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Oceanic Litter Conditions and Performance Evaluation of Marine Cleanups
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Oceanic Litter Conditions and Performance Evaluation of Marine Cleanups

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Marine Pollution".

Deadline for manuscript submissions: closed (20 April 2024) | Viewed by 10339

Special Issue Editors

Dr. Christophe Maes

E-Mail Website
Guest Editor
IRD/Laboratory for Ocean Physics and Satellite Remote Sensing (LOPS), 29280 Plouzane, France
Interests: physical oceanography; marine dispersion; ocean litter and debris; citizen science
Dr. Bruno Sainte-Rose

E-Mail Website
Guest Editor
The Ocean Cleanup, 3014 JH Rotterdam, The Netherlands
Interests: marine litter; oceanography; ocean engineering; computational fluid dynamics; data science; deep learning

Special Issue Information

Dear Colleagues,

The world's oceans and coastlines are constantly impacted by several threats related to the dispersal of pollutants (plastics, hydrocarbons, fertilizers), and algae blooms. Knowledge of global ocean modeling and dispersion has greatly increased in recent decades but remains inadequate for the development of regional and local responses. Accordingly, marine cleanups are increasingly being developed and conducted in response to these threats.

The invited Special Issue focuses on the performance evaluation of marine cleanups. This encompasses the cleanup systems' overall hydrodynamic and cleanup performance, as well as the measurement techniques, modeling, and operations used to support the research and development in order to improve overall performance and to better understand marine environmental conditions, dynamics, and their influence on the dispersal of floating materials in our environment.

Submissions are welcome from various fields of study:

  • Modeling of the fate of pollutants and algae;
  • Dynamics of marine dispersion;
  • Forecasting and steering strategy;
  • Cleanup system design;
  • Cleanup boat, boom, and nets hydrodynamics;
  • Model testing of cleanup systems;
  • Digital twin of cleanup systems;
  • Operational cleanup systems;
  • Remote sensing (marine litter, oil, algae);
  • Surface drifters and AUVs;
  • Oil spill response.

Dr. Christophe Maes
Dr. Bruno Sainte-Rose
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • marine litter
  • marine cleanups
  • remote sensing
  • hydrodynamic performance
  • oil spill response
  • dispersal modeling
  • algae blooms

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Published Papers (4 papers)

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Research

17 pages, 8581 KiB  
Article
Oil Spill Mitigation with a Team of Heterogeneous Autonomous Vehicles
by André Dias, Ana Mucha, Tiago Santos, Alexandre Oliveira, Guilherme Amaral, Hugo Ferreira, Alfredo Martins, José Almeida and Eduardo Silva
J. Mar. Sci. Eng. 2024, 12(8), 1281; https://doi.org/10.3390/jmse12081281 - 30 Jul 2024
Viewed by 1009
Abstract
This paper presents the implementation of an innovative solution based on heterogeneous autonomous vehicles to tackle maritime pollution (in particular, oil spills). This solution is based on native microbial consortia with bioremediation capacity, and the adaptation of air and surface autonomous vehicles for [...] Read more.
This paper presents the implementation of an innovative solution based on heterogeneous autonomous vehicles to tackle maritime pollution (in particular, oil spills). This solution is based on native microbial consortia with bioremediation capacity, and the adaptation of air and surface autonomous vehicles for in situ release of autochthonous microorganisms (bioaugmentation) and nutrients (biostimulation). By doing so, these systems can be applied as the first line of the response to pollution incidents from several origins that may occur inside ports, around industrial and extraction facilities, or in the open sea during transport activities in a fast, efficient, and low-cost way. The paper describes the work done in the development of a team of autonomous vehicles able to carry as payload, native organisms to naturally degrade oil spills (avoiding the introduction of additional chemical or biological additives), and the development of a multi-robot framework for efficient oil spill mitigation. Field tests have been performed in Portugal and Spain’s harbors, with a simulated oil spill, and the coordinate oil spill task between the autonomous surface vehicle (ASV) ROAZ and the unmanned aerial vehicle (UAV) STORK has been validated. Full article
(This article belongs to the Special Issue Oceanic Litter Conditions and Performance Evaluation of Marine Cleanups)
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Figure 1

