Probabilistic analysis of the inverse analysis of an excavation problem
Résumé
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. © 2010 Elsevier Ltd. All rights reserved.
Mots clés
Confidence interval
Construction projects
Field test
Geotechnical structure
In-situ measurement
Input datas
Numerical models
Probabilistic analysis
Sheet piles
Simple geometries
Soil parameters
Stochastic finite element method
Computational mechanics
Construction industry
Genetic algorithms
Geologic models
Soil surveys
Soils
Stochastic models
Stochastic systems
excavation
finite element method
genetic algorithm
inverse analysis
numerical model
prediction
probability
sheet piled wall
stochasticity