期刊
INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
卷 33, 期 12, 页码 1485-1511出版社
WILEY
DOI: 10.1002/nag.776
关键词
soil parameters identification; inverse analysis; optimization; genetic algorithm; principal component analysis; finite element method; geotechnics; synthetic data
This study concerns the identification of parameters of soil constitutive models front geotechnical measurements by inverse analysis. To deal with the non-uniqueness of the solution, the inverse analysis is based on a genetic algorithm (GA) optimization process. For a given uncertainty oil the measurements, the GA identifies a set of solutions. A statistical method based on a principal component analysis (PCA) is, then, proposed to evaluate the representativeness of this set. It is shown that this representativeness is controlled by the GA population size for which an optimal value can be defined. The PCA also gives a first-order approximation of the Solution set of the inverse problem as an ellipsoid. These developments are first made oil a synthetic excavation problem and oil a pressuremeter test. Some experimental applications are, then, studied in a companion paper, to show the reliability of the method. Copyright (C) 2009 John Wiley & Sons, Ltd.
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