Figure 1
<p>Oil spill incident detected by the Satellite radar images from Copernicus Sentinel-1 in the Mediterranean Sea [<a href="#B4-jmse-12-01281" class="html-bibr">4</a>].</p> Full article ">Figure 2
<p>Conceptual approach for multi-robot oil spill mitigation with a team of heterogeneous autonomous vehicles, particularly an ASV and a UAV.</p> Full article ">Figure 3
<p>Multi-robot framework for oil spill mitigation.</p> Full article ">Figure 4
<p>(<b>Left</b>): repulsive forces applied to the ASV for oil spill avoidance. (<b>Right</b>): resultant force from repulsive and attractive forces.</p> Full article ">Figure 5
<p>New point based on three consecutive contour points.</p> Full article ">Figure 6
<p>Coverage area of the powder spreader nozzle.</p> Full article ">Figure 7
<p>UAV path planning with the proposed algorithm.</p> Full article ">Figure 8
<p>ASV ROAZ II adapted for oil spill mitigation.</p> Full article ">Figure 9
<p>UAV STORK I (<b>left</b>) and GRIFO-X (<b>right</b>) prepared for oil spill mitigation missions.</p> Full article ">Figure 10
<p>Release system conceptual architecture for both autonomous vehicles. (<b>Left</b>): UAV release system for lyophilized spread. (<b>Right</b>): ASV release system with the ability to mix lyophilized powder mixture with native water.</p> Full article ">Figure 11
<p>UAV release system developed for both UAVs. (<b>Left</b>): release system for UAV STORK I with a capacity of 1 kg. (<b>Right</b>): release system for UAV GRIFO-X with a capacity of 7 kg on each reservoir, with an overall capacity of 14 kg.</p> Full article ">Figure 12
<p>ASV release system. Water pump and control system box.</p> Full article ">Figure 13
<p>Oil spill simulation environment developed in Gazebo to provide the oil spill to both vehicles during the field tests.</p> Full article ">Figure 14
<p>Field tests during the robotics exercise (REX).</p> Full article ">Figure 15
<p>Field Tests in Puerto of Medas, Portugal and Coruña, Spain.</p> Full article ">Figure 16
<p>Trajectory behavior of both vehicles to mitigate the oil spill. Field test in the harbor of Leixões, Portugal.</p> Full article ">Figure 17
<p>(<b>Left</b>): simulated oil spills in the Puerto A Coruña. (<b>Right</b>): ground Station 3D graphical user interface for monitoring the mission with the position of both vehicles and the generated path planning.</p> Full article ">Figure 18
<p>Trajectory behavior of both vehicles to mitigate the oil spill. Field test in the harbor of Coruña, Spain. (<b>Left</b>): UAV trajectory over the oil spill. (<b>Right</b>): ASV trajectory contours the oil spill.</p> Full article ">
24 pages, 9857 KiB  
Article
Seasonality of Marine Litter Hotspots in the Wider Caribbean Region
by Xiaobiao Xu, Eric P. Chassignet, Philippe Miron and Olmo Zavala-Romero
J. Mar. Sci. Eng. 2024, 12(2), 319; https://doi.org/10.3390/jmse12020319 - 13 Feb 2024
Cited by 2 | Viewed by 1545
Abstract
The persistent increase in marine plastic litter has become a major global concern, with one of the highest plastic concentrations in the world’s oceans found in the Wider Caribbean Region (WCR). In this study, we use marine plastic litter tracking simulations to investigate [...] Read more.
The persistent increase in marine plastic litter has become a major global concern, with one of the highest plastic concentrations in the world’s oceans found in the Wider Caribbean Region (WCR). In this study, we use marine plastic litter tracking simulations to investigate where marine plastic accumulates, i.e., hotspots, in the WCR and how the accumulation varies on seasonal timescales. We show that most of the marine plastic waste converges on the coastlines shortly after being released into the WCR because of the strong surface current and the predominant easterly winds. Major plastic accumulations take place along (i) the western coastline of the WCR, especially the north–south-oriented coasts of Costa Rica/Nicaragua, Guatemala/Belize/Mexico, and Texas, and (ii) the coastlines of Haiti–Dominican Republic and Venezuela. Relatively low plastic accumulation is found along western Florida, the western Yucatán peninsula, and the leeward and windward Caribbean islands. Accumulation along the western WCR coastlines is modulated primarily by ocean currents and exhibits significant seasonal variabilities due to changes in wind patterns. The accumulation observed on the Haiti–Dominican Republic and Venezuela coastlines is primarily due to the proximity of large, mismanaged plastic waste sources. Finally, we discuss the uncertainty associated with the choices made in defining the different criteria for plastic beaching in the models. Full article
(This article belongs to the Special Issue Oceanic Litter Conditions and Performance Evaluation of Marine Cleanups)
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Figure 1

