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Computers and Concrete
  Volume 26, Number 2, August 2020, pages 127-136
DOI: http://dx.doi.org/10.12989/cac.2020.26.2.127
 


Micromechanical investigation for the probabilistic behavior of unsaturated concrete
Qing Chen, Zhiyuan Zhu, Fang Liu, Haoxin Li and Zhengwu Jiang

 
Abstract
    There is an inherent randomness for concrete microstructure even with the same manufacturing process. Meanwhile, the concrete material under the aqueous environment is usually not fully saturated by water. This study aimed to develop a stochastic micromechanical framework to investigate the probabilistic behavior of the unsaturated concrete from microscale level. The material is represented as a multiphase composite composed of the water, the pores and the intrinsic concrete (made up by the mortar, the coarse aggregates and their interfaces). The differential scheme based two-level micromechanical homogenization scheme is presented to quantitatively predict the concrete\'s effective properties. By modeling the volume fractions and properties of the constituents as stochastic, we extend the deterministic framework to stochastic to incorporate the material\'s inherent randomness. Monte Carlo simulations are adopted to reach the different order moments of the effective properties. A distribution-free method is employed to get the unbiased probability density function based on the maximum entropy principle. Numerical examples including limited experimental validations, comparisons with existing micromechanical models, commonly used probability density functions and the direct Monte Carlo simulations indicate that the proposed models provide an accurate and computationally efficient framework in characterizing the material\'s effective properties. Finally, the effects of the saturation degrees and the pore shapes on the concrete macroscopic probabilistic behaviors are investigated based on our proposed stochastic micromechanical framework.
 
Key Words
    unsaturated concrete; probabilistic behaviors; effective properties; deterministic and stochastic micromechanics; distribution-free method; differential scheme; Monte Carlo simulations
 
Address
Qing Chen: Jiangsu Key Laboratory of Environmental Impact and Structural Safety in Engineering, University of Mining & Technology, Jiangsu, 221116, China; Key Laboratory of Advanced Civil Engineering Materials, Tongji University, Ministry of Education, 4800 Cao\'an Road, Shanghai 201804, China; School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
Zhiyuan Zhu: School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
Fang Liu: State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, 200092, China
Haoxin Li: Key Laboratory of Advanced Civil Engineering Materials, Tongji University, Ministry of Education,
4800 Cao\'an Road, Shanghai 201804, China; School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
Zhengwu Jiang: Key Laboratory of Advanced Civil Engineering Materials, Tongji University, Ministry of Education,
4800 Cao\'an Road, Shanghai 201804, China; School of Materials Science and Engineering, Tongji University, Shanghai 201804, China
 

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