Article(id=1240656101893525558, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240656096998773667, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2025.01.019, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1699027200000, receivedDateStr=2023-11-04, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773725064967, onlineDateStr=2026-03-17, pubDate=1742832000000, pubDateStr=2025-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773725064967, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773725064967, creator=13701087609, updateTime=1773725064967, updator=13701087609, issue=Issue{id=1240656096998773667, tenantId=1146029695717560320, journalId=1240618002186551303, year='2025', volume='48', issue='1', pageStart='1', pageEnd='198', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773725063800, creator=13701087609, updateTime=1773725118083, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240656324749480238, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240656096998773667, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240656324749480239, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1240656096998773667, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=150, endPage=156, ext={EN=ArticleExt(id=1240656102149378122, articleId=1240656101893525558, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=A study on power prediction of full-formed ships using a combined EFD/CFD method, columnId=1240655132208189615, journalTitle=Navigation of China, columnName=Ship and Ocean Engineering Equipment, runingTitle=null, highlight=null, articleAbstract=

To predict the delivered power of full-formed ships using a combined EFD/CFD method, this work investigated methods of obtaining the hull form factor (1+k) for three full-formed ships under various loading conditions, and analyzed their applicability. The hull form factors of each vessel were obtained using model test and numerical simulation, respectively. They were compared and then utilized to perform full-scale predictions of the delivered power using the combined method. The research indicated that the hull form factor obtained from numerical simulation resulted in a closer match between the predicted full-scale delivered power and the trial data, with an allowable difference. The research also validated the applicability of the delivered power prediction of full-formed ships using the combined method.

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对三种肥大船型不同载况下形状因子(1+k)的确定方法及其适应性开展研究,探讨建立基于模型试验流体动力学(EFD)和计算流体动力学(CFD)组合方法的肥大船型实船功率预报方法。以某肥大型散货船为主要研究对象,分别采用模型试验和数值模拟方法确定形状因子并进行对比分析,然后采用EFD和CFD组合方法进行实船性能预报。研究表明:基于CFD获取形状因子并结合模型试验进行肥大船型功率预报,结果与实船试航结果比较接近且在误差允许范围内,验证基于EFD和CFD组合方法预报实船航速功率具有实用性和可行性。

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高玉玲(1982—),女,研究员,研究方向为船舶水动力性能研究。E-mail:
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高旋(1997—),女,助理研究员,研究方向为船舶水动力性能研究。E-mail:

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基于EFD和CFD组合方法的肥大船型功率预报研究
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高旋 , 高玉玲 , 陈伟民
中国航海 | 船舶工程与装备 2025,48(1): 150-156
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中国航海 | 船舶工程与装备 2025, 48(1): 150-156
基于EFD和CFD组合方法的肥大船型功率预报研究
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高旋 , 高玉玲 , 陈伟民
作者信息
  • 上海船舶运输科学研究所有限公司 水路交通控制全国重点实验室,上海 200135;上海船舶运输科学研究所有限公司 航运技术交通行业重点实验室,上海 200135
  • 高旋(1997—),女,助理研究员,研究方向为船舶水动力性能研究。E-mail:

通讯作者:

高玉玲(1982—),女,研究员,研究方向为船舶水动力性能研究。E-mail:
A study on power prediction of full-formed ships using a combined EFD/CFD method
Xuan GAO , Yuling GAO , Weimin CHEN
Affiliations
  • State Key Laboratory of Maritime Technology and Safety, Shanghai Ship and Shipping Research Institute Co, Ltd, Shanghai 200135, China; Key Laboratory of Marine Technology, Ministry of Communications, PRC, Shanghai Ship and Shipping Research Institute Co, Ltd, Shanghai 200135, China
出版时间: 2025-03-25 doi: 10.3969/j.issn.1000-4653.2025.01.019
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对三种肥大船型不同载况下形状因子(1+k)的确定方法及其适应性开展研究,探讨建立基于模型试验流体动力学(EFD)和计算流体动力学(CFD)组合方法的肥大船型实船功率预报方法。以某肥大型散货船为主要研究对象,分别采用模型试验和数值模拟方法确定形状因子并进行对比分析,然后采用EFD和CFD组合方法进行实船性能预报。研究表明:基于CFD获取形状因子并结合模型试验进行肥大船型功率预报,结果与实船试航结果比较接近且在误差允许范围内,验证基于EFD和CFD组合方法预报实船航速功率具有实用性和可行性。

模型试验流体动力学  /  计算流体动力学  /  模型试验与数值计算组合方法  /  形状因子  /  实船功率预报

To predict the delivered power of full-formed ships using a combined EFD/CFD method, this work investigated methods of obtaining the hull form factor (1+k) for three full-formed ships under various loading conditions, and analyzed their applicability. The hull form factors of each vessel were obtained using model test and numerical simulation, respectively. They were compared and then utilized to perform full-scale predictions of the delivered power using the combined method. The research indicated that the hull form factor obtained from numerical simulation resulted in a closer match between the predicted full-scale delivered power and the trial data, with an allowable difference. The research also validated the applicability of the delivered power prediction of full-formed ships using the combined method.

experimental fluid dynamics  /  computational fluid dynamics  /  a combined EFD/CFD method  /  form factor  /  full-scale power prediction
高旋, 高玉玲, 陈伟民. 基于EFD和CFD组合方法的肥大船型功率预报研究. 中国航海, 2025 , 48 (1) : 150 -156 . DOI: 10.3969/j.issn.1000-4653.2025.01.019
Xuan GAO, Yuling GAO, Weimin CHEN. A study on power prediction of full-formed ships using a combined EFD/CFD method[J]. Navigation of China, 2025 , 48 (1) : 150 -156 . DOI: 10.3969/j.issn.1000-4653.2025.01.019
  • 国家重点研发计划(2022YFB4300802)
2025年第48卷第1期
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doi: 10.3969/j.issn.1000-4653.2025.01.019
  • 接收时间:2023-11-04
  • 首发时间:2026-03-17
  • 出版时间:2025-03-25
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  • 收稿日期:2023-11-04
基金
国家重点研发计划(2022YFB4300802)
作者信息
    上海船舶运输科学研究所有限公司 水路交通控制全国重点实验室,上海 200135;上海船舶运输科学研究所有限公司 航运技术交通行业重点实验室,上海 200135

通讯作者:

高玉玲(1982—),女,研究员,研究方向为船舶水动力性能研究。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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