不同成因沉积土物理力学指标概率统计分析

doi:10.16285/j.rsm.2017.12.022

›› 2017, Vol. 38 ›› Issue (12): 3565-3572.doi: 10.16285/j.rsm.2017.12.022

• Fundamental Theroy and Experimental Research • Previous Articles Next Articles

Probabilistically statistical analysis on physico-mechanical indices for sediment soils

LI Gang^{1, 2}, ZHANG Jin-li^{2, 3}, YANG Qing^{2, 3}

1. Shaanxi Key Laboratory of Safety and Durability of Concrete Structures, Xijing University, Xi’an, Shaanxi 710123, China; 2. Institute of Geotechnical Engineering, School of Civil Engineering, Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China; 3. State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China

Received:2015-12-22 Online:2017-12-11 Published:2018-06-05
Supported by:
This work was supported by the National Natural Science Foundation of China (41572252).

Abstract

Abstract: The physico-mechanical properties of soil vary in different regions. There are great differences on engineering properties for soils formed by different geological depositions. Based on the investigation data of Dalian offshore artificial island, the soils could be subdivided into three independent statistical unit according to the geological origin, i.e., the top marine deposit , middle marine-continental deposit, and deep continental deposit. The physico-mechanical indices of deposits are analyzed by the SPSS software incorporated with mathematical statistics methods. The Gaussian distribution behaviors of deposit soils are hypothesis testing by the skewness and kurtosis method. The shear strength indices are optimized by the Bayesian approach. The results show that there are significant differences in the engineering properties of the deposits and their distribution. The standard deviation and variable coefficient of shear strength indices decrease after Bayesian optimized, and the time-varying predictions of parameters are realized.

Key words: statistical analysis, geological origin, Gaussian distribution, hypothesis testing, Bayesian approach

CLC Number:

TU 471

LI Gang, ZHANG Jin-li, YANG Qing, . Probabilistically statistical analysis on physico-mechanical indices for sediment soils[J]., 2017, 38(12): 3565-3572.

References

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