Figure 1
<p>Wider Caribbean Region and transboundary lines delineating exclusive economic zones (EEZ), from Ambrose [<a href="#B20-jmse-12-00319" class="html-bibr">20</a>].</p> Full article ">Figure 2
<p>Time averaged (<b>a</b>) ocean surface circulation and (<b>b</b>) near-surface wind in the Wider Caribbean Region (WCR) over 2010–2021. The ocean circulation is from the global ocean forecasting system (GOFS3.1) reanalysis, and the wind is from the US Navy Global Environmental Model (NAVGEM).</p> Full article ">Figure 3
<p>Spatial distribution of (<b>a</b>) land-based and (<b>b</b>) river-based mismanaged plastic waste (MPW, in tons) sources into the WCR domain. The results are from Lebreton and Andrady [<a href="#B48-jmse-12-00319" class="html-bibr">48</a>] and Lebreton et al. [<a href="#B49-jmse-12-00319" class="html-bibr">49</a>], respectively.</p> Full article ">Figure 4
<p>Examples of the MPW particle trajectories on 2013-02-20 from (<b>a</b>) GLB, (<b>b</b>) REALISTIC, and (<b>c</b>) UNIFORM. All the particles were released on 2013-01-01, and for (<b>a</b>) GLB and (<b>b</b>) REALISTIC, only the particles released from the WCR countries are included. The particle trails for the last 10 days are shown in blue, with the end positions marked with black circles and the beached particles with red dots.</p> Full article ">Figure 5
<p>(<b>a</b>) Percentage of the beached MPW particles as a function of time after being released into the WCR in the GLB, REALISTIC, and UNIFORM experiments, averaged for the releases from 2010 to 2020. (<b>b</b>) Percentage of the beached MPW particles 6 months after being released (x axis) into the WCR for each release in the GLB, REALISTIC, and UNIFORM experiments.</p> Full article ">Figure 6
<p>Number of beached MPW particles in 2010–2021 in the UNIFORM experiment, in which MPW particles were released uniformly along the coastline of the WCR domain.</p> Full article ">Figure 7
<p>Distribution of beached MPW (in tons) in 2010–2021 from the particles that were released from the WCR countries in the (<b>a</b>) REALISTIC and (<b>b</b>) UNIFORM experiments; panel (<b>c</b>) shows their difference (red indicates more beached MPW in REALISTIC and vice versa).</p> Full article ">Figure 8
<p>The distribution of beached MPW (in tons) in 2010–2021 in the REALISTIC experiment, as in <a href="#jmse-12-00319-f007" class="html-fig">Figure 7</a>a, but from the particles that were transferred into the WCR domain through northern and eastern boundaries. Note that the scale of the MPW is 10 times smaller than that in <a href="#jmse-12-00319-f007" class="html-fig">Figure 7</a>.</p> Full article ">Figure 9
<p>Seasonal near-face wind anomalies (in m/s, relatively to annual means) averaged over 2010–2021 for (<b>a</b>) DJF (December to February), (<b>b</b>) MAM (March to May), (<b>c</b>) JJA (June to August), and (<b>d</b>) SON (September to November), corresponding to the seasonal MPW hotspots as shown in <a href="#jmse-12-00319-f010" class="html-fig">Figure 10</a>.</p> Full article ">Figure 10
<p>Spatial distribution of beached MPW (in tons) that are beached along the WCR coastline in different seasons: (<b>a</b>) DJF (December to February), (<b>b</b>) MAM (March to May), (<b>c</b>) JJA (June to August), and (<b>d</b>) SON (September to November), based on the REALISTIC experiment over 2010–2021 (note that the scale is scaled by a factor of 4 to be comparable to the MPW accumulated for the full year).</p> Full article ">Figure 11
