Shallow foundation response variability due to soil and model parameter uncertainty

doi:10.1007/s11709-014-0242-1

Front. Struct. Civ. Eng.

2014, Vol. 8

Issue (3) : 237-251 https://doi.org/10.1007/s11709-014-0242-1

RESEARCH ARTICLE

Shallow foundation response variability due to soil and model parameter uncertainty

Prishati RAYCHOWDHURY(

),Sumit JINDAL

Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur UP-208016, India

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Abstract

Geotechnical uncertainties may play crucial role in response prediction of a structure with substantial soil-foundation-structure-interaction (SFSI) effects. Since the behavior of a soil-foundation system may significantly alter the response of the structure supported by it, and consequently several design decisions, it is extremely important to identify and characterize the relevant parameters. Moreover, the modeling approach and the parameters required for the modeling are also critically important for the response prediction. The present work intends to investigate the effect of soil and model parameter uncertainty on the response of shallow foundation-structure systems resting on dry dense sand. The SFSI is modeled using a beam-on-nonlinear-winkler-foundation (BNWF) concept, where soil beneath the foundation is assumed to be an assembly of discrete, nonlinear elements composed of springs, dashpots and gap elements. The sensitivity of both soil and model input parameters on shallow foundation responses are investigated using first-order second-moment (FOSM) analysis and Monte Carlo simulation through Latin hypercube sampling technique. It has been observed that the degree of accuracy in predicting the responses of the shallow foundation is highly sensitive soil parameters, such as friction angle, Poisson’s ratio and shear modulus, rather than model parameters, such as stiffness intensity ratio and spring spacing; indicating the importance of proper characterization of soil parameters for reliable soil-foundation response analysis.

Keywords shallow foun dation sensitivity analysis centrifuge data first-order-second-moment (FOSM) method parameter uncertainty

Corresponding Author(s): Prishati RAYCHOWDHURY

Issue Date: 19 August 2014

Cite this article:

Prishati RAYCHOWDHURY,Sumit JINDAL. Shallow foundation response variability due to soil and model parameter uncertainty[J]. Front. Struct. Civ. Eng., 2014, 8(3): 237-251.

URL:

https://academic.hep.com.cn/fsce/EN/10.1007/s11709-014-0242-1
https://academic.hep.com.cn/fsce/EN/Y2014/V8/I3/237

Tab.1 Details of selected uncertain parameters

Tab.2 Assumed correlation coefficient between the parameters

Tab.3 Details of the experiments considered in the study

Fig.1 Shearwall resting on strip footing

Fig.2 Material models. (a) q-z element; (b) p-x element; (c) t-x element

Fig.3 Variable stiffness distribution of BNWF model and model input parameters

Fig.4 Response variation with different sample sizes

Tab.4 Absolute mean demands with varying input parameters

Tab.5 Absolute mean error in demands with varying input parameters

Fig.5 Footing response comparison for test SSG02 05 with varying friction angle. (a) Moment-rotation; (b) settlement-rotation; (c) shear-rotation

Fig.6 Variability of response prediction due to parameter uncertainty. (a) Friction angle; (b) Poisson’s ratio; (c) shear modulus; (d) end length ratio; (e) stiffness intensity ratio; (f) spring spacing

Tab.6 Variability in absolute errors of response prediction using Latin hypercube method/%

Fig.7 Sensitivity analysis using FOSM method. (a) Moment; (b) shear; (c) rotation; (d) settlement

