Article(id=1244340205340176733, tenantId=1146029695717560320, journalId=1244295746212642849, issueId=1244340201636610993, articleNumber=null, orderNo=null, doi=10.11776/j.issn.1000-4939.2025.06.005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1719158400000, receivedDateStr=2024-06-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1774603423675, onlineDateStr=2026-03-27, pubDate=1765728000000, pubDateStr=2025-12-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774603423675, onlineIssueDateStr=2026-03-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774603423675, creator=13701087609, updateTime=1774603423675, updator=13701087609, issue=Issue{id=1244340201636610993, tenantId=1146029695717560320, journalId=1244295746212642849, year='2025', volume='42', issue='6', pageStart='1207', pageEnd='1446', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1774603422792, creator=13701087609, updateTime=1774603751062, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1244341578555306992, tenantId=1146029695717560320, journalId=1244295746212642849, issueId=1244340201636610993, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1244341578555306993, tenantId=1146029695717560320, journalId=1244295746212642849, issueId=1244340201636610993, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1254, endPage=1262, ext={EN=ArticleExt(id=1244340206061597030, articleId=1244340205340176733, tenantId=1146029695717560320, journalId=1244295746212642849, language=EN, title=Investigation and optimization design of resistance and heat reduction of aircraft based on Taguchi-gray correlation method, columnId=1244340205021409622, journalTitle=Chinese Journal of Applied Mechanics, columnName=Special Column on Aeronautics and Astronautics, runingTitle=null, highlight=null, articleAbstract=

Hypersonic aircraft face extremely high aerodynamic resistance and heating during flight, posing a threat to flight safety and stability. Taguchi-gray correlation method is utilized to study the impact of size on the resistance and heat reduction performance of hypersonic aircraft. An orthogonal test is conducted, wherein design factors such as spike length-diameter ratio, airway diameter ratio, pneumatic disk diameter ratio, and lateral jet angle are considered. The response targets comprise total flight resistance, peak pressure coefficient, and Stanton number. Test results are obtained through numerical simulation. The findings indicate that the flight resistance is most significantly affected by the length-diameter ratio of the spike,while the lateral jet angle has the least effect. In regard to the peak pressure coefficient and Stanton number,the size factors exhibit a similar rank of influence. Among these factors,the length-diameter ratio of the pneumatic disk exerts the most significant impact. Increasing the length-diameter ratio of the spike and the diameter ratio of the pneumatic disk can effectively improve overall resistance and heat reduction performance. However,it should be noted that as the size increases,the lifting efficiency gradually diminishes. In comparison to the optimal group of orthogonal design,the optimized configuration demonstrates an overall performance improvement of 4.6%,thus indicating a favorable optimization effect.

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高超声速飞行器在飞行过程中,面临着极高的气动阻力和加热作用,对飞行安全和稳定造成威胁。采用灰色田口法开展构型参数对高超声速飞行器减阻降热性能影响的研究,以减阻杆长径比、气道直径比、气动盘直径比、侧喷角为尺寸因子,飞行阻力、钝体峰值压力系数、斯坦顿数为响应目标进行正交试验,通过计算流体力学(computational fluid dynamics,CFD)数值计算获得响应结果。研究表明:飞行阻力受减阻杆长径比的影响最显著,受侧喷角的影响最小。对于钝体峰值压力系数和斯坦顿数,尺寸因子表现出相同的影响等级,两者受到气动盘直径比的影响最显著,其次是减阻杆长径比。增加减阻杆长径比和气动盘直径比均能提升飞行器的减阻降热综合性能,但提升效果随着尺寸的增大逐渐减弱。相比于正交设计的最优构型,采用灰色关联法优化出的最佳构型综合性能提升了4.6%。

