Probabilistic Predictive Model for Liquefaction Triggering in Layered Sites Improved with Dense Granular Columns
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 147, Issue 10
Abstract
This paper presents a probabilistic model for evaluating the liquefaction-triggering hazard in level, layered, and saturated granular soil profiles improved with dense granular columns (DGCs). The model is developed using the results of a comprehensive numerical parametric study, validated with a dynamic centrifuge test, and subsequently tested with the available case histories involving DGCs as a liquefaction countermeasure. The numerical database includes a total of 30,000, three-dimensional (3D), fully coupled, nonlinear, dynamic finite-element simulations with a statistically determined range of layer-, profile-, DGC-, and ground motion–specific input parameters. The criteria for the predicted degree of liquefaction (i.e., full, marginal, and no liquefaction) are based on the peak values of excess pore pressure ratio and shear strain anticipated within each soil layer. A machine learning approach that performs multinomial logistic regression along with variable selection and regularization is used to develop a set of functional forms for estimating the probabilities of full-, marginal-, and no-liquefaction in sites improved with DGCs. The proposed probabilistic model is the first of its kind that explicitly considers variations in the area replacement ratio (), stiffness, and drainage capacity of the DGC; the thickness, depth, relative density, and hydraulic conductivity range of each layer; the evolutionary characteristics of ground motions; and the underlying uncertainty in the prediction of pore pressures and shear strains within each layer.
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Data Availability Statement
All data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to acknowledge the Chilean National Commission for Science and Technology (Grant No. CONICYT-PCHA/Doctorado Nacional/2015-21150231) as well as the Department of Civil, Environmental, and Architectural Engineering at University of Colorado at Boulder (CU) for the financial support given to the first author. This work utilized the Summit supercomputer, which is supported by the National Science Foundation (Award No. CNS-0821794) and CU. The Summit supercomputer is a joint effort of the CU, the University of Colorado at Denver, and the National Center for Atmospheric Research.
References
Adalier, K., and A. Elgamal. 2004. “Mitigation of liquefaction and associated ground deformations by stone columns.” Eng. Geol. 72 (3–4): 275–291. https://doi.org/10.1016/j.enggeo.2003.11.001.
Adalier, K., A. Elgamal, J. Meneses, and J. I. Baez. 2003. “Granular columns as liquefaction counter-measure in non-plastic silty soils.” Soil Dyn. Earthquake Eng. 23 (7): 571–584. https://doi.org/10.1016/S0267-7261(03)00070-8.
Alexander, G. J., J. Arefi, L. M. Wotherspoon, A. C. Stolte, B. R. Cox, R. A. Green, and C. M. Wood. 2019. “A case study of stone column ground improvement performance during a sequence of seismic events.” In Proc., 7th Int. Conf. on Earthquake Geotechnical Engineering (7ICEGE). London: CRC Press.
Arefi, J., G. Alexander, G. Martin, and L. Wotherspoon. 2019. “Lessons learned and need for appropriate philosophy for the design of stone column ground improvement under seismic scenarios.” In Proc., 11th Pacific Conf. on Earthquake Engineering. Wellington, New Zealand: New Zealand Society for Earthquake Engineering.
Asgari, A., M. Oliaei, and M. Bagheri. 2013. “Numerical simulation of improvement of a liquefiable soil layer using stone column and pile pinning techniques.” Soil Dyn. Earthquake Eng. 51 (Aug): 77–96. https://doi.org/10.1016/j.soildyn.2013.04.006.
Badanagki, M. 2019. “Centrifuge modeling of dense granular columns in layered liquefiable soils with varying stratigraphy and overlying structures.” Doctoral dissertation, Dept. of Civil, Environmental, and Architectural Engineering, Univ. of Colorado at Boulder.
Badanagki, M., S. Dashti, and P. Kirkwood. 2018. “Influence of dense granular columns on the performance of level and gently sloping liquefiable sites.” J. Geotech. Geoenviron. Eng. 144 (9): 04018065. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001937.
Badanagki, M., S. Dashti, B. Paramasivam, and J. C. Tiznado. 2019. “How do granular columns affect the seismic performance of non-uniform liquefiable sites and their overlying structures?” Soil Dyn. Earthquake Eng. 125 (Oct): 105715. https://doi.org/10.1016/j.soildyn.2019.105715.