1	Lacasse S, Nadim F. Uncertainties in characterizing soil properties. In: Uncertainty in the Geologic Environment: From Theory to Practic, Proceedings of Uncertainty 96. Madison, Wisconsin, July 31-August 3, 1996, New York, USA, ASCE Geotechnical Special Publication.1996, 58: 49–75
2	Chakraborty S, Dey S S. Stochastic finite-element simulation of random structure on uncertain foundation under random loading. International Journal of Mechanical Sciences, 1996, 38(11): 1209–1218
3	Foye K C, Salgado R, Scott B. Assessment of variable uncertainties for reliability based design of foundations. Journal of Geotechnical and Geoenviornmental Engineering. 2006, 132(9): 1197-1207
4	Jones A L, Kramer S L, Arduino P. Estimation of uncertainty in geotechnical properties for performance-based earthquake engineering. Tech. Rep. 2002/16, Pacific Earthquake Engineering Research Center, PEER, 2002
5	Lumb P. The variability of natural soils. Engineering Structures, 1966, 3: 74-97
6	Lutes L D, Sarkani S, Jin S. Response variability of an SSI system with uncertain structural and soil properties. Canadian Geotechnical Journal, 2000, 22(6): 605-620
7	Na U J, Chaudhuri S R, Shinozuka M. Probabilistic assessment for seismic performance of port structures. Soil Dynamics and Earthquake Engineering, 2008, 28(2): 147-158
8	Chaudhuri S R, Gupta V K. Variability in seismic response of secondary systems due to uncertain soil properties. Engineering Structures, 2002, 24(12): 1601-1613
9	Raychowdhury P. Effect of soil parameter uncertainty on seismic demand of low rise steel buildings on dense sand. Soil Dynamics and Earthquake Engineering, 2009, 29(10): 1367-1378 doi: 10.1016/j.soildyn.2009.03.004
10	Raychowdhury P, Hutchinson T C. Sensitivity of shallow foundation response to model input parameters. Journal of Geotechnical and Geoenvironmental Engineering, 2010, 136(3): 538-541
11	Ronold K O, Bjerager P. Model uncertainty representation in geotechnical reliability analysis. Journal of Geotechnical Engineering, 1992, 118(3): 363-376
12	Boulanger R W, Curras C J, Kutter B L, Wilson D W, Abghari A. Seismic soil-pile-structure interaction experiments and analyses. Journal of Geotechnical and Geoenvironmental Engineering, 1999, 125(9): 750-759
13	Raychowdhury P, Hutchinson T C. (2008) Nonlinear material models for Winkler-based shallow foundation response evaluation. In: GeoCongress 2008, Characterization, Monitoring,and Modeling of GeoSystems, March 9-12, 2008, New Orleans, LA, ASCE Geotechnical Special Publication No. 179, pp 686-693
14	Raychowdhury P, Hutchinson T C. Performance evaluation of a nonlinear Winkler-based shallow foundation model using centrifuge test results. Earthquake Engineering & Structural Dynamics, 2009, 38(5): 679-698 doi: 10.1002/eqe.902
15	Terzaghi K. Theoretical Soil Mechanics. New York: J Wiley, 1943
16	Meyerhof G G. Some recent research on the bearing capacity of foundations. Canadian Geotechnical Journal, 1963, 1(1): 16-26
17	Gazetas G. Foundation Engineering Handbook. Fang H Y ed. Van NostrandRienhold, 1991
18	Gajan, 2003a;
19	Gajan, 2003b;
20	Gajan, 2006
21	EPRI. Manual on Estimating Soil Properties for Foundation Design. Electric Power Research Institute, Palo Alto, California, 1990
22	Gajan S, Hutchinson T C, Kutter B, Raychowdhury P, Ugalde J A, Stewart J P. Numerical models for the analysis and performance-based design of shallow foundations subjected to seismic loading. PEER Data Report, Pacific Earthquake Engineering Research Center (PEER), 2008
23	Raychowdhury P. Nonlinear Winkler-based shallow foundation model for performance assessment of seismically loaded structures. Dissertation for the Doctoral Degree. San Diego: University of California, 2008
24	ATC-40. Seismic Evaluation and Retrofit of Concrete Buildings. Applied Technology Council (ATC), Redwood City, California, 1996
25	Harden C W, Hutchinson T C, Martin G R, Kutter B L. Numerical modeling of the nonlinear cyclic response of shallow foundations. Tech. Rep. 2005/04, Pacific Earthquake Engineering Research Center, PEER, 2005
26	OpenSees. Open System for Earthquake Engineering Simulation: OpenSees. Pacific Earthquake Engineering Research Center (PEER), University of California, Berkeley, 2008 (http://opensees.berkeley.edu)
27	McKay M D, Beckman R J, Conover W J. A 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
28	Iman R L, Conover W J. A distribution-free approach to including rank correlation among input variables. Bulletin of the Seismic Society of America, 1982, 11(3): 311-334
29	Stein M. Large sample properties of simulations using Latin hypercube sampling. Technometrics, 1987, 29(2): 143-151
30	Jindal S. Shallow foundation response analysis: a parametric study. Master’s thesis. Kanpur: Indian Institute of Technology Kanpur, 2011

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