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Establishment of the prediction model of soil liquefaction based on capacity energy concept and rigid regression

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Abstract

The accurate prediction for the soil liquefaction based on the field test data is the primary method of evaluating the dynamic property during the engineering geology survey, which will provide a reference for the subsequent engineering design. Considering the essence of soil liquefaction and the disadvantage of the conventional stress-based prediction method, the capacity energy concept was introduced in this paper. Firstly, prediction parameters were determined and analyzed from the mesoscopic aspect, then, the rigid regression was introduced to train the energy-based prediction model based on a huge amount of indoor experiment data; the dataset was divided into the training set and testing set by the empirical ratio of 6:4. Moreover, the sensitivity analysis for every parameter was conducted by removing the investigated parameter. The results showed that the rigid regression could well learn and fit the linear relationship between the capacity energy and influencing parameters. The parameters of \({C}_{c}\), \({C}_{u}\), \(FC\), \({D}_{r}\), and \({p}^{^{\prime}}\) all have a positive impact on the prediction accuracy; among them, the \({D}_{r}\) is the most important. By contrast, the \({D}_{50}\) disturbed the prediction result due to its average physical meaning and is suggested to be ignored in training in the future.

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References

  • Alavi AH, Gandomi AH (2012) Energy-based numerical models for assessment of soil liquefaction. Geosci Front 3:541–555. https://doi.org/10.1016/j.gsf.2011.12.008

    Article  Google Scholar 

  • Andrus RD, Stokoe KH II (2000) Liquefaction resistance of soils from shear-wave velocity. J Geotech Geoenviron Eng, ASCE 126:1015–1025

  • Andrus RD, Stokoe KH II, Chung RM (1999) Draft guidelines for evaluating liquefaction resistance using shear wave velocity measurements and simplified procedures. Gaithersburg, Md: National Institute of Standards and Technology

  • Baziar MH, Jafarian Y (2007) Assessment of liquefaction triggering using strain energy concept and ANN model: capacity energy. Soil Dyn Earthq Eng 27:1056–1072. https://doi.org/10.1016/j.soildyn.2007.03.007

    Article  Google Scholar 

  • Baziar MH, Jafarian Y, Shahnazari H et al (2011) Prediction of strain energy-based liquefaction resistance of sand-silt mixtures: an evolutionary approach. Comput Geosci 37:1883–1893. https://doi.org/10.1016/j.cageo.2011.04.008

    Article  Google Scholar 

  • Baziar MH, Sharafi H (2011) Assessment of silty sand liquefaction potential using hollow torsional tests-an energy approach. Soil Dyn Earthq Eng 31:857–865. https://doi.org/10.1016/j.soildyn.2010.12.014

    Article  Google Scholar 

  • Behavior SS, Symposium AG (2006) Soil stress-strain behavior: measurement, modeling and analysis geotechnical symposium in Roma, March 16 & 17, 2006. Sci Technol 1–10. https://doi.org/10.1007/978-1-4020-6146-2

  • Boulanger RW, Idriss IM (2004) State normalization of penetration resistance and the effect of overburden stress on liquefaction resistance. Proceedings of the 11th International Conference on Soil Dynamics and Earthquake Engineering, and 3rd International Conference on Earthquake Geotechnical Engineering, Berkeley, CA: University of California

  • Boulanger RW, Idriss IM (2014) Probabilistic standard penetration test-based liquefaction-triggering procedure. J Geotech Geoenviron Eng 138:1185–1195

    Article  Google Scholar 

  • Cabalar AF, Cevik A, Gokceoglu C (2012) Some applications of Adaptive Neuro-Fuzzy Inference System (ANFIS) in geotechnical engineering. Comput Geotech 40:14–33. https://doi.org/10.1016/j.compgeo.2011.09.008

  • Chemmam M, Arab A, Belkhatir M, Bouferra R (2016) Behavior of loose silty sand of Chlef River: effect of low plastic fine contents and other parameters. Mar Georesources Geotechnol 34:384–394. https://doi.org/10.1080/1064119X.2015.1014983

    Article  Google Scholar 

  • Chen YR, Hsieh SC, Chen JW, Shih CC (2005) Energy-based probabilistic evaluation of soil liquefaction. Soil Dyn Earthq Eng 25:55–68. https://doi.org/10.1016/j.soildyn.2004.07.002

    Article  Google Scholar 

  • Chen Z, Li H, Goh ATC et al (2020) Soil liquefaction assessment using soft computing approaches based on capacity energy concept. Geosciences 10:330. https://doi.org/10.3390/geosciences10090330

    Article  Google Scholar 

  • Chen L, Qiao L, Li Q (2019) Study on dynamic compaction characteristics of gravelly soils with crushing effect. Soil Dyn Earthq Eng 120:158–169. https://doi.org/10.1016/j.soildyn.2019.01.034

