Article(id=1241784311289020629, tenantId=1146029695717560320, journalId=1241715181215068175, issueId=1241784304989175988, articleNumber=null, orderNo=null, doi=10.6052/1672-6553-2025-040, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1727712000000, receivedDateStr=2024-10-01, revisedDate=1745337600000, revisedDateStr=2025-04-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1773994051048, onlineDateStr=2026-03-20, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773994051048, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773994051048, creator=13701087609, updateTime=1773994051048, updator=13701087609, issue=Issue{id=1241784304989175988, tenantId=1146029695717560320, journalId=1241715181215068175, year='2025', volume='23', issue='10', pageStart='1', pageEnd='96', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773994049546, creator=13701087609, updateTime=1773994239413, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241785101412012589, tenantId=1146029695717560320, journalId=1241715181215068175, issueId=1241784304989175988, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241785101412012590, tenantId=1146029695717560320, journalId=1241715181215068175, issueId=1241784304989175988, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=9, ext={EN=ArticleExt(id=1241784311708451035, articleId=1241784311289020629, tenantId=1146029695717560320, journalId=1241715181215068175, language=EN, title=Applications and Developemnt Trends of Structural Dynamics Modeling Techniques in Launch Vehicle Engineering, columnId=1241784311620370649, journalTitle=Journal of Dynamics and Control, columnName=Review Articles, runingTitle=null, highlight=null, articleAbstract=

Structural dynamics modeling is a crucial technological task in the development of launch vehicles, load design, mechanical environment prediction, control system design, and POGO vibration suppression. Based on the evolutionary process of launch vehicles technologies, this paper reviews the development and application of structural dynamics analysis from four modelling approaches: the beam model, beam-shell hybrid model, the 3D model based on direct modeling and the 3D model based on model assembly. Additionally, this paper also covers the evolution of structural dynamic modeling technique and modal test in launch vehicle areas. Building on advances in numerical computation and the iterative refinement of launch vehicle methodologies, this paper further examines several emerging trends in the field several aspects, including efficient liquid-solid coupling computational technology, multidisciplinary dynamics analysis technology, dynamics analysis twin technology, and launch vehicle dynamics analysis technology based on artificial intelligence.

, correspAuthors=Yuming Mao, 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=Wei Zheng, Yuming Mao, Dan Sun, Chunyan Zhu, Zhongping Shu), CN=ArticleExt(id=1241784313440698628, articleId=1241784311289020629, tenantId=1146029695717560320, journalId=1241715181215068175, language=CN, title=结构动力学建模技术在火箭工程中的应用及发展趋势, columnId=1241784311888806113, journalTitle=动力学与控制学报, columnName=综述论文, runingTitle=null, highlight=null, articleAbstract=

结构动力学建模是运载火箭研制过程中载荷设计、力学环境预示、姿态稳定控制、POGO振动抑制的关键技术工作.综述分析了火箭工程研制需求牵引下,结构动力学建模技术随着数字计算技术的提升,经历了集中质量梁模型、梁壳混合模型、三维精细化建模的发展历程,以及实际工程应用和模态试验的开展情况.结合数值计算技术发展,以及运载火箭迭代发展路径,从液固耦合高效计算技术、多学科动力学分析技术、动力学分析孪生技术和基于人工智能的运载火箭动力学分析技术等方面分析了运载火箭总体设计发展和工程应用的趋势.

, correspAuthors=毛玉明, authorNote=null, correspAuthorsNote=
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结构动力学建模技术在火箭工程中的应用及发展趋势
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郑威 , 毛玉明 , 孙丹 , 朱春艳 , 舒忠平
动力学与控制学报 | 综述论文 2025,23(10): 1-9
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动力学与控制学报 | 综述论文 2025, 23(10): 1-9
结构动力学建模技术在火箭工程中的应用及发展趋势
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郑威, 毛玉明 , 孙丹, 朱春艳, 舒忠平
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  • 上海宇航系统工程研究所,上海 201109

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Applications and Developemnt Trends of Structural Dynamics Modeling Techniques in Launch Vehicle Engineering
Wei Zheng, Yuming Mao , Dan Sun, Chunyan Zhu, Zhongping Shu
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  • Aerospace System Engineering Shanghai, Shanghai 201109, China
doi: 10.6052/1672-6553-2025-040
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结构动力学建模是运载火箭研制过程中载荷设计、力学环境预示、姿态稳定控制、POGO振动抑制的关键技术工作.综述分析了火箭工程研制需求牵引下,结构动力学建模技术随着数字计算技术的提升,经历了集中质量梁模型、梁壳混合模型、三维精细化建模的发展历程,以及实际工程应用和模态试验的开展情况.结合数值计算技术发展,以及运载火箭迭代发展路径,从液固耦合高效计算技术、多学科动力学分析技术、动力学分析孪生技术和基于人工智能的运载火箭动力学分析技术等方面分析了运载火箭总体设计发展和工程应用的趋势.

