Please wait a minute...
ZJUS-A
Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering)  2016, Vol. 17 Issue (1): 76-88    DOI: 10.1631/jzus.A1500031
    
An efficient parameter identification procedure for soft sensitive clays
Liang Ye1,†(),Yin-fu Jin2,3,†(),Shui-long Shen2,Ping-ping Sun4,Cheng Zhou5
1 Department of Civil Engineering, Zhejiang University of Science and Technology, Hangzhou 310012, China
2 State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean, and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
3 LUNAM University, Ecole Centrale de Nantes, GeM UMR CNRS, 6183, Nantes, France
4 Department of Civil Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
5 State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu 610065, China
Download: HTML     PDF(1286KB)
Export: BibTeX | EndNote (RIS)      

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.

Key words： Clay      Creep      Destructuration      Optimization      Simplex      Parameter identification     
Received: 05 February 2015      Published: 06 January 2016
Fund:  the National Natural Science Foundation of China(No. 41372283);the European Project CREEP(No. PIAPP-GA-2011-286397);the French Ministry of Research through ANR-RISMOGEO
Corresponding Authors: Liang Ye,Yin-fu Jin     E-mail: yeliang88@126.com;yinfu.jin9019@gmail.com
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Liang Ye
Yin-fu Jin
Shui-long Shen
Ping-ping Sun
Cheng Zhou
Cite this article:

Liang Ye,Yin-fu Jin,Shui-long Shen,Ping-ping Sun,Cheng Zhou. An efficient parameter identification procedure for soft sensitive clays. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(1): 76-88.

URL:

http://www.zjujournals.com/xueshu/zjus-a/10.1631/jzus.A1500031     OR     http://www.zjujournals.com/xueshu/zjus-a/Y2016/V17/I1/76

