Assessment of empirical equations of the compression index of muddy clay: sensitivity to geographic locality
The physical and mechanical indices of soft soils have regional characteristics, and the engineering properties are very different under diverse geological conditions. Empirical equations provide a quick and effective method to calculate the compression index using other physical indices that are easily obtained. However, it is often unsatisfactory to calculate the compression index for a special region using the existing empirical equations. Hence, there is a need to propose regional empirical equations on the basis of a special research data for calculating the compression index. The validity of existing empirical equations for the soft soil in the Jiangmen region was evaluated using measured data. The results show that the equations proposed by Gao et al. (Rock Soil Mech 38(09):2713–2720, 2017) and Al–Khafaji and Andersland (J Geotech Eng 118(1):148–153, 1992) are superior to other existing single-variable and multi-variable empirical equations for the Jiangmen region; the values of ranking distance are 0.432 and 0.430, respectively. In addition, a new regional empirical equation for Jiangmen is proposed, utilizing a regression analysis of the measured data. The corresponding value of ranking distance is 0.320. The new equation is proven to be more accurate than the existing single- and multi-variable empirical equations.
KeywordsMuddy soil Compression index Evaluation methods Regional empirical equation Statistics relationship Regression analysis
The support received from the Key Program of Natural Science Foundation of China (51774020) and the Beijing Training Project for the Leading Talent in S & T (Z151100000315014) is gratefully acknowledged.
- Bowles JE (1979) Physical and geotechnical properties of soils. McGraw–Hill Book Company, New YorkGoogle Scholar
- Chen XP, Huang GY, Liang ZS (2003) Study on soft soil properties of the Pearl River Delta. Chin J Rock Mech Eng 22(1):137–141 (in Chinese)Google Scholar
- Cherubini C, Greco VR (1998) A comparison between “measured” and “calculated” values in geotechnics. Proceedings of the Workshop Probamat–21st Century: Probabilities and Materials. Kluwer Academic Publishers, Dordrecht, Netherlands, pp 481–498Google Scholar
- Cherubini C, Orr TLL (2000) A rational procedure for comparing measured and calculated values in geotechnics. In: Yokohama IS, Nakase A, Tsuchida T (eds) Proceedings of the international symposium on coastal geotechnical engineering in practice, AA Balkema, Rotterdam, vol. 1, pp 261–265Google Scholar
- Gao YB, Zhang SB, Ge XN (2017) Comparisons of compression index of Chinese coastal soft clay and soils from foreign regions. Rock Soil Mech 38(09):2713–2720 (in Chinese)Google Scholar
- Hough BK (1957) Basic soils engineering. The Ronald Press Company, New York, pp 114–115Google Scholar
- Mayne PW (1980) Cam–clay predictions of undrained strength. J Geotech Eng Div 106(11):1219–1242Google Scholar
- Nishida Y (1956) A brief note on compression index of soil. J Soil Mech Found Div 82(3):1–14. https://doi.org/10.1016/j.coastaleng.2018.04.014
- Theil H (1966) Applied economic forecasting. North–Holland Pub. Co., AmsterdamGoogle Scholar
- Xia YF, Wu DH, Wen JH (2008) Statistic analysis of physical and mechanical indices of soft soil in Zhujiang Delta. JHTRD 25(1):47–50 (in Chinese). http://manu27.magtech.com.cn/Jwk_gljtkj_en/EN/column/column4290.shtml
- Zhao YM, Jiang HH, Zhang HM (2004) Deformation parameters of Shenzhen soft clay. China Railway Science 03:41–44 (in Chinese)Google Scholar