Garuda - Garba Rujukan Digital

Rahmani, Iraj

Salehan Institute of Higher Education

Author-ID : 844846

Civil Engineering, Building, Construction & Architecture

Published : 2 Documents Claim Missing Document

Claim Missing Document

Articles

Title

1

Numerical Comparison of the Performance of Genetic Algorithm and Particle Swarm Optimization in Excavations Hashemi, Seyyed Mohammad; Rahmani, Iraj
Civil Engineering Journal Vol 4, No 9 (2018): September
Publisher : Salehan Institute of Higher Education

Today, the back analysis methods are known as reliable and effective approaches for estimating the soil strength parameters in the site of project. The back analysis can be performed by genetic algorithm and particle swarm optimization in the form of an optimization process. In this paper, the back analysis is carried out using genetic algorithm and particle swarm optimization in order to determine the soil strength parameters in an excavation project in Tehran city. The process is automatically accomplished by linking between MATLAB and Abaqus software using Python programming language. To assess the results of numerical method, this method is initially compared with the results of numerical studies by Babu and Singh. After the verification of numerical results, the values of the three parameters of elastic modulus, cohesion and friction angle (parameters of the MohrâCoulomb model) of the soil are determined and optimized for three soil layers of the project site using genetic algorithm and particle swarm optimization. The results optimized by genetic algorithm and particle swarm optimization show a decrease of 72.1% and 62.4% in displacement differences in the results of project monitoring and numerical analysis, respectively. This research shows the better performance of genetic algorithm than particle swarm optimization in minimization of error and faster success in achieving termination conditions.

Determination of Multilayer Soil Strength Parameters Using Genetic Algorithm Hashemi, Seyyed Mohammad; Rahmani, Iraj
Civil Engineering Journal Vol 4, No 10 (2018): October
Publisher : Salehan Institute of Higher Education

This paper employs a back analysis method to determine soil strength parameters of the Mohr-Coulomb model from in situ geotechnical measurements. The lateral displacement of a soil nailed wall retaining an excavation in Tehran city used as a criterion for the back analysis. For this purpose, a genetic algorithm is applied as an optimization algorithm to minimize the error function, which can perform the back analysis process. When the accuracy of modeling is verified, the back analysis is performed automatically by creating a link between genetic algorithm in MATLAB and Abaqus software using Python programming language. This paper demonstrated that the genetic algorithm is a particularly suitable tool to determine 9 soil strength parameters simultaneously for 3 soil layers of the project site to decrease the difference of lateral displacement between the results of project monitoring and numerical analysis. The soil strength parameters have increased, with the most changes in Young's modulus of the first to third layers as the most effective parameter, 49.45%, 61.67% and 64.35% respectively. The results can be used in advanced engineering analyses and professional works.

Title Search

Found 2 Documents Search Journal : Civil Engineering Journal

Abstract

Abstract

Title

Found 2 Documents
Search
Journal : Civil Engineering Journal