    Article  Google Scholar 

  • Chen GX, Wu Q, Sun S et al (2021) Advances in the development of soil liquefaction triggering procedures during earthquakes: retrospect and prospect. J Disaster Prev Mitigationg Eng 41. https://doi.org/10.13409/j.cnki.jdpme.2021.04.001

  • Chen GX, Zhang KX, Xie JF (1991) Research on reliability of liquefaction prediction. Earthq Eng Eng Vib 11:85–96. (in Chinese)

  • Cetin KO, Der Kiureghian A, Seed RB (2002) Probabilistic models for the initiation of seismic soil liquefaction. Struct Saf 24:67–82

    Article  Google Scholar 

  • Cetin KO, Seed RB, Der Kiureghian A et al (2004) Standard penetration test-based probabilistic and deterministic assessment of seismic soil liquefaction potential. J Geotech Geoenviron Eng 130:1314–1340

    Article  Google Scholar 

  • Cetin KO, Seed RB, Kayen RE et al (2018a) Examination of differences between three SPT-based seismic soil liquefaction triggering relationships. Soil Dyn Earthq Eng 113:75–86

    Article  Google Scholar 

  • Cetin KO, Seed RB, Kayen RE et al (2018b) SPT-based probabilistic and deterministic assessment of seismic soil liquefaction triggering hazard. Soil Dyn Earthq Eng 115:698–709

    Article  Google Scholar 

  • Davis RO, Berrill JB (1982) Energy dissipation and seismic liquefaction in sands. Earthq Eng Struct D 10:59–68

    Article  Google Scholar 

  • Dief HM, Figueroa JL (2001) Liquefaction assessment by the energy method through centrifuge modeling. In: Zeng XW (ed) Proceedings of the NSF International Workshop on Earthquake Simulation in Geotechnical Engineering, CWRU, Cleveland, OH

  • Dobry R, Ladd RS, Yokel FY, Chung RM, Powell D (1982) Prediction of pore water pressure build-up and liquefaction of sands during earthquakes by the cyclic strain method. National Bureau of Standards, US Department of Commerce, US Governmental Printing Office, Building Science Series, Washington, DC

  • Dobry R, Stokoe KH II, Ladd RS et al (1981) Liquefaction susceptibility from S-wave velocity. Proceedings of the ASCE National Convention, In Situ Tests to Evaluate Liquefaction Susceptibility, ASCE, New York:[s.n.]

  • Figueroa JL, Saada AS, Liang L, Dahisaria MN (1994) Evaluation of soil liquefaction by energprinciples. J Geotech Geoenviron 20:1554–1569

    Google Scholar 

  • Green RA (2001) Energy-based evaluation and remediation of liquefiable soils. PhD dissertation, Virginia Polytechnic Institute and State University, Blacksburg, VA

  • Idriss IM, Boulanger RW (2004) Semi-empirical procedures for evaluating liquefaction potential during earthquakes. Proceedings of the 11th International Conference on Soil Dynamics and Earthquake Engineering, and the 3rd International Conference on Earthquake Geotechnical Engineering [s.l.]: Stallion Press, p 32–56

  • Idriss IM, Boulanger RW (2006) Semi-empirical procedures for evaluating liquefaction potential during earthquakes. Soil Dyn Earthq Eng 26:115–130

    Article  Google Scholar 

  • Idriss IM, Boulanger RW (2008) Soil liquefaction during earthquakes. Oakland, CA: Earthquake Engineering Research Institute

  • Idriss IM, Boulanger RW (2010) SPT-based liquefaction triggering procedures. University of California, Davis

    Google Scholar 

  • Idriss IM, Boulanger RW (2012) Examination of SPT-based liquefaction triggering correlations. Earthq Spectra 28(989–1):018

    Google Scholar 

  • Jafarian Y, Towhata I, Baziar MH et al (2012) Strain energy based evaluation of liquefaction and residual pore water pressure in sands using cyclic torsional shear experiments. Soil Dyn Earthq Eng 35:13–28. https://doi.org/10.1016/j.soildyn.2011.11.006

    Article  Google Scholar 

  • Jafarian Y, Vakili R, Abdollahi AS, Baziar MH (2014) Simplified soil liquefaction assessment based on cumulative kinetic energy density: attenuation law and probabilistic analysis. Int J Geomech 14:267–281. https://doi.org/10.1061/(asce)gm.1943-5622.0000317

    Article  Google Scholar 

  • Juang CH, Chen CH, Mayne PW (2008) CPTU simplified stress-based model for evaluating soil liquefaction potential. Soils Found 48:755–770. https://doi.org/10.3208/sandf.48.755