<p>Thirty-day trajectories from one release (2010/01/01) in the REALISTIC experiment to illustrate the “beaching” criterion using a distance threshold of (<b>a</b>) 25 km and (<b>b</b>) 100 km, respectively. The particles that traveled less (more) than the corresponding threshold values are marked in red (blue) and are defined as beached (moving).</p> Full article ">Figure 12
<p>Number of beached particles (in %) for each release in the REALISTIC experiment using distance threshold (red) and probability (blue) methods, respectively. The thick and thin lines are for the WCR particles and the boundary particles.</p> Full article ">Figure 13
<p>Distribution of beached MPW (in tons) along using the probability method for (<b>a</b>) the WCR particles and (<b>c</b>) the boundary particles, and (<b>b</b>,<b>d</b>) the corresponding differences from using the 25 km distance threshold method (red indicates more beaching with the probability method than the distance method and vice versa for blue).</p> Full article ">
18 pages, 3682 KiB  
Article
Qualitative Study of the Transport of Microplastics in the Río de la Plata Estuary, Argentina, through Numerical Simulation
by Alejandra Elisei Schicchi, Diego Moreira, Patricia Eisenberg and Claudia G. Simionato
J. Mar. Sci. Eng. 2023, 11(12), 2317; https://doi.org/10.3390/jmse11122317 - 7 Dec 2023
Cited by 3 | Viewed by 1899
Abstract
Information about the sources, sinks, dynamics, and how environmental variables affect the transport of microplastics (MPs) from continental deposits to marine systems is still limited. Most of the knowledge about the distribution of plastic in the oceans comes from the use of numerical [...] Read more.
Information about the sources, sinks, dynamics, and how environmental variables affect the transport of microplastics (MPs) from continental deposits to marine systems is still limited. Most of the knowledge about the distribution of plastic in the oceans comes from the use of numerical models to understand the routes of MPs moving in aquatic systems. The Río de la Plata (RdP) is an estuary located on the eastern coast of South America and is one of the most anthropized watercourses in the region. In this study, the trajectory of MPs in the RdP was examined through the implementation, for the first time for the region, of numerical simulation models. The impact of the estuary’s hydrodynamic characteristics, winds, and MP morphological properties on their trajectory was investigated. The simulations produced demonstrated a high correlation between the hydrodynamics of the Río de la Plata and the trajectory of positively buoyant MPs. The wind was identified as a significant driving force in the simulation of MP motion dynamics. Modifications in the size of the MPs have more influence on the trajectory than their morphology. The results constitute an initial step toward understanding the dynamics of these emerging pollutants in one of South America’s most important basins. Full article
(This article belongs to the Special Issue Oceanic Litter Conditions and Performance Evaluation of Marine Cleanups)
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Figure 1

