Probabilistic analyses of a strip footing on horizontally stratified sandy deposit using advanced constitutive model

An advanced hypoplastic constitutive model is used in probabilistic analyses of a typical geotechnical problem, strip footing. Spatial variability of soil parameters, rather than state variables, is considered in the study. The model, including horizontal and vertical correlation lengths, was calibrated using a comprehensive set of experimental data on sand from horizontally stratified deposit. Some parameters followed normal, whereas other followed lognormal distributions. Monte-Carlo simulations revealed that the foundation displacement uy for a given load followed closely the lognormal distribution, even though some model parameters were distributed normally. Correlation length in the vertical direction θv was varied in the simulation. The case of infinite correlation length was used for evaluation of different approximate probabilistic methods (first order second moment method and several point estimate methods). In the random field Monte-Carlo analyses with finite θv, the vertical correlation length was found to have minor effect on the mean value of uy, but significant effect on its standard deviation. As expected, it decreased with decreasing θv due to spatial averaging of soil properties.

[1]  A. Nour,et al.  Foundation settlement statistics via finite element analysis , 2002 .

[2]  Gordon A. Fenton,et al.  Bearing-capacity prediction of spatially random c ϕ soils , 2003 .

[3]  D. V. Griffiths,et al.  Bearing Capacity of Rough Rigid Strip Footing on Cohesive Soil: Probabilistic Study , 2002 .

[4]  R. Ghanem,et al.  Stochastic Finite Elements: A Spectral Approach , 1990 .

[5]  D. V. Griffiths,et al.  Bearing capacity of spatially random soil: the undrained clay Prandtl problem revisited , 2001 .

[6]  Ken Been,et al.  A STATE PARAMETER FOR SANDS , 1985 .

[7]  J. Christian,et al.  POINT-ESTIMATE METHOD AS NUMERICAL QUADRATURE , 2001 .

[8]  Emilio Rosenblueth,et al.  Two-point estimates in probabilities , 1981 .

[9]  Gerd Gudehus,et al.  Determination of parameters of a hypoplastic constitutive model from properties of grain assemblies , 1999 .

[10]  Michael A. Hicks,et al.  Stochastic evaluation of static liquefaction in a predominantly dilative sand fill , 2005 .

[11]  D. V. Griffiths,et al.  Three-Dimensional Probabilistic Foundation Settlement , 2005 .

[12]  M. Huber,et al.  Evaluation of soil variability and its consequences , 2010 .

[13]  Erich Bauer,et al.  CALIBRATION OF A COMPREHENSIVE HYPOPLASTIC MODEL FOR GRANULAR MATERIALS , 1996 .

[14]  D. V. Griffiths,et al.  Probabilistic analysis of multi-layered soil effects on shallow foundation settlement , 2004 .

[15]  G. Stefanou The stochastic finite element method: Past, present and future , 2009 .

[16]  G. Gudehus A COMPREHENSIVE CONSTITUTIVE EQUATION FOR GRANULAR MATERIALS , 1996 .

[17]  Gordon A. Fenton,et al.  Probabilistic methods in geotechnical engineering , 2007 .

[18]  D. V. Griffiths,et al.  Probabilistic Settlement Analysis by Stochastic and Random Finite-Element Methods , 2009 .

[19]  Andrew J. Whittle,et al.  Effects of spatial variability of cement-treated soil on undrained bearing capacity , 2006 .

[20]  Spatial variability of soil parameters in an analysis of a strip footing using hypoplastic model , 2000 .

[21]  D. V. Griffiths,et al.  Load and resistance factor design of shallow foundations against bearing failure , 2008 .

[22]  Gordon A. Fenton,et al.  Probabilistic Foundation Settlement on Spatially Random Soil , 2002 .

[23]  Chang Che-hao,et al.  Evaluation of probability point estimate methods , 1995 .

[24]  Gerd Gudehus,et al.  Graphical representation of constitutive equations , 2009 .

[25]  J. C. Helton,et al.  Uncertainty and sensitivity analysis in the presence of stochastic and subjective uncertainty , 1997 .

[26]  J. Tejchman Effect of fluctuation of current void ratio on the shear zone formation in granular bodies within micro-polar hypoplasticity , 2006 .

[27]  Armen Der Kiureghian,et al.  The stochastic finite element method in structural reliability , 1988 .

[28]  Erik H. Vanmarcke,et al.  Random Fields: Analysis and Synthesis. , 1985 .

[29]  J. Christian,et al.  Reliability Applied to Slope Stability Analysis , 1994 .

[30]  Dimitrios Kolymbas,et al.  Computer-aided design of constitutive laws , 1991 .

[31]  Michael Havbro Faber,et al.  Proceedings of the 8th International Conference on Structural Safety and Reliability , 2002 .

[32]  Gordon A. Fenton,et al.  Probabilistic slope stability analysis by finite elements , 2004 .

[33]  Andrzej S. Nowak,et al.  Integration formulas to evaluate functions of random variables , 1988 .

[34]  Sung-Eun Cho,et al.  Effect of spatial variability of cross‐correlated soil properties on bearing capacity of strip footing , 2010 .

[35]  M. E. Muller,et al.  A Note on the Generation of Random Normal Deviates , 1958 .

[36]  R. Suchomel,et al.  Comparison of different probabilistic methods for predicting stability of a slope in spatially variable c–φ soil , 2010 .

[37]  P. V. Wolffersdorff,et al.  A hypoplastic relation for granular materials with a predefined limit state surface , 1996 .

[38]  Wojciech Puła,et al.  A probabilistic analysis of foundation settlements , 1996 .

[39]  J. Baker,et al.  Random porosity fields and their influence on the stability of granular media , 2008 .

[40]  Christian Karcher,et al.  FE simulations of granular material with a given frequency distribution of voids as initial condition , 1998 .

[41]  Suk Nam Kim Probabilistic analysis of settlement for a floating foundation of soft clay , 2002 .

[42]  David Mašín,et al.  Capability of constitutive models to simulate soils with different OCR using a single set of parameters , 2009 .

[43]  H. F. Schweiger,et al.  Reliability Analysis in Geotechnics with Finite Elements --- Comparison of Probabilistic, Stochastic and Fuzzy Set Methods , 2003, ISIPTA.

[44]  Helmut Schweiger,et al.  Basic Concepts and Applications of Point Estimate Methods in Geotechnical Engineering , 2007 .