Numerical modeling and neural networks to identify constitutive parameters from in situ tests

This study proposes a new advanced algorithm for determining material parameters based on in situ tests. In situ testing gives an opportunity to perform soil characterization in natural stress conditions on a representative soil mass. Most field techniques reduce soil disturbances to minimum, allowing investigating the response of virgin soil. Self-boring pressuremeter tests (SBPT) and standard piezocone tests (CPTU) are widely used to deduce properties of clayey soils through analytical and empirical correlations between soil properties and experimental measurements. Empirical correlations usually require some tuning based on reference laboratory data because first-order estimates for typical correlation coefficients may give unreliable evaluation of soil properties. Analytical correlations are mostly based on cavity expansion methods which are restricted to either fully drained or perfectly undrained problems, so that inverse closed-form solutions for relatively simple constitutive models can be derived. In practice, however, depending on physical and consolidation properties of the soil, partially drained conditions may occur during field testing, leading to an erroneous estimation of clay characteristics. Therefore, elaborating a generic parameter identification framework, which is based on the artificial neural network (NN) technique and which may improve the reliability of soil properties derived from in situ testing, is the main goal of this research. This study explores the possibility of using NNs to solve complex inverse problems including partially drained conditions. In other words, NNs are used to map experimental measurements onto set of soil properties. The development of NN-based inverse models is based on a training data sets which consists of pseudo-experimental measurements derived from numerical simulations of both the SBPT and the CPTU test in normally- and lightly overconsolidated clay type material. The study presents a generic two-level procedure designed for the calibration of constitutive models of soils. It is demonstrated that NN inverse models can be easily integrated into the classical back-analysis. At the first level, the NN approach is applied to achieve the first approximation of parameters. This technique is used to avoid potential pitfalls related to the conventional gradient-based optimization (GBO) technique, considered here as a corrector that improves predicted parameters. Trained NNs as parallel operating systems can provide output variables instantly and without a costly GBO iterative scheme. The proposed framework is verified for the elasto-plastic Modified Cam Clay (MCC) model that can be calibrated based on standard triaxial laboratory tests, i.e. the isotropic consolidation test and the consolidated isotropic drained compression test. The study presents formulations of the input data for the NN predictors, enhanced by a dimensional reduction of experimental data using principal component analysis (PCA). The determination of model characteristics is demonstrated, first on numerical pseudo-experiments and then on the experimental data. Furthermore, the efficiency of the proposed approach in terms of accuracy and computational effort is also discussed. The verified two-level strategy is applied to a numerical procedure of parameter identification for the boundary value problem (BVP) of the SBPT. The coupled hydro-mechanical finite element (FE) formulation allows the generated excess pore water pressure to be dissipated during simulations of the expansion test, followed then by a holding test. Numerical simulations demonstrate that volume changes that may occur in clay during the expansion test due to partial drainage, can cause local soil hardening near the cavity wall and affect parameter interpretation for pressuremeter tests. Therefore, the NN technique is applied to obtain an initial guess for model parameters, taking into account the possible partially drained conditions during the expansion test. Parameter identification based on measurements obtained through the pressuremeter expansion test and two types of holding tests is illustrated on the MCC model. NNs are trained using a set of synthetic test samples, which are generated by means of FE simulations based on constrained random permutations of input model parameters. The measurements obtained through expansion and consolidation tests are normalized by the proposed normalizing formulas so that NN predictors operate independently of the testing depth. Examples of parameter determination are demonstrated on both numerical data and field measurements from the Fucino clay deposit. The efficiency of the combined parameter identification in terms of accuracy, effectiveness and computational effort is also discussed. Finally, an application of NN predictors as a stand-alone support for soil profiling is presented for the piezocone test. By similarity to the SBPT problem, a number of NN inverse models are developed based on the results derived from rigorous FE analyzes. The FE model of piezocone penetration involves numerical formulation for the two-phase material obeying the MCC law and including the large strain theory, as well as the large deformation formulation for contact interface. It is demonstrated that a considerable computational effort related to the generation of the training database can be reduced by optimizing the mesh size and "steady-state" depth in function of soil rigidity index. Due to a severe loss of measurement accuracy observed in the finite elements adhered to the "rough" interface, an equivalent semi-numerical approach is proposed to account for frictional effects in different drainage conditions which are delineated from a number of numerical simulations. The validity of the developed penetration model is verified in detail by means of comparisons with other theoretical solutions and parametric studies synthesized from literature, as well as experimental evidence for both undrained and partially drained scenarios. An extended parametric study including influence analyzes of strength and stress anisotropy, rigidity index and cone roughness on two cone factors provides new insight into the analysis of cone penetration. The shortcomings of the FE model due to the limitations of the applied constitutive model are also discussed. As regards NN models, different configurations of input variables, including standard normalized piezocone metrics and other available soil characteristics are investigated in terms of feasibility of effective NN training. The post-training regression analyzes are performed for numerical data allowing the assessment of the influence of specific input variables on accuracy of parameters predictions. Finally, the developed NN models are applied to predict parameters based on field measurements for a number of characterization sites. Provided examples demonstrate that NN inverse models may constitute an effective complementary support during the first-order quantification of the MCC parameters from piezocone measurements.

