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This paper presents a concept for the application of particle swarm optimization in geotechnical engineering. For the calculation of deformations in soil or rock, numerical simulations based on continuum methods are widely used. The material behavior is modeled using constitutive relations that require sets of material parameters to be specified. We present an inverse parameter identification technique, based on statistical analyses and a particle swarm optimization algorithm, to be used in the calibration process of geomechanical models. Its application is demonstrated with typical examples from the fields of soil mechanics and engineering geology. The results for two different laboratory tests and a natural slope clearly show that particle swarms are an efficient and fast tool for finding improved parameter sets to represent the measured reference data.

Inverse Parameter Identification Technique Using PSO Algorithm Applied to Geotechnical Modeling