Article(id=1244321218023768899, tenantId=1146029695717560320, journalId=1244284848500682798, issueId=1244321215637209904, articleNumber=null, orderNo=null, doi=10.16156/j.1004-7220.2025.05.027, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728835200000, receivedDateStr=2024-10-14, revisedDate=1741449600000, revisedDateStr=2025-03-09, acceptedDate=null, acceptedDateStr=null, onlineDate=1774598896747, onlineDateStr=2026-03-27, pubDate=1759248000000, pubDateStr=2025-10-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774598896747, onlineIssueDateStr=2026-03-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774598896746, creator=13701087609, updateTime=1774598896746, updator=13701087609, issue=Issue{id=1244321215637209904, tenantId=1146029695717560320, journalId=1244284848500682798, year='2025', volume='40', issue='5', pageStart='1079', pageEnd='1366', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1774598896178, creator=13701087609, updateTime=1774599509568, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1244323788452639476, tenantId=1146029695717560320, journalId=1244284848500682798, issueId=1244321215637209904, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1244323788452639477, tenantId=1146029695717560320, journalId=1244284848500682798, issueId=1244321215637209904, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1288, endPage=1294, ext={EN=ArticleExt(id=1244321218560639828, articleId=1244321218023768899, tenantId=1146029695717560320, journalId=1244284848500682798, language=EN, title=Simulation of Fluid Resistance at Different Drafting Positions in Marathon Swimming, columnId=null, journalTitle=Journal of Medical Biomechanics, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the fluid resistance characteristics of different drafting formations in marathon swimming using computational fluid dynamics (CFD) method, and provide theoretical guidance for selecting optimal drafting strategies in competitions and training.

Methods

Multi-swimmer models were established via three-dimensional body scanning technology, and various formation models (I-, A-, V-, L-, H-type) were created by adjusting lateral and longitudinal distances between swimmers. The ANSYS Discovery Live software was used to simulate the overall resistance of different models and the resistance of individual swimmers within formations.

Results

The I3-type formation exhibited an overall drag reduction effect, reducing total resistance by 55.21%, whereas other formations increased overall resistance. The V-type formation showed the most significant resistance increase (31.88%). During drafting, the lowest resistance position was the rear position in the I3-type formation, while the highest resistance position was the middle position in the L-type formation. When leading, the fluid resistance of the leading swimmer in the A-type formation was significantly greater than that of an individual swimmer (P<0.05).

Conclusions

Longitudinal drafting formations demonstrated superior drag reduction effects, with the rear position in a three-person longitudinal arrangement showing the optimal drag reduction. Considering both tactical considerations and drag reduction effects, swimmers are advised to avoid the middle position in lateral formations.

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目的

采用计算流体力学方法分析马拉松游泳比赛中不同位置跟游时的流体阻力特性,为比赛和训练中选择最佳跟游策略提供理论依据。

方法

通过三维人体扫描技术建立多人体游泳模型,调整运动员之间的横向和纵向间距,形成5种不同的编队模型(I、A、V、L及H型)。使用ANSYS Discovery Live软件,对不同编队模型的整体游进阻力及个体运动员的游进阻力进行模拟计算。

结果

I3型编队具有整体减阻的效果,总阻力减少了55.21%,其他编队方式总体阻力都增加,不具有整体减阻效果。V型编队的整体阻力增加最多(31.88%)。跟游时,阻力最小位置是I3型编队中的末端位置;阻力最大位置是L型编队中间位置。领游时,A型编队领游运动员受到的流体阻力显著大于单独游进时的阻力(P<0.05)。

结论

纵向编队跟游的减阻效果最佳,3人纵向编队的末端位置减阻效果最佳。综合考虑战术和减阻效果时,应避免处于横向编队中间的位置游进。

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张鹏,副研究员,E-mail:
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作者贡献声明:

戚雅茜负责论文选题,论文撰写;孙凯扬负责数据处理和分析,论文修改;张鹏负责论文方法学确定,论文修改;赵德峰负责论文修改;范湘波参与论文数据处理和分析。

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Overview of different drafting formations

