On the automatic parameter calibration of a hypoplastic soil model

Abstract This paper presents an approach for the automatic parameter calibration (AC) of a hypoplastic constitutive soil model. The software developed in this work simplifies calibration, reduces subjective “human” factor on result and lowers entry hurdle use performance was demonstrated by comparing automatically calibrated sets two sands their related simulations underlying experimental data with using reference sets. first set classical way, "by hand", second AC tool ExCalibre. Two different optimization methods were used, namely Differential Evolution (DE) Particle Swarm Optimization (PSO). performed parameters obtained from agree well show improvements over With respect to method, DE proved superior that PSO. Various measures comparison examined quantify discrepancy between experiment simulation. By repeating 500 runs, dispersion determined correlations model found.