张衡, 项煦, 刘宇浩, 黄斌, 曾磊. 基于改进的同伦随机有限元法的随机参数结构弹性稳定性分析[J]. 工程力学, 2023, 40(8): 11-23. DOI: 10.6052/j.issn.1000-4750.2021.12.1004
引用本文: 张衡, 项煦, 刘宇浩, 黄斌, 曾磊. 基于改进的同伦随机有限元法的随机参数结构弹性稳定性分析[J]. 工程力学, 2023, 40(8): 11-23. DOI: 10.6052/j.issn.1000-4750.2021.12.1004
ZHANG Heng, XIANG Xu, LIU Yu-hao, HUANG Bin, ZENG Lei. ADVANCED HOMOTOPY STOCHASTIC FINITE ELEMENT METHOD FOR STRUCTURAL ELASTIC STABILITY ANALYSIS[J]. Engineering Mechanics, 2023, 40(8): 11-23. DOI: 10.6052/j.issn.1000-4750.2021.12.1004
Citation: ZHANG Heng, XIANG Xu, LIU Yu-hao, HUANG Bin, ZENG Lei. ADVANCED HOMOTOPY STOCHASTIC FINITE ELEMENT METHOD FOR STRUCTURAL ELASTIC STABILITY ANALYSIS[J]. Engineering Mechanics, 2023, 40(8): 11-23. DOI: 10.6052/j.issn.1000-4750.2021.12.1004

基于改进的同伦随机有限元法的随机参数结构弹性稳定性分析

ADVANCED HOMOTOPY STOCHASTIC FINITE ELEMENT METHOD FOR STRUCTURAL ELASTIC STABILITY ANALYSIS

  • 摘要: 结构参数的不确定性将对结构稳定性产生不可忽视的影响,实现随机结构屈曲荷载与屈曲模态的高效高精度求解和统计分析,对结构设计与安全评估有重要意义。该文基于随机残差最小化法改进现有的同伦随机有限元法,并利用新方法高效高精度地求解了大变异随机参数结构的屈曲特征值和屈曲模态。将随机参数结构的屈曲特征值和屈曲模态以同伦级数的形式表达,并给出了同伦级数中任意阶系数的显式递推表达式;在此基础上,定义了关于弹性屈曲方程近似解的随机残余误差,通过使该随机残余误差最小化,得到了优化的随机屈曲特征值和屈曲模态的同伦级数展开表达式。该文提出的改进的同伦随机有限元法能够实现同伦级数展开的自动寻优,有效避免了现有同伦随机有限元法(HSFEM)计算精度易受样本选点影响的缺点。当随机参数变异性较大时,随着级数展开阶数的增加,该文方法计算结果除了能保持良好的收敛性外,相比于HSFEM具有更好的稳定性,而摄动随机有限元法则可能出现发散现象;与蒙特卡洛模拟法相比,新方法具有很高的求解效率。通过强非线性函数算例以及变截面轴心受压杆和框架结构的弹性稳定性分析说明了该文方法的有效性。

     

    Abstract: The uncertainty in structural parameters has notable impact on stability analysis of structures. It is of great significance for structural design and safety evaluation to obtain random buckling loads and buckling modes with efficiency and high-precision. The homotopy stochastic finite element method is improved to effectively solve the structural elastic stability problem involving large fluctuation of random parameters, and the statistical properties of the buckling eigenvalue and buckling mode are obtained. The buckling eigenvalue and buckling mode of the structure involving random parameters are expressed using the homotopy series, and the arbitrary order coefficients of the homotopy series are given as explicit recursive relationship formulas. Further, the stochastic residual error with respect to the buckling governing equation is defined, and the optimal form of the homotopy series is determined by minimizing the stochastic residual error. The proposed advanced homotopy stochastic finite element method can automatically realize the optimization process, which overcomes the drawbacks of the existing homotopy stochastic finite element method, named HSFEM, that the computational accuracy is affected by the selected samples and relies on empirical knowledge. In addition, for a structure involving large fluctuation of random parameters, the proposed method has better stability than HSFEM when higher-order terms in homotopy series are employed, while the results from the traditional perturbation method based on Taylor series may diverge. And the proposed method has an excellent computational efficiency compared with the Monte Carlo simulation method. The validity of the proposed method is verified through a strong-nonlinearity function, the stability analysis of a variable cross-section column subjected to axial force and the stability analysis of a 7-story frame structure.

     

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