An efficient strategy to implement local porosity constraints in the multiscale design of solids with parameterized biomimetic microstructures

被引:2
|
作者
Colabella L. [1 ]
Cisilino A.P. [1 ]
Fachinotti V. [2 ]
Kowalczyk P. [3 ]
机构
[1] Faculty of Engineering, National University of Mar del Plata (UNMDP)/Research Institute for Materials Science and Technology (INTEMA), National Scientific and Technical Research Council (CONICET), Av. Juan B. Justo 4302, Mar del Plata
[2] Centro de Investigación de Métodos Computacionales (CIMEC), Universidad Nacional del Litoral (UNL)/Consejo Nacional de Investigaciones Científias y Técnicas (CONICET), Predio CCT-CONICET Santa Fe, Ruta 168, Paraje El Pozo, Santa Fe
[3] Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawinskiego 5B, Warsaw
来源
Computers and Structures | 2023年 / 285卷
关键词
Computational performance; Large-scale problems; Multiscale optimization; Parameterized microstructures; Trabecular bone;
D O I
10.1016/j.compstruc.2023.107084
中图分类号
学科分类号
摘要
In previous works, the authors introduced a multiscale optimization method to maximize the stiffness of elastic solids with biomimetic cancellous microstructures described by a finite set of parameters. Although effective, the procedure is computationally expensive when solving large-scale problems using per-element non-linear constraints to impose local bounds on the solid volume fraction. This work improves the computational performance of the method by exploring two strategies to completely dispense with nonlinear local constraints: to bound the microparameters so the microsctructures are always within the solid fraction of trabecular bone, and to map the microparameters onto an auxiliary set of parameters that are linearly bounded. As a side effect, the design spaces are reduced. Such reductions are assessed in terms of the bulk and shear moduli and elastic symmetries, which are compared to those of natural bone. Performances of the two strategies are assessed by solving a series of benchmark problems and studying the stiffness of a hip prosthesis. The strategy based on the isoparametric mapping achieves the best results, performing up to 2000 times faster while marginally reducing the design space. Thus, the isoparametric mapping approach makes the multiscale design method a suitable tool for solving large-scale problems of practical interest. © 2023 Elsevier Ltd
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