Data assimilation strategies for parameter identification of elasto-plastic geomaterials and its application to geotechnical practice

The objective of this study is to demonstrate the numerical and the practical applicability of the particle filter (PF) to some geotechnical problems, i.e., the parameter identification of elasto-plastic geomaterials and the prediction of the deformation behavior of soil deposits and geotechnical structures, by applying the methodology to hypothetical experiments and an actual construction project. The results of the hypothetical experiments reveal that the parameters identified by the PF, based on the sequential importance sampling (SIS) algorithm, have converged into their true values, and that the approach presented herein can provide a highly accurate parameter identification strategy for elasto-plastic geomaterials. Moreover, the simulation results using the identified parameters are close to the actual observation data, and the ensemble-based approach produces more information about the parameters of interest than simple estimated values obtained from optimization methods. In other words, the identification comes in the form of a probability density function.