Fig. 1 Structure of Nelder-Mead simplex algorithm after Nelder and Mead (1965) pr, pe, pout, and pin are the points generated by the reflection, expansion, outside contraction, and inside contraction, respectively
Fig. 2 Definitions for the model in p′-q space (a) and 1D compression condition (b) (Yin et al., 2011a) σ′p0 and σ′pi0 are the pre-consolidated pressures for the natural sample and reconstituted sample, respectively; Knc is the coefficient of lateral pressure for normally consolidated clay
Group Parameter Definition Determination
Modified Cam clay parameters $\sigma_{{\text{p0}}}^{'\text{r}}$ Initial reference preconsolidation pressure From a selected oedometer test whose loading-rate is used as reference strain-rate
e0 Initial void ratio (state parameter) From oedometer test
υ Poisson’s ratio From initial part of stress-strain curve (typically varying from 0.15 to 0.35)
κ Slope of the swelling line From 1D or isotropic consolidation test
λi Intrinsic slope of the compression line From 1D or isotropic consolidation test
M Slope of the critical state line From triaxial shear test
Anisotropy parameters α0 Initial anisotropy (state parameter for calculating initial components of the fabric tensor) For K0-consolidated samples by P[1]§
Ω Absolute rate of yield surface rotation Calculated by Eq. (7)
Destructuration parameters χ0 Initial bonding ratio From shear vane test or oedometer test by P[2]§
ξ Absolute rate of bond degradation From consolidation tests with two different stress ratios η=q/p′, e.g., oedometer test and isotropic consolidation test, calculated by P[3]§
ξd Relative rate of bond degradation
Viscosity parameters Cαei Secondary compression coefficient for reconstituted clay From 24 h oedometer test on remoulded sample
Hydraulic parameters kv0, kh0 Initial vertical and horizontal permeability From oedometer tests
ck Permeability coefficient From curve e-logk
Table 1 State parameters and soil constants of an elastic viscoplastic model
Clay Depth (m) Density, γ (kN/m3) e0 Water content, w (%) Liquid limit, wL (%) Plastic limit, wP (%) σ′p0 (kPa) σ′v0 (kPa)
Wenzhou 10.5–11.5 15.5 1.895 67.5 63.4 27.6 81.3 75.4
Shanghai 10 17.7 1.402 51.8 44.2 22.4 110.5 68.6
Table 2 Physical properties typical of Wenzhou marine clay and soft Shanghai clay
Fig. 3 Triaxial test results on Wenzhou clay: (a) K0 consolidation stage; (b) axial strain-deviatoric stress; (c) axial strain-excess pore pressure
Fig. 4 Mono-objective optimization procedure
Parameter Minimal value Maximal value Step
Cαei 0.0001 0.1 0.0001
χ0 0 50 0.5
ξ 0 20 0.5
ξd 0 0.5 0.02
Table 3 Interval of creep and destructuration related parameters of the model for optimization
Fig. 5 Distribution of “satisfactory” solutions generated during optimization of the SA
Fig. 6 Distribution of satisfactory solutions obtained by the SA
Clay Optimal parameter Objective error (%)
Cαei χ0 ξ ξd
Wenzhou 0.0032 8.5 13.0 0.24 8.85
Shanghai 0.0025 4.0 9.5 0.45 17.21
Table 4 Optimal sets of parameters with objective error
Fig. 7 1D compression results of intact and reconstituted Wenzhou clay
Fig. 8 Relationship between Cαe and λ for Wenzhou marine clay
Fig. 9 Comparisons between simulated and measured results of a CRS oedometer test with axial strain-rate varying between 0.2%/h and 20%/h
Fig. 10 Comparisons between simulated and measured results of objective tests in compression (a and b) and corresponding extension (c and d) at initial vertical stresses of 75.4, 150, and 300 kPa
Fig. 11 Comparisons between simulated and measured results of undrained triaxial CRS tests in compression (a and b) and extension (c and d) at an initial vertical stress of 75.4 kPa CAUC: anisotropic consolidation undrained compression; CAUE: anisotropic consolidation undrained extension
Fig. 12 Triaxial test results on Shanghai clay: (a) axial strain-deviatoric stress; (b) stress path
Fig. 13 Simulations of objective tests of Shanghai clay using optimal parameters
Fig. 14 Simulated results of tests on isotropically consolidated Shanghai clay with different confining pressures CIUC: isotropic consolidation undrained compression
[1]   ASTM (American Society for Testing and Materials) Annual Book of ASTM Standards. 2004, Philadelphia, PA, USA: ASTM
[2]   Biarez J, Hicher PY . Elementary mechanics of soil behaviour: saturated remoulded soils. 1994, Rotterdam, the Netherlands: AA Balkema
[3]   Calvello M, Finno RJ . Selecting parameters to optimize in model calibration by inverse analysis. Computers and Geotechnics. 2004, 31(5): 410-424 doi: 10.1016/j.compgeo.2004.03.004
doi: 10.1016/j.compgeo.2004.03.004
[4]   Chang CS, Yin ZY . Micromechanical modeling for inherent anisotropy in granular materials. Journal of Engineering Mechanics. 2010, 136(7): 830-839 doi: 10.1061/(ASCE)EM.1943-7889.0000125
doi: 10.1061/(ASCE)EM.1943-7889.0000125