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赵文胜,教授。E-mail:
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diagram of grey correlation degree, figureFileSmall=SkVbq0xj/Gv9I0HMRW91+w==, figureFileBig=Ug/QzunQ4nE0x725Mowr2Q==, tableContent=null), ArticleFig(id=1244340227418993646, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=CN, label=图7, caption=灰色关联度的因子效应图, figureFileSmall=SkVbq0xj/Gv9I0HMRW91+w==, figureFileBig=Ug/QzunQ4nE0x725Mowr2Q==, tableContent=null), ArticleFig(id=1244340227561599990, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=EN, label=Fig.8, caption=Comparison of calculation results between A4B3C2D4and A4B3C4D4, figureFileSmall=opWMiBk4jpM71Rp5uePYTQ==, figureFileBig=A/M34oxaxl7E0CbDYExg1A==, tableContent=null), ArticleFig(id=1244340227754536962, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=CN, label=图8, caption=A4B3C2D4与A4B3C4D4的计算结果对比, figureFileSmall=opWMiBk4jpM71Rp5uePYTQ==, figureFileBig=A/M34oxaxl7E0CbDYExg1A==, tableContent=null), ArticleFig(id=1244340227955863564, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=EN, label=Tab.1, caption=

Factor levels

, figureFileSmall=null, figureFileBig=null, tableContent=
编号因子水平1水平2水平3水平4
ALs/D0.51.01.52.0
BDa/D0.020.040.060.08
CDd/D0.150.250.350.45
Dβ/(°)4575105135
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因子水平

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编号因子水平1水平2水平3水平4
ALs/D0.51.01.52.0
BDa/D0.020.040.060.08
CDd/D0.150.250.350.45
Dβ/(°)4575105135
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Four factors and four levels orthogonal experimental results

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方案尺寸因子性能响应
ABCD/(°)F/NCpSt
10.50.020.154578.6971.0090.022
20.50.040.257563.8080.6450.014
30.50.060.3510558.7560.4600.010
40.50.080.4513562.5700.3860.009
51.00.020.2510543.1940.3890.010
61.00.040.1513553.1690.6390.016
71.00.060.454554.5670.2380.007
81.00.080.357544.6240.2750.008
91.50.020.3513543.3490.2530.008
101.50.040.4510552.1290.2010.007
111.50.060.157546.4050.5420.014
121.50.080.254539.5260.3440.009
132.00.020.457556.8520.2480.007
142.00.040.354544.0510.2630.007
152.00.060.2513533.3020.2560.008
162.00.080.1510541.9500.4780.013
), ArticleFig(id=1244340230254342187, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=CN, label=表2, caption=

四因子-四水平正交试验结果

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方案尺寸因子性能响应
ABCD/(°)F/NCpSt
10.50.020.154578.6971.0090.022
20.50.040.257563.8080.6450.014
30.50.060.3510558.7560.4600.010
40.50.080.4513562.5700.3860.009
51.00.020.2510543.1940.3890.010
61.00.040.1513553.1690.6390.016
71.00.060.454554.5670.2380.007
81.00.080.357544.6240.2750.008
91.50.020.3513543.3490.2530.008
101.50.040.4510552.1290.2010.007
111.50.060.157546.4050.5420.014
121.50.080.254539.5260.3440.009
132.00.020.457556.8520.2480.007
142.00.040.354544.0510.2630.007
152.00.060.2513533.3020.2560.008
162.00.080.1510541.9500.4780.013
), ArticleFig(id=1244340230371782706, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=EN, label=Tab.3, caption=

Mean response signal-to-noise ratio at different factor levels

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水平FCpSt
ABCDABCDABCD
1-36.33-34.62-34.55-34.374.698.043.898.3137.8539.5836.0639.93
2-33.74-34.46-32.8-34.388.948.308.288.1240.3939.9340.0139.89
3-33.09-33.48-33.5-33.7210.119.0910.378.8240.9940.5141.7540.25
4-32.72-33.33-35.03-33.4110.498.7911.698.9841.2840.4942.6940.44
极差3.611.292.230.975.801.057.800.863.430.926.630.54
排秩132423142314
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不同因子水平的响应信噪比均值

