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ZHAO Yu-fei, WANG Yi, YASEN Nasier, WANG Wen-bo, LU Peng-fei, LIU Biao. Gradation of filling materials of sand-gravel dams based on multi-dimensional probability distribution[J]. Chinese Journal of Geotechnical Engineering, 2022, 44(11): 2007-2016. DOI: 10.11779/CJGE202211006
Citation: ZHAO Yu-fei, WANG Yi, YASEN Nasier, WANG Wen-bo, LU Peng-fei, LIU Biao. Gradation of filling materials of sand-gravel dams based on multi-dimensional probability distribution[J]. Chinese Journal of Geotechnical Engineering, 2022, 44(11): 2007-2016. DOI: 10.11779/CJGE202211006

Gradation of filling materials of sand-gravel dams based on multi-dimensional probability distribution

  • The gradation and particle size of filling materials of sand-gravel dams determine the inter-particle contact relationship, and further affect the macro-mechanical response. Based on more than 2000 groups of test data detected during dam construction, the relationship between particle gradation and basic physical characteristics of dam materials is explored by using the probability and statistics method, and three gradation characteristic parameters that are most closely related to dry density in sand-gravel materials and transition materials are obtained respectively. Based on the one-dimensional Weibull probability distribution, the test data analysis method for dam materials is proposed. The one-dimensional Weibull distribution model is respectively established for the above three factors, and the estimated value of gradation parameters of coarse-grained soil is obtained under certain assurance rate. The expression for the three-dimensional Weibull distribution function is further derived, and a three-dimensional Weibull distribution model which can reflect the dry density by using the correlation among the three gradation characteristic parameters is established. The K-S tests are used to verify the fitting degree of the model, which proves the reliability that the three-dimensional Weibull distribution model is used for the analysis of dam materials considering the influences of multiple parameters at the same time.
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