Application of unconstrained optimization and sensitivity analysis to calibration of a soil constitutive model

Large sets of soil experimental data (field and laboratory) are becoming increasingly available for calibration of soil constitutive models. A challenging task is to calibrate a potentially large number of model parameters to satisfactorily match many data sets simultaneously. This calibration effort can be facilitated by optimization techniques. The current study aims to explore systematic approaches for exercising optimization and sensitivity analysis in the area of soil constitutive modelling. Analytical, semi‐analytical and numerical optimization techniques are employed to calibrate a multi‐surface‐plasticity sand model. Calibration is based on results from a number of drained triaxial sample tests and a dynamic centrifuge liquefaction test. The analytical and semi‐analytical approaches and associated sensitivity analysis are applied to calibrate the model non‐linear shear stress–strain response. Thereafter, model parameters controlling shear–volume coupling effects (dilatancy) are calibrated using a solid–fluid fully coupled finite element program in conjunction with an advanced numerical optimization code. A related sensitivity study reveals the challenges often encountered in optimizing highly non‐linear functions. Overall, this study demonstrates applicability and limitations of optimization techniques for constitutive model calibration.