A combined neural network/gradient-based approach for the identification of constitutive model parameters using self-boring pressuremeter tests

Rafal Filip Obrzud, Laurent Vulliet

This paper presents a numerical procedure of material parameter identification for the coupled hydromechanical boundary value problem (BVP) of the self-boring pressuremeter test (SBPT) in clay. First, the neural network (NN) technique is applied to obtain an initial estimate of model parameters, taking into account the possible drainage conditions during the expansion test. This technique is used to avoid potential pitfalls related to the conventional gradient-based optimization techniques, considered here as a corrector that improves predicted parameters. Parameter identification based on measurements obtained through the pressuremeter expansion test and two types of holding tests is illustrated on the Modified Cam clay model. NNs are trained using a set of test samples, which are generated by means of finite element simulations of SBPT. The measurements obtained through expansion and consolidation tests are normalized so that NN predictors operate independently of the testing depth. Examples of parameter determination are demonstrated on both numerical and field data. The efficiency of the combined parameter identification in terms of accuracy, effectiveness and computational effort is also discussed.

2009

Numerical modeling and neural networks to identify model parameters from piezocone tests: I. FEM analysis of penetration in two-phase continuum

Rafal Filip Obrzud, Andrzej Truty, Laurent Vulliet

This study presents a numerical approach designed for material parameter identification for the coupled hydro-mechanical boundary value problem (BVP) of the piezocone test (CPTU) in normally and lightly overconsolidated clayey soils. The study is presented in two related papers and it explores the possibility of using neural networks (NNs) to solve the complex inverse problem of the penetration test, including partially drained conditions. It has been demonstrated that the development of NN-based inverse models can be based on training data sets that consist of pseudo-experimental measurements derived from numerical simulations of the piezocone test. The first paper presents the development of the FE model of the studied problem, which can be used to generate a training data population corresponding to typical piezocone measurements that are obtained for clayey soils. The paper contains a detailed description of the numerical model with a sensitivity analysis with respect to different model parameters including the effect of partial drainage. The analysis also includes the model verification by means of a comparative analysis with numerical models of penetration proposed in the literature, as well as experimental evidence. Finally, owing to the loss of accuracy observed when applying a 'rough' frictional interface in the Updated Lagrangian formulation, an equivalent semi-numerical model for the piezocone test is proposed, taking into account a possible occurrence of partial drainage during penetration. Copyright (C) 2010 John Wiley & Sons, Ltd.

Wiley-Blackwell2011

Assessment of mechanical properties in unirradiated and irradiated zircaloys and steels with non-standard tests and finite element calculations