[5]   Dano C, Hicher PY, Rangeard D et al. Interpretation of dilatometer tests in a heavy oil reservoir. International Journal for Numerical and Analytical Methods in Geomechanics. 2007, 31(10): 1197-1215 doi: 10.1002/nag.583
doi: 10.1002/nag.583
[6]   Huang M, Liu Y, Sheng D . Simulation of yielding and stress–stain behavior of Shanghai soft clay. Computers and Geotechnics. 2011, 38(3): 341-353 doi: 10.1016/j.compgeo.2010.12.005
doi: 10.1016/j.compgeo.2010.12.005
[7]   Karstunen M, Yin ZY . Modelling time-dependent behaviour of Murro test embankment. Géotechnique. 2010, 60(10): 735-749 doi: 10.1680/geot.8.P.027
doi: 10.1680/geot.8.P.027
[8]   Lagarias JC, Reeds JA, Wright MH et al. Convergence properties of the Nelder-Mead simplex method in low dimensions. SIAM Journal on Optimization. 1998, 9(1): 112-147 doi: 10.1137/S1052623496303470
doi: 10.1137/S1052623496303470
[9]   Lecampion B, Constantinescu A, Nguyen Minh D . Parameter identification for lined tunnels in a viscoplastic medium. International Journal for Numerical and Analytical Methods in Geomechanics. 2002, 26(12): 1191-1211 doi: 10.1002/nag.241
doi: 10.1002/nag.241
[10]   Leroueil S, Vaughan PR . The general and congruent effects of structure in natural soils and weak rocks. Géotechnique. 1990, 40(3): 467-488 doi: 10.1680/geot.1990.40.3.467
doi: 10.1680/geot.1990.40.3.467
[11]   Levasseur S, Malécot Y, Boulon M et al. Soil parameter identification using a genetic algorithm. International Journal for Numerical and Analytical Methods in Geomechanics. 2008, 32(2): 189-213 doi: 10.1002/nag.614
doi: 10.1002/nag.614
[12]   McKay MD, Beckman RJ, Conover WJ . Comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics. 1979, 21(2): 239-245 doi: 10.1080/00401706.1979.10489755
doi: 10.1080/00401706.1979.10489755
[13]   Nelder JA, Mead R . A simplex method for function minimization. The Computer Journal. 1965, 7(4): 308-313 doi: 10.1093/comjnl/7.4.308
doi: 10.1093/comjnl/7.4.308
[14]   Papon A, Riou Y, Dano C et al. Single- and multi-objective genetic algorithm optimization for identifying soil parameters. International Journal for Numerical and Analytical Methods in Geomechanics. 2012, 36(5): 597-618 doi: 10.1002/nag.1019
doi: 10.1002/nag.1019
[15]   Sheng D, Sloan S, Yu H . Aspects of finite element implementation of critical state models. Computational Mechanics. 2000, 26(2): 185-196 doi: 10.1007/s004660000166
doi: 10.1007/s004660000166
[16]   Wang L, Yin Z . Stress dilatancy of natural soft clay under an undrained creep condition. International Journal of Geomechanics. 2015, 15(5): A4014002 doi: 10.1061/(ASCE)GM.1943-5622.0000271
doi: 10.1061/(ASCE)GM.1943-5622.0000271
[17]   Yin ZY, Hicher PY . Identifying parameters controlling soil delayed behaviour from laboratory and in situ pressuremeter testing. International Journal for Numerical and Analytical Methods in Geomechanics. 2008, 32(12): 1515-1535 doi: 10.1002/nag.684
doi: 10.1002/nag.684
[18]   Yin ZY, Chang CS . Microstructural modelling of stress-dependent behaviour of clay. International Journal of Solids and Structures. 2009, 46(6): 1373-1388 doi: 10.1016/j.ijsolstr.2008.11.006
doi: 10.1016/j.ijsolstr.2008.11.006
[19]   Yin ZY, Karstunen M . Modelling strain-rate-dependency of natural soft clays combined with anisotropy and destructuration. Acta Mechanica Solida Sinica. 2011, 24(3): 216-230 doi: 10.1016/S0894-9166(11)60023-2
doi: 10.1016/S0894-9166(11)60023-2
[20]   Yin ZY, Wang JH . A one-dimensional strain-rate based model for soft structured clays. Science China Technological Sciences. 2012, 55(1): 90-100 doi: 10.1007/s11431-011-4513-y
doi: 10.1007/s11431-011-4513-y
[21]   Yin ZY, Chang CS, Karstunen M et al. An anisotropic elastic-viscoplastic model for soft clays. International Journal of Solids and Structures. 2010, 47(5): 665-677 doi: 10.1016/j.ijsolstr.2009.11.004
doi: 10.1016/j.ijsolstr.2009.11.004
[22]   Yin ZY, Karstunen M, Hicher PY . Evaluation of the influence of elasto-viscoplastic scaling functions on modelling time-dependent behaviour of natural clays. Soils and Foundations. 2010, 50(2): 203-214 doi: 10.3208/sandf.50.203
doi: 10.3208/sandf.50.203
[23]   Yin ZY, Chang CS, Hicher PY . Micromechanical modelling for effect of inherent anisotropy on cyclic behaviour of sand. International Journal of Solids and Structures. 2010, 47(14-15): 1933-1951 doi: 10.1016/j.ijsolstr.2010.03.028
doi: 10.1016/j.ijsolstr.2010.03.028
[24]   Yin ZY, Karstunen M, Chang CS et al. Modeling time-dependent behavior of soft sensitive clay. Journal of Geotechnical and Geoenvironmental Engineering. 2011, 137(11): 1103-1113 doi: 10.1061/(ASCE)GT.1943-5606.0000527
doi: 10.1061/(ASCE)GT.1943-5606.0000527
[25]   Yin ZY, Hattab M, Hicher PY . Multiscale modeling of a sensitive marine clay. International Journal for Numerical and Analytical Methods in Geomechanics. 2011, 35(15): 1682-1702 doi: 10.1002/nag.977
