快速拓优化多共振MEMS的两相方法,涉及模型顺序减少
Siyang Hu1,2, Billy Manansala1, Ulrike Fitzer1,2
1Department of Engineering, Jade University of Applied Sciences, Friedrich-Paffrath-Str. 101, 26389 Wilhelmshaven, Germany.
Micromachines
|April 26, 2025
概括
本研究介绍了微电机系统 (MEMS) 的双相拓优化方法,结合双向进化结构优化 (BESO) 和基于密度的方法,以实现更快,更高效的设计.
科学领域:
- 工程 工程师 工程师 工程师
- 材料科学 材料科学 材料科学
- 计算力学 计算力学 计算力学
背景情况:
- 在设计微电机系统 (MEMS) 时,拓优化至关重要.
- 经典方法,如基于密度的优化,可以是计算密集的.
- 双向进化结构优化 (BESO) 提供了更快的融合,但面临着挑战.
研究的目的:
- 为多共振MEMS开发一种快速拓优化方法.
- 为了最大限度地减少计算力度,实现最佳的MEMS设计.
- 为了解决BESO.中遇到的趋同问题.
主要方法:
- 一个两阶段的优化策略,结合了BESO和基于密度的方法.
- 实施模型订单减少 (MOR) 来减少计算时间.
- 在线陀螺仪和微镜设计上的基准测试.
主要成果:
- 这种两相方法在200次代内实现了最佳的MEMS设计.
- 使用BESO进行了初始优化,随后进行了基于密度的阶段,以确保融合.
- 在测试的示例中,模型顺序减少减少了50%的目标函数计算.
结论:
- 拟议的两相方法显著加快了MEMS拓优化.
- 将BESO与基于密度的阶段相结合,有效地解决了融合问题.
- 模型订单减少进一步提高了MEMS设计的计算效率.
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