›› 2015, Vol. 36 ›› Issue (5): 1357-1362.doi: 10.16285/j.rsm.2015.05.017

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

A method for determining the ratio of similar materials with cement and plaster as bonding agents

SHI Xiao-meng1, LIU Bao-guo1, XIAO Jie2   

  1. 1. School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China; 2. China Ordnance Industry and Geotechnical Institute, Beijing 100053, China
  • Received:2014-01-20 Online:2015-05-11 Published:2018-06-13

Abstract: In this study, a production method is proposed for making the similar material of sand and barite powder using cement and plaster as bonding agents. Three controlling factors including sand-blinder ratio, cement-plaster ratio and barite content are chosen to perform the orthogonal tests. The ratio schemes are obtained. A series of tests is carried out to determine the density, uniaxial compression strength and elasticity modulus of different similar materials. The extremum difference analysis is adopted to analyze the sensibilities of three factors to parameters of the similar material. It is found that the density is primarily controlled by the barite content, secondly by sand-blinder ratio, cement-plaster ratio; the uniaxial compression strength and the elasticity modulus are significantly affected by the sand-blinder ratio, next by the cement-plaster ratio and barite content. The density decreases as sand-blinder ratio increases, and increases with the cement-plaster ratio and barite content; the uniaxial compression strength and the elasticity modulus significantly decreases as the sand-blinder ratio increases, but gradually increases as cement-plaster ratio and barite content increase. Empirical equations for determining the similar material ratio are developed based on the multiple linear regressions of the test data using the program of MATLAB. The proposed method is validated through a practical case.

Key words: similar material, test technology, orthogonal design method, regression analysis

CLC Number: 

  • TU 452
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