Figure 1
<p>Río de la Plata estuary and principal geographic locations. MODIS color image. (<b>a</b>) Upper region RdP, (<b>b</b>) intermediate region RdP, (<b>c</b>) outer region RdP.</p> Full article ">Figure 2
<p>(<b>a</b>) Initial location chosen for MPs trajectories simulation (<a href="#jmse-11-02317-t001" class="html-table">Table 1</a>) and bathymetry of the Río de la Plata (in m). (<b>b</b>) Monthly average currents (m s<sup>−1</sup>) near the surface (black arrows) and near the bottom (red arrow) indicating the mean flow pattern, over bathymetry (m).</p> Full article ">Figure 3
<p>(<b>a</b>) Wind stress vector (N m<sup>−2</sup>) for the modelated month. The light blue bars show at which time of the month the simulation was initialized. The first period starts on the first of the month, the second on the 7th, and the third on the 19th. All three end on the 30th of the chosen month. (<b>b</b>) Current vector, (<b>c</b>) surface height for a site in the upper RdP (34.36° S, 58.29° W).</p> Full article ">Figure 4
<p>Trajectories of the four MPs: (<b>a</b>) continental discharge; (<b>b</b>) continental discharge + tides; (<b>c</b>) continental discharge + tides + winds; (<b>d</b>) discharge + tides + winds + waves. The “x” indicates the release location and the red dot indicates the final position. The resulting trajectories are colored orange for MP1, green for MP2, blue for MP3 and purple for MP4.</p> Full article ">Figure 5
<p>Upper panels: MP trajectories, (<b>a</b>) W-I releasing on the 1st, (<b>b</b>) case W-II releasing on the 7th, (<b>c</b>) W-III releasing on the 19th. The “x” indicates the release location and the red dot indicates the final position. The resulting trajectories are colored orange for MP1, green for MP2, blue for MP3 and purple for MP4.</p> Full article ">Figure 6
<p>(<b>a</b>) Vertical motion for MP3 in longitude, (<b>b</b>) vertical motion for MP3 in latitude. Both with morphology of sphere 150 μm (blue), sphere 10 μm (green), cylinder 150–3000 μm (yellow), and cylinder 10–200 μm (red), buoyant (cyan).</p> Full article ">Figure 6 Cont.
<p>(<b>a</b>) Vertical motion for MP3 in longitude, (<b>b</b>) vertical motion for MP3 in latitude. Both with morphology of sphere 150 μm (blue), sphere 10 μm (green), cylinder 150–3000 μm (yellow), and cylinder 10–200 μm (red), buoyant (cyan).</p> Full article ">
33 pages, 6756 KiB  
Article
On the Digital Twin of The Ocean Cleanup Systems—Part I: Calibration of the Drag Coefficients of a Netted Screen in OrcaFlex Using CFD and Full-Scale Experiments
by Martin Alejandro Gonzalez Jimenez, Andriarimina Daniel Rakotonirina, Bruno Sainte-Rose and David James Cox
J. Mar. Sci. Eng. 2023, 11(10), 1943; https://doi.org/10.3390/jmse11101943 - 8 Oct 2023
Cited by 2 | Viewed by 2645
Abstract
The Ocean Cleanup introduces a Digital Twin (DT) describing the cleanup systems made of netting to extract marine litter from our oceans. It consists of two wings forming a “U-shape” and a retention zone. During operation, the system is towed and drag-driven with [...] Read more.
The Ocean Cleanup introduces a Digital Twin (DT) describing the cleanup systems made of netting to extract marine litter from our oceans. It consists of two wings forming a “U-shape” and a retention zone. During operation, the system is towed and drag-driven with a span-to-length ratio of 0.6 ≤SR*≤ 0.8. The twine Reynolds number is Ret*∈[800:1600], making it experience various local drag coefficients. The DT was built with OrcaFlex (OF) aiming at: (i) avoiding over- or under-designing the system; (ii) supporting the scale-up of the system; and (iii) estimating the costs and/or the impact of our offshore operations. Therefore, we present an attempt to build an accurate DT using data from the Great Pacific Garbage Patch (GPGP). We developed a three-cycle validation: (i) initial guess applying Naumov’s semi-empirical drag coefficient to define the OF drag coefficients without the influence of the angles of attack θ of the wings; (ii) adjustment of the OF drag coefficients using AquaSim (AS) with its twine-by-twine drag correlation for various θ; (iii) re-adjustment of the OF drag coefficients from two-dimensional CFD simulations using Direct Numerical Simulation (DNS) for a twine-by-twine establishment of a drag correlation on a 1 m plane net, highlighting the shielding effects for θ<24°. Consequently, an initial underestimation of −3% in the combined towline tension, for a nominal span (SR*=0.6), was corrected to a slight overestimation of +7% compared to the GPGP data. For a wide span (SR*=0.8), the deviation remained between +1% and +15% throughout the validation process. For a narrow span (SR*∼ 0.02), mostly exhibiting low θ, the first cycle showed a +276% deviation, whereas at the end of the third cycle, it showed a +43% deviation. Full article
(This article belongs to the Special Issue Oceanic Litter Conditions and Performance Evaluation of Marine Cleanups)
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Figure 1

