Article(id=1243879845583766052, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1243879841024553767, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1007-7294.2024.09.004, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1710777600000, receivedDateStr=2024-03-19, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1774493665356, onlineDateStr=2026-03-26, pubDate=1726761600000, pubDateStr=2024-09-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774493665356, onlineIssueDateStr=2026-03-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774493665356, creator=13701087609, updateTime=1774493665356, updator=13701087609, issue=Issue{id=1243879841024553767, tenantId=1146029695717560320, journalId=1240685776644648972, year='2024', volume='28', issue='9', pageStart='1297', pageEnd='1462', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1774493664270, creator=13701087609, updateTime=1774493987725, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1243881197806404366, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1243879841024553767, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1243881197806404367, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1243879841024553767, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1328, endPage=1338, ext={EN=ArticleExt(id=1243879845868978727, articleId=1243879845583766052, tenantId=1146029695717560320, journalId=1240685776644648972, language=EN, title=Drag reduction study on the biomimetic adaptive deformation of the wall surface of underwater vehicles, columnId=1241023037940748650, journalTitle=Journal of Ship Mechanics, columnName=Hydrodynamics, runingTitle=null, highlight=null, articleAbstract=

Dolphins and other toothed cetaceans have high-speed swimming ability and are important research objects for underwater biomimetic drag reduction. In this paper, based on the characteristics of dolphin skin structure and adaptive deformation, an engineering-scale bionic study was carried out, a wall deformation motion control equation with the normal velocity of the boundary layer of the wall surface as the input signal was designed, and the drag reduction performance of the deformed wall surface was simulated by the dynamic mesh technology. The results show that the optimal frictional resistance reduction rate of the deformed wall surface is 19.24% and the optimal total resistance reduction rate is 6.4% at a flow rate of 0.5 to 10 m/s. Application of the biomimetic control results in the increase of the thickness of the turbulent boundary layer of the wall surface, reduction of both the surface friction resistance and the turbulence kinetic energy of the flow field. The bionic deformation wall was applied to the surface of the non-attached SUBOFF submarine model to carry out drag reduction design. In the speed range of 3.045-8.231 m/s, the total drag reduction rate greater than 8.0% was obtained.

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海豚等齿鲸亚目类动物具有高速游动能力,是水下仿生减阻的重要研究对象。本文根据海豚皮肤结构及自适应变形等特性进行工程尺度的仿生研究,设计一种以壁面边界层法向速度为输入信号的壁面变形运动控制方程,并通过动网格技术仿真模拟得到变形壁面的减阻性能。研究结果表明,在0.5~10 m/s流速下变形壁面最优摩擦阻力减阻率为19.24%,最优总阻力减阻率为6.4%。施加仿生控制后壁面湍流边界层厚度有所增加,表面摩擦阻力减小,流场湍动能降低。将该仿生变形壁面应用于无附体SUBOFF潜艇模型表面开展减阻设计,在3.045~8.231 m/s的速度范围内,潜艇总阻力减阻率均大于8.0%。

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通讯作者,E-mail:
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唐俊(1979-),男,博士,副研究员

李佳勇(1998-),男,硕士,通讯作者,E-mail:

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articleId=1243879845583766052, language=CN, orderNo=2, keyword=仿生), Keyword(id=1243879857453646676, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1243879845583766052, language=CN, orderNo=3, keyword=变形壁面), Keyword(id=1243879857600447323, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1243879845583766052, language=CN, orderNo=4, keyword=减阻)], refs=[Reference(id=1243879863078207578, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1243879845583766052, doi=null, pmid=null, pmcid=null, year=2009, volume=39, issue=5, pageStart=546, pageEnd=554, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=柯贵喜, 潘光, 黄桥高, journalName=力学进展, refType=null, unstructuredReference=柯贵喜,潘光,黄桥高,. 水下减阻技术研究综述[J]. 力学进展200939(5): 546-554., articleTitle=水下减阻技术研究综述, refAbstract=null), Reference(id=1243879863174676573, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1243879845583766052, doi=null, pmid=null, 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Boundary layer thicknesses at different locations