doi: 10.1002/nag.977
[26]   Yin ZY, Xu Q, Chang CS . Modeling cyclic behavior of clay by micromechanical approach. Journal of Engineering Mechanics. 2013, 139(9): 1305-1309 doi: 10.1061/(ASCE)EM.1943-7889.0000516
doi: 10.1061/(ASCE)EM.1943-7889.0000516
[27]   Yin ZY, Zhu QY, Yin JH et al. Stress relaxation coefficient and formulation for soft soils. Géotechnique Letters. 2014, 4(1): 45-51 doi: 10.1680/geolett.13.00070
doi: 10.1680/geolett.13.00070
[28]   Yin ZY, Xu Q, Yu C . Elastic viscoplastic modeling for natural soft clays considering nonlinear creep. International Journal of Geomechanics. 2015, 15(5): A6014001 doi: 10.1061/(ASCE)GM.1943-5622.0000284
doi: 10.1061/(ASCE)GM.1943-5622.0000284
[29]   Yin ZY, Yin JH, Huang HW . Rate-dependent and long-term yield stress and strength of soft Wenzhou marine clay: experiments and modeling. Marine Georesources and Geotechnology. 2015, 33(1): 79-91 doi: 10.1080/1064119X.2013.797060
doi: 10.1080/1064119X.2013.797060
[30]   Zeng LL . Deformation Mechanism and Compression Model of Natural Clays. 2010 Southeast University, Nanjing, China PhD Thesis (in Chinese)
[31]   Zhu QY, Jin YF, Yin ZY et al. Influence of natural deposition plane orientation on oedometric consolidation behavior of three typical clays from southeast coast of China. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering). 2013, 14(11): 767-777 doi: 10.1631/jzus.A1300156
doi: 10.1631/jzus.A1300156
[1] Peng Guo, Jun-hong Zhang. Numerical model and multi-objective optimization analysis of vehicle vibration[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2017, 18(5): 393-412.
[2] Tian-tian Zhang, Wei Huang, Zhen-guo Wang, Li Yan. A study of airfoil parameterization, modeling, and optimization based on the computational fluid dynamics method[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(8): 632-645.
[3] Hossein Rezaei, Ramli Nazir, Ehsan Momeni. Bearing capacity of thin-walled shallow foundations: an experimental and artificial intelligence-based study[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(4): 273-285.
[4] Bao-tong Li, Su-na Yan, Jun Hong. A growth-based topology optimizer for stiffness design of continuum structures under harmonic force excitation[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(12): 933-946.
[5] Cheng-ming Lan , Hui Li, Jun-Yi Peng , Dong-Bai Sun . A structural reliability-based sensitivity analysis method using particles swarm optimization: relative convergence rate[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(12): 961-973.
[6] Jin Cheng, Ming-yang Tang, Zhen-yu Liu, Jian-rong Tan. Direct reliability-based design optimization of uncertain structures with interval parameters[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2016, 17(11): 841-854.
[7] Antoine Dumas, Jean-Yves Dantan, Nicolas Gayton, Thomas Bles, Robin Loebl. An iterative statistical tolerance analysis procedure to deal with linearized behavior models[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(5): 353-360.
[8] Qing-long Meng, Xiu-ying Yan, Qing-chang Ren. Global optimal control of variable air volume air-conditioning system with iterative learning: an experimental case study[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(4): 302-315.
[9] Lei Fu, Zhen-ping Feng, Guo-jun Li, Qing-hua Deng, Yan Shi, Tie-yu Gao. Experimental validation of an integrated optimization design of a radial turbine for micro gas turbines[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(3): 241-249.
[10] Xiang-yu Shang, Guo-qing Zhou, Yong Lu. Stress-dependent undrained shear behavior of remolded deep clay in East China[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(3): 171-181.
[11] Wei Wei, Ang Liu, Stephen C. Y. Lu, Thorsten Wuest. A multi-principle module identification method for product platform design[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(1): 1-10.
[12] Hui Liu, Ming-hua He, Jia Guo, Yong-jiu Shi, Zhao-xin Hou, Lu-lu Liu. Design-oriented modeling of circular FRP-wrapped concrete columns after sustained axial compression[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2015, 16(1): 47-58.
[13] Abbas Al-Refaie. Applying process analytical technology framework to optimize multiple responses in wastewater treatment process[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(5): 374-384.
[14] Qi-yin Zhu, Ze-xiang Wu, Yan-ling Li, Chang-jie Xu, Jian-hua Wang, Xiao-he Xia. A modified creep index and its application to viscoplastic modelling of soft clays[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(4): 272-281.
[15] Jian Zhou, Jia-jia Yan, Zheng-yi Liu, Xiao-nan Gong. Undrained anisotropy and non-coaxial behavior of clayey soil under principal stress rotation[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2014, 15(4): 241-254.