Showing 3 results for Sohrabi
M. Kamalian and A. Sohrabi Bidar,
Volume 24, Issue 2 (1-2006)
Abstract
This paper presents the complete algorithm of site response analysis of nonhomogeneous topographic structures using transient two-dimensional boundary element method (BEM). Seismic behaviour of various topographic features including canyon, half plane, sedimentary filled valley and ridge sections, subjected to incident SV and P waves are analysed. The analysis shows the efficiency of the proposed algorithm and its advantage over common transformed domains methods in forming a basis for extension to non-linear behaviour.
M. Kamalian, M.k. Jafari and A. Sohrabi-Bidar,
Volume 26, Issue 1 (7-2007)
Abstract
This paper presents the preliminary results of an extensive parametric study on seismic response of two-dimensional semi-sine shaped hills to vertically propagating incident P- and SV-waves. Clear perspectives of the induced diffraction and amplification patterns are given by investigation of time-domain and frequency-domain responses. It is shown that site geometry, wave characteristics , and material parameters are the key parameters governing the hill’s response, simple formula and some tables are proposed for estimating the characteristic site period and also the average amplification potential of semi-sine shaped hills, which could be easily applied in site effect microzonation studies of topographic areas.
R. Ghiasi, M. R. Ghasemi, M. R. Sohrabi,
Volume 36, Issue 1 (9-2017)
Abstract
Utilizing surrogate models based on artificial intelligence methods for detecting structural damages has attracted the attention of many researchers in recent decades. In this study, a new kernel based on Littlewood-Paley Wavelet (LPW) is proposed for Extreme Learning Machine (ELM) algorithm to improve the accuracy of detecting multiple damages in structural systems. ELM is used as metamodel (surrogate model) of exact finite element analysis of structures in order to efficiently reduce the computational cost through updating process. In the proposed two-step method, first a damage index, based on Frequency Response Function (FRF) of the structure, is used to identify the location of damages. In the second step, the severity of damages in identified elements is detected using ELM. In order to evaluate the efficacy of ELM, the results obtained from the proposed kernel were compared with other kernels proposed for ELM as well as Least Square Support Vector Machine algorithm. The solved numerical problems indicated that ELM algorithm accuracy in detecting structural damages is increased drastically in case of using LPW kernel.
