Parameter identification for elasto-plastic modelling of unsaturated soils from pressuremeter tests by parallel modified particle swarm optimization

Abstract This paper presents a methodology for the identification of parameter values in the Barcelona Basic Model (BBM) by inverse analysis of the experimental cavity pressure–cavity strain curve from pressuremeter tests in unsaturated soils. This methodology involves a high-dimensional optimization process which is particularly challenging due to the existence of a large number of local minima caused by the nonlinearity of the BBM. A novel parallel modified particle swarm optimization algorithm is utilized to minimize the difference between measured and computed values on the cavity pressure–cavity strain curve. The computed cavity pressure–cavity strain curve is obtained by using a finite element model of an unsaturated soil whose mechanical behaviour is described by the BBM. An example is presented to validate the proposed methodology making use of artificial experimental results that had been calculated by a finite element simulation of pressuremeter tests. Finally, the application to a real case is presented by showing that the proposed methodology can safely identify the values of at least six BBM parameters via inverse analysis of pressuremeter tests at different suction levels.

[1]  Bernhard A. Schrefler,et al.  Parameter identification for a suction‐dependent plasticity model , 2001 .

[2]  Y. Cui,et al.  Yielding and plastic behaviour of an unsaturated compacted silt , 1996 .

[3]  Guy T. Houlsby,et al.  FINITE CAVITY EXPANSION IN DILATANT SOILS: LOADING ANALYSIS , 1991 .

[4]  John A. Nelder,et al.  A Simplex Method for Function Minimization , 1965, Comput. J..

[5]  Antonio Gens,et al.  A constitutive model for partially saturated soils , 1990 .

[6]  Antonio Gens,et al.  A stress point algorithm for an elastoplastic model in unsaturated soils , 2000 .

[7]  Charles E. Augarde,et al.  Identification of Hydraulic Parameters for Unsaturated Soils Using Particle Swarm Optimization , 2008 .

[8]  Marc Boulon,et al.  Inverse analysis of soil parameters for Finite Element simulation of geotechnical structures: Pressuremeter test and excavation problem , 2004 .

[9]  Domenico Gallipoli,et al.  Development of an Object-Oriented Parallel Finite Element Code for Unsaturated Soils , 2007 .

[10]  Andrew J. Whittle,et al.  Interpretation of pressuremeter tests in sand using advanced soil model , 2002 .

[11]  Andres Alcolea,et al.  Inverse problem in hydrogeology , 2005 .

[12]  Guy T. Houlsby,et al.  A large strain analytical solution for cavity contraction in dilatant soils , 1995 .

[13]  Lyesse Laloui,et al.  Calibration of an elasto-plastic constitutive model by a constrained optimisation procedure , 2006 .

[14]  Marc Boulon,et al.  Statistical inverse analysis based on genetic algorithm and principal component analysis: Applications to excavation problems and pressuremeter tests , 2010 .

[15]  J. Booker,et al.  Cavity expansion in cohesive frictional soils , 1986 .

[16]  A. Gens,et al.  An elasto-plastic model for unsaturated soil incorporating the effects of suction and degree of saturation on mechanical behaviour , 2003 .

[17]  Marc Boulon,et al.  Soil parameter identification using a genetic algorithm , 2008 .

[18]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[19]  Charles E. Augarde,et al.  Simulation-based calibration of geotechnical parameters using parallel hybrid moving boundary particle swarm optimization , 2009 .

[20]  M. Fahey,et al.  A finite element study of the pressuremeter test in sand using a non-linear elastic plastic model , 1993 .

[21]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[22]  Simon J. Wheeler,et al.  An elasto-plastic critical state framework for unsaturated soil , 1995 .

[23]  Charles E. Augarde,et al.  Parallel computing of unsaturated soils using element-by-element and domain decomposition methods , 2007 .

[24]  Fernando Schnaid,et al.  Unsaturated Constitutive Surfaces from Pressuremeter Tests , 2004 .

[25]  R Cudmani,et al.  The cavity expansion problem for the interpretation of cone penetration and pressuremeter tests , 2001 .

[26]  Xia-Ting Feng,et al.  Identification of visco-elastic models for rocks using genetic programming coupled with the modified particle swarm optimization algorithm , 2006 .

[27]  Russell C. Eberhart,et al.  Parameter Selection in Particle Swarm Optimization , 1998, Evolutionary Programming.

[28]  David G. Toll,et al.  The MUSE Network: sharing research expertise on unsaturated soils across Europe , 2006 .

[29]  Domenico Gallipoli,et al.  Parallel Hybrid Particle Swarm Optimization and Applications in Geotechnical Engineering , 2009, ISICA.

[30]  D. Gallipoli,et al.  A sequential method for selecting parameter values in the Barcelona basic model , 2010 .

[31]  Delwyn G. Fredlund,et al.  The relationship of the unsaturated soil shear strength to the soil-water characteristic curve , 1996 .

[32]  Nasser Khalili,et al.  A unified bounding surface plasticity model for unsaturated soils , 2006 .

[33]  D. Gallipoli.  Constitutive and numerical modelling of unsaturated soils , 2000 .

[34]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).