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Abstract: The compression index is a key parameter in the field of soft clay engineering. In this paper, we propose an improved method for correlating the compression index with the physical properties of intact Chinese marine clays that are involved in many construction projects in coastal regions in China. First, the compression index and some common physical properties of clays from 21 regions along the Chinese coast are extracted from the literature. Then, a basic regression analysis for the compression index using the natural water content and atterberg limits is conducted. To improve the correlation performance, an evolutionary polynomial regression (EPR) and real coded genetic algorithm (RCGA) combined technique is adopted to formulate different equations involving different numbers of variables. An optimal correlation using only natural water content and liquid limit as input parameters is finally selected according to the root mean square error (RMSE), Akaike’s information criterion (AIC), and Bayesian information criterion (BIC). The proposed correlation is evaluated and shown to perform better than existing empirical correlations in predicting the compression index for all selected Chinese marine clays. This correlation is validated to be reliable and applicable to engineering applications through the prediction of the properties of an embankment on the southeast coast of China using finite element method. All comparisons show that the EPR and RCGA combined technique is powerful for correlating the compression index with the physical properties of the clay, and that model selection by RMSE, AIC, and BIC is effective. The proposed correlation could be used to update current formulations, and is applicable to engineering design in coastal regions of China.

It is an interesting work of application of an optimisation method to determine compressibility parameter of Chinese marine clay. The optimal correlation using only natural water content and liquid limit is selected according to the RMSE, AIC and BIC . The proposed correlation is evaluated in better performance than existing empirical correlations on predicting the compression index for all selected Chinese marine clays. This correlation is validated using finite element method. The EPR and RCGA combined technique is powerful for the correlation of compression index by physical properties of clay.

中国海相黏土的压缩指数的EPR-RCGA回归模型和RMSE-AIC-BIC模型选择及其工程应用

[1]Akaike H, 1998. Information theory and an extension of the maximum likelihood principle. Selected Papers of Hirotugu Akaike. Springer, p.199-213.

[2]Azzouz AS, Krizek RJ, Corotis RB, 1976. Regression analysis of soil compressibility. Soils and Foundations, 16(2):19-29.

[3]Bowles JE, 1979. Physical and Geotechnical Properties of Soils. McGraw Hill, New York, USA.

[4]Burland J, 1990. On the compressibility and shear strength of natural clays. Géotechnique, 40(3):329-378.

[5]Carrier WD, 1985. Consolidation parameters derived from index tests. Géotechnique, 35(2):211-213.

[6]Chen B, Sun DA, Lu HB, 2013. Experimental study of compression behavior of marine soft clays. Rock and Soil Mechanics, 34(2):381-388 (in Chinese).

[7]Faramarzi A, Alani AM, Javadi AA, 2014. An EPR-based self-learning approach to material modelling. Computers & Structures, 137:63-71.

[8]Gao DZ, Wei DD, Hu ZX, 1986. Geotechnical properties of Shanghai soils and engineering applications. Marine Geotechnology and Nearshore/Offshore Structures. ASTM International, USA.

[9]Giustolisi O, Savic DA, 2006. A symbolic data-driven technique based on evolutionary polynomial regression. Journal of Hydroinformatics, 8(3):207-222.

[10]Herrero AA, 1983. End-product inhibition in anaerobic fermentations. Trends in Biotechnology, 1(2):49-53.

[11]Hong ZS, Yin J, Cui YJ, 2010. Compression behaviour of reconstituted soils at high initial water contents. Géotechnique, 60(9):691-700.

[12]Hong ZS, Zeng LL, Cui YJ, et al., 2012. Compression behaviour of natural and reconstituted clays. Géotechnique, 62(4):291-301.

[13]Huang MS, Liu YH, Sheng DC, 2010. Simulation of yielding and stress–stain behavior of Shanghai soft clay. Computers and Geotechnics, 38(3):341-353.

[14]Jin YF, Yin ZY, Shen SL, et al., 2016a. Investigation into MOGA for identifying parameters of a critical state based sand model and parameters correlation by factor analysis. Acta Geotechnica, 11(5):1131-1145.

