CFD Simulation of the Safety of Unmanned Ship Berthing under the Influence of Various Factors
The safety of unmanned ship berthing is of paramount importance. In order to explore the influence of wind and wave coupling, a berthing computational fluid dynamics (CFD) model was established, and the characteristics of speed field, pressure field, and vortex have been obtained under different spe...
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description | The safety of unmanned ship berthing is of paramount importance. In order to explore the influence of wind and wave coupling, a berthing computational fluid dynamics (CFD) model was established, and the characteristics of speed field, pressure field, and vortex have been obtained under different speed, wind direction, and the quay wall distances. The results show that the total resistance of the hull against the current can be about 1.60 times higher compared to the downstream resistance, water flow resistance is the dominant factor, accounting for more than 80% of the total resistance. When changing the distance between ship and shore at fixed speed, the results found that the torque is small, but the growth rate is very large when driving below 2 m/s, and the torque growth rate is stable above 2 m/s. Based on the established coupling model, a multi-factor berthing safety study is carried out on an actual unmanned ship. The results show that when the speed increases from 4 m/s to 12 m/s, the curve slope is small, the resistance increases from 3666 N to 18,056 N, and the rear slope increases. The pressure increases with the speed, and when the speed is 24 m/s, the maximum pressure is up to 238,869 Pa. When the wind speed is fixed, the vertical force of the unmanned ship increases first and then decreases to zero and then reverses the same law change, and the maximum resistance is about 425 N at the wind angle of about 45 degrees; At 90 degrees, the maximum lateral force on an unmanned boat is about 638 N. The above results can provide control strategy for unmanned ship berthing safety, and provide theoretical basis for unmanned ship route planning and obstacle avoidance, safety design, etc. |
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In order to explore the influence of wind and wave coupling, a berthing computational fluid dynamics (CFD) model was established, and the characteristics of speed field, pressure field, and vortex have been obtained under different speed, wind direction, and the quay wall distances. The results show that the total resistance of the hull against the current can be about 1.60 times higher compared to the downstream resistance, water flow resistance is the dominant factor, accounting for more than 80% of the total resistance. When changing the distance between ship and shore at fixed speed, the results found that the torque is small, but the growth rate is very large when driving below 2 m/s, and the torque growth rate is stable above 2 m/s. Based on the established coupling model, a multi-factor berthing safety study is carried out on an actual unmanned ship. The results show that when the speed increases from 4 m/s to 12 m/s, the curve slope is small, the resistance increases from 3666 N to 18,056 N, and the rear slope increases. The pressure increases with the speed, and when the speed is 24 m/s, the maximum pressure is up to 238,869 Pa. When the wind speed is fixed, the vertical force of the unmanned ship increases first and then decreases to zero and then reverses the same law change, and the maximum resistance is about 425 N at the wind angle of about 45 degrees; At 90 degrees, the maximum lateral force on an unmanned boat is about 638 N. The above results can provide control strategy for unmanned ship berthing safety, and provide theoretical basis for unmanned ship route planning and obstacle avoidance, safety design, etc.</description><identifier>ISSN: 2076-3417</identifier><identifier>EISSN: 2076-3417</identifier><identifier>DOI: 10.3390/app11157102</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Accuracy ; autonomous berthing algorithm ; Autonomous cars ; Berthing ; berthing safety ; CFD coupling model ; Computational fluid dynamics ; Computer applications ; Driving ability ; Flow resistance ; Fluid dynamics ; Fluid mechanics ; Growth rate ; Hydrodynamics ; Obstacle avoidance ; Pressure ; Real time ; Research methodology ; Resistance factors ; Route planning ; Safety ; Safety engineering ; Ships ; Simulation ; Torque ; Unmanned aerial vehicles ; unmanned ship ; Unmanned vehicles ; Vertical forces ; Water flow ; Wind ; Wind direction ; Wind effects ; Wind speed</subject><ispartof>Applied sciences, 2021-08, Vol.11 (15), p.7102</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c364t-676df7f0506ee3da4d2efdb40e6298b2154698a5a241ca73f53dba888a09b9763</citedby><cites>FETCH-LOGICAL-c364t-676df7f0506ee3da4d2efdb40e6298b2154698a5a241ca73f53dba888a09b9763</cites><orcidid>0000-0003-1650-525X ; 0000-0002-9933-1330</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,865,2103,27926,27927</link.rule.ids></links><search><creatorcontrib>Xiao, Guoquan</creatorcontrib><creatorcontrib>Tong, Chao</creatorcontrib><creatorcontrib>Wang, Yue</creatorcontrib><creatorcontrib>Guan, Shuaishuai</creatorcontrib><creatorcontrib>Hong, Xiaobin</creatorcontrib><creatorcontrib>Shang, Bin</creatorcontrib><title>CFD Simulation of the Safety of Unmanned Ship Berthing under the Influence of Various Factors</title><title>Applied sciences</title><description>The safety of unmanned ship berthing is of paramount importance. In order to explore the influence of wind and wave coupling, a berthing computational fluid dynamics (CFD) model was established, and the characteristics of speed field, pressure field, and vortex have been obtained under different speed, wind direction, and the quay wall distances. The results show that the total resistance of the hull against the current can be about 1.60 times higher compared to the downstream resistance, water flow resistance is the dominant factor, accounting for more than 80% of the total resistance. When changing the distance between ship and shore at fixed speed, the results found that the torque is small, but the growth rate is very large when driving below 2 m/s, and the torque growth rate is stable above 2 m/s. Based on the established coupling model, a multi-factor berthing safety study is carried out on an actual unmanned ship. The results show that when the speed increases from 4 m/s to 12 m/s, the curve slope is small, the resistance increases from 3666 N to 18,056 N, and the rear slope increases. The pressure increases with the speed, and when the speed is 24 m/s, the maximum pressure is up to 238,869 Pa. When the wind speed is fixed, the vertical force of the unmanned ship increases first and then decreases to zero and then reverses the same law change, and the maximum resistance is about 425 N at the wind angle of about 45 degrees; At 90 degrees, the maximum lateral force on an unmanned boat is about 638 N. The above results can provide control strategy for unmanned ship berthing safety, and provide theoretical basis for unmanned ship route planning and obstacle avoidance, safety design, etc.</description><subject>Accuracy</subject><subject>autonomous berthing algorithm</subject><subject>Autonomous cars</subject><subject>Berthing</subject><subject>berthing safety</subject><subject>CFD coupling model</subject><subject>Computational fluid dynamics</subject><subject>Computer applications</subject><subject>Driving ability</subject><subject>Flow resistance</subject><subject>Fluid dynamics</subject><subject>Fluid mechanics</subject><subject>Growth rate</subject><subject>Hydrodynamics</subject><subject>Obstacle avoidance</subject><subject>Pressure</subject><subject>Real time</subject><subject>Research methodology</subject><subject>Resistance factors</subject><subject>Route planning</subject><subject>Safety</subject><subject>Safety engineering</subject><subject>Ships</subject><subject>Simulation</subject><subject>Torque</subject><subject>Unmanned aerial vehicles</subject><subject>unmanned ship</subject><subject>Unmanned vehicles</subject><subject>Vertical forces</subject><subject>Water flow</subject><subject>Wind</subject><subject>Wind direction</subject><subject>Wind effects</subject><subject>Wind speed</subject><issn>2076-3417</issn><issn>2076-3417</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>DOA</sourceid><recordid>eNpNkctOwzAQRSMEElXpih-wxBIF7NixnSUUCpUqsShlh6yJH22q1A5Osujfk7YIdTbz0NGd0dwkuSX4gdICP0LTEEJyQXB2kYwyLHhKGRGXZ_V1MmnbLR6iIFQSPEq-p7MXtKx2fQ1dFTwKDnUbi5bgbLc_dCu_A--tQctN1aBnG7tN5deo98bGIzr3ru6t1_ZAf0GsQt-iGeguxPYmuXJQt3byl8fJavb6OX1PFx9v8-nTItWUsy7lghsnHM4xt5YaYCazzpQMW54VssxIznghIYeMEQ2CupyaEqSUgIuyEJyOk_lJ1wTYqiZWO4h7FaBSx0GIawWxq3RtlZGEUcqcYaxgpeYlZcZowwTWUg_qg9bdSauJ4ae3bae2oY9-OF9leS758EuWDdT9idIxtG207n8rwepghzqzg_4CI6575w</recordid><startdate>20210801</startdate><enddate>20210801</enddate><creator>Xiao, Guoquan</creator><creator>Tong, Chao</creator><creator>Wang, Yue</creator><creator>Guan, Shuaishuai</creator><creator>Hong, Xiaobin</creator><creator>Shang, Bin</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-1650-525X</orcidid><orcidid>https://orcid.org/0000-0002-9933-1330</orcidid></search><sort><creationdate>20210801</creationdate><title>CFD Simulation of the Safety of Unmanned Ship Berthing under the