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距平板前端距离/m来流速度/(m·s-1边界层厚度/m
0.4100.0071
1.60.0215
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不同位置边界层厚度

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距平板前端距离/m来流速度/(m·s-1边界层厚度/m
0.4100.0071
1.60.0215
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Parameters of different scenarios

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方案形变方程参数
1h=2.4
2h=2
3h=1.7
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不同方案参数

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方案形变方程参数
1h=2.4
2h=2
3h=1.7
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Optimal deformation of the wall

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速度/(m·s-10.513610
最优变形量/mm1.671.701.962.002.00
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壁面最优变形量

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速度/(m·s-10.513610
最优变形量/mm1.671.701.962.002.00
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Wall drag reduction efficiency at different speeds

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来流速度/(m·s-10.513610
减阻效率0.251.9837.86225.75825.77
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不同速度下壁面减阻效率

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来流速度/(m·s-10.513610
减阻效率0.251.9837.86225.75825.77
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Experimental data of uninhibited SUBOFF submarine

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来流速度/(m·s-13.0455.1446.0918.231
总阻力/N87.40242.2332.9576.9
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无附体SUBOFF潜艇实验数据

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来流速度/(m·s-13.0455.1446.0918.231
总阻力/N87.40242.2332.9576.9
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Simulation results of uninhibited SUBOFF submarine

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来流速度/(m·s-1光滑表面摩擦阻力/N光滑表面总阻力/N变形后摩擦阻力/N变形后总阻力/N摩擦阻力减阻率(%)总阻力减阻率(%)
3.04576.8387.8865.1580.0715.208.89
5.144206.65236.52176.85216.1014.428.63
6.091283.20324.32242.95296.6814.218.52
8.231491.13563.42424.08517.4813.658.15
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无附体SUBOFF潜艇仿真结果

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来流速度/(m·s-1光滑表面摩擦阻力/N光滑表面总阻力/N变形后摩擦阻力/N变形后总阻力/N摩擦阻力减阻率(%)总阻力减阻率(%)
3.04576.8387.8865.1580.0715.208.89
5.144206.65236.52176.85216.1014.428.63
6.091283.20324.32242.95296.6814.218.52
8.231491.13563.42424.08517.4813.658.15
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水下航行器壁面仿生自适应变形的减阻研究
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唐俊 a, b , 李佳勇 a , 孙鑫淼 a
船舶力学 | 流体力学 2024,28(9): 1328-1338
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船舶力学 | 流体力学 2024, 28(9): 1328-1338
水下航行器壁面仿生自适应变形的减阻研究
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唐俊a, b, 李佳勇a , 孙鑫淼a
作者信息
  • a.天津大学 建筑工程学院,天津 300354
  • b.天津大学 港口与海洋工程天津市重点实验室,天津 300354
  • 唐俊(1979-),男,博士,副研究员

    李佳勇(1998-),男,硕士,通讯作者,E-mail:

通讯作者:

通讯作者,E-mail:
Drag reduction study on the biomimetic adaptive deformation of the wall surface of underwater vehicles
Jun TANGa, b, Jia-yong LIa , Xin-miao SUNa
Affiliations
  • a.School of Civil Engineering and Architecture, Tianjin University, Tianjin 300354, China
  • b.Tianjin Key Laboratory of Port and Ocean Engineering, Tianjin University, Tianjin 300354, China
出版时间: 2024-09-20 doi: 10.3969/j.issn.1007-7294.2024.09.004
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海豚等齿鲸亚目类动物具有高速游动能力,是水下仿生减阻的重要研究对象。本文根据海豚皮肤结构及自适应变形等特性进行工程尺度的仿生研究,设计一种以壁面边界层法向速度为输入信号的壁面变形运动控制方程,并通过动网格技术仿真模拟得到变形壁面的减阻性能。研究结果表明,在0.5~10 m/s流速下变形壁面最优摩擦阻力减阻率为19.24%,最优总阻力减阻率为6.4%。施加仿生控制后壁面湍流边界层厚度有所增加,表面摩擦阻力减小,流场湍动能降低。将该仿生变形壁面应用于无附体SUBOFF潜艇模型表面开展减阻设计,在3.045~8.231 m/s的速度范围内,潜艇总阻力减阻率均大于8.0%。