运载火箭  /  结构动力学  /  模态试验  /  动力学建模  /  有限元法

Structural dynamics modeling is a crucial technological task in the development of launch vehicles, load design, mechanical environment prediction, control system design, and POGO vibration suppression. Based on the evolutionary process of launch vehicles technologies, this paper reviews the development and application of structural dynamics analysis from four modelling approaches: the beam model, beam-shell hybrid model, the 3D model based on direct modeling and the 3D model based on model assembly. Additionally, this paper also covers the evolution of structural dynamic modeling technique and modal test in launch vehicle areas. Building on advances in numerical computation and the iterative refinement of launch vehicle methodologies, this paper further examines several emerging trends in the field several aspects, including efficient liquid-solid coupling computational technology, multidisciplinary dynamics analysis technology, dynamics analysis twin technology, and launch vehicle dynamics analysis technology based on artificial intelligence.

launch vehicles  /  structural dynamics  /  modal testing  /  dynamics modeling  /  finite element method
郑威, 毛玉明, 孙丹, 朱春艳, 舒忠平. 结构动力学建模技术在火箭工程中的应用及发展趋势. 动力学与控制学报, 2025 , 23 (10) : 1 -9 . DOI: 10.6052/1672-6553-2025-040
Wei Zheng, Yuming Mao, Dan Sun, Chunyan Zhu, Zhongping Shu. Applications and Developemnt Trends of Structural Dynamics Modeling Techniques in Launch Vehicle Engineering[J]. Journal of Dynamics and Control, 2025 , 23 (10) : 1 -9 . DOI: 10.6052/1672-6553-2025-040
运载火箭是一项复杂的系统工程,在系统总体设计过程中,结构动力学与载荷环境、姿态稳定控制系统、纵向耦合振动(POGO)稳定性等各专业交叉耦合紧密[1],共同影响运载火箭技术指标和可靠性.数十年来,在运载火箭工程发展需求的牵引下,结构动力学建模技术逐渐得到更深的应用[2],时至今日已在运载火箭总体设计中拥有着不可或缺的地位[3].运载火箭发展早期,箭体规模较小,在全箭整体模态预示、舱段截面载荷分析、舱段级动力学响应传递分析等需求牵引下,依靠全箭模态试验结果修正后的梁模型完成结构动力学设计,进而应用于载荷环境设计和稳定控制系统设计[4].运载火箭应用发展阶段,在载人航天和深空探测等任务的牵引下,大型、重型运载火箭的研制受到大力推进.大型、重型运载火箭频率低、模态密集的特点,对结构动力学分析的精度提出了精确预示局部位置模态特性、POGO特性、局部结构载荷环境的要求.同时,得益于计算软硬件技术的发展,采用更为精细的梁壳混合模型进行结构动力学设计,开展全箭模态试验或缩比模型模态试验完成结构动力学模型验证[5].运载火箭成熟发展阶段,为提高系统可靠性,增大国际发射市场竞争力,各运载火箭研制方将三维模型、流固耦合、声固耦合等方法应用于结构动力学设计,进一步提升仿真精度[6].近年来,运载火箭进入商业化发展阶段,为缩短研制周期,降低研制成本,结合部段级模态试验、模型修正、动态子结构方法、模型缩聚和不确定性量化等方法构建数字火箭,完成多层级多专业仿真分析[7].
本文结合运载火箭发展工程需求,从集中质量梁模型、梁壳混合模型、基于直接建模的三维模型和基于模型组装的三维模型四个方面综述了结构动力学分析技术在国内外运载火箭领域的应用;结合数值计算软硬件技术发展以及运载火箭工程发展需求,分析了面向数字火箭工程的结构动力学分析技术发展趋势.