, figureFileSmall=null, figureFileBig=null, tableContent=
队形人数队形描述横向间距/cm纵向间距/cm
I型(I1/I2/I3)1/2/3前后线型排列0
V型3外侧2人领游,中间1人跟游90100
L型3最外侧领游,2人侧向跟游90100
A型3中间领游,2人分两侧跟游90100
H型3并排同行,无领游90100
), ArticleFig(id=1244321229658767804, tenantId=1146029695717560320, journalId=1244284848500682798, articleId=1244321218023768899, language=CN, label=表1, caption=

不同模型组合方式

, figureFileSmall=null, figureFileBig=null, tableContent=
队形人数队形描述横向间距/cm纵向间距/cm
I型(I1/I2/I3)1/2/3前后线型排列0
V型3外侧2人领游,中间1人跟游90100
L型3最外侧领游,2人侧向跟游90100
A型3中间领游,2人分两侧跟游90100
H型3并排同行,无领游90100
), ArticleFig(id=1244321229797179850, tenantId=1146029695717560320, journalId=1244284848500682798, articleId=1244321218023768899, language=EN, label=Tab. 2, caption=

ICC analysis of fluid simulation and experimental results

, figureFileSmall=null, figureFileBig=null, tableContent=
测量同类相关性95%置信区间使用真值0的F检验
下限上限自由度1自由度2显著性
单个0.9970.9170.99486.15910100.000
平均0.9980.9570.99786.15910100.000
), ArticleFig(id=1244321229889454548, tenantId=1146029695717560320, journalId=1244284848500682798, articleId=1244321218023768899, language=CN, label=表2, caption=

流体模拟与实验结果的组内相关系数(ICC)分析

, figureFileSmall=null, figureFileBig=null, tableContent=
测量同类相关性95%置信区间使用真值0的F检验
下限上限自由度1自由度2显著性
单个0.9970.9170.99486.15910100.000
平均0.9980.9570.99786.15910100.000
), ArticleFig(id=1244321230006895075, tenantId=1146029695717560320, journalId=1244284848500682798, articleId=1244321218023768899, language=EN, label=Tab. 3, caption=

Simulated results of resistance for individual athletes in different drafting formations at flow speed of 1.0-2.0 m/s

, figureFileSmall=null, figureFileBig=null, tableContent=
队形游进阻力/N
位置1位置2位置3
I1型23.0±9.8a  
I2型18.2±7.7a15.6±6.6a 
I3型14.2±6.0a11.7±5.0a9.8±4.2a
A型16.6±7.1a48.2±20.5cd16.6±7.1a
H型15.9±6.8a35.0±14.9bc15.9±6.8a
L型16.0±6.8a51.1±18.0d17.1±7.3a
V型19.0±8.1a36.0±15.3bcd19.0±8.1a
), ArticleFig(id=1244321230107558381, tenantId=1146029695717560320, journalId=1244284848500682798, articleId=1244321218023768899, language=CN, label=表3, caption=

流速1.0~2.0 m/s下不同队形中个体运动员游进阻力值模拟计算结果

, figureFileSmall=null, figureFileBig=null, tableContent=
队形游进阻力/N
位置1位置2位置3
I1型23.0±9.8a  
I2型18.2±7.7a15.6±6.6a 
I3型14.2±6.0a11.7±5.0a9.8±4.2a
A型16.6±7.1a48.2±20.5cd16.6±7.1a
H型15.9±6.8a35.0±14.9bc15.9±6.8a
L型16.0±6.8a51.1±18.0d17.1±7.3a
V型19.0±8.1a36.0±15.3bcd19.0±8.1a
), ArticleFig(id=1244321230216610294, tenantId=1146029695717560320, journalId=1244284848500682798, articleId=1244321218023768899, language=EN, label=Tab. 4, caption=

