Rock and Soil Mechanics ›› 2020, Vol. 41 ›› Issue (9): 3031-3040.doi: 10.16285/j.rsm.2019.1250

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Application and analysis of matrix-structuring coefficient for graded aggregates used in heavy-haul railway subgrade surface

CHEN Xiao-bin1, 2, YU Zhao-sheng1, 2, GUANG Chao1, 2, ZHANG Jia-sheng1, 2, DONG Liang3   

  1. 1. School of Civil Engineering, Central South University, Changsha, Hunan 410075, China; 2. MOE Key Laboratory of Engineering Structures of Heavy Haul Railway, Central South University, Changsha, Hunan 410075, China; 3. China Academy of Railway Sciences, Beijing 100081, China
  • Received:2019-07-16 Revised:2020-04-24 Online:2020-09-11 Published:2020-10-21
  • Supported by:
    This work was supported by National Nature Science Foundation(5167082383, 51608533).

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Abstract: The physical and mechanical properties of aggregates are determined by their internal physical matrix-structuring, which cannot be directly demonstrated by traditional gradation curves. Also, there is a lack of optimal target function in designing of graded aggregates used in heavy-haul railway subgrade surface. This study established a grading curve model based on logarithmic probability regression equation and transformation of traditional gradation integral curve, and proposed a coefficient of matrix-structuring ‘R’. The mathematical expression of R was derived and the sensitivity of related parameters was analyzed. Based on the physical meaning of R, a practice engineering approach to optimize graded aggregates used in heavy-haul railway subgrade surface was proposed with the target of optimizing R. The feasibility of the proposed approach was verified by compaction test, large direct shear test and permeability test. The optimal value of R was determined by experimentation and optimization, between 21.17 and 22.08. Findings in this study provide reference for gradation optimization designing of graded aggregates used in heavy-haul railway subgrade surface.

Key words: graded aggregates, coefficient of matrix-structuring, gradation optimization, subgrade surface, heavy-haul railway

CLC Number: 

  • TD 325
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