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Shahram Pezeshk

Researcher at University of Memphis

Publications -  116
Citations -  2452

Shahram Pezeshk is an academic researcher from University of Memphis. The author has contributed to research in topics: Seismic analysis & Peak ground acceleration. The author has an hindex of 22, co-authored 112 publications receiving 2083 citations. Previous affiliations of Shahram Pezeshk include University of Illinois at Urbana–Champaign.

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Optimized Design of Two-Dimensional Structures Using a Genetic Algorithm

TL;DR: A design procedure incorporating a simple genetic algorithm (GA) is developed for discrete optimization of two-dimensional structures.
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Design of Nonlinear Framed Structures Using Genetic Optimization

TL;DR: This paper employs a group selection mechanism, discusses an improved adapting crossover operator, and provides recommendations on the penalty function selection, and compares the differences between optimized designs obtained by linear and geometrically nonlinear analyses.
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Selection and Scaling of Ground Motion Time Histories for Structural Design Using Genetic Algorithms

TL;DR: The proposed method is capable of searching a set consisting of thousands of earthquake records and recommending a desired subset of records that match the target design spectrum with minimal tampering and the least mean square of deviation from the target spectrum.
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Flexural Design of Reinforced Concrete Frames Using a Genetic Algorithm

TL;DR: In this article, a design procedure implementing a genetic algorithm is developed for discrete optimization of reinforced concrete frames, which conforms to the American Concrete Institute (ACI!) Building Code and Commentary, and demonstrates the efficiency of the procedure for the flexural design of simply-supported beams, uniaxial columns, and multi-story frames.
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Hybrid Empirical Ground-Motion Prediction Equations for Eastern North America Using NGA Models and Updated Seismological Parameters

TL;DR: In this article, a hybrid empirical method is used to develop a new GMPE for ENA, using five new ground-motion prediction models developed by the Pacific Earthquake Engineering Research Center (PEER) for WNA.