre Wigneron, Ernesto Lopez-Baeza, Antonio Rius and Joseph Tenerelli
Sensors 2011, 11(1), 719-742; https://doi.org/10.3390/s110100719 - 12 Jan 2011
Cited by 48 | Viewed by 15471
Abstract
The “Cooperative Airborne Radiometer for Ocean and Land Studies” (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It [...] Read more.
The “Cooperative Airborne Radiometer for Ocean and Land Studies” (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer—STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity. Full article
(This article belongs to the Special Issue 10 Years Sensors - A Decade of Publishing)
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<p>Block diagram of the antenna and receiver unit.</p>
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<p>The CAROLS radiometer inside the ATR42 research aircraft, <b>(a)</b> illustration of nadir antenna inside the aircraft, <b>(b)</b> illustration of CAROLS system (receiver and antennas) inside the aircraft.</p>
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<p>Radiometric resolution of the CAROLS radiometer.</p>
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<p>Illustration of CAROLS receiver linearity.</p>
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<p>Stability of the CAROLS measurements. Non corrected data correspond to one calibration point; corrected data correspond to two calibration points before and after data acquisition.</p>
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<p><b>a.</b> (top) CAROLS instrument with one slant antenna and the STORM instrument, <b>b.</b> (bottom) CAROLS instrument with two antennas (one slant and one nadir).</p>
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<p>Illustration of flight transects, <b>a</b> (top) illustration of one ocean flight transect over the Gulf of Biscay, <b>b</b> (middle) Illustration of a SMOSMONIA flight transect. Markers are pointing to the location of the 12 SMOSMANIA measurement sites, <b>c</b> (bottom) Illustration of a Valencia transect flight.</p>
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<p>Measurements (8 ms average) recorded at the Y port (close to H-pol), by the nadir (top) and side (bottom) antennas on 24 September 2007. Incidence angles are indicated by the color coding. The simulated values of Ty are indicated by the black line.</p>
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<p>Top: Variations in Ty (1s averages) as observed (colored points), and simulated using the 2scale/DV2 (black) and SSA/Kudr. (grey) models during three circular flights. The azimuth angle is color coded. Bottom: Modeled variations of scattered galactic noise. Left: nadir antenna on 24/09/07; wind speed of 8.3 m/s. Right: side antenna on 28/09/07; wind speed of 8.4 m/s. (a bias has been artificially added to the measurements, to facilitate visual interpretation).</p>
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<p>Top: Variations in Ty (1s averages) as observed (colored points), and simulated using the 2scale/DV2 (black) and SSA/Kudr. (grey) models during three circular flights. The azimuth angle is color coded. Bottom: Modeled variations of scattered galactic noise. Left: nadir antenna on 24/09/07; wind speed of 8.3 m/s. Right: side antenna on 28/09/07; wind speed of 8.4 m/s. (a bias has been artificially added to the measurements, to facilitate visual interpretation).</p>
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