    Article  Google Scholar 

  • Juang CH, Chen CJ, Tang WH et al (2000a) CPT-based liquefaction analysis, part 1: determination of limit state function. Geotechnique 50:583–592. https://doi.org/10.1680/geot.2000.50.5.583

    Article  Google Scholar 

  • Juang CH, Chen CJ, Rosowsky DV et al (2000b) CPT-based liquefaction analysis, part 2: reliability for design. Geotechnique 50:593–599. https://doi.org/10.1680/geot.2000.50.5.593

    Article  Google Scholar 

  • Juang CH, Ching J, Luo Z et al (2012) New models for probability of liquefaction using standard penetration tests based on an updated database of case histories. Eng Geol 133:85–93

    Article  Google Scholar 

  • Juang CH, Fang SY, Tang WH et al (2009) Evaluating model uncertainty of an SPT-based simplified method for reliability analysis for probability of liquefaction. Soils Found 49:135–152

    Article  Google Scholar 

  • Juang CH, Jiang T, Andrus RD (2002) Assessing probability-based methods for liquefaction potential evaluation. J Geotech Geoenviron Eng 128:580–589

    Article  Google Scholar 

  • Juang CH, Rosowsky DV, Tang WH (1999) Reliability-based method for assessing liquefaction potential of soils. J Geotech Geoenviron Eng 125:684–689

    Article  Google Scholar 

  • Jafariavval Y, Derakhshani A (2020) New formulae for capacity energy-based assessment of liquefaction triggering. Mar Georesources Geotechnol 38:214–222. https://doi.org/10.1080/1064119X.2019.1566297

    Article  Google Scholar 

  • Javdanian H (2019) Evaluation of soil liquefaction potential using energy approach: experimental and statistical investigation. Bull Eng Geol Environ 78:1697–1708. https://doi.org/10.1007/s10064-017-1201-6

    Article  Google Scholar 

  • Javdanian H, Heidari A, Kamgar R (2017) Energy-based estimation of soil liquefaction potential using GMDH algorithm. Iran J Sci Technol - Trans Civ Eng 41:283–295. https://doi.org/10.1007/s40996-017-0061-4

    Article  Google Scholar 

  • Kokusho T (2017) Liquefaction potential evaluations by energy-based method and stress-based method for various ground motions: supplement. Soil Dyn Earthq Eng 95:40–47. https://doi.org/10.1016/j.soildyn.2017.01.033

    Article  Google Scholar 

  • Kokusho T (2007) Liquefaction strengths of poorly-graded and well-graded granular soils investigated by lab tests. Geotech Geol Earthq Eng 6:159–184. https://doi.org/10.1007/978-1-4020-5893-6_8

    Article  Google Scholar 

  • Liang L (1995) Development of an energy method for evaluating the liquefaction potential of a soil deposit. PhD dissertation, Department of Civil Engineering, Case Western Reserve University, Cleveland, OH; deposit. PhD thesis, Department of Civil Engineering, Case Western Reserve University, Cleveland, OH

  • Moss RE, Seed RB, Kayen RE et al (2006) CPT-based probabilistic and deterministic assessment of in situ seismic soil liquefaction potential. J Geotech Geoenviron Eng 132:1032–1051. https://doi.org/10.1061/(ASCE)1090-0241(2006)132:8(1032)

  • Olsen RS (1997) Cyclic liquefaction based on the cone penetrometer test. Proceedings of the NCEER Workshop on Evaluation of Liquefaction Resistance of Soils, Buffalo: State University of New York, p 225–276

  • Pan K, Yang ZX (2020) Evaluation of the liquefaction potential of sand under random loading conditions: equivalent approach versus energy-based method. J Earthquake Eng 24:59–83

    Article  Google Scholar 

  • Pirhadi N, Tang X, Yang Q (2019) Energy evaluation of triggering soil liquefaction based on the response surface method. Appl Sci (Switzerland) 9(4)

  • Robertson PK, Woeller DJ, Finn WDL (1992) Seismic cone penetration test for evaluating liquefaction potential under cyclic loading. Can Geotech J, Ottawa 29:686–695

  • Robertson PK, Wride CE (1997) Cyclic liquefaction and its evaluation based on SPT and CPT. Proceedings of the NCEER Workshop on Evaluation of Liquefaction Resistance of Soils

  • Samui P, Kurup P (2012) Multivariate adaptive regression spline and least square support vector machine for prediction of undrained shear strength of clay. Int J Appl Metaheuristic Comput 3:33–42. https://doi.org/10.4018/jamc.2012040103

    Article  Google Scholar 

  • Seed HB (1980) Closure to soil liquefaction and cyclic mobility evaluation for level ground during earthquakes. J Geotech Eng-ASCE 106(GT6):724

    Google Scholar 

  • Seed HB, Idriss IM (1971) Simplified procedure for evaluating soil liquefaction potential. J Soil Mech Found 97:1249–1273

