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Prediction of spectral acceleration of a light structure with a flexible secondary system using artificial neural networks

Prediction of spectral acceleration of a light structure with a flexible secondary system using... The effect of a flexible secondary system (FSS) on the design spectra is studied in this paper. An FSS affects the primary structure (PS) during ground excitation differently than a secondary system that is rigidly attached to it. A modal superposition analysis is performed on a 2DOF system (PS + FSS). The influence of various parameters such as mass ratio and length of FSS on the design spectra is addressed. A methodology to estimate the spectral acceleration of the PS with FSS is developed. A design expression is proposed using statistical nonlinear regression and artificial neural network (ANN) to estimate the spectral acceleration of PS with FSS as a function of the structural period, length of FSS, and mass ratio. ANN modelling is proved to be more efficient than nonlinear regression model. An example calculation is shown for the estimation of spectral acceleration of the PS using ANN and nonlinear regression models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Structural Engineering Inderscience Publishers

Prediction of spectral acceleration of a light structure with a flexible secondary system using artificial neural networks

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1758-7328
eISSN
1758-7336
DOI
10.1504/IJSTRUCTE.2020.109857
Publisher site
See Article on Publisher Site

Abstract

The effect of a flexible secondary system (FSS) on the design spectra is studied in this paper. An FSS affects the primary structure (PS) during ground excitation differently than a secondary system that is rigidly attached to it. A modal superposition analysis is performed on a 2DOF system (PS + FSS). The influence of various parameters such as mass ratio and length of FSS on the design spectra is addressed. A methodology to estimate the spectral acceleration of the PS with FSS is developed. A design expression is proposed using statistical nonlinear regression and artificial neural network (ANN) to estimate the spectral acceleration of PS with FSS as a function of the structural period, length of FSS, and mass ratio. ANN modelling is proved to be more efficient than nonlinear regression model. An example calculation is shown for the estimation of spectral acceleration of the PS using ANN and nonlinear regression models.

Journal

International Journal of Structural EngineeringInderscience Publishers

Published: Jan 1, 2020

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