Figure 1
<p>Above-water and underwater footage of <tt>System 002</tt>. <span class="html-fig-inline" id="jmse-11-01943-i001"><img alt="Jmse 11 01943 i001" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i001.png"/></span> Port-side vessel. <span class="html-fig-inline" id="jmse-11-01943-i002"><img alt="Jmse 11 01943 i002" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i002.png"/></span> Starboard-side vessel. <span class="html-fig-inline" id="jmse-11-01943-i003"><img alt="Jmse 11 01943 i003" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i003.png"/></span> Port-side tow bar and towing bridle, connected to a towing line. <span class="html-fig-inline" id="jmse-11-01943-i004"><img alt="Jmse 11 01943 i004" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i004.png"/></span> Starboard-side tow bar and towing bridle, connected to a towing line. <span class="html-fig-inline" id="jmse-11-01943-i005"><img alt="Jmse 11 01943 i005" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i005.png"/></span> Port-side wingspan. <span class="html-fig-inline" id="jmse-11-01943-i006"><img alt="Jmse 11 01943 i006" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i006.png"/></span> Starboard-side wingspan. <span class="html-fig-inline" id="jmse-11-01943-i007"><img alt="Jmse 11 01943 i007" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i007.png"/></span> Retention opening. <span class="html-fig-inline" id="jmse-11-01943-i008"><img alt="Jmse 11 01943 i008" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i008.png"/></span> Retention zone. <span class="html-fig-inline" id="jmse-11-01943-i009"><img alt="Jmse 11 01943 i009" src="/jmse/jmse-11-01943/article_deploy/html/images/jmse-11-01943-i009.png"/></span> Extraction pick-up line. (<b>a</b>) Aerial view of <tt>System 002</tt> towed by two vessels. (<b>b</b>) Underwater view of the retention zone made of nets.</p> Full article ">Figure 2
<p>Running Line Monitor (RLM) to measure towline tension.</p> Full article ">Figure 3
<p>Example comparison between <math display="inline"><semantics> <msub> <mi>u</mi> <mi>stw</mi> </msub> </semantics></math> from DVL and <math display="inline"><semantics> <msub> <mi>u</mi> <mi>stw</mi> </msub> </semantics></math> calculated with SOG-sea current.</p> Full article ">Figure 4
<p>Local and global coordinate systems in OrcaFlex.</p> Full article ">Figure 5
<p>Basic definition of a knot-less net.</p> Full article ">Figure 6
<p>A twine in the wake of a leading twine. Illustration with dimensionless vorticity field from 2D direct numerical simulation.</p> Full article ">Figure 7
<p>Method flowchart.</p> Full article ">Figure 8
<p>Sketch of the system with basic definitions.</p> Full article ">Figure 9
<p>Wing section model in OF.</p> Full article ">Figure 10
<p>The 3D sketch of a plane net. Vertical twines in green color. Horizontal twines in red color. These colors are corresponding to the components of Equations (<a href="#FD27-jmse-11-01943" class="html-disp-formula">27</a>) and (<a href="#FD28-jmse-11-01943" class="html-disp-formula">28</a>).</p> Full article ">Figure 11
<p>(<b>a</b>) Top view of Jenny’s wing modeled as collections of successive plane nets. (<b>b</b>) The 2D cross-sectional sketch of a plane net modeled as circular cylinders.</p> Full article ">Figure 12
<p>Illustration of a complex boundary layer separation at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math> as seen in the research of Bouard and Coutanceau [<a href="#B47-jmse-11-01943" class="html-bibr">47</a>], Koumoutsakos and Leonard [<a href="#B48-jmse-11-01943" class="html-bibr">48</a>], Mohaghegh and Udaykumar [<a href="#B49-jmse-11-01943" class="html-bibr">49</a>] captured by Basilisk [<a href="#B33-jmse-11-01943" class="html-bibr">33</a>]. Vorticity field (<b>top</b>) and the quadtree structure (<b>bottom</b>).</p> Full article ">Figure 13
<p>Illustration of the drag coefficient and the numerical parameters related to its computation. (<b>a</b>) Instantaneous drag coefficient at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math> for various smallest grid sizes. (<b>b</b>) Instantaneous drag coefficient at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1600</mn> </mrow> </semantics></math> for various smallest grid sizes. (<b>c</b>) Instantaneous number of cells for <math display="inline"><semantics> <mrow> <msup> <mi>δ</mi> <mrow> <mo>*</mo> <mo>−</mo> <mn>1</mn> </mrow> </msup> <mo>=</mo> <mn>128</mn> </mrow> </semantics></math> as a function of <span class="html-italic">c</span> at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math>. (<b>d</b>) Instantaneous number of cells for <math display="inline"><semantics> <mrow> <msup> <mi>δ</mi> <mrow> <mo>*</mo> <mo>−</mo> <mn>1</mn> </mrow> </msup> <mo>=</mo> <mn>128</mn> </mrow> </semantics></math> as a function of <span class="html-italic">c</span> at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1600</mn> </mrow> </semantics></math>. (<b>e</b>) Instantaneous drag coefficient for <math display="inline"><semantics> <mrow> <msup> <mi>δ</mi> <mrow> <mo>*</mo> <mo>−</mo> <mn>1</mn> </mrow> </msup> <mo>=</mo> <mn>128</mn> </mrow> </semantics></math> as a function of <math display="inline"><semantics> <msup> <mi>c</mi> <mo>*</mo> </msup> </semantics></math> at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math>. (<b>f</b>) Instantaneous drag coefficient for <math display="inline"><semantics> <mrow> <msup> <mi>δ</mi> <mrow> <mo>*</mo> <mo>−</mo> <mn>1</mn> </mrow> </msup> <mo>=</mo> <mn>128</mn> </mrow> </semantics></math> as a function of <math display="inline"><semantics> <msup> <mi>c</mi> <mo>*</mo> </msup> </semantics></math> at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1600</mn> </mrow> </semantics></math>.</p> Full article ">Figure 14
<p>Close-up illustration of the shielding effect mechanism for <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <msup> <mn>8</mn> <mo>°</mo> </msup> </mrow> </semantics></math> at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math>. Blue and red, respectively, indicate negative and positive values of the vorticity fields.</p> Full article ">Figure 15
<p>Illustration of the flow structure using the velocity field <math display="inline"><semantics> <msub> <mi>u</mi> <mi>x</mi> </msub> </semantics></math> as a function of <math display="inline"><semantics> <mi>θ</mi> </semantics></math> at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>1000</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msup> <mi>t</mi> <mo>*</mo> </msup> <mo>=</mo> <mn>90</mn> </mrow> </semantics></math>. Blue and red, respectively, indicate low and high values of <math display="inline"><semantics> <msubsup> <mi>u</mi> <mi>x</mi> <mo>*</mo> </msubsup> </semantics></math>.</p> Full article ">Figure 16
<p>Influence of the number of twines <math display="inline"><semantics> <msubsup> <mi>N</mi> <mi>t</mi> <mo>*</mo> </msubsup> </semantics></math> on the instantaneous total drag coefficient for various low angles of attack <math display="inline"><semantics> <mi>θ</mi> </semantics></math> at <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mi mathvariant="script">R</mi> <mi>e</mi> </mrow> <mi>t</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mn>800</mn> </mrow> </semantics></math>.</p> Full article ">Figure 17
<p>Dependence of the drag coefficient on the angle of attack. The median of the fluctuations is shown with the standard deviation.</p> Full article ">Figure 18
<p>Dependence of the lift coefficient on the angle of attack. Median of the fluctuations is shown with standard deviation.</p> Full article ">Figure 19
<p>Dependence of the combined towline tension on the <math display="inline"><semantics> <msub> <mi mathvariant="bold-italic">u</mi> <mi>stw</mi> </msub> </semantics></math>. Superscripts 16, 480, and 630 indicate the span in meters. The colored areas are the 15% increase in the mean load. GPGP data selected from August 2021 to August 2022. The error bar estimation is explained in <a href="#sec2dot1-jmse-11-01943" class="html-sec">Section 2.1</a>.</p> Full article ">Figure 20
<p>Distribution of the angles of attack.</p> Full article ">Figure 21
<p>Schematic representation of the boundaries for the application of the results.</p> Full article ">Figure 22
<p>Interdependence of the twine diameter, the mesh size, the solidity, and the drag coefficient of a net. Adapted from the work of Cheng et al. [<a href="#B13-jmse-11-01943" class="html-bibr">13</a>]. (<b>a</b>) Dependence of the solidity <math display="inline"><semantics> <mrow> <mi>S</mi> <msup> <mi>n</mi> <mo>*</mo> </msup> </mrow> </semantics></math> on the twine diameter and the mesh size. (<b>b</b>) Dependence of the drag coefficient on the solidity for nylon nets at <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <msup> <mn>90</mn> <mo>°</mo> </msup> </mrow> </semantics></math>. (<span class="html-italic">I</span>) Tang et al. [<a href="#B59-jmse-11-01943" class="html-bibr">59</a>], (<span class="html-italic">II</span>) Gansel et al. [<a href="#B60-jmse-11-01943" class="html-bibr">60</a>], (<span class="html-italic">III</span>) Tsukrov et al. [<a href="#B61-jmse-11-01943" class="html-bibr">61</a>].</p> Full article ">
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