Baez, J. I. 1995. “A design model for the reduction of soil liquefaction by vibro-stone columns.” Ph.D. thesis, Dept. of Civil and Environmental Engineering, Univ. of Southern California.
Bardet, J. P., Q. Huang, and S. W. Chi. 1993. “Verification of numerical procedures for the analysis of soil liquefaction problems.” In Proc., Verification of Numerical Procedures for the Analysis of Soil Liquefaction Problems. Rotterdam, Netherlands: A.A. Balkema.
Boulanger, R. W., and I. M. Idriss. 2014. CPT and SPT based liquefaction triggering procedures. Rep. No. UCD/GCM. Davis, CA: Univ. of California.
Bradley, B., and M. Hughes. 2012. Conditional peak ground accelerations in the Canterbury earthquakes for conventional liquefaction assessment. Christchurch, New Zealand: Univ. of Canterbury.
Bullock, Z. 2020. “A framework for performance-based evaluation of liquefaction effects on buildings.” Doctoral dissertation, Dept. of Civil, Environmental, and Architectural Engineering, Univ. of Colorado at Boulder.
Bullock, Z., S. Dashti, Z. Karimi, A. Liel, K. Porter, and K. Franke. 2019. “Probabilistic models for residual and peak transient tilt of mat-founded structures on liquefiable soils.” J. Geotech. Geoenviron. Eng. 145 (2): 04018108. https://doi.org/10.1061/(ASCE)GT.1943-5606.0002002.
Campbell, K. W., and Y. Bozorgnia. 2019. “Ground motion models for the horizontal components of Arias intensity (AI) and cumulative absolute velocity (CAV) using the NGA-West2 database.” Earthquake Spectra 35 (3): 1289–1310. https://doi.org/10.1193/090818EQS212M.
Coduto, D. P., W. A. Kitch, and M. R. Yeung. 2010. Geotechnical engineering: Principles & practices. 2nd ed. London: Pearson.
Cubrinovski, M., K. Ishihara, and T. Shibayama. 2003. “Seismic 3-D effective stress analysis: Constitutive modelling and application.” In Proc., 3rd Int. Conf. on Deformation Characteristics of Geomaterials. Amsterdam: IOS Press.
Das, B. M., and K. Sobhan. 2014. Principles of geotechnical engineering. 8th ed. Boston: Cengage Learning.
Dashti, S., and Z. Karimi. 2017. “Ground motion intensity measures to evaluate. I: The liquefaction hazard in the vicinity of shallow-founded structures.” Earthquake Spectra 33 (1): 241–276. https://doi.org/10.1193/103015eqs162m.
Elgamal, A., J. Lu, and D. Forcellini. 2009. “Mitigation of liquefaction-induced lateral deformation in a sloping stratum: Three-dimensional numerical simulation.” J. Geotech. Geoenviron. Eng. 135 (11): 1672–1682. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000137.
Elgamal, W. A., Z. Yang, E. Parra, and A. Ragheb. 2003. “Modeling of cyclic mobility in saturated cohesionless soils.” Int. J. Plast. 19 (6): 883–905. https://doi.org/10.1016/S0749-6419(02)00010-4.
Gelman, A., and J. Hill. 2006. Data analysis using regression and multilevel/hierarchical models. New York: Cambridge University Press.
Halton, J. H. 1960. “On the efficiency of certain quasi-random sequences of points in evaluating multidimensional integrals.” Numer. Math. 2 (1): 84–90. https://doi.org/10.1007/BF01386213.
Han, J. 2015. Principles and practice of ground improvement. New York: Wiley.
Hanmer, M. J., and K. O. Kalkan. 2013. “Behind the curve: Clarifying the best approach to calculating predicted probabilities and marginal effects from limited dependent variable models.” Am. J. Polit. Sci. 57 (1): 263–277. https://doi.org/10.1111/j.1540-5907.2012.00602.x.
Hausler, E. A. 2002. “Influence of ground improvement on settlement and liquefaction: A study based on field case history evidence and dynamic geotechnical centrifuge tests.” Ph.D. thesis, Dept. of Civil and Environmental Engineering, Univ. of California.