Influence of Various Factors</title><author>Xiao, Guoquan ; Tong, Chao ; Wang, Yue ; Guan, Shuaishuai ; Hong, Xiaobin ; Shang, Bin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-676df7f0506ee3da4d2efdb40e6298b2154698a5a241ca73f53dba888a09b9763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>autonomous berthing algorithm</topic><topic>Autonomous cars</topic><topic>Berthing</topic><topic>berthing safety</topic><topic>CFD coupling model</topic><topic>Computational fluid dynamics</topic><topic>Computer applications</topic><topic>Driving ability</topic><topic>Flow resistance</topic><topic>Fluid dynamics</topic><topic>Fluid mechanics</topic><topic>Growth rate</topic><topic>Hydrodynamics</topic><topic>Obstacle avoidance</topic><topic>Pressure</topic><topic>Real time</topic><topic>Research methodology</topic><topic>Resistance factors</topic><topic>Route planning</topic><topic>Safety</topic><topic>Safety engineering</topic><topic>Ships</topic><topic>Simulation</topic><topic>Torque</topic><topic>Unmanned aerial vehicles</topic><topic>unmanned ship</topic><topic>Unmanned vehicles</topic><topic>Vertical forces</topic><topic>Water flow</topic><topic>Wind</topic><topic>Wind direction</topic><topic>Wind effects</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xiao, Guoquan</creatorcontrib><creatorcontrib>Tong, Chao</creatorcontrib><creatorcontrib>Wang, Yue</creatorcontrib><creatorcontrib>Guan, Shuaishuai</creatorcontrib><creatorcontrib>Hong, Xiaobin</creatorcontrib><creatorcontrib>Shang, Bin</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Applied sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xiao, Guoquan</au><au>Tong, Chao</au><au>Wang, Yue</au><au>Guan, Shuaishuai</au><au>Hong, Xiaobin</au><au>Shang, Bin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>CFD Simulation of the Safety of Unmanned Ship Berthing under the Influence of Various Factors</atitle><jtitle>Applied sciences</jtitle><date>2021-08-01</date><risdate>2021</risdate><volume>11</volume><issue>15</issue><spage>7102</spage><pages>7102-</pages><issn>2076-3417</issn><eissn>2076-3417</eissn><abstract>The safety of unmanned ship berthing is of paramount importance. In order to explore the influence of wind and wave coupling, a berthing computational fluid dynamics (CFD) model was established, and the characteristics of speed field, pressure field, and vortex have been obtained under different speed, wind direction, and the quay wall distances. The results show that the total resistance of the hull against the current can be about 1.60 times higher compared to the downstream resistance, water flow resistance is the dominant factor, accounting for more than 80% of the total resistance. When changing the distance between ship and shore at fixed speed, the results found that the torque is small, but the growth rate is very large when driving below 2 m/s, and the torque growth rate is stable above 2 m/s. Based on the established coupling model, a multi-factor berthing safety study is carried out on an actual unmanned ship. The results show that when the speed increases from 4 m/s to 12 m/s, the curve slope is small, the resistance increases from 3666 N to 18,056 N, and the rear slope increases. The pressure increases with the speed, and when the speed is 24 m/s, the maximum pressure is up to 238,869 Pa. When the wind speed is fixed, the vertical force of the unmanned ship increases first and then decreases to zero and then reverses the same law change, and the maximum resistance is about 425 N at the wind angle of about 45 degrees; At 90 degrees, the maximum lateral force on an unmanned boat is about 638 N. The above results can provide control strategy for unmanned ship berthing safety, and provide theoretical basis for unmanned ship route planning and obstacle avoidance, safety design, etc.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/app11157102</doi><orcidid>https://orcid.org/0000-0003-1650-525X</orcidid><orcidid>https://orcid.org/0000-0002-9933-1330</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy autonomous berthing algorithm Autonomous cars Berthing berthing safety CFD coupling model Computational fluid dynamics Computer applications Driving ability Flow resistance Fluid dynamics Fluid mechanics Growth rate Hydrodynamics Obstacle avoidance Pressure Real time Research methodology Resistance factors Route planning Safety Safety engineering Ships Simulation Torque Unmanned aerial vehicles unmanned ship Unmanned vehicles Vertical forces Water flow Wind Wind direction Wind effects Wind speed |
title | CFD Simulation of the Safety of Unmanned Ship Berthing under the Influence of Various Factors |
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