Estimating Target Displacement in Nonlinear Dynamic Analysis Using ANNs
Publish Year: 1395
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
RCEAUD02_347
تاریخ نمایه سازی: 16 شهریور 1395
Abstract:
Predicting the response of structures subjected to specific earthquake has attracted a deal of attention over the last decades and its result has been used as an index to present the status of structures under seismic loads. For this purpose, nonlinear static and dynamic analyses have been commonly used. Nonlinear dynamic analysis approach is more accurate method for predicting the structural response under seismic excitation, but this method is time-consuming. In this research, by using the series of single degree of freedom (SDOF) structures with different structural parameters and some earthquake records, it has been tried to determine amount of maximum displacement of various SDOF structures. This displacement depends on structural and record parameters like PGA and frequency content. For predicting the amount of structural response an artificial neural network has been created for each kind of data, depending on the soil parameters and hysteresis behavior of members. For training the network, thousands of generated data have been used. The test results have been compared with real data and finally the developed method has been utilized for predicting the response of some real structures under different earthquake records. In these analyses some parameters of structures which can affect the amount of response have been considered. The results indicated that it is possible to estimate the target displacement of the multi degree of freedom (MDOF) structures without performing nonlinear dynamic analysis. Also this approach can be utilized as an alternative method for predicting the target displacement in nonlinear static analysis with methods which have been proposed in FEMA356 and ATC40.
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Authors
Benyamin Mohebi
Assistant Professor, Imam Khomeini International University, Qazvin, Iran
Matin Hajikazemi
M.Sc. Imam Khomeini International University, Qazvin, Iran