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Showing 2 results for Iraji

G. Ghodrati Amiri, K. Iraji , P. Namiranian,
Volume 4, Issue 1 (3-2014)
Abstract

The Hartley transform, a real-valued alternative to the complex Fourier transform, is presented as an efficient tool for the analysis and simulation of earthquake accelerograms. This paper is introduced a novel method based on discrete Hartley transform (DHT) and radial basis function (RBF) neural network for generation of artificial earthquake accelerograms from specific target spectrums. Acceleration time histories of horizontal earthquake ground motion are obtained by the capability of learning of RBF neural network to expand the knowledge of the inverse mapping from the response spectrum to earthquake accelerogram. In the first step, Hartley transform is used to decompose earthquake accelerograms, then a RBF neural network is trained to learn to relate the response spectrum to Hartley spectrum. Finally, the generated accelerogram using inverse discrete Hartley transform is obtained from target spectrum. Approximately 200 uniformly scaled horizontal ground motion records from recent Iran’s earthquakes are used to decompose with real Hartley transform and train networks.
M. Danesh, A. Iraji,
Volume 10, Issue 4 (10-2020)
Abstract

The efficiency of braced structures depends significantly on structure response under seismic loads. The main design challenge for these type of structures is to select shape, number of spans, and type of connections appropriately. Therefore, introducing an optimized and cost-effective design including a certain level of safety and performance against natural hazards seems to be an inevitable necessity. The present work introduces a performance-based design for braced steel structures as well as an optimized arrangement of braces and connection types via using finite difference algorithm. The results show that the latter two factors are very important and necessary to achieve an optimized design for braced steel structures.

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