Hwang, Y. W., J. Ramirez, S. Dashti, P. Kirkwood, A. B. Liel, G. Camata, and M. Petracca. 2021. “Seismic interaction of adjacent structures on liquefiable soils: Insight from centrifuge and numerical modeling.” J. Geotech. Geoenviron. Eng. 147 (8): 04021063. https://doi.org/10.1061/(ASCE)GT.1943-5606.0002546.
Idriss, I. M., and R. W. Boulanger. 2008. Soil liquefaction during earthquakes. Oakland, CA: Earthquake Engineering Research Institute.
Karimi, Z., and S. Dashti. 2016. “Seismic performance of shallow founded structures on liquefiable ground: Validation of numerical simulations using centrifuge experiments.” J. Geotech. Geoenviron. Eng. 142 (6): 04016011. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001479.
Karimi, Z., and S. Dashti. 2017. “Ground motion intensity measures to evaluate. II: The performance of shallow-founded structures on liquefiable ground.” Earthquake Spectra 33 (1): 277–298. https://doi.org/10.1193/103015eqs163m.
Karimi, Z., S. Dashti, Z. Bullock, K. Porter, and A. Liel. 2018. “Key predictors of structure settlement on liquefiable ground: A numerical parametric study.” Soil Dyn. Earthquake Eng. 113 (Oct): 286–308. https://doi.org/10.1016/j.soildyn.2018.03.001.
Kramer, S. L., and R. A. Mitchell. 2006. “Ground motion intensity measures for liquefaction hazard evaluation.” Earthquake Spectra 22 (2): 413–438. https://doi.org/10.1193/1.2194970.
Law, H. K., and I. P. Lam. 2001. “Application of periodic boundary for large pile group.” J. Geotech. Geoenviron. Eng. 127 (10): 889–892. https://doi.org/10.1061/(ASCE)1090-0241(2001)127:10(889).
Li, P., S. Dashti, M. Badanagki, and P. Kirkwood. 2018. “Evaluating 2D numerical simulations of granular columns in level and gently sloping liquefiable sites using centrifuge experiments.” Soil Dyn. Earthquake Eng. 110 (Aug): 232–243. https://doi.org/10.1016/j.soildyn.2018.03.023.
Lu, J., J. Peng, A. Elgamal, Z. Yang, and K. H. Law. 2004. “Parallel finite element modeling of earthquake ground response and liquefaction” Earthquake Eng. Eng. Vibr. 3 (1): 23–37. https://doi.org/10.1007/BF02668848.
Luco, N., C. A. Cornell. 2007. “Structure-specific scalar intensity measures for near-source and ordinary earthquake ground motions.” Earthquake Spectra 23 (2): 357–392.
Lysmer, J., and R. L. Kuhlemeyer. 1969. “Finite dynamic model for infinite media.” J. Eng. Mech. Div. 95 (4): 859–877.
Mazzoni, S., F. McKenna, M. Scott, and G. Fenves. 2006. Open system for earthquake engineering simulation user command-language. Berkeley, CA: Network for Earthquake Engineering Simulations.
Menq, F. Y. 2003. “Dynamic properties of sandy and gravelly soils.” Ph.D. dissertation, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin.
Mitchell, J. K., and F. J. Wentz. 1991. Performance of improved ground during the Loma Prieta earthquake. Washington, DC: National Science Foundation.
NCEER (National Center for Earthquake Engineering Research). 1997. NCEER workshop on evaluation of liquefaction resistance of soils. Technical Rep. No. NCEER-97-0022. New York: NCEER.
Nikolaou, S., X. Vera-Grunauer, and R. Gilsanz. 2016. GEER-ATC earthquake reconnaissance. Muisne, Ecuador: Geotechnical Extreme Events Reconnaissance Association.
Olson, S. M., X. Mei, and Y. M. A. Hashash. 2020. “Nonlinear site response analysis with pore-water pressure generation for liquefaction triggering evaluation.” J. Geotech. Geoenviron. Eng. 146 (2): 04019128. https://doi.org/10.1061/(ASCE)GT.1943-5606.0002191.
