Article(id=1263557423109890953, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263557421033767765, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2026.01.008, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1743177600000, receivedDateStr=2025-03-29, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1779185165430, onlineDateStr=2026-05-19, pubDate=1771948800000, pubDateStr=2026-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1779185165430, onlineIssueDateStr=2026-05-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1779185165430, creator=13701087609, updateTime=1779185165430, updator=13701087609, issue=Issue{id=1263557421033767765, tenantId=1146029695717560320, journalId=1240618002186551303, year='2026', volume='49', issue='1', pageStart='1', pageEnd='197', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1779185164936, creator=13701087609, updateTime=1779185226134, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1263557677813252309, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263557421033767765, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1263557677813252310, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263557421033767765, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=78, endPage=88, ext={EN=ArticleExt(id=1263557425282540441, articleId=1263557423109890953, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Numerical simulation and identification of submarine wake characteristics in stratified flow, columnId=1240655017900823355, journalTitle=Navigation of China, columnName=Marine Traffic Safety, runingTitle=null, highlight=null, articleAbstract=

Hydrodynamic wake is one of the important physical fields for the non-acoustic detection of submarines, and its accurate prediction is difficult due to the complexity of the marine environment. The Volume of Fluid (VOF) method is used to numerically simulate the stratified flow field of a submarine under direct navigation, and the influence laws of the speed, dive depth, and seawater stratification on the free-surface wake features and internal-wave wake features are obtained. Canny edge detection operator theory is applied to extract the wake profile features, and the wake angle and transverse wave tensor angle are measured. The results show that the submarine's wake does not present a typical "V" wave when the Fr number is low at a large dive depth, but gradually changes from a "spot" to a parallel wave with the increase of the Fr number, and eventually evolves into a distinct "V" wave. The strong stratification of seawater enhances free-surface perturbation, making the free-surface wake characteristics more pronounced. These results provide a basis for image recognition of hydrodynamic wake characteristics of submarines.

, correspAuthors=Eryun CHEN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Eryun CHEN, Xingsheng LIU, Zhenlai MA, Xinxin ZHAO, Guoping LI, Ailing YANG), CN=ArticleExt(id=1263557427828482988, articleId=1263557423109890953, tenantId=1146029695717560320, journalId=1240618002186551303, language=CN, title=分层流中潜艇尾迹特征的数值模拟及识别, columnId=1240655018068595518, journalTitle=中国航海, columnName=海上交通安全, runingTitle=null, highlight=null, articleAbstract=

水动力尾迹是潜艇非声学探测的重要物理场之一。鉴于复杂的海洋环境，水动力尾迹的准确预测具有较大困难。采用多相流（VOF）方法对直航条件下潜艇分层流场进行数值模拟，获得航速、相对潜深和海水分层等因素对自由表面尾迹特征及内波尾迹特征的影响规律。采用Canny边缘检测理论提取尾迹轮廓特征，测量尾迹角和横波张角。结果表明：潜艇在相对潜深较大且弗劳德数（Fr）较低条件下，自由表面尾迹并不呈现典型“V”形波；随着Fr数的增加，尾迹形态逐渐由“斑”状演变为平行波，最终呈现明显的“V”形波。海水密度分层的增强会加剧自由表面的扰动，使自由表面尾迹特征更加突出。研究结果可为潜艇水动力尾迹特征的图像识别提供参考依据。

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陈二云（1977—），男，教授，博士，研究方向为计算流体力学。

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陈二云（1977—），男，教授，博士，研究方向为计算流体力学。

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