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Finding three-dimensional layouts for crashworthiness load cases using the graph and heuristic based topology optimization
Structural and Multidisciplinary Optimization ( IF 3.6 ) Pub Date : 2020-11-14 , DOI: 10.1007/s00158-020-02768-0
F. Beyer , D. Schneider , A. Schumacher

In this paper we present a new procedure using the graph and heuristic based topology optimization in order to find layouts for three-dimensional frame structures under crash loads. A three-dimensional graph describes the geometry and is used to derive a finite element shell model. The model of the frame structure consists of different profiles with continuous cross-sections. The ends of the profiles are currently rigidly connected. Each cross-section is defined by an individual two-dimensional graph. After performing a simulation its results are used by competing heuristics to propose new topologies for the frame structure. Most of these heuristics are derived from expert knowledge. Over several iterations, the goal is to improve the structures mechanical behavior. Typical objectives are the minimization of the structural intrusion in a crash scenario or the minimization of the maximal contact force between structural components. The presented method includes topology optimization by heuristics and shape optimization respectively sizing by mathematical optimization algorithms. The new flexible syntax for three- and two-dimensional graphs, the optimization process and the currently used heuristics are described. The performance is demonstrated for two examples, each optimized twice with opposing objectives.



中文翻译:

使用图和基于启发式的拓扑优化来查找耐撞性工况的三维布局

在本文中,我们提出了一种使用图和基于启发式拓扑优化的新程序,以查找碰撞载荷下三维框架结构的布局。三维图描述了几何形状,并用于导出有限元壳模型。框架结构的模型由具有连续横截面的不同轮廓组成。型材的端部目前已牢固连接。每个横截面由单独的二维图形定义。完成模拟后,竞争启发法将其结果用于为框架结构提出新的拓扑。这些启发式方法大多数都来自专家知识。经过多次迭代,目标是改善结构的机械性能。典型的目标是在碰撞情况下最小化结构侵入或最小化结构组件之间的最大接触力。所提出的方法包括通过启发式的拓扑优化和通过数学优化算法分别确定尺寸的形状优化。描述了用于三维图和二维图的新的灵活语法,优化过程和当前使用的启发式算法。演示了两个示例的性能,每个示例针对相反的目标进行了两次优化。描述了优化过程和当前使用的启发式方法。演示了两个示例的性能,每个示例针对相反的目标进行了两次优化。描述了优化过程和当前使用的启发式方法。演示了两个示例的性能,每个示例针对相反的目标进行了两次优化。

更新日期:2020-11-15
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