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水平FCpSt
ABCDABCDABCD
1-36.33-34.62-34.55-34.374.698.043.898.3137.8539.5836.0639.93
2-33.74-34.46-32.8-34.388.948.308.288.1240.3939.9340.0139.89
3-33.09-33.48-33.5-33.7210.119.0910.378.8240.9940.5141.7540.25
4-32.72-33.33-35.03-33.4110.498.7911.698.9841.2840.4942.6940.44
极差3.611.292.230.975.801.057.800.863.430.926.630.54
排秩132423142314
), ArticleFig(id=1244340230640218184, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=EN, label=Tab.4, caption=

Grey correlation degree of multiple response targets

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方案FCpStRGRG排序
10.333 3330.333 3330.333 3330.333 33316
20.426 6190.476 5630.515 3580.472 84715
30.471 3730.609 8650.659 3890.580 20912
40.436 7800.686 1450.764 9440.629 29010
50.696 4570.682 6520.673 4460.684 1859
60.533 2460.479 6410.453 4530.488 78014
70.516 2940.916 2060.943 7500.792 0836
80.667 1820.845 4600.874 8550.795 8325
90.693 1730.885 9010.873 8430.817 6393
100.546 6031.000 0001.000 0000.848 8682
110.634 0010.542 5050.501 6610.559 38913
120.784 8070.738 5290.737 3050.753 5478
130.490 7840.897 1200.906 3630.764 7567
140.678 6300.867 5950.885 1110.810 4454
151.000 0000.880 8370.850 2250.910 3541
160.724 1000.593 6930.537 3670.618 38711
), ArticleFig(id=1244340230782824526, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=CN, label=表4, caption=

多响应目标的灰色关联度

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方案FCpStRGRG排序
10.333 3330.333 3330.333 3330.333 33316
20.426 6190.476 5630.515 3580.472 84715
30.471 3730.609 8650.659 3890.580 20912
40.436 7800.686 1450.764 9440.629 29010
50.696 4570.682 6520.673 4460.684 1859
60.533 2460.479 6410.453 4530.488 78014
70.516 2940.916 2060.943 7500.792 0836
80.667 1820.845 4600.874 8550.795 8325
90.693 1730.885 9010.873 8430.817 6393
100.546 6031.000 0001.000 0000.848 8682
110.634 0010.542 5050.501 6610.559 38913
120.784 8070.738 5290.737 3050.753 5478
130.490 7840.897 1200.906 3630.764 7567
140.678 6300.867 5950.885 1110.810 4454
151.000 0000.880 8370.850 2250.910 3541
160.724 1000.593 6930.537 3670.618 38711
), ArticleFig(id=1244340230900265045, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=EN, label=Tab.5, caption=

Grey correlation degree of different factor levels

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水平ABCD
10.503 920.649 9780.456 4540.672 352
20.690 220.655 2350.705 2330.648 206
30.744 8610.710 5090.751 0310.682 912
40.775 9860.699 2640.758 7490.711 516
极差0.272 0660.060 5310.302 2960.063 31
等级2413
), ArticleFig(id=1244340231034482781, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=CN, label=表5, caption=

不同因子水平下的灰色关联度

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水平ABCD
10.503 920.649 9780.456 4540.672 352
20.690 220.655 2350.705 2330.648 206
30.744 8610.710 5090.751 0310.682 912
40.775 9860.699 2640.758 7490.711 516
极差0.272 0660.060 5310.302 2960.063 31
等级2413
), ArticleFig(id=1244340231160311913, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=EN, label=Tab.6, caption=

Response results of A4B3C2D4and A4B3C4D4

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构型RGRG
A4B3C4D40.952
A4B3C2D40.910
), ArticleFig(id=1244340231298723961, tenantId=1146029695717560320, journalId=1244295746212642849, articleId=1244340205340176733, language=CN, label=表6, caption=