Drag reduction effects of different drafting positions

, figureFileSmall=null, figureFileBig=null, tableContent=
队形平均减阻效果/%
位置1位置2位置3
I1型0
I2型-20.87(领游)-32.17(跟游)
I3型-38.26(领游)-49.13(跟游)-57.39(跟游)
A型-27.83(跟游)109.57(领游)-27.83(跟游)
H型-30.87(并排)52.17(并排)-30.87(并排)
L型-30.43(领游)122.17(跟游)-25.65(跟游)
V型-17.39(领游)56.52(跟游)-17.39(领游)
), ArticleFig(id=1244321230342439422, tenantId=1146029695717560320, journalId=1244284848500682798, articleId=1244321218023768899, language=CN, label=表4, caption=

不同编队各位置的平均减阻效果

, figureFileSmall=null, figureFileBig=null, tableContent=
队形平均减阻效果/%
位置1位置2位置3
I1型0
I2型-20.87(领游)-32.17(跟游)
I3型-38.26(领游)-49.13(跟游)-57.39(跟游)
A型-27.83(跟游)109.57(领游)-27.83(跟游)
H型-30.87(并排)52.17(并排)-30.87(并排)
L型-30.43(领游)122.17(跟游)-25.65(跟游)
V型-17.39(领游)56.52(跟游)-17.39(领游)
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马拉松游泳比赛中不同跟游位置的流体阻力模拟
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戚雅茜 1 , 孙凯扬 1 , 赵德峰 1 , 张鹏 1 , 范湘波 2
医用生物力学 | 论著 2025,40(5): 1288-1294
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医用生物力学 | 论著 2025, 40(5): 1288-1294
马拉松游泳比赛中不同跟游位置的流体阻力模拟
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戚雅茜1, 孙凯扬1, 赵德峰1, 张鹏1 , 范湘波2
作者信息
  • 1.上海体育科学研究所(上海市反兴奋剂中心),上海 200030
  • 2.上海体育大学 竞技运动学院,上海 200438

通讯作者:

张鹏,副研究员,E-mail:
Simulation of Fluid Resistance at Different Drafting Positions in Marathon Swimming
Yaqian QI1, Kaiyang SUN1, Defeng ZHAO1, Peng ZHANG1 , Xiangbo FAN2
Affiliations
  • 1.Shanghai Research Institute of Sports Science (Shanghai Anti-doping Agency), Shanghai 200030, China
  • 2.School of Athletic Performance, Shanghai University of Sport, Shanghai 200438, China
出版时间: 2025-10-01 doi: 10.16156/j.1004-7220.2025.05.027
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目的

采用计算流体力学方法分析马拉松游泳比赛中不同位置跟游时的流体阻力特性,为比赛和训练中选择最佳跟游策略提供理论依据。

方法

通过三维人体扫描技术建立多人体游泳模型,调整运动员之间的横向和纵向间距,形成5种不同的编队模型(I、A、V、L及H型)。使用ANSYS Discovery Live软件,对不同编队模型的整体游进阻力及个体运动员的游进阻力进行模拟计算。

结果

I3型编队具有整体减阻的效果,总阻力减少了55.21%,其他编队方式总体阻力都增加,不具有整体减阻效果。V型编队的整体阻力增加最多(31.88%)。跟游时,阻力最小位置是I3型编队中的末端位置;阻力最大位置是L型编队中间位置。领游时,A型编队领游运动员受到的流体阻力显著大于单独游进时的阻力(P<0.05)。

结论

纵向编队跟游的减阻效果最佳,3人纵向编队的末端位置减阻效果最佳。综合考虑战术和减阻效果时,应避免处于横向编队中间的位置游进。

马拉松游泳  /  跟游位置  /  流体阻力  /  减阻  /  计算流体力学
Objective

To analyze the fluid resistance characteristics of different drafting formations in marathon swimming using computational fluid dynamics (CFD) method, and provide theoretical guidance for selecting optimal drafting strategies in competitions and training.

Methods

Multi-swimmer models were established via three-dimensional body scanning technology, and various formation models (I-, A-, V-, L-, H-type) were created by adjusting lateral and longitudinal distances between swimmers. The ANSYS Discovery Live software was used to simulate the overall resistance of different models and the resistance of individual swimmers within formations.