Parra, E. 1996. “Numerical modeling of liquefaction and lateral ground deformation including cyclic mobility and dilation response in soil system.” Ph.D. thesis, Dept. of Civil Engineering, Rensselaer Polytechnic Institute.
Ramirez, J., A. R. Barrero, L. Chen, S. Dashti, A. Ghofrani, M. Taiebat, and P. Arduino. 2018. “Site response in a layered liquefiable deposit: Evaluation of different numerical tools and methodologies with centrifuge experimental results.” J. Geotech. Geoenviron. Eng. 142 (10): 04018073. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001947.
Rayamajhi, D., S. A. Ashford, R. W. Boulanger, and A. Elgamal. 2016a. “Dense granular columns in liquefiable ground. I: Shear reinforcement and cyclic stress ratio reduction.” J. Geotech. Geoenviron. Eng. 142 (7): 4016023. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001474.
Rayamajhi, D., R. W. Boulanger, S. A. Ashford, and A. Elgamal. 2016b. “Dense granular columns in liquefiable ground. II: Effects on deformations.” J. Geotech. Geoenviron. Eng. 142 (7): 04016024. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001475.
Rayamajhi, D., T. V. Nguyen, S. A. Ashford, R. W. Boulanger, J. Lu, A. Elgamal, and L. Shao. 2014. “Numerical study of shear stress distribution for discrete columns in liquefiable soils.” J. Geotech. Geoenviron. Eng. 140 (3): 04013034. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000970.
Seed, H. B., and I. M. Idriss. 1970. Soil moduli and damping factors for dynamic response analyses. Berkeley, CA: Univ. of California.
Skempton, A. W. 1986. “Standard penetration test procedures and the effects in sands of overburden pressure, relative density, particle size, ageing and overconsolidation.” Géotechnique 36 (3): 425–447. https://doi.org/10.1680/geot.1986.36.3.425.
Tibshirani, R. 1996. “Regression shrinkage and selection via the Lasso.” J. R. Stat. Soc. Ser. B (Methodol.) 58 (1): 267–288. https://doi.org/10.1111/j.2517-6161.1996.tb02080.x.
Tiznado, J. C., S. Dashti, C. Ledezma, B. P. Wham, and M. Badanagki. 2020. “Performance of embankments on liquefiable soils improved with dense granular columns: Observations from case histories and centrifuge experiments.” J. Geotech. Geoenviron. Eng. 146 (9): 04020073. https://doi.org/10.1061/(ASCE)GT.1943-5606.0002309.
Wotherspoon, L. M., R. P. Orense, M. Jacka, R. A. Green, B. R. Cox, and C. M. Wood. 2014. “Seismic performance of improved ground sites during the 2010–2011 Canterbury earthquake sequence.” Earthquake spectra 30 (1): 111–129. https://doi.org/10.1193/082213EQS236M.
Yang, Z., A. Elgamal, and E. Parra. 2003. “Computational model for cyclic mobility and associated shear deformation.” J. Geotech. Geoenviron. Eng. 129 (11): 1119–1127. https://doi.org/10.1061/(ASCE)1090-0241(2003)129:12(1119).
Yang, Z., J. Lu, and A. Elgamal. 2008. OpenSees soil models and solid-fluid fully coupled elements: User’s manual. San Diego: Univ. of California.
Zeghal, M., A.-W. Elgamal, H. T. Tang, and J. C. Stepp. 1995. “Lotung downhole array. II: Evaluation of soil nonlinear properties.” J. Geotech. Eng. 121 (4): 363–378. https://doi.org/10.1061/(ASCE)0733-9410(1995)121:4(363).
Zhang, Y., Z. Yang, J. Bielak, J. P. Conte, and A. Elgamal. 2003. “Treatment of seismic input and boundary conditions in nonlinear seismic analysis of a bridge ground system.” In Proc., 16th Engineering Mechanics Conf. Reston, VA: ASCE.
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Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 147 • Issue 10 • October 2021
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© 2021 American Society of Civil Engineers.
History
Received: Aug 18, 2020
Accepted: May 14, 2021
Published online: Aug 4, 2021
Published in print: Oct 1, 2021
Discussion open until: Jan 4, 2022
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