Reliability Assessment of Dynamic Soil Properties

Document Type : Original Article


1 M.Sc. of Geotechnical Engineering, Department of Civil and Environmental Engineering, Shiraz University of Technology

2 B.Sc. of Architectural Engineering, Department of Architectural Engineering, Ardestan Branch, Islamic Azad University, Ardestan, Iran


Dynamic soil properties are very important topic in geotechnical earthquake engineering due to associated with dynamic loading. Probabilistic analysis of dynamic soil properties is as effective tools to evaluate uncertainty of soil parameters. In this paper, Monte Carlo Simulation (MCS) is used for reliability assessment of dynamic soil properties. For this purpose, a famous model is selected for predicting normalized shear modulus reduction and damping ratio curves. The selected stochastic parameters are internal friction angle, dry and saturated unit weight of soil which is modeled using normal probability distribution functions. To assess the reliability of dynamic soil parameters a computer model is developed for generating input parameter uncertainties. The results show that the shear modulus and damping ratio have more uncertainty for middle range of shear strain. The sensitivity analysis’s results show that saturated unit weight is the most effective parameter in shear modulus and damping ratio.


[1]- Prakash, S., 1981, Soil Dynamics, Mc. Graw Hill Book Co., New York, NY, Reprint, 1991, S.P. Foundation, Rolla, MO.
[2]- Kramer, S. L., 1996, Geotechnical Earthquake Engineering, Prentice Hall; 1996.
[3]- Ishibashi, I. and Zhang, X., 1993, Unified dynamic shear moduli and damping ratios of sand and clay, soils and foundations, 33, 1, 182-191.
[4]-Whitman, V. W., 1996, Organizing and evaluating uncertainty in geotechnical engineering, in: Uncertainty in Geologic Environment: from Theory to Practice, Proceedings of Uncertainty ’96, Geotechnical Special Publication, ASCE, 58(1), 1-38.
[5]-Griffiths, D. V., 2007, Fenton GA. Probabilistic Methods in Geotechnical Engineering, New York: Springer Wien.
[6]-Sowers, G. S., 1991, The human factor in failure, Civil Engineering, ASCE, 72–3.
[7]-Cornell, C. A., 1968, Engineering seismic risk analysis, Bulletin of the Seismological Society of America, 58, 1583–1606.
[8]-Ang, A. H. S., and Tang, W., 1984, Probability Concepts in Engineering Planning and Design, New York, USA: John Wiley and Sons.
[9]-Rosenblueth, E., 1975, Point estimates for probability moments, Proceedings, National Academy of Science, 72(10), 3812–3814.
[10]- Chameau, J. L., and Clough, G. W., 1983, Probabilistic pore pressure analysis for seismic loading, Journal of Geotechnical Engineering Division, ASCE, 109(GT4), 507–524.
[11]-Metropolis, N., and Ulam, S., 1949, The Monte Carlo method, Journal of the American Statistical Association, 44, 335–341.
[12]-Harr, M. E., 1987, Reliability-Based Design in Civil Engineering, McGraw-Hill Book Company.