表6 A4B3C2D4与A4B3C4D4的响应结果

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构型RGRG
A4B3C4D40.952
A4B3C2D40.910
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基于灰色田口法的飞行器减阻降热研究与优化设计
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覃振奇 1, 2, 3 , 罗翔宇 1, 2, 3 , 赵文胜 1, 2, 3
应用力学学报 | 航空航天工程专栏 2025,42(6): 1254-1262
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应用力学学报 | 航空航天工程专栏 2025, 42(6): 1254-1262
基于灰色田口法的飞行器减阻降热研究与优化设计
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覃振奇1, 2, 3, 罗翔宇1, 2, 3, 赵文胜1, 2, 3
作者信息
  • 1.水力机械过渡过程教育部重点实验室(武汉大学),430072 武汉
  • 2.流体机械与动力工程装备技术湖北省重点实验室(武汉大学),430072 武汉
  • 3.武汉大学动力与机械学院,430072 武汉

通讯作者:

赵文胜,教授。E-mail:
Investigation and optimization design of resistance and heat reduction of aircraft based on Taguchi-gray correlation method
Zhenqi QIN1, 2, 3, Xiangyu LUO1, 2, 3, Wensheng ZHAO1, 2, 3
Affiliations
  • 1.Key Laboratory of Hydraulic Machinery Transients(Wuhan University), Ministry of Education, 430072 Wuhan, China
  • 2.Hubei Provincial Key Laboratory of Fluid Machinery and Power Engineering Equipment Technology (Wuhan University), Ministry of Education, 430072 Wuhan, China
  • 3.School of Power and Mechanical Engineering, Wuhan University, 430072 Wuhan, China
出版时间: 2025-12-15 doi: 10.11776/j.issn.1000-4939.2025.06.005
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高超声速飞行器在飞行过程中,面临着极高的气动阻力和加热作用,对飞行安全和稳定造成威胁。采用灰色田口法开展构型参数对高超声速飞行器减阻降热性能影响的研究,以减阻杆长径比、气道直径比、气动盘直径比、侧喷角为尺寸因子,飞行阻力、钝体峰值压力系数、斯坦顿数为响应目标进行正交试验,通过计算流体力学(computational fluid dynamics,CFD)数值计算获得响应结果。研究表明:飞行阻力受减阻杆长径比的影响最显著,受侧喷角的影响最小。对于钝体峰值压力系数和斯坦顿数,尺寸因子表现出相同的影响等级,两者受到气动盘直径比的影响最显著,其次是减阻杆长径比。增加减阻杆长径比和气动盘直径比均能提升飞行器的减阻降热综合性能,但提升效果随着尺寸的增大逐渐减弱。相比于正交设计的最优构型,采用灰色关联法优化出的最佳构型综合性能提升了4.6%。

数值模拟  /  田口方法  /  灰色关联  /  高超声速飞行器  /  减阻降热

Hypersonic aircraft face extremely high aerodynamic resistance and heating during flight, posing a threat to flight safety and stability. Taguchi-gray correlation method is utilized to study the impact of size on the resistance and heat reduction performance of hypersonic aircraft. An orthogonal test is conducted, wherein design factors such as spike length-diameter ratio, airway diameter ratio, pneumatic disk diameter ratio, and lateral jet angle are considered. The response targets comprise total flight resistance, peak pressure coefficient, and Stanton number. Test results are obtained through numerical simulation. The findings indicate that the flight resistance is most significantly affected by the length-diameter ratio of the spike,while the lateral jet angle has the least effect. In regard to the peak pressure coefficient and Stanton number,the size factors exhibit a similar rank of influence. Among these factors,the length-diameter ratio of the pneumatic disk exerts the most significant impact. Increasing the length-diameter ratio of the spike and the diameter ratio of the pneumatic disk can effectively improve overall resistance and heat reduction performance. However,it should be noted that as the size increases,the lifting efficiency gradually diminishes. In comparison to the optimal group of orthogonal design,the optimized configuration demonstrates an overall performance improvement of 4.6%,thus indicating a favorable optimization effect.