随着计算机科学、数值计算方法和试验方法等领域的发展,在航天运输装备发展需求的驱动下,结构动力学建模技术在运载火箭领域的应用不断深入.全箭动力学模型实现了从梁模型到梁壳混合模型再到三维模型的演变,液固耦合分析精度不断提升,动力学模型验证技术也从全箭模态试验到缩比模态试验再到部段级模态试验的精简.运载火箭研制周期不断缩短,研制成本不断降低,运载火箭的商业价值逐步体现.
二十世纪六七十年代,有限元法在连续介质力学领域的应用逐渐受到重视,各国工程师开始利用有限元模型解决航天工程问题.这一时期的运载火箭以串联形式为主,结构形式简单,结构动力学分析的任务主要集中在全箭整体模态预示、舱段截面载荷分析、舱段级动力学响应传递分析.结合当时计算机技术和数值计算方法的发展水平,选择梁模型模拟箭体结构,将液体简化为集中质量开展结构动力学分析,进而完成载荷环境设计、姿态稳定控制系统设计、POGO稳定性设计.
NASA的土星-Ⅰ、土星-Ⅴ火箭;欧空局的阿里安-Ⅳ、阿里安-Ⅴ火箭;我国的长征二号E、长征二号D、长征四号B、长征四号C等早期“长征”系列运载火箭均采用了集中质量梁模型进行结构动力学分析[3].随着计算机技术的快速发展,时至今日计算能力已经不再是仿真分析的瓶颈,然而,梁模型凭借着计算效率高的优势在运载火箭方案论证阶段仍然有着广泛的应用.
梁模型在局部振型斜率预示、液固耦合效应体现和舱段连接不确定性体现方面存在不足,因此,早期运载火箭均通过开展全箭模态试验对模型进行验证和修正[8].
在载人航天和深空探测等大型载荷任务牵引下,各国开始发展大型、重型运载火箭.大型、重型运载火箭频率低、模态密集的特点,对结构动力学分析精度提出了更高的要求.为实现对局部位置模态特性、POGO特性、局部结构载荷环境的精确预示,对部分舱段建立三维模型,并开展部段级模态试验进行验证和修正.最终获取更为精细的全箭梁壳混合模型,同时将液体简化为集中质量,应用于结构动力学分析,进而开展载荷环境设计、姿态稳定控制系统设计、POGO稳定性设计.
NASA的土星-Ⅰ[9]、土星-Ⅴ[10-12]除了建立梁模型外,还建立了梁壳混合模型用于结构动力学分析.我国的长征二号F、长征五号、长征六号、长征七号火箭均采用了梁壳混合模型开展结构动力学分析,全箭动特性预示精度,特别是振型斜率预示精度得到有效提升.
梁壳混合模型仍然难以体现液固耦合效应和舱段连接不确定性,因此,这一时期各国工程师综合考虑箭体结构特性、试验条件和试验成本,有选择地开展了全箭模态试验或缩比模型模态试验进行结构动力学模型验证.“十五”“十一五”期间我国在新一代运载火箭长征五号、长征六号、长征七号的研制过程中,均开展了大量全箭模态试验[1].
随着国际发射市场规模的扩大,航天发射服务竞争日趋激烈,各国为增大自身在国际发射市场的竞争力,对运载火箭可靠性提出更高要求.将全箭三维模型应用于结构动力学设计,同时采用流固耦合、声固耦合等方法考虑液固耦合效应,并结合缩比模态试验和全箭模态试验完成模型验证.系统结构动力学特性预示精度得到进一步提升,推动载荷环境、姿态稳定控制系统、POGO稳定性等专业实现精细化设计.
NASA针对航天飞机建立了三维模型,并结合缩比模态试验和全箭模态试验完成全箭结构动力学模型验证[13,14].
我国首款固体捆绑火箭长征六号A由液氧煤油芯级和四个固体助推器组成,在研制阶段建立了全箭三维精细化有限元模型,同时将全箭划分为助推器、一子级、二子级和星罩组合体等若干个部段,并开展一系列部段级模态试验,基于试验数据完成模型修正,最终经全箭模态试验,完成全箭模型和虚质量法应用的验证.全箭三维模型的应用有效提升了结构动力学专业仿真能力,为后续系列型号研制奠定了基础[15].