海豚皮肤  /  仿生  /  变形壁面  /  减阻

Dolphins and other toothed cetaceans have high-speed swimming ability and are important research objects for underwater biomimetic drag reduction. In this paper, based on the characteristics of dolphin skin structure and adaptive deformation, an engineering-scale bionic study was carried out, a wall deformation motion control equation with the normal velocity of the boundary layer of the wall surface as the input signal was designed, and the drag reduction performance of the deformed wall surface was simulated by the dynamic mesh technology. The results show that the optimal frictional resistance reduction rate of the deformed wall surface is 19.24% and the optimal total resistance reduction rate is 6.4% at a flow rate of 0.5 to 10 m/s. Application of the biomimetic control results in the increase of the thickness of the turbulent boundary layer of the wall surface, reduction of both the surface friction resistance and the turbulence kinetic energy of the flow field. The bionic deformation wall was applied to the surface of the non-attached SUBOFF submarine model to carry out drag reduction design. In the speed range of 3.045-8.231 m/s, the total drag reduction rate greater than 8.0% was obtained.

dolphin skin  /  bionics  /  deformed wall surface  /  drag reduction
唐俊, 李佳勇, 孙鑫淼. 水下航行器壁面仿生自适应变形的减阻研究. 船舶力学, 2024 , 28 (9) : 1328 -1338 . DOI: 10.3969/j.issn.1007-7294.2024.09.004
Jun TANG, Jia-yong LI, Xin-miao SUN. Drag reduction study on the biomimetic adaptive deformation of the wall surface of underwater vehicles[J]. Journal of Ship Mechanics, 2024 , 28 (9) : 1328 -1338 . DOI: 10.3969/j.issn.1007-7294.2024.09.004