Emiliano Campitelli

Nuclear materials have been successfully employed in commercial fission reactors for many decades. Research and material development for advanced fission system and future thermo-nuclear fusion reactors have acquired maturity while great challenges remain to be taken up. The goal of the material scientist is to understand the way neutron irradiation and aggressive reactor environment alter the original material properties and to safely manage the operation conditions for each particular reactor component. In the framework of surveillance programme, the need has arisen to design experimental methods to be used with a limited amount of material for Post Irradiation Examination (PIE) of reactor components to test the integrity of those on a regular time basis. Having to deal with radioactive material, it is particularly important to devise experimental testing procedures as simple as possible but from which reliable information can be drawn. Within materials development programme, irradiations have continuously been performed either in reactors or with particle accelerators. In both cases, the irradiation volumes are usually limited. The concern was to optimize the volume of the irradiated samples in order to increase their number to obtain a good statistical representation of their mechanical behavior after irradiation, and to have a very definite and homogeneous damage dose and irradiation temperature. The concerns explained above originated the development of small-scale specimen testing methods. Advantage is taken of the fact that, within size and geometry limitations, some mechanical properties of a sample are independent of its absolute size. In this way it is possible to perform mechanical tests on samples of reduced volume that represents big advantages to face the aforementioned challenges. Non-standard test on very small specimen have also been proposed to extract mechanical properties of the bulk. If these non-standard testing methods are to be employed for PIE, it becomes necessary to develop modeling tool to understand under what circumstances they can provide useful information and specially how to obtain it. Finite element modeling (FEM) of the non-standard tests has played a key role in this sense, providing a link between standard test analysis and that of the non-standard ones. The goal of this work was to implement finite element models for non-standard tests to ultimately study the mechanical properties of Zircaloy cladding tube and tempered martensitic steels in the unirradiated and irradiated condition. One model was developed for ring tensile tests. It was first validated with a quite ductile iron-chromium ferritic alloy, for which ring and uniaxial tensile test were performed at room temperature. Using the constitutive behavior determined from the uniaxial tensile tests, the load – displacement curves of the ring tensile tests were very well reproduced. Another model was developed for the so-called small ball punch test, which consists in deforming a 3 mm diameter disk clamped between two dies with a ball puncher and to record the load – displacement curve. In order to validate the model, a series of ball punch tests and of tensile tests were carried out on the austenitic steel 316L at room temperature. In this last case, the ball punch test curves were also well reconstructed with the model. Based upon a simple analysis and simulation results, we showed that it is possible to obtain, by ring tensile tests, a quick and accurate assessment of the constitutive behavior of an unknown material, simply by processing the experimental force-elongation data in the same way as for uniaxial tests, taking half the ring perimeter as initial length and twice the ring cross section as the sample cross section. The ring tensile test method was used to determine the hoop mechanical properties of Zircaloy tubes used in fission reactors. Tensile tests were also performed in the axial direction of the Zircaloy tubes. Differences between the yield stress as well as the post-yield behaviors in the axial direction and those in the circumferential direction of the tube could be measured reflecting some component of the anisotropy of the tube. Ball punch specimens were cut also out of the tube in the radial direction and tested. Using the FE model for punch test, in which the anisotropy of the mechanical properties are taken into account through the Hill's theory, the values of the Hill's yield function parameters were estimated. The irradiation hardening of neutron irradiated Zircaloy tube was finally determined. The ball punch test model was extensively used for numerical investigations, to determine how the constitutive behavior of the materials (uniaxial true stress – true strain) employed as input acts in combination with other experimental factors (specimen thickness, friction coefficient) in mediating the shape of the experimental curves. In the light of the results, we derived calibrations between parameters of the non-standard and standard tests. For instance we proposed a new approach to determine the yield stress from the ball punch test. We also showed how the slope of the punch tests scales with the average flow stress of the material. The calibrations proposed in the past by authors and published in the open literature have been revisited and critically reviewed. Based upon the findings of the numerical studies, we propose a given methodology to unambiguously evaluate the material constitutive behavior of a material in a case where the only available data comes from various non-standard tests. Experimental ball punch test results obtained on proton-irradiated specimen (0.5 dpa and Tirr = 523 K), of the tempered martensitic steel, EUROFER97, have been obtained. The irradiation hardening was found equal to about 150 MPa, consistently with previous data on similar steels and irradiation conditions. From the simulations of the ball punch test curves of the irradiated specimens, it was concluded that the irradiation does not affect the strain hardening at relatively low fluence.

EPFL2005

Assessment of mechanical properties in unirradiated and irradiated zircaloys and steels with non-standard tests and finite element calculations

Emiliano Campitelli

EPFL2005