[15]Jin YF, Yin ZY, Shen SL, et al., 2016b. Selection of sand models and identification of parameters using an enhanced genetic algorithm. International Journal for Numerical and Analytical Methods in Geomechanics, 40(8):1219-1240.

[16]Jin YF, Yin ZY, Riou Y, et al., 2017a. Identifying creep and destructuration related soil parameters by optimization methods. KSCE Journal of Civil Engineering, 21(4):1123-1134.

[17]Jin YF, Yin ZY, Shen SL, et al., 2017b. A new hybrid real-coded genetic algorithm and its application to parameters identification of soils. Inverse Problems in Science and Engineering, 25(9):1343-1366.

[18]Karstunen M, Yin ZY, 2010. Modelling time-dependent behaviour of Murro test embankment. Géotechnique, 60(10):735-749.

[19]Koppula S, 1981. Statistical estimation of compression index. Geotechnical Testing Journal, 4(2):68-73.

[20]Li G, Zhang JL, Yang Q, 2016. Geotechnical investigations at the Dalian offshore airport, China. Marine Georesources & Geotechnology, 34(8):747-758.

[21]Liu S, Shao G, Du Y, et al., 2011. Depositional and geotechnical properties of marine clays in Lianyungang, China. Engineering Geology, 121(1-2):66-74.

[22]Miao LC, Zhang JH, Chen YN, 2007. Study on compressibility of Jiangsu marine clay. Chinese Journal of Geotechnical Engineering, 29(11):1711-1714 (in Chinese).

[23]Nagaraj T, Murthy BS, 1986. A critical reappraisal of compression index equations. Géotechnique, 36(1):27-32.

[24]Nath A, DeDalal SS, 2004. The role of plasticity index in predicting compression behaviour of clays. Electronic Journal of Geotechnical Engineering, 9:1-7.

[25]Ng CW, Li Q, Liu GB, 2011. Characteristics of one-dimensional compressibility of Shanghai clay. Chinese Journal of Geotechnical Engineering, 33(4):630-636 (in Chinese).

[26]Ozer M, Isik NS, Orhan M, 2008. Statistical and neural network assessment of the compression index of clay-bearing soils. Bulletin of Engineering Geology and the Environment, 67(4):537-545.

[27]Park HI, Lee SR, 2011. Evaluation of the compression index of soils using an artificial neural network. Computers and Geotechnics, 38(4):472-481.

[28]Poles S, Fu Y, Rigoni E, 2009. The effect of initial population sampling on the convergence of multi-objective genetic algorithms. Multiobjective Programming and Goal Programming. Springer, p.123-133.

[29]Rezania M, Javadi AA, Giustolisi O, 2010. Evaluation of liquefaction potential based on CPT results using evolutionary polynomial regression. Computers and Geotechnics, 37(1-2):82-92.

[30]Schwarz G, 1978. Estimating the dimension of a model. The Annals of Statistics, 6(2):461-464.

[31]Shen SL, Chai JC, Hong ZS, et al., 2005. Analysis of field performance of embankments on soft clay deposit with and without PVD-improvement. Geotextiles and Geomembranes, 23(6):463-485.

[32]Shen SL, Wu HN, Cui YJ, et al., 2014. Long-term settlement behaviour of metro tunnels in the soft deposits of Shanghai. Tunnelling and Underground Space Technology, 40:309-323.

[33]Shen SL, Wang JP, Wu HN, et al., 2015. Evaluation of hydraulic conductivity for both marine and deltaic deposits based on piezocone testing. Ocean Engineering, 110:174-182.

[34]Sridharan A, Nagaraj H, 2000. Compressibility behaviour of remoulded, fine-grained soils and correlation with index properties. Canadian Geotechnical Journal, 37(3):712-722.

[35]Sridharan A, Gurtug Y, 2005. Compressibility characteristics of soils. Geotechnical & Geological Engineering, 23(5):615-634.