对于水下航行器和水上船只,减少阻力能够减少能源的损耗和提高快速性。对于水上船只,表面总阻力中摩擦阻力占比为50%,而水下航行器的摩擦阻力占比高达70%,因此研究减少摩擦阻力的技术意义重大[1-3]。许多海洋生物进化形成了具有高效减阻功能的皮肤结构,其中鲨鱼皮表面的盾鳞微结构[4]受到广泛研究,而海豚皮肤结构同样是一个重要研究对象,目前对海豚皮肤减阻机理有柔性壁面减阻[5-6]、随行波减阻[7-8]、自适应形变减阻[9-11]等解释。
相关研究表示,由于近壁区的湍流相干结构的影响,壁面会产生较大的摩擦阻力[12]。因此正确改变表面结构会干扰边界层内湍流结构,从而降低物体表面摩擦阻力[13-14]。Choi[15]等通过数值模拟方法研究了反向控制下的壁面吹吸方法,取得了25%的最优减阻效果,发现施加控制可以短时间阻止扫掠运动。Chung[16]分别考虑了吹壁和吸力控制输入的振幅和相位的影响,结果表明,吹吸的振幅以及检测平面位置在主动控制降低壁面摩擦阻力方面发挥了重要作用,通过改变振幅,所有考虑的探测平面位置都实现了大幅减阻。随着智能控制与智能材料等技术的发展,湍流减阻主动控制的实际应用成为可能[17]。因此通过控制壁面变形来降低摩擦力的研究具有重要意义。
过往仿生减阻的研究中较少考虑海豚皮肤自适应减阻的特性,并且仿生结构多为微尺度,在实际应用中存在加工精度要求高、易被生物附着而失效等困难。本文基于海豚皮肤的减阻特性,利用大尺度的余弦函数代替海豚表皮的微型随行波结构,更具有工程实用性;根据海豚皮肤的自适应特性,设计一种根据近壁区流场法向速度控制壁面变形的程序,以此模拟海豚皮肤的自适应形变功能。将此变形控制程序应用于光滑平板进行仿真,研究自适应减阻性能和减阻机理;对无附体SUBOFF潜艇模型表面施加变形控制程序,研究该控制程序是否适用于实际航行器表面,证明该仿生减阻方法的实用性以设计更高性能及更低能耗的水下航行器。
海豚等齿鲸亚目类动物游动速度很快,经研究发现这类动物的表皮组织分布着波纹状的微小沟嵴,皮肤嵴的波宽约为0.41~2.35 mm,峰谷与波峰的高度差约为7~112 μm[18]。海豚大部分皮肤嵴结构是规则的,而且方向垂直于来流方向[19]图1为该皮肤嵴结构及其截面曲线示意图,可以看到该截面曲线与三角函数较为相似。
海豚的皮肤嵴属于微结构,在船舶或潜艇等交通工具的表面复刻微米级结构并不现实,智能蒙皮技术实现大面积精准的变形难度很高且性价比很低,因此依据仿生学原理使用余弦函数代替海豚皮肤嵴形状,并对其尺度进行适当放大以提高工程实用性,设计了一种用于代替海豚皮肤随行波结构的壁面变形函数,壁面变形函数为
式中:h为壁面形变的幅值,根据控制方程决定幅值的大小;d为变形区域前端平板的长度;ω为变形区域一个周期的宽度。本文dω的取值分别为0.4 m和0.06 m。
活体海豚皮肤不仅存在皮肤嵴结构,其皮下的真皮乳突阵列更能感受到外部流体的变化[20-21],如脉动压力和速度等的变化,并通过皮肤表面微小变形起到一个自适应减阻的效果。本文设计壁面变形的控制方程来模拟海豚皮肤自适应形变的过程,且暂不考虑海豚皮肤弹性影响。
根据对湍流主动控制输入信号的研究[22],仿照海豚皮肤的感应原理设计了一种使用近壁区边界层法向速度作为输入信号的控制算法,控制方程如下:
式中:r=0.005为时间松弛系数;c=1.425为控制量的调整系数;(vnn+1与(vnn分别代表在第n+1时间步与第n时间步时,控制壁面在y方向变形的速度;(vyn为在第n个时间步时获取的法向速度的值。
图2所示,计算域模型长(x方向)为2 m,高(y方向)和宽(z方向)均为0.25 m。其中左右表面边界条件分别设置为速度入口和压力出口,前后表面设置为对称壁面,上下表面设置为普通壁面。下表面分为三部分,其中从速度入口处到0.4 m处为前端发展区域,使流体在到达变形控制区之前形成湍流;中间0.4 m到1.6 m处为变形控制区域,分为20个部分,可通过编译加载UDF程序实现壁面变形,以形成20个随行波结构;从1.6 m到2 m处为后端缓冲区域,研究壁面变形对后续流场的影响。
通过主动控制壁面降低湍流摩擦阻力,使变形对近壁区边界层内的流场产生有利的干扰,因此壁面变形量应小于边界层的厚度。平板湍流边界层公式为