numerical simulation  /  Taguchi method  /  gray correlation  /  hypersonic aircraft  /  reduce drag and heat
覃振奇, 罗翔宇, 赵文胜. 基于灰色田口法的飞行器减阻降热研究与优化设计. 应用力学学报, 2025 , 42 (6) : 1254 -1262 . DOI: 10.11776/j.issn.1000-4939.2025.06.005
Zhenqi QIN, Xiangyu LUO, Wensheng ZHAO. Investigation and optimization design of resistance and heat reduction of aircraft based on Taguchi-gray correlation method[J]. Chinese Journal of Applied Mechanics, 2025 , 42 (6) : 1254 -1262 . DOI: 10.11776/j.issn.1000-4939.2025.06.005
高超声速飞行器[1]以速度快、突防能力强等优势被世界各国重视,具有重要的军事战略意义和广泛的民用前景[2]。由于可压缩流的高速撞击,飞行器前进方向会产生主激波、分离激波、再附激波等系列气动现象,给飞行器壁面带来极高的压力[3]和加热[4]效应,严重威胁飞行安全。因此,寻求有效的减阻和降热系统一直是高超声速飞行器研究的重要课题[5-7]。目前已经发展出多种减阻降热方案,如高温耐热材料[8]、能量沉积[9-10]、发汗冷却[11]、减阻杆[12]、射流[13]以及它们的组合技术[14]等。
减阻杆通过将激波推离结构壁面来实现阻力和热量减少,结构相对简单。ALEXANDER[15]于1947年首次提出用于高超声速飞行器的减阻杆技术,随后,CRAWFORD[16]在马赫数6.8的风洞实验中研究了减阻杆长度和来流雷诺数对减阻降热性能影响,其实验数据常常被用来验证数值方法的精确性。GUO等[17]对减阻杆的气动热力学行为进行了时变流热耦合数值模拟,研究发现增加减阻杆长度不仅能有效地降低热流密度峰值,也会降低钝体头部表面以及内部结构的温升速度。GERDROODBARY等[18]对不同减阻杆头部构型的减阻降热特性进行了三维数值研究,研究表明安装气动盘能增强减阻效果,但减阻杆长度过大会降低降热效果。KHARATI-KOOPAEE等[19]用数值方法研究了气动盘尺寸对减阻和气动加热的影响,得到了低阻气动加热的最佳气动盘尺寸,与平面钝体模型相比,阻力和热流分别减少了62%和35%。
射流作为一种虚拟减阻杆技术,通过注入高压工质的方式,改变原有恶劣的波系结构,以达到减阻降热的效果。许阳[20]把减阻杆、气动盘、逆向射流相结合,研究结构尺寸和射流参数对流场的影响,研究发现增加射流总压比能显著降低钝体壁面热流。冀晨等[21]采用三维可压缩N-S方程和k-ω SST湍流模型,对钝化前缘多孔逆向射流进行参数化研究,结果表明多孔逆向射流在减阻和降热方面均能起到良好的效果。在单射流模式的基础上,ZHU等[22]将逆向射流和侧向射流组合,采用共轭传热法求解结构的热响应,研究发现,组合构型具有更好的减阻和降热效果,引入侧向射流还可以有效地减小由反向射流引起的负推力。考虑到实现射流需要复杂的供气系统,张帅等[23]提出一种减阻杆开槽进气、中部侧向排气的构型,实现了无源侧向射流的效果,分析了槽道收敛半角和侧向排气孔位置对减阻降热的影响。
针对高超声速飞行器的研究,多数集中于对结构设计参数的单变量分析,无法兼顾多个参数变化对减阻降热性能的综合影响。田口正交试验设计[24]通过最少的试验次数来系统地量化研究多个因素对某个响应变量的影响,可帮助识别主要影响因素和优化因素设置。而灰色关联法[25]是一种基于灰色系统理论的分析和决策方法,通过量化变量之间的关联度,找出各个因素对目标变量的贡献程度,从而进行综合评价和优化。灰色田口方法综合了田口方法对参数设计的优化和灰色关联法对因素关联度的评估,以实现更准确的分析和决策,广泛应用在社会科学和自然科学的多个领域[26-29]
