Settlement prediction for an embankment on soft clay

Abstract A model prediction using FE modeling is performed for a trial embankment on soft clay in Ballina, Australia. The comparison between the prediction and the in situ measurement exhibits significant differences. A detailed analysis is performed to validate the model and determine necessary improvements. Sensitivity analyses elaborate upon the most dominant constitutive parameters. Based on site measurements, inverse analyses are performed to identify the optimum parameters. The inverse analysis approach is validated regarding its dependency on the objective function and data incorporated. A comparison between the prediction and the back-calculated parameters confirms the importance of engineering judgment as well as the sensitivity of the modeling strategies to the input information.

[1]  K. Phoon,et al.  Characterization of Geotechnical Variability , 1999 .

[2]  Peter Mark,et al.  Prediction of tunnel lining forces and deformations using analytical and numerical solutions , 2017 .

[3]  Tom Schanz,et al.  Model validation and calibration via back analysis for mechanized tunnel simulations – The Western Scheldt tunnel case , 2015 .

[4]  Ilya M. Sobol,et al.  Sensitivity Estimates for Nonlinear Mathematical Models , 1993 .

[5]  Raoul Hölter,et al.  Constitutive Parameter Adjustment for Mechanized Tunneling with Reference to Sub-system Effects , 2014, NMA.

[6]  Pieter A. Vermeer,et al.  A soft soil model that accounts for creep , 2019, Beyond 2000 in Computational Geotechnics.

[7]  Tom Schanz,et al.  Global sensitivity analysis for subsoil parameter estimation in mechanized tunneling , 2014 .

[8]  I W Redana,et al.  LABORATORY DETERMINATION OF SMEAR ZONE DUE TO VERTICAL DRAIN INSTALLATION. TECHNICAL NOTE , 1998 .

[9]  Richard Kelly,et al.  Bayesian updating for one-dimensional consolidation measurements , 2015 .

[10]  Tom Schanz,et al.  The hardening soil model: Formulation and verification , 2019, Beyond 2000 in Computational Geotechnics.

[11]  Elham Mahmoudi,et al.  Sensitivity analysis and parameter identification of a time dependent constitutive model for rock salt , 2016, J. Comput. Appl. Math..

[12]  Jinchun Chai,et al.  Simple Method of Modeling PVD-Improved Subsoil , 2001 .

[13]  Richard Kelly,et al.  Characterisation of Ballina clay , 2016 .

[14]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[15]  Federica Cotecchia,et al.  A general framework for the mechanical behaviour of clays , 2000 .

[16]  Tom Schanz,et al.  Sensitivity analysis of the model response in mechanized tunneling simulation – A case study assessment , 2014 .

[17]  Mostafa Sharifzadeh,et al.  Displacement-based numerical back analysis for estimation of rock mass parameters in Siah Bisheh powerhouse cavern using continuum and discontinuum approach , 2012 .

[18]  Markus König,et al.  Robust and reliable metamodels for mechanized tunnel simulations , 2014 .

[19]  Masato Shinji,et al.  Back analysis for tunnel engineering as a modern observational method , 2003 .

[20]  R. Kelly,et al.  Site characterisation for the Ballina field testing facility , 2017 .

[21]  Buddhima Indraratna,et al.  PLANE-STRAIN MODELING OF SMEAR EFFECTS ASSOCIATED WITH VERTICAL DRAINS. TECHNICAL NOTE , 1997 .

[22]  Saltelli Andrea,et al.  Global Sensitivity Analysis: The Primer , 2008 .

[23]  Minna Karstunen,et al.  Effect of anisotropy and destructuration on the behavior of Murro test embankment , 2005 .

[24]  S. Wheeler,et al.  An anisotropic elastoplastic model for soft clays , 2003 .

[25]  J. Burland.  On the compressibility and shear strength of natural clays , 1990 .

[26]  Markus König,et al.  A probabilistic analysis of subsoil parameters uncertainty impacts on tunnel-induced ground movements with a back-analysis study , 2015 .

[27]  Federica Cotecchia,et al.  The influence of structure on the pre-failure behaviour of a natural clay , 1997 .

[28]  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).