式中:x为距速度入口的距离;δx处的边界层厚度;Rex)为x处的雷诺数;ρ=998.2 kg/m3,为水的密度;U为来流速度;μ=1.003×10-3,为水的运动粘度。
由公式可知,来流速度增加会使平板的边界层厚度减少,因此取最高流速10 m/s时平板不同位置求边界层最小厚度,如表1所示。
因此仿生变形壁面变形量应小于7.1 mm,为避免壁面变形引起上下壁面的相互影响,计算域的上下表面间距为250 mm,远大于最大变形量的20倍,以保证计算结果的准确性。
由于结构化六面体网格不能用于动网格重构,因此选择四面体非结构化网格进行网格划分,对变形壁面近壁区网格进行加密,其中计算域模型网格与变形前后近壁区边界层网格如图3所示。
为避免网格数量对计算结果造成影响,在流速分别为0.5 m/s、3 m/s和10 m/s时进行了网格无关性验证,在平板模型网格数达到100万时,网格数增加对结果影响很小;在主动控制模型网格数达到350万时,网格数增加对结果影响很小。在此平板网格密度下计算光滑平板不同流速的摩擦阻力系数,如图4所示,仿真计算结果与理论公式计算结果误差在2%以内,证明了计算结果的准确性。
流体域的介质是水,为不可压缩流体,采用不可压的雷诺平均法进行湍流模拟计算。考虑壁面变形会导致壁面边界层特征的改变,湍流模型选择SST k-ω模型,该模型在模拟壁面边界层特征的细节方面更加精确,比如近壁区扰流以及转捩等湍流活动。SST k-ω模型的输运方程为
式中,k为湍流动能,ω为湍流比耗散率,ρ为流体介质的密度,ΓkΓω分别为与kω的有效扩散项,GkGω分别是平均速度梯度产生的湍动能和湍流比耗散率方程,YkYω分别代表kω在湍流作用下的耗散,Dω是湍流交叉项,SkSω是相关源项。
壁面变形选择瞬态计算并启用动网格模块,网格更新方法为弹簧光顺(smoothing)和网格重构(remeshing)方法,变形控制区域通过UDF程序控制变形,将流体与对称壁面设置为变形边界(deforming),使该区域与变形壁面连接处网格随壁面变形而变形。
选择PISO算法对问题进行求解,求解速度快且在求解瞬态问题上更为稳定。压力项选择标准离散格式,动量及湍流输运方程采用二阶迎风格式离散。将瞬态计算的时间步长设为0.002 s,步数设为500步,在每一步中迭代20次进行瞬态计算。
在0.5~10 m/s速度范围内对仿生控制壁面进行仿真计算,为考察不同壁面形变方程对壁面阻力的影响,本文根据1.1节的壁面变形函数设计不同的方案,如表2所示,且设置变形宽度为60 mm不变,h代表壁面允许形变的约束幅值,单位为mm。
根据仿真分别计算得到几种不同方案的摩擦阻力Ff和总阻力Fall,仿生变形壁面摩擦阻力减阻率Rf和总阻力减阻率Rall
式中,Ffp为光滑平板的摩擦阻力,Fallp为光滑平板的总阻力。
程序控制壁面变形0.6 s后总阻力减阻率达到最优,图5为不同速度下的摩擦阻力减阻率和压差阻力增阻率,其中纯色图例代表摩擦阻力减阻率,阴影图例代表压差阻力增阻率。图6为总阻力的最优减阻率。壁面的变形会使壁面在减少摩擦阻力的同时产生额外的压差阻力,总阻力减阻率=摩擦阻力减阻率-压差阻力增阻率。从图5可以看到,随着速度的增加,仿生表面的摩擦阻力减阻率与压差阻力增阻率整体呈下降趋势;在0.5 m/s到3 m/s的低速范围内,压差阻力增阻率的下降趋势明显大于摩擦阻力减阻率的下降趋势,总阻率减阻率随速度增加而上升;反之,在3 m/s到10 m/s的中高速范围,总阻力减阻率随着速度增加而降低。三种方案在3 m/s到6 m/s(雷诺数范围为5.96×106~1.19×107)范围内均获得较好的总阻力减阻率,且3种方案均能有效降低总阻力以及摩擦阻力。
在相同速度下,三种方案的仿生变形壁面变形量越大,摩擦阻力减阻率越高,但随之产生的压差阻力增阻率也越大,因此最高的摩擦阻力减阻率并不一定带来最大的总阻力减阻效果。表3给出了不同流速条件下,总阻力减阻率最优时对应的壁面变形量的值,根据图6表3可以看出,壁面最优变形量会随流速的增加而增加,趋近于一个最佳值。
