The multi-factor effect of tensile strength of concrete in numerical simulation based on the Monte Carlo random aggregate distribution. (20th March 2018)

• Record Type: Journal Article
• Authors: Chen, Changhong; Zhang, Qian; Keer, Leon M.; Yao, Yao; Huang, Ying
• Is Part Of: Construction & building materials. Volume 165(2018)
• Page Start: 585
• Page End: 595
• Publication Date: 2018-03-20
• Subjects: Random aggregate model -- Size effect -- Meso-scale simulation -- Nominal tensile strength -- Multi-factor effect; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2018.01.056
• Languages: English
• ISSNs: 0950-0618

Abstract

Highlights: A four-phase random aggregate model, consisting of cement mortar matrix, coarse aggregate, the cohesive band and the initial defect is presented. The numerical simulation is carried out by considering the factors of specimen size, area fraction of coarse aggregate and porosity on the nominal tensile strength of concrete, and corresponding fitting formulas are proposed. The combined effect relationship on the nominal tensile strength of concrete is shown by using the multiplicative form of power exponential function. The proposed formula for the multi-factor combined effect shows good precision. Abstract: The effects of specimen size, area fraction of coarse aggregates and porosity on the nominal tensile strength of concrete are investigated by uniaxial tensile simulations based on the Monte Carlo random aggregate model. First, a four-phase random aggregate model, consisting of cement mortar matrix, coarse aggregate, cohesive band and the initial defect, is presented. The numerical simulation is carried out by considering specimen size, area fraction of coarse aggregate and porosity on the nominal tensile strength of concrete, and corresponding fitting formulas are proposed. Next, the relationships of the combined effects on the nominal tensile strength of concrete are shown using the multiplicative form of power exponential function. The proposed formula for the multi-factor combined effect shows good precision.