本研究采用数值仿真和灰色田口方法,对减阻降热的影响因素进行了全面分析,并优化出具有最佳性能的构型参数,为高超音速飞行器的减阻降热设计提供研究思路。
基于减阻杆-射流组合的减阻降热方案,研究一种通过减阻杆内部开设气道以实现无源射流的构型[23],气道构型的三维示意图如图1所示,主体部分由钝体、减阻杆、气动盘构成。飞行器头部采用半球形钝体[30]代替,减阻杆一端安装在钝体的鼻锥上,另一端安装有一个开口的气动盘,高超声速流从气动盘的收敛开口段流入,经过减阻杆内部气道的引导后从侧喷口射出,发挥无源侧射流的作用。
假设侧向喷口间的距离无限小,忽略各喷口射流之间的相对作用,并且自由来流攻角为0°,因此本研究的数值计算采用二维轴对称模型,如图2所示。
本研究讨论减阻杆长径比Ls/D、气道直径比Da/D、气动盘直径比Dd/D、侧喷口角β对高超声速飞行器减阻降热性能的影响,其他几何尺寸相同:钝体直径D=60 mm;减阻杆直径Ds=6 mm;气动盘收敛半角α=60°;气道侧喷口始终位于减阻杆中部,La/Ls=0.5。
数值计算采用二维轴对称的雷诺平均Navier-Stokes方程与剪切应力传输k-ω SST湍流模型,该组合被验证在预测高超音速流动分离现象和热特性方面具有优异的性能[31],其方程为
连续性方程
动量方程
能量方程
k-ω SST方程
式中:k表示湍动能;ω表示湍动耗散率;t表示时间;ρ表示密度;U表示速度;f为单位质量流体的质量力;τ为黏性应力;Et为单位体积的总能;T为温度;λEff为有效热传导系数;参数σkσωMN根据混合函数φ=F1φ1+(1-F1φ2计算得到;F1为混合函数因子。
采用无量纲的压力系数Cp和斯坦顿数St作为飞行器钝体的减阻和热防护性能指标,CpSt定义如下。
式中:Ps为壁面静压;Taw为绝热壁温;Tw为壁面温度;Pρvcp分别代表自由来流的压力、密度、速度和定压比热容。qw为壁面热流密度,且
式中:λ为流体的导热系数;T为壁面附近的流体分布;n为边界的法向单位矢量。
采用基于有限体积法的流体模拟软件Fluent进行数值计算。自由来流入口设置为压力远场,来流参数基于海拔25 km的高空条件(马赫数Ma=5,静压Ps=2 549 Pa,静温Ts=221.55 K);采用无滑移壁面边界条件,壁面温度Tw=295 K。
自由来流的介质为可压缩空气,其黏度采用Sutherland公式进行拟合。使用基于密度基的双精度隐式求解器,通量使用AUSM格式计算,二阶迎风格式用于空间离散化,该设置在计算高速飞行器减阻杆槽道构型的减阻降热性能具有良好效果[23]。为了保证计算收敛性和效率,在稳态计算的前5 000步,库朗数固定设定为0.2,随后,库朗数随着计算步长的增加从0.2缓慢增加到2,直到所有残差小于0.001,且进出口流量差小于1×10-5kg/s时,则认为计算收敛完成。
对计算域采用O型网格划分方法,生成的网格如图3(a)所示。对近壁面网格做加密处理,壁面第一层网格厚度设定为0.01 mm,网格厚度增长率为1.1,满足k-ω SST湍流模型对y+值小于1的需求。
通过调整网格单元的最大尺寸(δmax=1、0.7、0.4、0.2 mm),对应生成4种网格单元总数(105 670,256 975,335 612,402 011),计算结果如图3(b)所示,可以看出,第3种数量的网格保证了计算效率的同时能满足计算精度需要,故在剩余的计算中采用该种网格划分方法,调整网格单元最大尺寸为0.4 mm。
图4展示了数值计算与NARAYANA等[32]的试验结果对比。在图4(a)中,数值计算的密度云图和试验纹影图像非常接近,数值计算准确捕捉到了弓形激波、剪切层、再附激波等特征。图4(b)中,两者的热流均呈现出先增大后减小的趋势,数值计算的峰值热流误差为7.1%,由此可见,本研究提出的数值方法可以较为准确地模拟和预测高超声速流绕流减阻杆的空气动力学行为。
