基于协同移动回归的结构低周疲劳寿命可靠性评估代理建模框架

IF 7.3 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Xiao-Wei Dong , Zhen-Ao Li , Jia-Hao Liang , Qing-Long Li , Chun-Yan Zhu , Ming Wang , Wei-Kai Li
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引用次数: 0

摘要

为实现机械结构低周疲劳寿命预测和可靠性评估,将协同移动回归(CMR)策略、启发式算法、自适应混合代理建模方法和矩阵分析理论相融合,提出了基于协同移动回归的代理建模(CMR- sm)框架。在此框架下,CMR策略由分解-协调(DC)方法和移动最小二乘(MLS)技术发展而来,以减小模型非线性并获取有效样本;通过二次插值优化(QIO)确定紧凑支撑区域的最优半径;应用矩阵分析理论构建未知参数的向量和单元阵列,同步建立数学模型。在此概念下,进一步发展了基于cmr的响应面法(CMR-RSM)、基于cmr的Kriging模型(CMR-KM)、基于cmr的支持向量机(CMR-SVM)和基于cmr的人工神经网络(CMR-ANN)。考虑到模型的鲁棒性,采用自适应加权技术进一步发展了基于协同运动回归的自适应混合代理建模方法。通过数值算例(即嵌套非线性函数的概率分析)和工程算例(即涡轮叶片LCF寿命可靠性评估)验证了所提出方法良好的建模能力和仿真性能。该方法为工程结构LCF寿命可靠性评估提供了新的思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Collaborative moving regression-based surrogate modeling framework for structural low cycle fatigue life reliability assessment
To achieve low-cycle fatigue (LCF) life prediction and reliability assessment for mechanical structures, a collaborative moving regression-based surrogate modeling (CMR-SM) framework is proposed by fusing the collaborative moving regression (CMR) strategy, heuristic algorithm, adaptive hybrid surrogate modeling method, and matrix analysis theory. In this framework, the CMR strategy is developed from the decomposition-coordination (DC) method and moving least squares (MLS) technique to reduce model nonlinearity and acquire effective samples; the optimal radius for compact support region is determined through quadratic interpolation optimization (QIO); Matrix analysis theory is applied to construct vectors and cell arrays of unknown parameters, synchronously establishing the mathematical model. Under this concept, the CMR-based response surface method (CMR-RSM), CMR-based Kriging model (CMR-KM), CMR-based support vector machine (CMR-SVM), and CMR-based artificial neural network (CMR-ANN) are further developed. Considering the robustness of model, an adaptive weighting technique is employed to further develop the collaborative moving regression-based adaptive hybrid surrogate modeling (CMR-AHSM) method. The excellent modeling capabilities and simulation performance of the proposed method are validated through a numerical case (i.e., the probability analysis of a nested nonlinear function) and an engineering case (i.e., the LCF life reliability assessment of turbine blisk). The proposed method provides new insights for LCF life reliability assessment in engineering structures.
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来源期刊
CiteScore
12.70
自引率
15.30%
发文量
719
审稿时长
44 days
期刊介绍: Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.
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