This paper presents a concept for the application of particle swarm optimization in geotechnical engineering. For the calculationof deformations in soil or rock, numerical simulations based on continuum methods are widely used. The material behavior ismodeled using constitutive relations that require sets of material parameters to be specified. We present an inverse parameteridentification technique, based on statistical analyses and a particle swarm optimization algorithm, to be used in the calibrationprocess of geomechanical models. Its application is demonstrated with typical examples from the fields of soil mechanics andengineering geology. The results for two different laboratory tests and a natural slope clearly show that particle swarms are anefficient and fast tool for finding improved parameter sets to represent the measured reference data
Inverse Parameter Identification Technique using PSO Algorithm applied to Geotechnical Modelling / Meier, J.; Schaedler, W.; Borgatti, L.; Corsini, Alessandro; Schanz, T.. - In: JOURNAL OF ARTIFICIAL EVOLUTION AND APPLICATIONS. - ISSN 1687-6229. - ELETTRONICO. - vol. 2008:(2008), pp. 1-14.
Inverse Parameter Identification Technique using PSO Algorithm applied to Geotechnical Modelling
CORSINI, Alessandro;
2008
Abstract
This paper presents a concept for the application of particle swarm optimization in geotechnical engineering. For the calculationof deformations in soil or rock, numerical simulations based on continuum methods are widely used. The material behavior ismodeled using constitutive relations that require sets of material parameters to be specified. We present an inverse parameteridentification technique, based on statistical analyses and a particle swarm optimization algorithm, to be used in the calibrationprocess of geomechanical models. Its application is demonstrated with typical examples from the fields of soil mechanics andengineering geology. The results for two different laboratory tests and a natural slope clearly show that particle swarms are anefficient and fast tool for finding improved parameter sets to represent the measured reference dataFile | Dimensione | Formato | |
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