此外,我国新一代中型运载火箭长征十二号在研制中也建立了全箭三维模型,并根据部段级和全箭模态试验完成模型验证和修正.
全三维模型和流固耦合、声固耦合等方法应用提升仿真精度的同时也增加了计算时长.为提升运载火箭设计效率,各国工程师针对高效计算方法展开研究.
近年来,空间站任务、低轨互联网星座任务快速发展,航天发射任务呈现出航班化、商业化的趋势.运载火箭也逐渐开始注重高效性、通用性和更低的研制成本.结合部段级模态试验、模型修正、动态子结构方法、模型缩聚和不确定性量化等方法构建数字火箭,完成多层级多专业仿真分析,并提高计算效率.
NASA的战神-Ⅰ、战神-Ⅴ火箭[16-20];欧空局的阿里安-Ⅳ、阿里安-Ⅴ火箭[21,22];日本的H-2火箭[23,24]均采用了基于三维模型和模型组装的运载火箭结构动力学分析技术.
太空发射系统(space launch system,SLS)是NASA基于航天飞机部分技术研制的一款超重型运载火箭,运载能力与土星五号相近,被称为史上最强运载火箭系统[25].在SLS研制过程中,NASA没有开展全箭自由状态的模态试验,而是主要采用仿真分析的手段进行动力学设计.SLS运载火箭可以被划分为二子级级间段组合体、芯一子级、左助推器、右助推器四个模块.由于SLS运载火箭继承了航天飞机的部分技术,部分舱段(部段)存在模态测试数据,同时针对新研舱段(部段)开展舱段(部段)级模态试验,并根据试验数据修正模型,最终组装得到全箭模型[26].
为提高缺乏全箭模态试验情况下系统可靠性,NASA使用结合参数和非参数不确定性的混合参数变化方法(HPV)对SLS全箭模型开展了不确定性量化(uncertainty quantification,UQ)[26].
虽然没有开展全箭自由状态的模态试验,但是为了实现对SLS全箭模型的验证以及可能的模型修正,NASA开展了SLS全箭竖立状态模态试验.参试产品为SLS运载火箭(加压,不带液)、移动发射平台(含勤务塔架,不含履带式运输机)和猎户座质量模拟器的组合体.针对试验状态,将移动发射平台和猎户座质量模拟器各视为一个模块,结合全箭四个模块,开展不确定量化,根据量化结果,对全箭竖立状态进行蒙特卡罗分析,获取模态相关指标的统计数据.对比量化数据分布情况与仿真相对实验结果偏差情况,验证全箭模型[26].
NASA通过加速度解耦方法(accelerance decoupling,AD)从组合体模态测试结果中分离出箭体自由模态数(图1),并采用与竖立状态相同的不确定量化方法,验证全箭自由状态仿真结果.
此外,NASA在SLS结构动力学设计中还采用残余模态增强方法(residual mode augmentation,RMA)提高有限元模型的模态灵敏度分析准确性;采用试验模态验证方法(experimental mode verification,EMV)区分测试结果中的真实模态与伪模态或激发不足的模态,从而确认模态测试数据真实性[28].
长征八号系列运载火箭是我国新一代中型运载火箭.长征八号充分利用长征七号与长征三号A系列的成熟模块[29],采用基于部段模型组装的运载火箭结构动力学分析技术[30],并开展连接刚度不确定性量化分析、全箭竖立状态模态试验验证、基于局部振型斜率分析的惯性器件选位合理性评估、模态偏差及阻尼统计包络分析等技术降低未开展全箭模态试验的风险[31].
长征六号C运载火箭是我国面向未来商业发射市场研制的新一代运载火箭.长征六号C采用了基于部段模型组装的运载火箭结构动力学分析技术.长征六号C全箭大部分舱段为新研舱段,仅一子级与长征六号A方案、材料、工艺相同,且相关建模方法经过了长征六号A全箭模态试验验证和飞行试验考核,因此可对一子级各舱段直接建模,并开展整流罩、二级共底贮箱、安装有惯性器件的级间段的模态试验.根据模态试验结果,修正舱段三维模型.同时利用舱段级模态试验产品,开展分离面连接刚度模态试验,确定连接刚度建模方法,完成全箭模型组装.进一步考虑分离面连接刚度的不确定性,开展连接刚度偏差对全箭模态的影响分析,并进行模态偏差量化.依托合练期间开展的全箭竖立状态模态试验,对比对应状态仿真分析结果相对试验结果的偏差和模态偏差量化的分布情况,验证全箭模型.
