Inverse Analysis: A Tool for Model Parameter Estimation (original) (raw)

This paper reports the development of a generalized inverse analysis formulation for the parameter estimation of four-parameter Burger model that is used to represent the time-dependent deformation of a viscoelastic soil medium such as a consolidating clay stratum. Aided by a suitable optimization technique (Sequential Quadratic Programming, SQP), a mathematical programming has been developed in terms of identification of the design vector, objective function and design constraints. In order to comprehend the efficacy and establish the proper functionality of the developed technique, a synthetic case study accounting only the loading cycle of the Burger model has been considered. Prime issues related to the back-estimation of the parameters namely identification of variable bounds, global optimality and optimal number of data-points required are explored and reported herein. The efficacy of the developed technique is also illustrated with a case-study.