A New MEMS Stochastic Model Order Reduction Method: Research and Application

作者：Bian Xiangjuan; Gong, Youping^*; Chen Guojin; Lv Yunpeng

来源：Journal of Sensors, 2015, 2015: 125621.

DOI：10.1155/2015/125621

• DESIGN OPTIMIZATION
• VARIABILITY
• PERFORMANCE
• RESONATORS
• ROBUST

Modeling and simulation of MEMS devices is a very complex tasks which involve the electrical, mechanical, fluidic, and thermal domains, and there are still some uncertainties that need to be accounted for during the robust design of MEMS actuators caused by uncertain material and/or geometric parameters. According to these problems, we put forward stochasticmodel order reduction method under random input conditions to facilitate fast time and frequency domain analyses; the method makes use of polynomial chaos expansions in terms of the random input variables for the matrices of a finite element model of the system and then uses its transformation matrix to reduce the model; the method is independent of the MOR algorithm, so it is seamlessly compatible with MOR method used in popular finite element solvers. The simulation results verify the method is effective in large scale MEMS design process.

• 出版日期2015
• 单位杭州电子科技大学; 浙江外国语学院