Results

The I3-type formation exhibited an overall drag reduction effect, reducing total resistance by 55.21%, whereas other formations increased overall resistance. The V-type formation showed the most significant resistance increase (31.88%). During drafting, the lowest resistance position was the rear position in the I3-type formation, while the highest resistance position was the middle position in the L-type formation. When leading, the fluid resistance of the leading swimmer in the A-type formation was significantly greater than that of an individual swimmer (P<0.05).

Conclusions

Longitudinal drafting formations demonstrated superior drag reduction effects, with the rear position in a three-person longitudinal arrangement showing the optimal drag reduction. Considering both tactical considerations and drag reduction effects, swimmers are advised to avoid the middle position in lateral formations.

marathon swimming  /  drafting position  /  fluid resistance  /  drag reduction  /  computational fluid dynamics
戚雅茜, 孙凯扬, 赵德峰, 张鹏, 范湘波. 马拉松游泳比赛中不同跟游位置的流体阻力模拟. 医用生物力学, 2025 , 40 (5) : 1288 -1294 . DOI: 10.16156/j.1004-7220.2025.05.027
Yaqian QI, Kaiyang SUN, Defeng ZHAO, Peng ZHANG, Xiangbo FAN. Simulation of Fluid Resistance at Different Drafting Positions in Marathon Swimming[J]. Journal of Medical Biomechanics, 2025 , 40 (5) : 1288 -1294 . DOI: 10.16156/j.1004-7220.2025.05.027
速度类竞技比赛中,跟随战术为取得优异比赛成绩发挥至关重要的作用[1-4]。对鱼类成群游动的研究发现,鱼群存在一定节能机制和最优排列方式[5]。马拉松游泳比赛(如公开水域等)也存在有多人成团游进的情况。跟游策略可以减少自身游进时的阻力[6],降低能量消耗[7]并保持冲刺的能力[8],但如何在游泳团中选择合适的游进位置以达到节能甚至有利于自身游进目的,还未开展深入研究。马拉松跑步和自行团队赛中,已经利用风洞实验和流体仿真模拟方法开展多人组队的实验及模拟计算,为运动员获得更多比赛优势提供依据。计算流体力学(computational fluid dynamics,CFD)方法被认为是计算游泳阻力简便可行的方法[9],但多针对单人游或跟游时的模拟分析[1,3-4,10],研究结果无法为多人共同游进时选择比赛策略提供依据。本文采用CFD分析方法,对多名运动员以不同组合方式游进时的阻力进行模拟计算,以期为比赛及训练中选择合适的游进位置及调整比赛策略提供有价值的理论参考。
