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Probabilistic analysis of the inverse analysis of an excavation problem
Authors:J. Baroth  Y. Malecot
Affiliation:Université Joseph Fourier – Grenoble I, Laboratoire Sols Solides Structures – Risques, CNRS UMR 5521, BP 53, 38041 Grenoble Cedex 9, France
Abstract:This study presents the probabilistic analysis of the inverse analysis of an excavation problem. Two techniques are used during two successive stages. First, a genetic algorithm inverse analysis is conducted to identify soil parameters from in situ measurements (i.e. first stage of the construction project). For a given tolerable error between the measurement and the response of the numerical model the genetic algorithm is able to generate a statistical set of soil parameters, which may then serve as input data to a stochastic finite element method. The second analysis allows predicting a confidence interval for the final behaviour of the geotechnical structure (i.e. second stage of the project). The tools employed in this study have already been presented in previous papers, but the originality herein consists of coupling them. To illustrate this method, a synthetic excavation problem with a very simple geometry is used.
Keywords:Prediction   Inverse analysis   Genetic algorithm   Stochastic finite element method   Excavation   Sheetpile wall field test
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