图7显示的是方案2中第11变形区域在形变过程中不同时刻法向位置的变化,使用变形区域一个周期的宽度ω对横坐标进行无量纲化。由图可知在变形过程中壁面逐渐形成波峰与波谷,使得壁面向着海豚皮肤简化结构转化。
由于壁面变形需要外部输入能量,因此在考虑减阻率的同时也需要考虑减阻效率。在控制方案2下,主动控制壁面系统的输入能量为
式中:ρ为智能蒙皮材料的密度,这里取为铜锌铝记忆合金密度7.76×103 kg/m3w=0.25 m,为控制壁面展向长度;h=0.002 m,为智能蒙皮材料的厚度;axt)为不同时刻不同位置壁面的加速度;vyxt)为不同时刻不同位置壁面的法向速度。
主动壁面变形做的有用功率为
式中,u为来流速度,Δf为减小的总阻力。
主动变形壁面的减阻效率η
表4为不同来流速度下减阻效率的值。由表4可以看出,来流速度越大减阻效率越高,在0.5 m/s时输入功率大于有用功率,但在1 m/s以上,均是有用功率大于输入功率,即节约的能量多于系统输入的能量。
近壁区相干结构的自维持过程是壁面湍流产生和维持的关键[23]。由于方案2的减阻效果较好,因此对方案2进行分析,分别从近壁区边界层厚度与速度梯度、表面切应力以及湍流统计量等方面对仿生变形壁面的湍流减阻机理进行分析。
图8为中间横截面在不同时刻的速度云图,由图可知,边界层厚度沿流向逐渐增加。随着壁面的运动,壁面对近壁区流场的影响越来越明显,增大了变形处边界层厚度。
将仿生变形壁面区域1不同时刻的速度云图放大(图9)。对比区域1不同变形时刻的云图可以发现,壁面的变形降低了壁面附近的速度梯度,从而降低了仿生变形壁面的摩擦阻力,且变形对距壁面更远处的流场产生了影响,使其流速降低。
图10为仿生变形壁面第11变形区域的速度矢量图,从图中可以看出,流体流入波谷时壁面附近速度梯度明显下降。壁面的变形引动流体速度方向发生变化,且近壁面流体流速逐渐降低,进而使变形壁面的波谷区域不断地存留低速流体引起边界层厚度的增加,且存留的低速流体的粘性作用使经过波谷的流体速度梯度降低,使得壁面的摩擦力得到了降低。
图11为仿生变形壁面的切应力云图,可以看到不同区域的切应力以周期条带的形式表现,壁面摩擦阻力可以通过表面切应力代表。图12为光滑平板表面和仿生变形壁面在第10与第11个变形区域的表面切应力曲线,使用变形区域一个周期的宽度ω对横坐标进行无量纲化。由图12可知,仿生变形壁面切应力曲线呈周期性变化,但与形状函数的峰谷起伏相比有所偏移。仿生变形壁面表面切应力的波动对应着图11的周期条带,且由图12可以看出仿生变形壁面的整体切应力明显小于光滑表面,因此仿生变形壁面的运动能够有效地降低摩擦阻力。
图13为距光滑平板表面和第0.6 s时仿生变形壁面0.001 m处平面的湍动能值。由图可知,在变形区域前端湍动能基本相同;而在仿生变形壁面区域,壁面的运动可以对近壁面附近的流场进行扰动,使得流场的湍动能降低;从曲线末端可以看出,变形区域后端的湍动能仍小于平板的湍动能,整体上降低了壁面湍流摩擦阻力。
图14展示了不同时刻第18、19变形区域部分仿生变形区域的中横剖面图。由图可知,在未变形情况下壁面附近的湍动能是规律的梯度变化;而随着壁面的变形,壁面附近的湍动能整体减小,表现为云图等值区域的下移,且湍动能峰值部分区域减小至波谷处;随着壁面继续变形,在波谷的湍动能峰值与变形壁面之间出现湍动能突然减小的条带状区域,且此区域随壁面的变形逐渐增加,以至于影响到下一个波峰,使得近壁区的湍动能逐渐减小。
为研究该仿生变形控制表面是否可以应用于复杂结构,将该控制方法应用于无附体SUBOFF潜艇标准模型表面。SUBOFF潜艇标准模型总长为4.356 m,平行中体长2.229 m,最大直径为0.508 m[24]。由于SUBOFF潜艇标准模型平行中体处流场平行于来流方向更利于法向速度的获取,将表2中的模型方案2在潜艇模型上进行应用,在潜艇模型的圆柱中段部分划分34个变形控制区域。
根据1/4潜艇模型建立1/4圆柱体流体域模型,速度入口距艇首取4 m,出口距艇尾取8 m,径向取6 m。采用四面体网格进行划分,在潜艇表面设立边界层网格,第一层网格高度满足y+接近5,且对潜艇变形控制区域网格进行加密,艇体表面网格如图15所示。来流速度范围为3.045~8.231 m/s,潜艇湍流模型设置同平板模型湍流设置。