通过Anthroscan三维人体扫描仪(Human Solutions公司,德国),对游进姿势的三维静态模型进行采集和整理,建立单个运动员模型。通过模拟比赛中单人游进、双人游进、3人组队游进等战术设想,取1~3个人体模型组成编队,通过调整个体模型之间的横向与纵向间距,建立不同游进编队组合的整体模型。模型建立后,在ANSYS Discovery Live(ANSYS公司,美国)中进行模拟计算[11]。ANSYS Discovery Live为基于图形处理器(graphics processing unit,GPU)计算的无网格实时模拟分析软件。计算中将1~3人模型组合的编队看成一个整体,设置流场范围时,人体模型距离流域底部约为3 m,且处于水面下0.1 m。对于流域左右的边界,取大于人体模型2倍体长的距离;对于流域前后的边界,取其在距离人体前后足够远的位置。为保证流动充分发展,设定压力出口边界条件为0。选择密度为998.2 kg/m3、黏性为1 mPa·s液体作为流体,根据实际比赛场地条件,设置水温为22 ℃。参数设置完成后,依据比赛时的游速,设置入口处水流速度的变化区间为1.0~2.0 m/s,取0.1 m/s递增的变化量,且入口速度在运行期间保持恒定。模拟计算单独个体的前进方向的阻力值及不同组合中整个多人编队模型的总阻力值。
所有编队方式中的单个模型采用某健将级男性运动员(年龄22岁,身高180 cm,体重75 kg)进行3D扫描后,以1∶1建立人体模型。人体模型姿势采用自由泳中交叉技术入水阶段的技术姿态。对于多人编队,采用完全相同的多个单人模型,并通过调整横向间距(H)和纵向间距(D)实现不同编队方式的组合[3]。模型中个体的组合方式分为5种:纵向编队I型(I1、I2、I3)及横向编队V、L、A、H型(见表1图1)。其中,I型编队方式中,前后运动员手、脚在水平面上的投影的纵向间距D=0 cm,但不相交。其他所有编队的横向投影距离为H=1/2模型身高(90 cm),纵向投影距离为D=100 cm。为更好体现多名运动员编队队形对阻力的影响效果,重点对不同速度条件下整个编队模型的总体及其中个体所受阻力的变化进行分析,当队形为对称型时,考虑自由泳运动的动作特征为左右上下肢交替运动,故将两侧对称位置的平均值作为该位置的模拟结果。
本文定义不同人数编队的“减阻效果”,计算公式如下:
当“减阻效果”计算值为负值时,认为具有减阻效果;为正值时,不具有减阻效果。
模拟仿真结果以(平均数±标准差)表示,采用SPSS 20.0软件进行统计学分析。采用可靠性分析对验证模拟计算结果的准确性进行验证。采用单因素方差分析对比不同游进位置个体所受流体阻力的差异,事后多重比较检验采用Tukey法,显著性水平设为P<0.05。
当计算结果与模型试验结果,趋势基本吻合,认为精度可接受[12]。由于缺乏多人模型的实验测试结果,本研究中将单个模型的模拟结果与游泳水槽中单人实验测试结果进行可靠性分析和趋势比较,以验证本研究结果可靠性。
对比身长1.8 m的人体玻璃钢人体模型自由浮态时的拖拽实验测试结果[13]曲线发现,模拟数据与实验数据的变化趋势一致(见图2)。
组内相关系数(intra-class correlation coefficient,ICC)分析表明,流体模拟结果与实验测试结果的ICC=0.997,显著性水平P<0.05(见表2)。模拟结果与实验测试结果的一致性较高,故本文采用的流体模拟仿真软件分析结果具有较高的准确性。
图3显示了入口速度为2.0 m/s,模拟运行时间大于5 s的实时仿真计算结果。在相同入口速度条件下,各个位置及整体编队周围的流场分布和压力分布都不同。图3(a)显示,H、A、L和V型编队中,相比于周围流速单个模型的前部出现了压力集中情况。流速模拟结果见图3(b),I3型编队的末端位置及A、L型编队中各位置的运动员周围出现流速加快情况。
由流速1.0~2.0 m/s变化范围内不同编队各位置的流体阻力模拟计算值统计结果可知,单独游进时的阻力为(23.0±9.8)N,当运动员处于I2、I3编队中时所有位置,以及A、H、L和V型中处于编队侧边(1和3号位置)的运动员受到的流体阻力都小于其单独游进时受到的流体阻力,但差异不具有显著性。A、H、L和V型中,中间(2号)位置的运动员受到的流体阻力显著大于其所在编队的两侧位置游进时受到的流体阻力(P<0.05)。A型编队的2号位置受到的流体阻力及L型编队2号位置受到的流体阻力都显著大于其他所有游进位置受到的阻力(P<0.05),见表3