本研究讨论结构参数对高超声速飞行器减阻降热性能的影响,选取减阻杆长径比Ls/D、气道直径比Da/D、气动盘直径比Dd/D、侧喷口角β为尺寸因子,响应目标设定为飞行总阻力F、钝体峰值压力系数Cp和钝体峰值斯坦顿数St。其中,侧喷口角β过小或过大时,将阻碍侧向射流的形成,各因子水平等间距设置(表1)。数值计算采用的构型尺寸通过正交试验设计方法确定,表2显示了四因子四水平的正交试验设计尺寸和性能响应的数值计算结果。
数值计算的马赫数云图如图5所示。
图5可知,高超声速来流受到压缩阻碍作用后,距气动盘上游一定的距离会形成弓形激波,一部分来流绕流到气动盘后侧拐角处发生流动分离现象,一部分进入气道并逐渐加速至超声速后从侧喷口喷出,与减阻杆表面的剪切层发生相互冲击作用。钝体肩部面临着上游来流强烈的冲击,形成再附冲击。随着构型尺寸的不同,高超声速流场的弓形激波、分离剪切层、再附激波等流场特征显示出较大的差异,说明结构尺寸会对飞行器的减阻降热性能产生显著的影响。
为了得到尺寸因子与性能响应的关系,对正交计算结果进行田口信噪比分析。高超声速飞行的总阻力F、钝体壁面的峰值压力系数Cp、峰值斯坦顿数St越小越好,故使用最小特性的信噪比,其定义为
式中:RS/Nk)为第k组试验结果的信噪比;yk)为第k组试验所对应的响应结果;n表示每组试验次数,本研究取n=1。不同水平下尺寸因子对应的响应目标信噪比平均值计算结果如表3所示。通过极差分析可判断单一尺寸因子对单一响应目标的影响程度,由极差结果得出,对飞行阻力影响最大的因子是减阻杆长径比;而对钝体峰值压力系数和斯坦顿数,各因子对其影响的排秩序列相同,影响最大的因子是气动盘直径比,其次是减阻杆长径比,气道直径比和侧喷角对其的影响相对较小。
图6为各个响应目标平均信噪比的效应图,信噪比越大代表性能越好。对于飞行总阻力F,最佳尺寸构型是A4B4C2D4,即Ls/D=2.0、Da/D=0.08、Dd/D=0.25、β=135°。对于CpSt,两者取决于钝体再附冲击的强度,所以因子效应图的变化趋势相近,最佳构型为A4B3C4D4,即Ls/D=2.0、Da/D=0.06、Dd/D=0.45、β=135°。
田口信噪比分析能对单一响应目标做优化设计,不同响应目标的最优因子组合之间存在矛盾。灰色关联系数可以反映实际值与期望值之间的关联程度,灰色关联系数越大,说明越接近优化目标。为了获得最佳的减阻和热防护综合性能,通过灰色关联分析将复杂的多目标优化问题转化为仅对灰色关联度的单目标优化,采用灰色关联度作为减阻降热综合性能的衡量指标。对性能响应结果进行灰色关联分析,步骤如下。
高超声速飞行器的飞行总阻力F、钝体峰值压力系数Cp、钝体峰值斯坦顿数St越小,说明减阻降热性能越好,对性能响应计算结果进行望小特征的归一化处理,公式如下
式中:y′k)为第k组试验响应结果的归一化值,ymaxymin分别为响应结果在所有试验中的最大值和最小值。
归一化响应结果与期望值的灰色关联系数可由下式求出
式中:ξk)为响应结果在第k组试验的灰色关联系数;ΔminΔmax表示所有试验中绝对差Δ的最小值和最大值;θ表示分辨系数,取0.5,以赋予响应结果相同的权重;Δk)为期望值与归一化响应结果在第k组试验的绝对差,期望值y′(0)取1。
式(13)可求出各响应间灰色关联系数的平均值,即多响应目标的灰色关联度,灰色关联度越大,意味着优化目标越接近理想值。
式中:RGRGk)为第k组试验的灰色关联度;m为响应目标的种类数,m=3。
根据以上步骤,计算出多响应目标的灰色关联度如表4所示,第15组试验(A4B3C2D4)对应着最佳的减阻降热综合性能。
不同因子水平下灰色关联度的计算结果如表5所示,通过极差分析可以得出结构参数对减阻降热综合性能的影响,气动盘直径比的影响最大,其次是减阻杆长径比和侧喷口角度,影响最小的是气道直径比。
灰色关联度随因子水平的变化效应如图7所示,由图可知,增加减阻杆长径比和气动盘直径比均能提升减阻降热综合性能,但提升效果会随着尺寸的增加逐渐减弱。通过灰色关联度分析,A4B3C4D4为多目标优化的最佳构型,即当尺寸设置为Ls/D=2、Da/D=0.06、Dd/D=0.45、β=135°,对应着最佳的减阻降热综合性能。
