Statistical inverse analysis based on genetic algorithm and principal component analysis: Applications to excavation problems and pressuremeter tests

S. Levasseur (1, 2) , Y. Malecot (3, 4) , M. Boulon (3) , E. Flavigny (3)

1 Université de Liège
2 FNRS - Fonds National de la Recherche Scientifique [Bruxelles]
3 3SR - Laboratoire sols, solides, structures - risques [Grenoble]
4 RV - Risques, Vulnérabilité des structures et comportement mécanique des matériaux

This study concerns the identification of constitutive models from geotechnical measurements by inverse analysis. Soil parameters are identified from measured horizontal displacements of sheet pile walls and from a measured pressuremeter curve. An optimization method based on a genetic algorithm (GA) and a principal component analysis (PCA), developed and tested on synthetic data in a previous paper, is applied. These applications show that the conclusions deduced from synthetic problems can be extrapolated to real problems. The GA is a robust optimization method that is able to deal with the non-uniqueness of the solution in identifying a set of solutions for a given uncertainty on the measurements. This set is then characterized by a PCA that gives a first-order approximation of the solution as an ellipsoid. When the solution set is not too curved in the research space, this ellipsoid characterizes the soil properties considering the measured data and the tolerate margins for the response of the numerical model. Besides, optimizations from different measurements provide solution sets with a common area in the research space. This intersection gives a more relevant and accurate identification of parameters. Finally, we show that these identified parameters permit to reproduce geotechnical measurements not used in the identification process. © 2009 John Wiley & Sons, Ltd.

Mots clés: First-order approximations; Geotechnical measurement; Horizontal displacements; Identification process; Identified parameter; Measured data; Nonuniqueness; Numerical models; Optimization method; Pressuremeter test; Pressuremeter tests; Pressuremeters; Real problems; Robust optimization method; Sheet pile wall; Soil parameter identification; Soil parameters; Soil property; Solution set; Synthetic data; Synthetic problem; Genetic algorithms; Geologic models; Inverse problems; Parameter estimation; Soil testing; Soils; Statistical tests; excavation; genetic algorithm; identification method; inverse analysis; numerical model; optimization; parameterization; pressuremeter; principal component analysis; uncertainty analysis; underground construction

Domaines: Mécanique [physics.med-ph]

S. Levasseur, Y. Malecot, M. Boulon, E. Flavigny. Statistical inverse analysis based on genetic algorithm and principal component analysis: Applications to excavation problems and pressuremeter tests. International Journal for Numerical and Analytical Methods in Geomechanics, 2010, 34 (5), pp.471-491. ⟨hal-01998310⟩