以单独游进时的阻力为评价标准,计算得到不同流速条件下各游进位置的平均减阻效果,发现3人游进编队中,I3型编队中各个位置都有具有减阻效果,其中3号跟游位置的减阻效果为-57.39%,减阻效果最佳。L型编队中间跟游位置的阻力最大,减阻效果计算结果显示阻力增加了122.17%。A、H和V型编队中位于两侧的游进位置减阻效果较好,其中H型编队的两侧位置减阻效果优于A型和V型的减阻效果,为-30.87%。A、H、V和L型编队中位于中间的游进位置的减阻效果都较差,这些队形位于中间位置运动员受到的流体阻力相比单独游进时反而增加了。根据领游及跟游位置比较,I3型编队的领游位置的阻力最小,A型编队中领游位置阻力最大(见表4)。
各编队整体阻力模拟计算结果表明,两人游进时的整体减阻效果为-26.3%,3人以不同编队方式游进时,仅I3型队形具有整体减阻的效果,总阻力比3人单独游进时减少了55.21%。其他3人队形整体受到的阻力均大于3人单独游进时受到的阻力。3人编队中,V型编队整体的减阻效果最差,比3人单独游进所受阻力之和增加31.88%(见图4)。
人体在水中游进时受到流体动力学阻力主要来自由压差阻力和摩擦阻力,其中压差阻力包括由物体尾流和肢端后面的涡流引起的形状阻力和兴波阻力[14]。沿人体长轴方向不同身体部位的三维曲面的弧度不同,当流体流过人体表面时,表面形状和流速的变化会产生涡旋,涡旋会在人体表面形成低压区和高压区,导致流体流动的不稳定性增加[15]。漩涡随着流体的运动传递至跟游位置运动员流场范围内,使跟游位置运动员身体表面的压力重新分布,从而导致跟游位置运动员阻力发生变化。
多人编队游进时,领游者掀起的尾波会改变跟游者周围的流场,而导致其阻力发生变化。同时,跟游运动员引起的首波也会对领游运动员的尾波产生扰动,改变领游者尾部的压力分布,从而导致领游位置运动员的阻力发生变化。本文模拟结果显示,与周围压力相比,H和V型编队中处于前排运动员在游进过程中受到的前部压力增加,L和A型编队的领游运动员前部的压力大于跟游运动员。因此,这些位置的运动员在编队中游进时受到的流体阻力相较于单独游进时反而增加,整体编队也不具有减阻效果。I型编队中,跟游运动员受到领游运动员遮挡,其所受流体压力明显减少,具有较好的减阻效果。
压差阻力与游进速度有直接关系[15],速度越快,兴波阻力越大。低速节段波浪微弱,兴波阻力亦小,但随着速度提升,波浪幅度增大且波长缩短,兴波阻力也随之增加。领游位置运动员掀起的波浪随人体前进,可能会在领游运动员身后形成“低速区”,导致跟游位置运动员相对于来流的实际速度小于领游位置运动员,从而实现减速。由图3(a)可知,I型编队中,跟游运动员处于领游运动员的低速区内,其受到的流体阻力降低。在运动员身体两侧看到明显的“高速区”,H、A、L和V型编队中间位置的运动员处于两侧运动员形成的“高速区”内,导致其阻力相较于两侧游进位置运动员明显增加。Chatard等[3]实验表明,跟游者在距离领游者脚尖后0~50 cm位置受到的游泳阻力比单独游进时减少约20%,而距离领游者侧向100 cm距离时也可以使阻力显著降低6%~7%。本文结果中,正后方跟游带来的减阻效果与实验研究结果一致,但侧向跟游进时的部分研究结果与实验测试结果[3]存在差异,推测这是由于实际游泳实验时受心理、生理等多因素干扰,且实验条件受限制,仅凭由跟游产生的阻力变化不够显著。
多人游进时,运动员之间相对距离的变化会对相互间的水动力作用产生影响。考虑运动员游进时需保持舒适的相对位置以确保有足够空间完成四肢运动,本文将侧向距离设定为90 cm。虽然侧向游动时的减阻效果不如纵向跟随时的减阻效果明显,A型队形的模拟计算结果显示可达到-27.83%的减阻效果。L型队形中,两个侧向跟游位置的减阻效果不同,最后的跟游位置具有减阻效果,而中间跟游位置却不具有减阻效果。而H型队形呈现的侧向并排游进的模拟结果显示,两侧游进的位置也具有一定减阻效果。
根据已有的比赛成绩可知,10 km游泳比赛的全程平均速度为1.4 m/s,此时运动员游泳相对于水处于低流速运动状态,在这种低流速状态下,各种编队均具有一定减阻效果[16]。研究认为,运动员处于编队游泳中会比单独游进时能量消耗更低[17],而本文模拟计算结果显示,3人不同编队时,只有纵向编队(I型)能减少总体的阻力,而其他编队时只是处于特定位置的运动员才具有一定的减阻效果。本文认为是多个物体的排列方式导致其周围的涡流互相干扰,从而影响整体的阻力,而特定位置的减阻效果是受周围运动物体影响的综合结果。