    Article  Google Scholar 

  • Shibata T, Teparaksa W (1988) Evaluation of liquefaction potentials of soils using tip penetration tests. Soils Found 28:49–60. https://doi.org/10.1016/0148-9062(89)90158-7

    Article  Google Scholar 

  • Sitharam TG (2003) Discrete element modelling of cyclic behaviour of granular materials. Geotech Geol Eng 21:297–329. https://doi.org/10.1023/B:GEGE.0000006036.00597.0b

    Article  Google Scholar 

  • Suzuki Y, Tokimatsu K, Taya Y et al (1995) Correlation between CPT data and dynamic properties of in situ frozen samples. Proceedings of the 3rd International Conference on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics St. Louis, MO:[s.n.]

  • Towhata I, Ishihara K (1985) Shear work and pore water pressure in undrained shear. Soils Found 25:73–84

    Article  Google Scholar 

  • Vieux-Champagne F, Sieffert Y, Grange S et al (2013) This preprint is a PDF of a manuscript that has been accepted for. Earthq Spectra 33:1075–1100

    Article  Google Scholar 

  • Wang G, Wang Z, Ye Q, Wei X (2020) Particle breakage and deformation behavior of carbonate sand under drained and undrained triaxial compression. Int J Geomech 20:1–12. https://doi.org/10.1061/(ASCE)GM.1943-5622.0001601

    Article  Google Scholar 

  • Zhang WG, Goh ATC (2013) Multivariate adaptive regression splines for analysis of geotechnical engineering systems. Comput Geotech 48:82–95. https://doi.org/10.1016/j.compgeo.2012.09.016

    Article  Google Scholar 

  • Zhang W, Goh ATC (2016) Evaluating seismic liquefaction potential using multivariate adaptive regression splines and logistic regression. Geomech Eng 10:269–284

    Article  Google Scholar 

  • Zhang W, Goh ATC, Zhang Y et al (2015) Assessment of soil liquefaction based on capacity energy concept and multivariate adaptive regression splines. Eng Geol 188:29–37. https://doi.org/10.1016/j.enggeo.2015.01.009

    Article  Google Scholar 

  • Zhang W, Li H, Li Y et al (2021a) Application of deep learning algorithms in geotechnical engineering: a short critical review. Springer, Netherlands

    Google Scholar 

  • Zhang W, Wu C, Zhong H et al (2021b) Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization. Geosci Front 12:469–477. https://doi.org/10.1016/j.gsf.2020.03.007

    Article  Google Scholar 

  • Zhou YG, Chen YM (2007) Laboratory investigation on assessing liquefaction resistance of sandy soils by shear wave velocity. J Geotech Geoenviron Eng, ASCE 133:959–972

    Article  Google Scholar 

  • Zhou YG, Chen YM, Ke H (2005) Improvement of simplified procedure for liquefaction potential evaluation of sands by shear wave velocity. Chin J Rock Mech Eng 24:2369–2375. (in Chinese)

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Authors and Affiliations

  1. College of Civil and Transportation Engineering, Hohai University, Nanjing, 210098, China

    Yan Zhang

  2. Key Laboratory of Ministry of Education for Geomechanics and Embankment Engineering, Hohai University, Nanjing, 210098, China

    Yan Zhang

  3. Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, and Department of Geotechnical Engineering, Tongji University, Shanghai, 200092, China

    Yong-gang Zhang

  4. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610000, China

    Chao Zhai

  5. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 610051, China

    Yuanlun Xie

  6. College of Civil Engineering, University of Science and Technology Liaoning, Anshan, 114053, China

    Junbo Qiu

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  1. Yan Zhang
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  2. Yong-gang Zhang
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  3. Chao Zhai
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  4. Yuanlun Xie
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  5. Junbo Qiu
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Contributions

Yan Zhang performed material preparation, data collection, and the first draft. Chao Zhai performed data analysis and model parameter determination. Yong-gang Zhang proposed the idea of this research and supervised the structure; Yuanlun Xie and Junbo Qiu revised the first draft and provided suggestions for improvement. All authors give their final approval of the manuscript version to be submitted and any revised version of it.

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Correspondence to Yong-gang Zhang.

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Highlights

• The soil liquefaction is induced by deformation accumulation and energy dissipation.

• The shear strain accumulation process is related to the soil particle shape and soil skeleton structure.

• The rigid regression algorithm is very suitable for fitting the weakly linear relationship between the capacity energy and influencing parameters.

• The parameter mean grain diameter \({D}_{50}\) has a negative effect on the model performance.

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Zhang, Y., Zhang, Yg., Zhai, C. et al. Establishment of the prediction model of soil liquefaction based on capacity energy concept and rigid regression. Bull Eng Geol Environ 81, 123 (2022). https://doi.org/10.1007/s10064-022-02620-3

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