Optimization framework for calibration of constitutive models enhanced by neural networks

International Journal for Numerical and Analytical Methods in Geomechanics

Volumn 33, Issue 1, 2009, Pages 71-94

  Obrzud, Rafał F ^a   Vulliet, Laurent ^a   Truty, Andrzej ^b  

^a EPFL   (Switzerland)

^b CRACOW UNIVERSITY OF TECHNOLOGY   (Poland)

Author keywords

Back analysis; Elasto plastic model calibration; Neural networks; Optimization; Parameter identification; Principal component analysis

Indexed keywords

CALIBRATION; CLAY MINERALS; COMPRESSION TESTING; CONSTITUTIVE MODELS; ELASTOPLASTICITY; GEOLOGIC MODELS; NEURAL NETWORKS; OPTIMIZATION; PARAMETER ESTIMATION; PLASTICS;

BACK ANALYSIS; COMPRESSION TESTS; COMPUTATIONAL EFFORTS; DIMENSIONAL REDUCTIONS; ELASTO PLASTICS; ELASTO-PLASTIC MODEL CALIBRATION; EXPERIMENTAL DATUM; FEED FORWARDS; GAUSS-NEWTON ALGORITHMS; GRADIENT-BASED OPTIMIZATIONS; INPUT DATUM; ISOTROPIC CONSOLIDATIONS; LABORATORY TESTS; MODIFIED CAM CLAY MODELS; NEURAL-NETWORK; OPTIMIZATION FRAMEWORKS; PARAMETER IDENTIFICATION;

PRINCIPAL COMPONENT ANALYSIS;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; BACK ANALYSIS; CALIBRATION; CAM-CLAY MODEL; CONSTITUTIVE EQUATION; ELASTOPLASTICITY; ESTIMATION METHOD; GAUSSIAN METHOD; GEOSTATISTICS; NUMERICAL MODEL; OPTIMIZATION; PARAMETERIZATION; PRINCIPAL COMPONENT ANALYSIS;

EID: 61449267736     PISSN: 03639061     EISSN: 10969853     Source Type: Journal    
DOI: 10.1002/nag.707     Document Type: Article

References (44)

