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Multiscale design of functionally graded cellular structures for additive manufacturing using level-set descriptions
Structural and Multidisciplinary Optimization ( IF 3.9 ) Pub Date : 2021-06-03 , DOI: 10.1007/s00158-021-02959-3
Cong Hong Phong Nguyen , Young Choi

The emergence of additive manufacturing (AM) has enabled the design of complex structures with high performance, such as functionally graded cellular structures (FGCSs). Concurrent topology optimization is commonly utilized for designing FGCSs; however, this approach suffers from an extremely high computational cost due to the complexity of the design problem. Recently, level-set-based methods, which rely on the implicit-based modeling technique, have gained increased attention and been considered as an efficient design tool for structures fabricated with AM. In this work, a multiscale structural optimization method for FGCS design utilizing level-set descriptions is proposed. Contrary to the well-known level-set topology optimization, in this approach, the shape is represented and parameterized with implicit functions, and the optimization process is performed to find the optimal parameters. The proposed method can replace topology optimization for microscale structural optimization within the multiscale structural design with reduced computation cost and comparable optimally designed results. Moreover, the unique behaviors of pre-selected cellular structures could be maintained during the optimization process by proper parametric constraints. The proposed design approach was validated through two design examples, both of which demonstrate remarkable structural performance enhancements in comparison with the single-scale design approach. Furthermore, two three-dimensional design examples, commonly found in automotive and aerospace industries, further prove the applicability of the proposed method in practice.



中文翻译:

使用水平集描述的增材制造功能梯度蜂窝结构的多尺度设计

增材制造 (AM) 的出现使设计具有高性能的复杂结构成为可能,例如功能梯度蜂窝结构 (FGCS)。并发拓扑优化通常用于设计 FGCS;然而,由于设计问题的复杂性,这种方法的计算成本非常高。最近,依赖于基于隐式建模技术的基于水平集的方法受到越来越多的关注,并被认为是使用 AM 制造的结构的有效设计工具。在这项工作中,提出了一种利用水平集描述的 FGCS 设计的多尺度结构优化方法。与众所周知的水平集拓扑优化相反,在这种方法中,形状用隐函数表示和参数化,并执行优化过程以找到最佳参数。所提出的方法可以在多尺度结构设计中替代拓扑优化进行微尺度结构优化,同时降低计算成本和可比较的优化设计结果。此外,通过适当的参数约束,可以在优化过程中保持预先选择的细胞结构的独特行为。所提出的设计方法通过两个设计示例得到验证,与单尺度设计方法相比,这两个设计示例都展示了显着的结构性能增强。此外,在汽车和航空航天工业中常见的两个三维设计实例进一步证明了所提出方法在实践中的适用性。所提出的方法可以在多尺度结构设计中替代拓扑优化进行微尺度结构优化,同时降低计算成本和可比较的优化设计结果。此外,通过适当的参数约束,可以在优化过程中保持预先选择的细胞结构的独特行为。所提出的设计方法通过两个设计示例得到验证,与单尺度设计方法相比,这两个设计示例都展示了显着的结构性能增强。此外,在汽车和航空航天工业中常见的两个三维设计实例进一步证明了所提出方法在实践中的适用性。所提出的方法可以在多尺度结构设计中替代拓扑优化进行微尺度结构优化,同时降低计算成本和可比较的优化设计结果。此外,通过适当的参数约束,可以在优化过程中保持预先选择的细胞结构的独特行为。所提出的设计方法通过两个设计示例得到验证,与单尺度设计方法相比,这两个设计示例都展示了显着的结构性能增强。此外,在汽车和航空航天工业中常见的两个三维设计实例进一步证明了所提出方法在实践中的适用性。

更新日期:2021-06-03
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