[36]Terzaghi K, Peck RB, Mesri G, 1996. Soil Mechanics in Engineering Practice. John Wiley & Sons.

[37]Tiwari B, Ajmera B, 2012. New correlation equations for compression index of remolded clays. Journal of Geotechnical and Geoenvironmental Engineering, 138(6):757-762.

[38]Wei DD, Hu ZX, 1980. Experimental study of preconsolidation pressure and compressibility parameters of Shanghai subsoil. Chinese Journal of Geotechnical Engineering, 2(4):13-22 (in Chinese).

[39]Wroth C, Wood D, 1978. The correlation of index properties with some basic engineering properties of soils. Canadian Geotechnical Journal, 15(2):137-145.

[40]Wu CJ, Ye GL, Wang JH, 2014. Relationship between compression index and natural water content of Shanghai clay. Rock and Soil Mechanics, 35(11):3184-3190 (in Chinese).

[41]Wu CJ, Ye GL, Zhang LL, et al., 2015. Depositional environment and geotechnical properties of Shanghai clay: a comparison with Ariake and Bangkok clays. Bulletin of Engineering Geology and the Environment, 74(3):717-732.

[42]Wu HN, Shen SL, Ma L, et al., 2015. Evaluation of the strength increase of marine clay under staged embankment loading: a case study. Marine Georesources & Geotechnology, 33(6):532-541.

[43]Yao YP, Sun DA, 2000. Application of Lade’s criterion to Cam-clay model. Journal of Engineering Mechanics, 126(1):112-119.

[44]Yao YP, Hou W, Zhou AN, 2009. UH model: three dimensional unified hardening model for overconsolidated clays. Géotechnique, 59(5):451-469.

[45]Yin JH, 1999. Properties and behaviour of Hong Kong marine deposits with different clay contents. Canadian Geotechnical Journal, 36(6):1085-1095.

[46]Yin JH, 2002. Stress-strain strength characteristics of a marine soil with different clay contents. Geotechnical Testing Journal, 25(4):459-462.

[47]Yin ZY, Hicher PY, 2008. Identifying parameters controlling soil delayed behaviour from laboratory and in situ pressuremeter testing. International Journal for Numerical and Analytical Methods in Geomechanics, 32(12):1515-1535.

[48]Yin ZY, Wang JH, 2012. A one-dimensional strain-rate based model for soft structured clays. Science China Technological Sciences, 55(1):90-100.

[49]Yin ZY, Chang CS, Hicher PY, et al., 2009. Micromechanical analysis of kinematic hardening in natural clay. International Journal of Plasticity, 25(8):1413-1435.

[50]Yin ZY, Chang CS, Karstunen M, et al., 2010. An anisotropic elastic-viscoplastic model for soft clays. International Journal of Solids and Structures, 47(5):665-677.

[51]Yin ZY, Karstunen M, Chang CS, et al., 2011. Modeling time-dependent behavior of soft sensitive clay. Journal of Geotechnical and Geoenvironmental Engineering, 137(11):1103-1113.

[52]Yin ZY, Xu Q, Hicher PY, 2013. A simple critical-state-based double-yield-surface model for clay behavior under complex loading. Acta Geotechnica, 8(5):509-523.

[53]Yin ZY, Zhu QY, Yin JH, et al., 2014. Stress relaxation coefficient and formulation for soft soils. Géotechnique Letters, 4(1):45-51.

[54]Yin ZY, Yin JH, Huang HW, 2015. Rate-dependent and long-term yield stress and strength of soft Wenzhou marine clay: experiments and modelling. Marine Georesources & Geotechnology, 33(1):79-91.

[55]Yoon GL, Kim BT, Jeon SS, 2004. Empirical correlations of compression index for marine clay from regression analysis. Canadian Geotechnical Journal, 41(6):1213-1221.

[56]Zhu QY, Jin YF, Yin ZY, et al., 2013. Influence of natural deposition plane orientation on oedometric consolidation behavior of three typical clays from southeast coast of China. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 14(11):767-777.