1. Graham J. The 2003 R.M. Hardy Lecture: soil parameters for numerical analysis in clay. Canadian Geotechnical Journal 2006; 43:187-209.
2. Anandarajah A, Agarwal D. Computer-aided calibration of soil plasticity model. International Journal for Numerical and Analytical Methods in Geomechanics 1991; 15:835-856.
3. Ghaboussi J, Garrett JH, Wu X. Knowledge-based modeling of material behavior with neural networks. Journal of Engineering Mechanics 1991; 117:132-151.
4. Ghaboussi J, Sidarta DE. New nested adaptive neural networks (NANN) for constitutive modeling. Computers and Geotechnics 1998; 22(1):29-52.
5. Sidarta DE, Ghaboussi J. Constitutive modeling of geomaterials from non-uniform material tests. Computers and Geotechnics 1998; 22(1):53-71.
6. Ghaboussi J, Pecknold DA, Zhang M, Haj-Ali RM. Autoprogressive training of neural network constitutive models. International Journal for Numerical Methods in Engineering 1998; 42:105-126.
7. Shin HS, Pande GN. On self-learning finite element codes based on monitored response of structures. Computers and Geotechnics 2000; 27:161-178.
8. Hashash YM, Jung S, Ghaboussi J. Numerical implementation of a neural network based material model in finite element analysis. International Journal for Numerical Methods in Engineering 2004; 59:989-1005.
9. Mayoraz F, Vulliet L. Neural networks for slope movement prediction. International Journal of Geomechanics 2002; 2(2):153-173.
10. Jan JC, Hung SL, Chi SY, Chern JC. Neural network forecast model in deep excavation. Journal of Computing in Civil Engineering 2002; 16(1):59-65.
11. Ding W, Shang JQ. Neural networks in soil characterization. In ISC-2 on Geotechnical and Geophysical Site Characterization, Fonseca AVd, Mayne P (eds). Millpress: Rotterdam, 2004; 889-896.
12. Goh ATC, Kulhawy FH. Reliability assessment of serviceability performance of braced retaining walls using a neural network approach. International Journal for Numerical and Analytical Methods in Geomechanics 2005; 29:627-642.
13. Waszczyszyn Z. Some new results in applications of backpropagation neural networks in structural and civil engineering. In Advances in Engineering Computational Technology, Topping BHV (ed.). Civil-Comp Press: Edinburgh, 1998; 173-187.
14. Shin HS, Pande GN. Identification of elastic constants for orthotropic materials from structural test. Computers and Geotechnics 2003; 30:571-577.
15. Pichler B, Lackner R, Mang HA. Back analysis of model parameters in geotechnical engineering by means of soft computing. International Journal for Numerical Methods in Engineering2003; 57:1943-1978.
16. Sakurai S, Takeuchi K. Back analysis of measured displacements of tunnels. Rock Mechanics and Rock Engineering 1983; 16:173-180.
17. Gioda G, Sakurai S. Back analysis procedure for the interpretation of field measurements in geomechanics. International Journal for Numerical and Analytical Methods in Geomechanics 1987; 11:555-583.
18. Ou CY, Tang YG. Soil parameter determination for deep excavation analysis by optimization. Journal of Chinese Institute of Engineers 1994; 17(5):671-688.
19. Zentar R, Hicher PY, Moulin G. Identification of soil parameters by inverse analysis. Computers and Geotechnics 1994; 28:129-144.
20. Finno RJ, Calvello M. Supported excavations: the observational method and inverse modeling. Journal of Geotechnical and Geoenvironmental Engineering (ASCE) 2005; 131(7):826-836.
21. Cailletaud G, Pilvin P. Identification and inverse problems related to material behaviour. In Inverse Problems in Engineering Mechanics, Swoboda G (ed.). Balkema: Rotterdam, 1994; 79-86.
22. Ledesma A, Gens A, Alonso EE. Estimation of parameters in geotechnical backanalysis - I. Maximum likelihood approach. Computers and Geotechnics 1996; 18(1):1-27.
23. Poeter EP, Hill MC. Documentation of UCODE, a computer code for universal inverse modeling. US Geological Survey Water-Resources Investigations Report 98-4080, 1998.
24. Cividini A, Maier G, Nappi A. Parameter estimation of a static geotechnical model using a Bayes' approach. International Journal of Rock Mechanics and Mining Sciences and Geomechanics Abstract 1983; 20(5):215-226.
25. Cekerevac C, Girardin S, Klubertanz G, Laloui L. Calibration of an elasto-plastic constitutive model by a constrained optimisation procedure. Computers and Geotechnics 2006; 33:432-443.
26. Pal S, Wathugala GW, Kundu S. Calibration of a constitutive model using genetic algorithms. Computers and Geotechnics 1996; 19(4):325-348.
27. Samarajiva P, Macari EJ, Wathugala W. Genetic algorithms for the calibration of constitutive models for soils. International Journal of Geomechanics 2005; 5(3):206-217.
28. Levasseur S, Malecot Y, Boulon M, Flavigny E. Soil parameter identification using a genetic algorithm. International Journal for Numerical and Analytical Methods in Geomechanics 2008; 32(2):189-213.
29. Roscoe KH, Burland JB. On the generalized strain-stress behaviour of 'wet' clay. In Engineering Plasticity, Heyman J, Leckie FA (eds). Cambridge University Press: Cambridge, MA, 1968; 535-609.
30. Kaczmarczyk Ł, Waszczyszyn Z. Identification of characteristic length of microstructure for second order continuum multiscale model by Bayesian neural networks. Computer Assisted Mechanics and Engineering Sciences 2007; 14:183-196.
31. Haykin S. Neural Networks. A Comprehensive Foundation (2nd edn). Prentice-Hall: Upper Saddle River, NJ, 1999.
32. Rumelhart DE, Hinton GE, Williams RJ. Learning internal representations by error propagation. In Parallel Distributed Processing, Rumelhart DE, McClelland JL (eds). MIT Press: Cambridge, MA, 1986; 287-302.
33. Flood I, Kartam N. Neural networks in civil engineering. I: principles and understanding. Journal of Computing in Civil Engineering 1994; 8(2):131-147.
34. Diamantaras KI, Kung SY. Principal Component Neural Networks: Theory and Applications. Wiley: New York, 1996.
35. Hujeux JC. Une loi de comportement pour le chargement cyclique des sols. In Genie Parasismique, Davidovici V (ed.). E.N.P.C.: Paris, 1985; 287-302.
36. Z Soil.PC 2003. User Manual: Soil, Rock and Structural Mechanics in Dry or Partially Saturated Media. ZACE Services Ltd, Software Engineering: Lausanne, 2003.
37. Dascal O, Laroque GS. Caractéristique de copressibilité des argiles du complex Nottaway-Broadback-Rupert (Baie James). Canadian Geotechnical Journal 1973; 10(1):41-63.
38. Dzwilewski PT, Richards AF. Consolidation properties of Wilkinson basin soils. Journal of Geotechnical Engineering (ASCE) 1974; 100(GT10):1175-1179.
39. Rendon-Herrero O. Universal compression index equation. Journal of Geotechnical Engineering (ASCE) 1980; 106(GT11):1179-1200.
40. Krizek RJ, Corotis RB, El-Moursi HH. Probabilistic analysis of predicted and measured settlements. Canadian Geotechnical Journal 1977; 14(1):17-33.
41. Leroueil S, Tavenas F, Le Bihan JP. Propriétés caractéristiques des argiles de l'est du Canada. Canadian Geotechnical Journal 1983; 20(4):681-705.
42. Mayne PW. Cam-Clay predictions of undrained strength. Journal of Geotechnical Engineering (ASCE) 1980; 106(GT11):1219-1242.
43. Chang CC, Chang TYP, Xu YG, To WM. Selection of training samples for model updating using neural networks. Journal of Sound and Vibration 2002; 249(5):867-883.
44. Calvello M, Finno RJ. Calibration of soil models by inverse analysis. In 8th International Symposium on Numerical Models in Geomechanics - NUMOG VIII, Pande GN, Pietruszczak S (eds). Balkema: Rotterdam, 2002; 107-113.