Analysis of Äspö Pillar Stability Experiment: Continuous thermo-mechanical model development and calibration

Abstract The paper describes an analysis of thermo-mechanical (TM) processes appearing during the Aspo Pillar Stability Experiment (APSE). This analysis is based on finite elements with elasticity, plasticity and damage mechanics models of rock behaviour and some least squares calibration techniques. The main aim is to examine the capability of continuous mechanics models to predict brittle damage behaviour of granite rocks. The performed simulations use an in-house finite element software GEM and self-developed experimental continuum damage MATLAB code. The main contributions are twofold. First, it is an inverse analysis, which is used for (1) verification of an initial stress measurement by back analysis of convergence measurement during construction of the access tunnel and (2) identification of heat transfer rock mass properties by an inverse method based on the known heat sources and temperature measurements. Second, three different hierarchically built models are used to estimate the pillar damage zones, i.e. elastic model with Drucker–Prager strength criterion, elasto-plastic model with the same yield limit and a combination of elasto-plasticity with continuum damage mechanics. The damage mechanics model is also used to simulate uniaxial and triaxial compressive strength tests on the Aspo granite.

[1]  Owe Axelsson,et al.  Material Parameter Identification with Parallel Processing and Geo-applications , 2011, PPAM.

[2]  C. Vogel Computational Methods for Inverse Problems , 1987 .

[3]  Milan Jirásek,et al.  Inelastic Analysis of Structures , 2001 .

[4]  Rolf Mahnken,et al.  Identification of Material Parameters for Constitutive Equations , 2004 .

[5]  Ondrej Jakl,et al.  GEM - A Platform for Advanced Mathematical Geosimulations , 2009, PPAM.

[6]  Zhangzhi Cen,et al.  Identification of damage parameters for jointed rock , 2002 .

[7]  Milan Jirásek,et al.  A nonlocal constitutive model for trabecular bone softening in compression , 2010, Biomechanics and modeling in mechanobiology.

[8]  M. Kwas´niewski M. Takahashi Strain-based Failure Criteria For Rocks: State of the Art And Recent Advances , 2010 .

[9]  M. Jirásek Damage and Smeared Crack Models , 2011 .

[10]  Ondrej Jakl,et al.  Solution of Identification Problems in Computational Mechanics - Parallel Processing Aspects , 2010, PARA.

[11]  E. Haber,et al.  On optimization techniques for solving nonlinear inverse problems , 2000 .

[12]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[13]  C. Derek Martin,et al.  The Äspö pillar stability experiment: Part I—Experiment design , 2009 .

[14]  J. Christer Andersson,et al.  Rock Mass Response to Coupled Mechanical Thermal Loading : Äspö Pillar Stability Experiment, Sweden , 2007 .

[15]  Roman Kohut,et al.  Schwarz methods for discrete elliptic and parabolic problems with an application to nuclear waste repository modelling , 2007, Math. Comput. Simul..

[16]  Håkan Stille,et al.  The Äspö Pillar Stability Experiment: Part II—Rock mass response to coupled excavation-induced and thermal-induced stresses , 2009 .

[17]  Jean Lemaitre,et al.  A Course on Damage Mechanics , 1992 .

[18]  D. Owen,et al.  Computational methods for plasticity : theory and applications , 2008 .

[19]  Hai‐Sui Yu,et al.  Plasticity and geotechnics , 2006 .

[20]  Petr Byczanski,et al.  Large scale parallel FEM computations of far/near stress field changes in rocks , 2006, Future Gener. Comput. Syst..

[21]  P. Wriggers,et al.  Mesoscale models for concrete: homogenisation and damage behaviour , 2006 .

[22]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.