基于参数化水平集方法的多离散化拓扑优化方案

P. Wei, Yang Liu, Zuyu Li
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引用次数: 5

摘要

在参数化水平集方法的框架下,结构分析和拓扑表示可以解耦实现。一个参数化的水平集函数,通常使用径向基函数(rbf),是一组规定的rbf和系数的线性组合。一旦确定了系数,理论水平集函数就确定了。利用这一固有特性,提出了一种基于参数化水平集方法的多重离散化方法。在这种方法中,采用粗离散化来进行结构分析,而采用另一种密集离散化来表示结构拓扑。因此,高效的分析和高分辨率的拓扑设计是可用的。请注意,密集离散化只是对理论水平集函数的更精确和平滑的描述,而不是引入额外的设计自由或对结构分析或优化过程产生干扰。换句话说,这种解耦方式不会增加结构分析的计算负担,也不会导致特定分析设置的收敛结果的非唯一性。二维和三维的数值算例表明了该方法的有效性和适用性。
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A multi-discretization scheme for topology optimization based on the parameterized level set method
In the framework of the parameterized level set method, the structural analysis and topology representation can be implemented in a decoupling way. A parameterized level set function, typically, using radial basis functions (RBFs), is a linear combination of a set of prescribed RBFs and coefficients. Once the coefficients are determined, the theoretical level set function is determined. Exploiting this inherent property, we propose a multi-discretization method based on the parameterized level set method. In this approach, a coarse discretization is applied to do the structural analysis whereas another dense discretization is employed to represent the structure topology. As a result, both efficient analysis and high-resolution topological design are available. Note that the dense discretization only accounts for a more precise and smooth description of the theoretical level set function rather than introduce extra design freedom or incur interference to structural analysis or the optimization process. In other words, this decoupling way will not add to the computational burden of structural analysis or result in non-uniqueness of converged results for a particular analysis setting. Numerical examples in both two-dimension and three-dimension show effectiveness and applicability of the proposed method.
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来源期刊
CiteScore
2.00
自引率
0.00%
发文量
19
审稿时长
16 weeks
期刊介绍: The International Journal for Simulation and Multidisciplinary Design Optimization is a peer-reviewed journal covering all aspects related to the simulation and multidisciplinary design optimization. It is devoted to publish original work related to advanced design methodologies, theoretical approaches, contemporary computers and their applications to different fields such as engineering software/hardware developments, science, computing techniques, aerospace, automobile, aeronautic, business, management, manufacturing,... etc. Front-edge research topics related to topology optimization, composite material design, numerical simulation of manufacturing process, advanced optimization algorithms, industrial applications of optimization methods are highly suggested. The scope includes, but is not limited to original research contributions, reviews in the following topics: Parameter identification & Surface Response (all aspects of characterization and modeling of materials and structural behaviors, Artificial Neural Network, Parametric Programming, approximation methods,…etc.) Optimization Strategies (optimization methods that involve heuristic or Mathematics approaches, Control Theory, Linear & Nonlinear Programming, Stochastic Programming, Discrete & Dynamic Programming, Operational Research, Algorithms in Optimization based on nature behaviors,….etc.) Structural Optimization (sizing, shape and topology optimizations with or without external constraints for materials and structures) Dynamic and Vibration (cover modelling and simulation for dynamic and vibration analysis, shape and topology optimizations with or without external constraints for materials and structures) Industrial Applications (Applications Related to Optimization, Modelling for Engineering applications are very welcome. Authors should underline the technological, numerical or integration of the mentioned scopes.).
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