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首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Non-probabilistic Reliability-based Topology Optimization (NRBTO) Scheme for Continuum Structures Based on the parameterized Level-Set method and Interval Mathematics
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Non-probabilistic Reliability-based Topology Optimization (NRBTO) Scheme for Continuum Structures Based on the parameterized Level-Set method and Interval Mathematics

机译：基于参数化级别方法和间隔数学的连续结构基于非概率可靠性的拓扑优化（NRBTO）方案

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摘要

In this paper, a study on non-probabilistic reliability-based topology optimization (NRBTO) scheme for continuum structures based on the parameterized Level-Set method (PLSM) is conducted, in which the unknown-but-bounded (UBB) uncertainties of material and external loads are taken into account simultaneously. By interpolating the level set function (LSF) with the compactly supported radial basis functions (CSRBFs), the partial differential equation (PDE) is transformed into an ordinary differential equation (ODE). Based on the interval-set model, the displacement constraint is transformed into the non-probabilistic reliability-based scheme and the reliability is evaluated by the optimization feature distance (OFD). Moreover, the interval parametric vertex approach, the concept of shape derivative and the adjoint vector method are employed to obtain the sensitivity between the optimization model and the pseudo time to obtain the evolution velocity field of LSF. By utilizing the optimization criterion (OC) method, the optimization problem can be solved iteratively. To verify the validity and applicability of the proposed NRBTO method, three examples are presented, and numerical results show that taking the UBB uncertainties effects into account during the topology optimization may have a significant influence on the final structural configurations. (C) 2020 Elsevier B.V. All rights reserved.
机译：在本文中，进行了基于参数化级别方法（PLSM）的基于非概率可靠性的拓扑优化（NRBTO）方案的研究，其中材料的未知界（UBB）不确定性外部负载同时考虑到。通过用紧凑地支持的径向基函数（CSRBFS）内插级别设定功能（LSF），将部分微分方程（PDE）变换为常微分方程（ode）。基于间隔集模型，将位移约束转换为基于非概率可靠性的方案，通过优化特征距离（OFD）评估可靠性。此外，采用间隔参数，形状导数和伴随载体方法的概念来获得优化模型与伪时间之间的灵敏度，以获得LSF的演化速度场。通过利用优化标准（OC）方法，可以迭代地解决优化问题。为了验证所提出的NRBTO方法的有效性和适用性，提出了三种示例，数值结果表明，在拓扑优化期间考虑到UBB不确定性效应可能对最终结构配置产生重大影响。 （c）2020 Elsevier B.v.保留所有权利。

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