A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling

This paper presents a systematic and efficient design approach for the two degree-of-freedom (2-DoF) capacitive microelectromechanical systems (MEMS) accelerometer by using combined design and analysis of computer experiments (DACE) and Gaussian process (GP) modelling. Multiple output responses of t...

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Autores principales:	Shayaan Saghir, Muhammad Mubasher Saleem, Amir Hamza, Kashif Riaz, Sohail Iqbal, Rana Iqtidar Shakoor
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	microelectromechanical systems (MEMS) design and analysis of computer experiments (DACE) Gaussian process (GP) finite element method (FEM) multiphysics optimization Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/fbddf3b1230e41ebbc9b2460ce959f04
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spelling	oai:doaj.org-article:fbddf3b1230e41ebbc9b2460ce959f042021-11-11T19:12:39ZA Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling10.3390/s212172421424-8220https://doaj.org/article/fbddf3b1230e41ebbc9b2460ce959f042021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7242https://doaj.org/toc/1424-8220This paper presents a systematic and efficient design approach for the two degree-of-freedom (2-DoF) capacitive microelectromechanical systems (MEMS) accelerometer by using combined design and analysis of computer experiments (DACE) and Gaussian process (GP) modelling. Multiple output responses of the MEMS accelerometer including natural frequency, proof mass displacement, pull-in voltage, capacitance change, and Brownian noise equivalent acceleration (BNEA) are optimized simultaneously with respect to the geometric design parameters, environmental conditions, and microfabrication process constraints. The sampling design space is created using DACE based Latin hypercube sampling (LHS) technique and corresponding output responses are obtained using multiphysics coupled field electro–thermal–structural interaction based finite element method (FEM) simulations. The metamodels for the individual output responses are obtained using statistical GP analysis. The developed metamodels not only allowed to analyze the effect of individual design parameters on an output response, but to also study the interaction of the design parameters. An objective function, considering the performance requirements of the MEMS accelerometer, is defined and simultaneous multi-objective optimization of the output responses, with respect to the design parameters, is carried out by using a combined gradient descent algorithm and desirability function approach. The accuracy of the optimization prediction is validated using FEM simulations. The behavioral model of the final optimized MEMS accelerometer design is integrated with the readout electronics in the simulation environment and voltage sensitivity is obtained. The results show that the combined DACE and GP based design methodology can be an efficient technique for the design space exploration and optimization of multiphysics MEMS devices at the design phase of their development cycle.Shayaan SaghirMuhammad Mubasher SaleemAmir HamzaKashif RiazSohail IqbalRana Iqtidar ShakoorMDPI AGarticlemicroelectromechanical systems (MEMS)design and analysis of computer experiments (DACE)Gaussian process (GP)finite element method (FEM)multiphysicsoptimizationChemical technologyTP1-1185ENSensors, Vol 21, Iss 7242, p 7242 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	microelectromechanical systems (MEMS) design and analysis of computer experiments (DACE) Gaussian process (GP) finite element method (FEM) multiphysics optimization Chemical technology TP1-1185
spellingShingle	microelectromechanical systems (MEMS) design and analysis of computer experiments (DACE) Gaussian process (GP) finite element method (FEM) multiphysics optimization Chemical technology TP1-1185 Shayaan Saghir Muhammad Mubasher Saleem Amir Hamza Kashif Riaz Sohail Iqbal Rana Iqtidar Shakoor A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling
description	This paper presents a systematic and efficient design approach for the two degree-of-freedom (2-DoF) capacitive microelectromechanical systems (MEMS) accelerometer by using combined design and analysis of computer experiments (DACE) and Gaussian process (GP) modelling. Multiple output responses of the MEMS accelerometer including natural frequency, proof mass displacement, pull-in voltage, capacitance change, and Brownian noise equivalent acceleration (BNEA) are optimized simultaneously with respect to the geometric design parameters, environmental conditions, and microfabrication process constraints. The sampling design space is created using DACE based Latin hypercube sampling (LHS) technique and corresponding output responses are obtained using multiphysics coupled field electro–thermal–structural interaction based finite element method (FEM) simulations. The metamodels for the individual output responses are obtained using statistical GP analysis. The developed metamodels not only allowed to analyze the effect of individual design parameters on an output response, but to also study the interaction of the design parameters. An objective function, considering the performance requirements of the MEMS accelerometer, is defined and simultaneous multi-objective optimization of the output responses, with respect to the design parameters, is carried out by using a combined gradient descent algorithm and desirability function approach. The accuracy of the optimization prediction is validated using FEM simulations. The behavioral model of the final optimized MEMS accelerometer design is integrated with the readout electronics in the simulation environment and voltage sensitivity is obtained. The results show that the combined DACE and GP based design methodology can be an efficient technique for the design space exploration and optimization of multiphysics MEMS devices at the design phase of their development cycle.
format	article
author	Shayaan Saghir Muhammad Mubasher Saleem Amir Hamza Kashif Riaz Sohail Iqbal Rana Iqtidar Shakoor
author_facet	Shayaan Saghir Muhammad Mubasher Saleem Amir Hamza Kashif Riaz Sohail Iqbal Rana Iqtidar Shakoor
author_sort	Shayaan Saghir
title	A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling
title_short	A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling
title_full	A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling
title_fullStr	A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling
title_full_unstemmed	A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling
title_sort	systematic design optimization approach for multiphysics mems devices based on combined computer experiments and gaussian process modelling
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/fbddf3b1230e41ebbc9b2460ce959f04
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A Systematic Design Optimization Approach for Multiphysics MEMS Devices Based on Combined Computer Experiments and Gaussian Process Modelling

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