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
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.
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
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 1State 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 2Physical properties typical of Wenzhou marine clay and soft Shanghai clay
Table 3Interval of creep and destructuration related parameters of the model for optimization
Fig. 5Distribution of “satisfactory” solutions generated during optimization of the SA
Fig. 6Distribution 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 4Optimal sets of parameters with objective error
Fig. 71D compression results of intact and reconstituted Wenzhou clay
Fig. 8Relationship between Cαe and λ for Wenzhou marine clay
Fig. 9Comparisons between simulated and measured results of a CRS oedometer test with axial strain-rate varying between 0.2%/h and 20%/h
Fig. 10Comparisons 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. 12Triaxial test results on Shanghai clay: (a) axial strain-deviatoric stress; (b) stress path
Fig. 13Simulations of objective tests of Shanghai clay using optimal parameters
Fig. 14Simulated results of tests on isotropically consolidated Shanghai clay with different confining pressuresCIUC: isotropic consolidation undrained compression
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