Stress-weighted spatial averaging of random fields in geotechnical risk assessment

• Autorzy: Brząkała Włodzimierz

Identyfikatory

DOI

10.2478/sgem-2021-0039

• Języki publikacji: EN

Abstrakty

EN

Effects of spatial fluctuations of soil parameters are considered in a new context – considering variability of soil parameters in conjunction with non-uniform stress fields, which can locally amplify (or suppress) subsoil inhomogeneities. In this way, several design situations for the Coulomb frictional material with random tan(φ(x)) reveal a reduction of variance, which is less significant than for the standard volume averaging. When looking for an 'effective' random variable [tan(φ)]_a – that is, a random variable, which is equivalent to the random field tan(φ(x)) – the Vanmarcke averaging by simple volume integrals is insufficient; it systematically overestimates effects of variance reduction, thus causing potentially unsafe situations. The new proposed approach is coherent, formally defined and more realistic.

Słowa kluczowe

EN

spatial variability; effective soil parameter; variance reduction; Vanmarcke averaging; safety factor

• Wydawca: De Gruyter
• Czasopismo: Studia Geotechnica et Mechanica
• Rocznik: 2021
• Tom: Vol. 43, nr 4
• Strony: 465--478
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Brząkała Włodzimierz

• Department of Geotechnics, Hydroengineering, Underground- and Water-Structures, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland

Bibliografia

• [1] Bagińska, I., Kawa, M. & Janecki, W. (2016). Spatial variability of lignite mine dumping ground soil properties using CPTu results. Studia Geotechnica et Mechanica, 38(1), 3–13.
• [2] Brząkała, W. (1981). Randomness of subsoil parameters (in Polish). Archiwum Inżynierii Lądowej (Archives of Civil Engineering), XXVII(4), 599–606.
• [3] Ching, J. & Hu, Y.-G. (2017). Effective Young's modulus for a footing on a spatially variable soil mass. Geo-Risk 2017, ASCE Conf. Proceedings, Denver, USA, 360–369.
• [4] Ching, J., Hu, Y.G. & Phoon, K.K. (2016). On characterizing spatially variable soil shear strength using spatial average. Probabilistic Engineering Mechanics, 45, 31–43.
• [5] Ching, J. & Phoon, K.K. (2013). Mobilized shear strength of spatially variable soils under simple stress states. Structural Safety, 41, 20–28.
• [6] Cho, S.E. (2007). Effects of spatial variability of soil properties on slope stability. Engineering Geology, 92, 97–109.
• [7] Chwała, M. (2019). Undrained bearing capacity of spatially random soil for rectangular footings. Soils and Foundations, 59(5), 1508–1521.
• [8] Deng, Z.P., Li, D.Q., Qi, X.H., Cao, Z.J. & Phoon, K.K. (2017). Reliability evaluation of slope considering geological uncertainty and inherent variability of soil parameters. Computers and Geotechnics, 92, 121–131.
• [9] EN 1997-1: Eurocode 7. Geotechnical design. Part 1: General rules.
• [10] Farah, K., Ltifi, M. & Hassis, H. (2015). A Study of probabilistic FEMs for a slope reliability analysis using the stress fields. The Open Civil Engineering Journal, 9(1), 196–206.
• [11] Fenton, G.A. & Griffiths, D.V. (2003). Bearing-capacity prediction of spatially random c-φ soils. Canadian Geotechnical Journal, 40(1), 54–65.
• [12] Griffiths, D.V. & Fenton, G.A. (2001). Bearing capacity of spatially random soil: The undrained clay Prandtl problem revisited. Géotechnique, 51(4), 351–359.
• [13] Huang, J., Lyamin, A.V., Griffiths, D.V., Sloan, S.W., Krabbenhoft, K. & Fenton, G.A. (2013). Undrained bearing capacity of spatially random clays by finite elements and limit analysis. Proceedings of the XVIII Int. Confer. on SMGE, 731–734.
• [14] Jaksa, M.B., Kaggawa, W.S. & Brooker, P.I. (1999). Experimental evaluation of the scale of fluctuation of a stiff clay. ICASP-8 Conf. Proceedings, Sydney, Australia. Vol. 1, 415–422.
• [15] Javankhoshdel, S. & Bathurst, R.J. (2015). Influence of cross correlation between soil parameters on probability of failure of simple cohesive and c-φ slopes. Canadian Geotechnical Journal, 2015-0109 (November),
• [16] Ji, J., Zhang, C., Gao, Y. & Kodikara, J. (2018). Effect of 2D spatial variability on slope reliability: A simplified FORM analysis. Geoscience Frontiers, 9(6), 1631–1638.
• [17] Jiang, S.H., Li, D.Q., Zhang, L.M. & Zhou, C.B. (2014). Slope reliability analysis considering spatially variable shear strength parameters using a non-intrusive stochastic finite element method. Engineering Geology, 168, 120–128.
• [18] Jiang, S.H., Li, D.Q., Cao, Z.J., Zhou, C.B. & Phoon, K.K. (2015). Efficient system reliability analysis of slope stability in spatially variable soils using Monte Carlo Simulation. Journal of Geotechnical and Geoenvironmental Engineering, 141(2), 04014096.
• [19] Kim, J.M. & Sitar, N. (2013). Reliability approach to slope stability analysis with spatially correlated soil properties. Soils and Foundations, 53(1), 1–10.
• [20] Li, D.Q., Qi, X.-H., Cao, Z.-J., Tang, X.-S., Zhou, W., Phoon, K.-K. & Zhou, C.-B. (2015). Reliability analysis of strip footing considering spatially variable undrained shear strength that linearly increases with depth. Soils and Foundations, 55(4), 866–880.
• [21] Li, X.Y., Zhang, L.M., Gao, L. & Zhu, H. (2017). Simplified slope reliability analysis considering spatial soil variability. Engineering Geology, 216, 90–97.
• [22] Liu, L.L., Cheng, Y.M. & Zhang, S.H. (2017). Conditional random field reliability analysis of a cohesion-frictional slope. Computers and Geotechnics, 82, 173–186.
• [23] Liu, Y., Zhang, W., Zhang, L., Zhu, Z., Hu, J. & Wei, H. (2018). Probabilistic stability analyses of undrained slopes by 3D random fields and finite element methods. Geoscience Frontiers, 9(6), 1657–1664.
• [24] Lloret-Cabot, M., Fenton, G.A. & Hicks, M.A. (2014). On the estimation of scale of fluctuation in geostatistics. Georisk:Assessment and Management of Risk for Engineered Systems and Geohazards, 8(2), 129–140.
• [25] Low, B.K. & Phoon, K.K. (2015). Reliability based design and its complementary role to Eurocode 7 design approach. Computers and Geotechnics, 65, 30–44.
• [26] Oguz, E.A., Huvaj, N., & Griffiths, D.V. (2019). Vertical spatial correlation length based on standard penetration tests. Marine Georesources & Geotechnology, 37(1), 45–56.
• [27] Ostoja-Starzewski, M. (2006). Material spatial randomness. From statistical to representative volume element. Probabilistic Engineering Mechanics, 21, 112–132.
• [28] Phoon, K.K. & Kulhawy, F.H. (1999a). Characterization of geotechnical variability. Canadian Geotechnical Journal, 36(4), 612–624.
• [29] Phoon, K.K. & Kulhawy, F.H. (1999b). Evaluation of geotechnical property variability. Canadian Geotechnical Journal, 36(4), 625–639.
• [30] Pieczyńska-Kozłowska, J.M., Puła, W. & Vessia, G. (2017). A collection of fluctuation scale values and autocorrelation functions of fine deposits in Emilia Romagna Palin, Italy. Geo-Risk 2017, ASCE Conf. Proceedings, Denver, USA, 360–369.
• [31] Puła, W. & Chwała, M., (2015). On spatial averaging along random slip lines in the reliability computations of shallow strip foundations. Computers and Geotechnics, 68, 128–136.
• [32] Shen, Z., Jin, D., Pan, Q., Yang, H. & Chian, S.Ch. (2021). Effect of soil spatial variability on failure mechanisms and undrained capacities of strip foundations under uniaxial loading. Computers and Geotechnics, 139 (November), 104387.
• [33] Tietje, O., Fitze, P. & Schneider, H.R. (2014). Slope stability analysis based on autocorrelated shear strength parameters. Geotechnical and Geological Engineering, 32, 1477–1483.
• [34] Vanmarcke, E.H. (2010). Random Fields. Analysis and Synthesis. World Scientific, Singapore. (rev. ed. of MIT Press, 1983).