灰色关联分析得出的最佳组合并不在正交试验中,故需要重新计算予以验证。正交实验最优组合A4B3C2D4(方案15)与灰色关联分析给出的最佳组合A4B3C4D4的计算结果对比如图8所示,由马赫数云图可知,A4B3C4D4相比于A4B3C2D4拥有更大直径的气动盘,因此气动盘前方的弓形激波张角更大,减阻杆附近的回流区范围更大,从气动盘拐角分离出的剪切层不会附着在减阻杆上。从压力云图可观察到,A4B3C4D4钝体肩部的再附激波角度更大,激波强度更小,钝体壁面的压力总体上都要小于A4B3C2D4构型。
两种构型响应目标的计算结果如表6所示,灰色关联分析得出的最佳组合A4B3C2D4相比于A4B3C2D4,减阻降热综合性能提升了4.6%。
此外,为了验证灰色关联法进行多目标优化的准确性,根据式(14),对最佳输入参数A4B3C4D4的灰色关联度进行预测。
式中:为灰色关联度的预测值;为各因素在最优水平下灰色关联度的均值;为所有试验的灰色关联度均值。
可计算出A4B3C4D4对应的灰色关联度预测值,与数值计算的试验值0.952相比,误差仅为3.26%,表明利用田口正交设计和灰色关联法对高超声速飞行器的减阻降热性能进行多目标优化具有良好的效果。
本研究采用田口信噪比和灰色关联分析研究了尺寸因子对高超声速飞行器减阻降热性能响应的影响,通过CFD数值计算获得响应数据,得出以下主要结论。
1)减阻杆长径比对飞行阻力影响最大,其次是气动盘直径比。对于钝体峰值压力系数和斯坦顿数,两者受因子变化的影响排秩相同,气动盘直径比>减阻杆长径比>气道直径比>侧喷口角度。
2)减阻降热综合性能达到最优的设计尺寸为:减阻杆长径比为2,气道直径比为0.06,气动盘直径比为0.45,侧喷口角度为135°。相比于正交设计的最佳构型,多目标优化的最佳构型综合性能提升了4.6%。
3)本研究揭示了结构参数对高超声速飞行器减阻降热性能的影响规律,并通过田口信噪比和灰色关联分析方法确定了最佳构型,研究结果可为高超声速飞行器的设计和优化提供参考。
  • 国家自然科学基金资助项目(52279089)
  • 湖北省中央引导地方科技发展专项(2024CSA086)
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2025年第42卷第6期
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doi: 10.11776/j.issn.1000-4939.2025.06.005
  • 接收时间:2024-06-24
  • 首发时间:2026-03-27
  • 出版时间:2025-12-15
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  • 收稿日期:2024-06-24
基金
国家自然科学基金资助项目(52279089)
湖北省中央引导地方科技发展专项(2024CSA086)
作者信息
    1.水力机械过渡过程教育部重点实验室(武汉大学),430072 武汉
    2.流体机械与动力工程装备技术湖北省重点实验室(武汉大学),430072 武汉
    3.武汉大学动力与机械学院,430072 武汉

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2种不同金属材料的力学参数

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total species (%)

Genus
种数
Number of
species
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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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