A METHOD FOR CALCULATING STRUCTURAL RELIABILITY OF MEMS SYSTEMS BY THE IMPLICIT FUNCTIONAL FUNCTION.

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Bibliographic Details
Title:	A METHOD FOR CALCULATING STRUCTURAL RELIABILITY OF MEMS SYSTEMS BY THE IMPLICIT FUNCTIONAL FUNCTION.
Authors:	DU, Juan¹ djsd2007@126.com, LI, Haibin², HE, Yun³ heyun1021@163.com
Source:	Thermal Science. 2026, Vol. 30 Issue 2A, p961-971. 11p.
Subjects:	Structural reliability, Microelectromechanical systems, Structural analysis (Engineering), Computer simulation, Implicit functions, Nonlinear statistical models, Artificial neural networks
Abstract:	In this paper, a novel approach to calculate the structural reliability of micro-electro-mechanical systems systems is proposed. This approach utilizes the implicit functional function, which involves the acquisition of multiple sets of inputs and responses of the structure through numerical simulation or experimentation. Concurrently, the exponential function is employed as the activation function of the hidden layer of the neural network. A multi-layer neural network possesses the capacity to approximate the properties of arbitrary non-linear functions with arbitrary precision and construct a customized neural network structure. The training of this customized neural network enables the visualization and expression of the structural function. This approach has been demonstrated to enhance the precision of functional fitting. The proposed method for modeling complex structural systems reliability is substantiated by numerical examples. Micro-electro-mechanical systems play a pivotal role in modern engineering, and their integration has the potential to further enhance structural analysis and reliability assessment. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	In this paper, a novel approach to calculate the structural reliability of micro-electro-mechanical systems systems is proposed. This approach utilizes the implicit functional function, which involves the acquisition of multiple sets of inputs and responses of the structure through numerical simulation or experimentation. Concurrently, the exponential function is employed as the activation function of the hidden layer of the neural network. A multi-layer neural network possesses the capacity to approximate the properties of arbitrary non-linear functions with arbitrary precision and construct a customized neural network structure. The training of this customized neural network enables the visualization and expression of the structural function. This approach has been demonstrated to enhance the precision of functional fitting. The proposed method for modeling complex structural systems reliability is substantiated by numerical examples. Micro-electro-mechanical systems play a pivotal role in modern engineering, and their integration has the potential to further enhance structural analysis and reliability assessment. [ABSTRACT FROM AUTHOR]
ISSN:	03549836
DOI:	10.2298/TSCI2602961D