TY - JOUR
T1 - Conditional probabilistic analysis of cement-treated soil column strength
AU - Namikawa, Tsutomu
N1 - Funding Information:
The author is grateful to Takenaka Corporation for their cooperation in the numerical analysis. The author also acknowledges the support of the Japan Society for the Promotion of Science (JSPS KAKENHI Grant No. 25420509).
PY - 2016/2/1
Y1 - 2016/2/1
N2 - The quality of cement-treated soil columns is usually assessed by examining the strength of cored samples. This paper presents a finite-element analysis approach with random field theory for assessing the quality of a cement-treated soil column from which cored samples are retrieved. Monte Carlo simulations with conditional distribution (conditional simulation) were conducted to generate spatial dependence random fields with the data known at some locations. Simulations without the known data (unconditional simulation) were also performed for comparison. Using the random field samples generated from the Monte Carlo simulations, finite-element analysis was performed to simulate the compression behavior of a full-scale column in which material properties vary with a presence of spatial autocorrelation. Finite-element analysis with conditional simulation predicts the overall strength of a targeted cement-treated soil column appropriately, and the overall strength variability obtained with the conditional simulation is lower than that obtained with the unconditional simulation. The results suggest that the conditional simulation offers advantages over the unconditional simulation when assessing the probability of failure of a cement-treated soil column with large autocorrelation distance.
AB - The quality of cement-treated soil columns is usually assessed by examining the strength of cored samples. This paper presents a finite-element analysis approach with random field theory for assessing the quality of a cement-treated soil column from which cored samples are retrieved. Monte Carlo simulations with conditional distribution (conditional simulation) were conducted to generate spatial dependence random fields with the data known at some locations. Simulations without the known data (unconditional simulation) were also performed for comparison. Using the random field samples generated from the Monte Carlo simulations, finite-element analysis was performed to simulate the compression behavior of a full-scale column in which material properties vary with a presence of spatial autocorrelation. Finite-element analysis with conditional simulation predicts the overall strength of a targeted cement-treated soil column appropriately, and the overall strength variability obtained with the conditional simulation is lower than that obtained with the unconditional simulation. The results suggest that the conditional simulation offers advantages over the unconditional simulation when assessing the probability of failure of a cement-treated soil column with large autocorrelation distance.
KW - Cement-treated soils
KW - Compressive strength
KW - Conditional simulation
KW - Finite-element analysis
KW - Spatial variability
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U2 - 10.1061/(ASCE)GM.1943-5622.0000481
DO - 10.1061/(ASCE)GM.1943-5622.0000481
M3 - Article
AN - SCOPUS:84954348570
SN - 1532-3641
VL - 16
JO - International Journal of Geomechanics
JF - International Journal of Geomechanics
IS - 1
M1 - 04015021
ER -