此外,长征六号C还利用三维精细化模型(图2图3),分析局部振型斜率,评估惯性器件选位合理性;开展模态偏差及阻尼统计包络分析,降低首飞未开展全箭模态试验的风险.
未来,载人登月、月球科研站建设、深空探测等航天发射任务将会对运载火箭提出更高要求.运载火箭整体上也将呈现出大型化、复杂化与轻量化的趋势.运载火箭的大型化将会使地面模态试验设施不足以支撑全箭模态试验的开展,运载火箭的复杂化与轻量化将会使全箭动力学特性呈现出频率低、模态密、纵横扭振动耦合、局部变形复杂的特点,这些都向传统的结构动力学建模技术提出巨大挑战.
得益于计算机技术、数值仿真技术和人工智能的发展,运载火箭领域各专业建模仿真技术逐渐得到更深的应用.其中,运载火箭结构动力学建模仿真技术在液固耦合高效计算、多学科建模、集成分析和智能分析方面都呈现出了积极的发展趋势.全箭模态试验正在逐步被部段级模态试验和特定状态的模态试验取代,最终实现满足后续高质量、高效率、高效益运载火箭研制需求.
液体运载火箭中液体推进剂质量一般占全箭起飞质量的90%左右,为准确反映全箭结构动力学特性,需考虑液体的质量效应及液固耦合效应[32].运载火箭液体推进剂模拟方法主要包括解析法、线性有限元法、有限元-边界元法、计算流体动力学/计算结构动力学(CSD/CFD)耦合方法、非线性有限元法以及半数值半解析法[33-36].不同方法描述物理量的能力和精度不同,计算量和分析时间也有很大差异.面向运载火箭,发挥各种方法优势,深化工程应用.
(1)建立运载火箭多层级动力学模型,选择不同的分析方法,适应总体设计不同阶段的计算需求.上海航天技术研究院在长征六号C运载火箭研制过程中,针对载荷环境设计环节建立纵横扭一体化模型[37],针对弹性设计和星箭耦合分析环节采用三维模型和虚质量方法[38],以适应不同计算效率和计算精度的需求.
(2)采用模型缩聚、模态整合、模态降阶等方法降低计算量.NASA在SLS研制过程中,采用模态整合(mode consolidation,MC)技术从大量阶次的模态结果中识别箭体的主模态,并进行模态降阶提高计算效率.模态整合技术主要包括改进Guyan缩聚方法(modified Guyan reduction,MGR)和谐波缩聚方法(harmonic reduction,HR)[39].上海航天技术研究院在长征六号C运载火箭研制过程中,采用模型缩聚技术提高弹性设计和星箭耦合分析计算效率[38].
(3)从算法层面发展高效计算技术,缩短总体设计周期,提高精细化三维模型、精细化流固耦合方法的工程应用价值.
在飞行过程中,运载火箭箭体结构系统、推进剂系统、动力系统、控制系统会互相耦合,共同影响全箭动力学特性、载荷环境[40].传统单一学科动力学分析技术仅考虑箭体结构系统、推进剂系统对全箭动力学特性影响.随着未来运载火箭对箭体力学各相关专业提出更高的要求,动力学分析技术还需考虑动力系统中的液固耦合效应、控制系统中伺服机构电磁(液压)组件耦合效应.建立多学科仿真模型,不断细化完善数字火箭工程,全方位提高运载火箭动力学分析能力.
(1)建立运载火箭箭体结构系统、推进剂系统、动力系统多学科仿真模型,可充分考虑箭体主结构纵向特性与动力系统液体流动特性和发动机推力的相互影响,精细化预示运载火箭飞行状态纵向动力学特性,优化POGO稳定性设计、提高箭体纵向载荷环境精度.航天推进技术研究院针对真实液体火箭发动机充液导管进行了流固耦合动力学特性分析[41].上海航天技术研究院针对我国新一代液氧煤油运载火箭进行了纵向动力学特性精细化预示及POGO稳定性设计优化[42].
