Aggregate Simulation with Statistical Approach Considering Substituting

Byeong Hun Woo, Jeong Bae Lee, Hyunseok Lee and Hong Gi Kim
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Byeong Hun Woo: Civil and Environmental Engineering Department, Hanyang University, Seoul 04763, Korea
Jeong Bae Lee: Department of Civil Engineering, Daejin University, Pocheon-si 11159, Korea
Hyunseok Lee: Division of Horticulture and Medicinal Plant, College of Life Science and Biotechnology, Andong National University, Andong 36729, Korea
Hong Gi Kim: Civil and Environmental Engineering Department, Hanyang University, Seoul 04763, Korea

Sustainability, 2022, vol. 14, issue 3, 1-13

Abstract: This work focused on reflecting the substituting ratio of fine aggregate in an aggregate simulation. The existing simulation studies showed superior performance on generating the particles; however, the studies did not and could not reflect the substituting ratio of fine aggregate. Therefore, a statistical approach with the Monte Carlo simulation method was tried to improve the lacking part. According to the fitting of the distributions, the Cauchy distribution was best for the natural sand and the log-normal distribution was best for the substituting materials. The chosen two distributions were mixed and applied, using the Monte Carlo method with the mixed model, rather than the existing particle generation formula of the simulation. The substitution ratio was considered to be 0, 30, 50, 70, 100%. The fraction of small particles was gradually increased by the substituting ratio. As a result, the simulated particle distribution reflected well the statistical model. In addition, the simulation was almost the same as that of real particle distribution, according to the CT scanning.

Keywords: simulation; aggregate; substituting; Monte Carlo simulation; statistical approach (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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