Parameter identification for lined tunnels in a viscoplastic medium

Lecampion, Brice; Constantinescu, Andreï; Minh, Đức Nguyễn

doi:10.1002/nag.241

Cited by 37 publications

(14 citation statements)

References 19 publications

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“…Deterministic algorithms. Single-objective inverse problems in the geotechnical area have been commonly carried out by using gradient methods [15][16][17][18][19][20]. However, the robustness of the simplex method [21], also known as the Nelder and Mead downhill method, has been preferred by Gioda [5] because it does not require the derivative of the error function contrary to the algorithms based on local gradients.…”

Section: Optimization Algorithmsmentioning

confidence: 99%

Single‐and multi‐objective genetic algorithm optimization for identifying soil parameters

Papon¹,

Riou²,

Dano³

et al. 2011

Num Anal Meth Geomechanics

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SUMMARYThis paper discusses the quality of the procedure employed in identifying soil parameters by inverse analysis. This procedure includes a FEM-simulation for which two constitutive models-a linear elastic perfectly plastic Mohr-Coulomb model and a strain-hardening elasto-plastic model-are successively considered. Two kinds of optimization algorithms have been used: a deterministic simplex method and a stochastic genetic method. The soil data come from the results of two pressuremeter tests, complemented by triaxial and resonant column testing. First, the inverse analysis has been performed separately on each pressuremeter test. The genetic method presents the advantage of providing a collection of satisfactory solutions, among which a geotechnical engineer has to choose the optimal one based on his scientific background and/or additional analyses based on further experimental test results. This advantage is enhanced when all the constitutive parameters sensitive to the considered problem have to be identified without restrictions in the search space. Second, the experimental values of the two pressuremeter tests have been processed simultaneously, so that the inverse analysis becomes a multi-objective optimization problem. The genetic method allows the user to choose the most suitable parameter set according to the Pareto frontier and to guarantee the coherence between the tests. The sets of optimized parameters obtained from inverse analyses are then used to calculate the response of a spread footing, which is part of a predictive benchmark. The numerical results with respect to both the constitutive models and the inverse analysis procedure are discussed.

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Section: Optimization Algorithmsmentioning

confidence: 99%

Single‐and multi‐objective genetic algorithm optimization for identifying soil parameters

Papon¹,

Riou²,

Dano³

et al. 2011

Num Anal Meth Geomechanics

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show abstract

“…The gradient based methods are efficient, and amongst them we have chosen the Levenberg-Marquardt algorithm which is an improvement of the Gauss-Newton method. It is easy to implement and has been widely used in the identification problems in the mechanical field (Mahken and Stein, 1996;Lecampion et al, 2002). Moreover, it is well adapted for the inverse problems aiming at identifying parameters, for which the second order terms can easily be neglected in the derivatives of the cost functional near its minimum.…”

Section: Minimisation Algorithmmentioning

confidence: 99%

“…A review of those methods is given in Tarantola (1987), Bonnans et al (1997) and Gill et al (1982). Such methods have been commonly used for parameter identification for elastic materials in geomechanics (Ledesma et al, 1996;Swoboda et al, 1999) and more recently for elasto-plastic and elasto-viscoplastic media in the context of geomechanics (Lecampion, 2002;Lecampion et al, 2002) and materials science (Mahnken and Stein, 1996). Tonon et al (2001) used such an identification procedure to assess the far-field state of stress in a rock mass with non-linear behaviour around a tunnel.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional finite element modelling of stress relaxation tests in anisotropic clayey medium: direct problem and back analysis

2006

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This paper deals with a new strategy for initial stress identification by stress relaxation methods, coupled with finite element calculation, and applied to the overcoring test. The back-analysis of such a test uses an inversion method which consists in the minimisation, with a gradient-based algorithm, of a cost functional of least-squares type, which quantizes the difference between measured and computed strains. The computed strains are assessed by three-dimensional finite element modellings of the overcoring test. The inversion methodology is applied to a recent in situ overcoring test performed at Mont Terri laboratory, Switzerland. The inversion gave good results and allows us to validate the inversion methodology. The constitutive law considered for this application is transverse isotropic elasticity but the inversion method developed is applicable to most constitutive laws and every kind of in situ test.

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“…These applications involved different kinds of tests, such as laboratory tests (Calvello and Finno, 2004) and field tests (Lecampion et al, 2002;Yin and Hicher, 2008;Papon et al, 2012), which were performed on different soils. Different constitutive models, such as the Mohr-Coulomb model (Papon et al, 2012), hardening soil model (Calvello and Finno, 2004;Papon et al, 2012), and modified Cam clay model (Dano et al, 2007), have been adopted and combined with these tests in the optimization process to identify their parameters.…”

Section: Introductionmentioning

confidence: 99%

An efficient parameter identification procedure for soft sensitive clays

Liang

Jin

Shen

et al. 2016

JZUS-A

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Abstract:The creep and destructuration characteristics of soft clay are always coupled under loading, making it difficult for engineers to determine these related parameters. This paper proposes a simple and efficient optimization procedure to identify both creep and destructuration parameters based on low cost experiments. For this purpose, a simplex algorithm (SA) with random samplings is adopted in the optimization. Conventional undrained triaxial tests are performed on Wenzhou clay. The newly developed creep model accounting for the destructuration is enhanced by anisotropy of elasticity and adopted to simulate tests. The optimal parameters are validated first by experimental measurements, and then by simulating other tests on the same clay. Finally, the proposed procedure is successfully applied to soft Shanghai clay. The results demonstrate that the proposed optimization procedure is efficient and reliable in identifying creep and destructuration related parameters.

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Parameter identification for lined tunnels in a viscoplastic medium

Cited by 37 publications

References 19 publications

Single‐and multi‐objective genetic algorithm optimization for identifying soil parameters

Single‐and multi‐objective genetic algorithm optimization for identifying soil parameters

Three-dimensional finite element modelling of stress relaxation tests in anisotropic clayey medium: direct problem and back analysis

An efficient parameter identification procedure for soft sensitive clays

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