表5为无附体SUBOFF潜艇标准模型实验数值[25],与表6中仿真结果相比较,误差在2.5%以内,证明了计算的准确性。
表6为光滑表面和仿生变形表面的SUBOFF潜艇摩擦阻力与总阻力的仿真结果。从表中可以看出,经过仿生变形控制后,潜艇的摩擦阻力减阻率与总阻力减阻率随速度增加而减少,与图5图6中3.045~8.231 m/s速度范围内摩擦阻力与总阻力变化趋势相符。在3.045~8.231 m/s的速度范围内SUBOFF潜艇的摩擦阻力减阻率在13.5%以上,总阻力减阻率在8%以上。表明仿生变形控制方法也适用于结构更加复杂的潜艇模型。
图16为SUBOFF潜艇模型变形前后表面切应力云图,经仿生变形控制后潜艇模型的变形区域表面切应力以周期条带的形式表示,与仿生控制变形后平板模型的切应力云图特征一致,证明了减阻机理的正确性;与光滑表面无附体SUBOFF模型相比,仿生控制变形后的模型变形区域的切应力显著降低,使得潜艇表面整体的摩擦阻力得到降低。
本文根据仿生学原理,基于海豚皮肤的减阻特性,利用大尺度的余弦函数代替海豚表皮的微型皮肤嵴结构,设计了一种根据近壁区流场法向速度控制壁面变形的程序,代替海豚皮肤的自适应形变功能。通过仿真结果可以得出,壁面的仿生变形运动能够有效地降低壁面总阻力以及湍流摩擦阻力,且在0.5~10 m/s的流速下都有较好的减阻效果,摩擦阻力减阻率的最大值为19.3%,总阻力减阻率的最大值为6.4%。在3.045~8.231 m/s的流速范围内,仿生变形后无附体SUBOFF潜艇的摩擦阻力减阻率在13.5%以上,总阻力减阻率在8%以上。
通过分析仿生变形壁面不同时刻的近壁区流场及壁面信息,得出仿生变形壁面的减阻机理:(1)壁面变形能够降低速度梯度,随着低速流体在壁面波谷处滞留,使得低速流体上移以增加边界层厚度;(2)壁面的运动可以抑制湍流相干结构的自维持过程,使湍动能波动降低,流动更加稳定,且能够影响周围流场使其湍动能相应减小。
研究结果证实了自适应减阻的可行性,由于仿生变形控制方法较为简单,变形不局限于微尺度,且在较大流速范围内都具有较好的减阻效果,具有工程实用性,因此有利于设计更高性能以及更为节能的水下航行器等运输工具。但主动控制的柔性仿生表面需要较多传感器来获取流场数据,控制系统复杂;长时间水下高压条件下智能蒙皮的有效性与安全性有待提升;大面积智能柔性蒙皮的一体化应用等工程实践问题还需进一步研究。
  • 装备预先研究资助项目(61402100104)
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2024年第28卷第9期
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doi: 10.3969/j.issn.1007-7294.2024.09.004
  • 接收时间:2024-03-19
  • 首发时间:2026-03-26
  • 出版时间:2024-09-20
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  • 收稿日期:2024-03-19
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    a.天津大学 建筑工程学院,天津 300354
    b.天津大学 港口与海洋工程天津市重点实验室,天津 300354

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2种不同金属材料的力学参数

Family
属数
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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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