(2)建立运载火箭动力系统、控制系统小回路多学科仿真模型.采用数字化物理模型描述发动机系统、采用数学模型描述控制系统算法、采用数字化半物理模型描述伺服机构及其电磁(液压)组件,集成分析小回路的动态特性,精细化预示小回路横向动力学特性,优化姿态稳定性设计、提高箭体横向载荷环境精度[43].内蒙古工业大学、清华大学针对永磁同步交流伺服电机建立了机电耦合动力学方程并完成了动力学仿真[44].
(3)建立电动振动台多学科仿真模型.建立振动台机械结构、电磁组件机电耦合模型,建立振动台控制系统数学模型,构建虚拟振动台,实现大型试验件虚拟地面振动试验,提高产品可靠性,降低型号研制成本.西安航天动力研究所对电动振动台机电耦合系统进行辨识,建立机电耦合模型,结合振动台控制系统数学模型,构建了闭环虚拟正弦扫描振动试验平台,并对试验件开展正弦扫描振动试验[45].
随着未来运载火箭的商业化,研制过程的高质量、高效率和高效益已经成为运载火箭研制方的生存关键.运载火箭动力学分析孪生技术是解决这些工程需求的关键技术[46].
(1)依托多学科动力学建模技术,发展运载火箭动力学孪生分析平台,建立全流程数字火箭,全面代替大型地面试验,满足研制过程的高效益要求.北京宇航系统工程研究所提出了一种运载火箭飞行过程数字孪生系统,通过地面与火箭飞行数据的实时交互,实现对火箭飞行全过程的跟踪映射、故障诊断、预示评估和智能决策,全面提升火箭的智能化健康管理水平,提高运载火箭的飞行可靠性[47].
(2)依托运载火箭动力学孪生分析平台,实现各专业高效协同合作,实现运载火箭的快速迭代设计,满足研制过程的高效率要求.上海宇航系统工程研究所构建的多学科协同设计优化平台实现了运载火箭总体设计流程自动化,显著缩短运载火箭设计周期,已支撑多个型号首飞[48].
(3)量化分析运载火箭总体设计、载荷环境设计和姿态控制系统等专业设计偏差,进一步提升运载火箭总体技术指标的合理性和系统可靠性.最终依托运载火箭动力学孪生分析平台,进行飞行试验结果预示,实现运载火箭的数字伴飞,满足研制过程的高质量要求.上海宇航系统工程研究所在长征十二号运载火箭研制过程中,采用概率化设计方法实现总体各专业偏差量化与精细化偏差控制[49].
随着深度学习技术的提出和图形处理器的发展,数据驱动成为科学发展的新途径.深度学习技术在运载火箭动力学分析领域也有着广阔的应用前景.
时至今日,精细化模型已经成为运载火箭动力学分析不可或缺的工具.而建立精细化模型和模型修正往往需要耗费大量的时间成本和人力资源.依据行业有限元建模准则和模型修正准则,利用人工智能实现高效精确的有限元建模和模型修正,可有效缩短运载火箭研制周期,降低研制成本.
近年来,通用大模型发展迅猛,基于通用大模型和行业内数据开展二次训练,并根据使用场景微调,可实现领域大模型的构建,借助领域大模型,可实现运载火箭动力学特性的快速分析与结构优化,提高运载火箭方案论证阶段的迭代效率.华为公司联合中国商用飞机有限责任公司和西北工业大学开发的大模型已经应用于流场的高效高精度预测.
运载火箭发展至今日,已经积累了大量的飞行试验数据和地面试验数据.基于深度学习技术对试验数据进行挖掘[50],在偏差量化、模型修正、参数识别、参数反演等方面为结构动力学、载荷环境等专业提供新的发展思路.
结构动力学建模技术作为运载火箭工程中的关键技术,每一次突破都能推动运载火箭的发展.随着结构动力学建模精度和效率的提升,逐步采用结构动力学数值计算和部件级模态试验相结合的方式,取代了全箭模态试验.后续随着大型运载火箭研制需求,以及动载荷环境预示精度提升的需要,液固耦合高效计算技术、多学科动力学分析技术、动力学分析孪生技术和基于人工智能的运载火箭动力学分析技术是运载火箭工程领域的发展趋势,支撑着我国未来先进运载火箭的快速发展.推动运载火箭数字化、智能化建设,提升我国航天工业的技术水平、创新能力和国际竞争力,助推我国从航天大国迈向航天强国.
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2种不同金属材料的力学参数

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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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