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Stochastic stress-based topology optimization of structural frames based upon the second deviatoric stress invariant

机译:基于随机应力的基于结构框架的拓扑优化,其基于第二偏离偏离应力不变的结构框架

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This work pertains to the stochastic stress-based topology optimization of frame structures considering uncertainty. Specifically, this paper presents an investigation of the second deviatoric stress invariant, J(2), as the measure of stress in the domain where the objective is to minimize the maximum of the expected values of the stress invariant. Analytical expressions for the expected value of the J(2) invariant are developed employing the perturbation approach. The premise being that the J(2) invariant eliminates the square root operator that would otherwise be present if using the von Mises stress, and by eliminating this operator, the nonlinearity in the functional mapping between the random input (magnitude and direction of external forces) and uncertain output (expected values of stress) is reduced. Hence, an improved accuracy can be achieved with an analytical approximation of a given order. The analytical expressions of the expected value of the J(2) invariant to the second order are obtained based on a Taylor series expansion along with the associated sensitivities for gradient-based optimization. The analytical expressions are implemented in an optimization scheme and applied for the design of three ground structures considering different variability in the input random variables. For each example, the relative error between the maximum of the expected values of the J(2) invariant obtained using the analytical expressions and corresponding values evaluated by performing stochastic finite element analysis, whereby the input distribution is sampled using Monte Carlo methods, finite element simulation performed for each sample realization, then computing the expected value of the stress measure using straightforward statistical expressions, and finally estimation of the maximum via the p-norm, were observed to be less than 2%, even for a coefficient of variation of 0.4. The optimized designs were again analyzed using the von Mises stress and the relative error again computed with respect to those obtained from Monte Carlo sampling and finite element simulation. In general, the relative error using the analytical expressions of the von Mises stress was greater than, except in a couple instances, those obtained using the J(2) invariant.
机译:这项工作涉及考虑不确定性的框架结构的随机应力的拓扑优化。具体地,本文提出了对第二脱离抗应力不变,J(2)的研究,作为域中的应力的量度,其中目标是最小化应力不变的预期值的最大值。采用扰动方法开发了J(2)不变的预期值的分析表达。如果使用von mises应力,并且通过消除该操作者在随机输入之间的功能映射中的非线性(外力的幅度和方向之间的功能映射中的非线性,则j(2)不变地消除了否则存在的方形根算子。 ),不确定的输出(应力的预期值)降低。因此,可以通过给定顺序的分析近似来实现改善的精度。基于泰勒序列扩展以及基于梯度的优化的相关灵敏度,获得了J(2)的预期值的分析表达式。分析表达式在优化方案中实现,并应用于考虑到输入随机变量中不同可变性的三个地面结构的设计。对于每个示例,使用分析表达式和通过执行随机有限元分析评估的分析表达式和相应的值获得的j(2)不变的最大值之间的相对误差,由此使用蒙特卡罗方法采样输入分布,有限元针对每个样本实现执行的模拟,然后使用直接统计表达计算应力测量的预期值,并且最终通过P-NAR的最大估计为小于2%,即使对于0.4的变化系数也是小于2% 。使用Von Mises应力分析优化的设计,并且相对于从蒙特卡罗采样和有限元模拟获得的相对误差再次计算。通常,使用Von Mises Regress的分析表达的相对误差大于,除了几种情况下,使用J(2)不变获得的那些。

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