Optimization Methods for Parametric Identification of Geotechnical Systems

Abstract

Parameters which characterize geotechnical systems and are representative of the behaviour of soil or rock masses are often known with a high degree of uncertainty. A way of reducing uncertainties and thus improving the mathematical models for analysis and design purposes is provided by a systematic adjustment of parameters so that theoretical predictions through the model match observational data. This identification or “inverse” problem frequently implies recourse to techniques of mathematical optimization and particularly of mathematical programming. This paper concerns the role played in this context by direct search methods, least squares procedures and quadratic and nonlinear programming for identifying parameters in purely numerical models, linear models and linear complementarity models, respectively. A procedure of statistical identification is briefly mentioned at the end. The scope is not to survey the field but merely to elucidate some aspects and potentialities of identification methods in geomechanics on the basis of a variety of recent results on particular problems.