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A novel elastoplastic topology optimization formulation for enhanced failure resistance via local ductile failure constraints and linear buckling analysis

机译:一种新的弹塑性拓扑优化配方,通过局部延展性衰竭约束和线性屈曲分析提高失效阻力

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A new formulation is proposed for incorporating local ductile failure constraints and buckling resistance into elastoplastic structural design in the context of extreme loading. Many strides have been made in recent years regarding continuum topology optimization with elastoplasticity and buckling separately, but these phenomena are typically not considered together. The formulation we propose is computationally efficient and robust, partly due to its reliance on small strain kinematics and a separation of the elastoplastic response from the buckling load factors computed during the optimization procedure. An aggregate objective function is constructed in which the total work in an elastoplastic analysis is maximized and an aggregation function of the load factors from a separate linear elastic buckling analysis is included. Additionally, local ductile failure constraints are handled via a framework without aggregation functions and a new pseudo buckling mode filter is proposed. Each of the obtained topologies are then subject to a verification step in which a large strain ductile failure model is used in order to compare the performance of the optimized designs obtained for three numerical examples. The results demonstrate that structural responses such as peak load carrying capacity and total external work required to reach the peak load may be significantly improved using the suggested framework. Other interesting observations are also discussed. (C) 2020 Elsevier B.V. All rights reserved.
机译:提出了一种新的配方,用于将局部延性故障约束和屈曲性抵抗在极端载荷的背景下掺入弹塑性结构设计中。近年来,近年来,近年来的拓扑拓扑优化具有弹性塑性和分别屈曲,但这些现象通常不被认为是在一起的。我们提出的制剂是计算上的计算上高效且稳健,部分原因是其对小菌株运动学的依赖性和从优化过程中计算的屈曲负载因子的弹性塑料响应的分离。构建了聚集目标函数,其中包括弹性塑性分析中的总工作最大化,并且包括来自单独的线性弹性屈曲分析的负载因子的聚集函数。另外,局部延展性故障约束通过不具有聚合功能的框架处理,提出了一种新的伪屈曲模式滤波器。然后,每个获得的拓扑受到验证步骤,其中使用大应变延展性故障模型来比较三个数值示例所获得的优化设计的性能。结果表明,使用所建议的框架,可以显着改善诸如达到峰值负荷所需的峰值负荷承载能力和总外部工作的结构响应。还讨论了其他有趣的观察。 (c)2020 Elsevier B.v.保留所有权利。

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