竞技体育运动中“跟随”策略研究结果可以为教练员和运动员科学运动训练和比赛提供参考依据,应该有效利用跟游和同步运动带来的水动力优势[18],而过早地脱离比赛主队伍,往往会导致运动员因为体能过早消耗而失去最后突破的机会[19]。根据A、V和I3型编队的模拟结果,当多人成团游进时,单独游进的个体在前程应避免成为领游者,尽量选择合适位置(如I2或I3型编队的任意位置或两侧位置)跟游或与队友组成有效的减阻编队(如I3、I2型编队)共同游进,以有效减少游进时的阻力,为比赛后程的冲刺节省体能。当处于被对手跟随时,亦可参考A和L型编队形式,通过适当调整自身与对手的侧向间距,特别是L型编队,达到既可以在保持自身侧向领先优势同时减少自身游进阻力,也可增加对手游进时阻力的效果;甚至可适当调整位置,与对手形成H型编队,不仅有利于观察对手的状态,也可实现自身30%的减阻效果。当有队友同时游进时,可以利用L型队形产生的特殊减阻效果,形成侧向夹击的队形,不仅可增加对手阻力并减少自身阻力,也有利于随时留意对手的行动,领先的队友可在适当时机以领先优势进行冲刺。当并排游进时,处于两侧的运动员相对于个人游进阻力会减少。两侧跟游或并排游状态也可能使对手的心理产生一定的变化,甚至可以利用对手的心理,形成有利于自身的游进编队方式(如A、V、H型),不仅可以增加对手的阻力,增加其能量消耗,也可以节省自身的能量。
游进时保持适当的距离也很重要。在正后方跟游时,跟游位置运动员会受到领游位置运动员打腿动作的影响。虽然研究认为领先运动员的打腿动作对跟随运动员的被动阻力没有显著影响[4],但由于打腿会造成更多气泡和涡流,特别是在高速打腿冲刺情况下,产生的气泡、涡流及领游者的打腿动作,会对跟游运动员的视线产生影响,甚至反而增加了游泳时被动阻力,增加游进难度[20]。距离太近会受到领游运动员打腿动作的影响,距离太远则无法利用其尾流作用节省能量。关于有效的尾迹效应区,由于测试难度等原因,目前并未开展全面的实验研究。CFD计算认为,没有尾流影响的游泳距离应大于2.5 m[2-3],但本文未开展对于尾迹效应区的分析。
本文采用简化的流体模拟方法,对不同编队整体及个体的流体阻力进行分析。研究中虽参考实际运动状态设定模型姿态,但未能模拟完整运动周期的各典型动作;模拟时认为多名运动员完全同步运动且流速为恒定,而实际运动更具复杂多变。未来将考虑更复杂运动模型来完善数据,深入探索不同编队在实际比赛中的应用效果。此外,需进一步分析不同环境条件(如水温、复杂流)对多人编队减阻效果的影响,为不同比赛场景下的策略制定提供细致的模拟分析,为运动员及教练员制定更科学训练与比赛策略提供更全面的理论支撑。
纵向编队跟游的减阻效果优于横向排列的减阻效果,3人纵向排列的末端位置减阻效果最佳。综合考虑战术和减阻效果,应避免处于横向编队中间的位置游进。
  • 2024年国家体育总局创新项目(24KJCX009)
  • 上海市社会发展科技攻关项目(22dz1200100)
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doi: 10.16156/j.1004-7220.2025.05.027
  • 接收时间:2024-10-14
  • 首发时间:2026-03-27
  • 出版时间:2025-10-01
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  • 收稿日期:2024-10-14
  • 修回日期:2025-03-09
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2024年国家体育总局创新项目(24KJCX009)
上海市社会发展科技攻关项目(22dz1200100)
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    1.上海体育科学研究所(上海市反兴奋剂中心),上海 200030
    2.上海体育大学 竞技运动学院,上海 200438

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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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