Prediction of Maximum Story Drift of MDOF Structures under Simulated Wind Loads Using Artificial Neural Networks

Omar Payán-Serrano,Manuel Barraza,Héctor Rodríguez-Lozoya,Edgar Corona,Alfredo Reyes-Salazar,Robespierre Chávez,Edén Bojórquez,Arturo López-Barraza,Juan Bojórquez

doi:10.3390/app7060563

Omar Payán-Serrano, Manuel Barraza + Show 7 more

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https://doi.org/10.3390/app7060563

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Journal: Applied sciences	Publication Date: May 30, 2017
Citations: 8	License type: CC BY 4.0

Affiliation: Autonomous University of Sinaloa

Abstract

The aim of this paper is to investigate the prediction of maximum story drift of Multi-Degree of Freedom (MDOF) structures subjected to dynamics wind load using Artificial Neural Networks (ANNs) through the combination of several structural and turbulent wind parameters. The maximum story drift of 1600 MDOF structures under 16 simulated wind conditions are computed with the purpose of generating the data set for the networks training with the Levenberg–Marquardt method. The Shinozuka and Newmark methods are used to simulate the turbulent wind and dynamic response, respectively. In order to optimize the computational time required for the dynamic analyses, an array format based on the Shinozuka method is presented to perform the parallel computing. Finally, it is observed that the already trained ANNs allow for predicting adequately the maximum story drift with a correlation close to 99%.

Highlights

The maximum story drift of Multi-Degree of Freedom (MDOF) structures under wind loads is an important parameter for the structural design; for structural engineers, the estimation of this parameter by dynamic analysis could be impractical
[8,9,10,11].as prediction, classification, data processing, robotic and engineering problems. For this reason, the aim of this study is to evaluate the efficiency of Artificial Neural Networks (ANNs) as computational models theprediction aim of thisofstudy is to evaluate efficiency of ANNs as computational models wind for prediction for the maximum storythe drift of MDOF
Shows taken the mean square error generated for theinANNs with different number small percentage randomly of the(MSE)

Summary

Introduction

The maximum story drift of Multi-Degree of Freedom (MDOF) structures under wind loads is an important parameter for the structural design; for structural engineers, the estimation of this parameter by dynamic analysis could be impractical. Due to the complexity of obtaining synthetic wind records and the dynamic structural response, the engineers have used non-complex methods such as the equivalent static analysis, which tries to consider the dynamic effects of the turbulent wind supported by the use of the well-known dynamic amplification factor [4]. Some modifications and improvements to the equivalent static method, originally presented by Davenport [5], have been proposed by different authors [6,7]. These methods are not complex, they require several calculation steps in order to estimate

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