Title: Bayesian-based durability life prediction method of nano-modified concrete

Authors: Zhanzhan Zheng; Pu Miao; Lina Zheng

Addresses: School of Civil Engineering, Shangqiu Institute of Technology, Shangqiu 476000, China ' School of Civil Engineering, Shangqiu Institute of Technology, Shangqiu 476000, China ' School of Civil Engineering, Shangqiu Institute of Technology, Shangqiu 476000, China

Abstract: Due to the low prediction accuracy of traditional concrete durability life prediction methods, a Bayesian-based durability life prediction method for nano-modified concrete is proposed. Firstly, the diffusion function of CO₂ in concrete is established through Fick's first law, and the carbonation depth of concrete is determined based on regression analysis. Then, according to the damage mechanics theory, the freeze-thaw cycle damage function of nano-modified concrete is established. Finally, according to the Bayesian theorem and the binary normal distribution relationship, combined with the prediction criteria, a Bayesian-based durability life prediction model of nano-modified concrete is established, and the determined concrete carbonation depth is input into the prediction model to output the prediction results. The experimental results show that the prediction accuracy of concrete durability life is high.

Keywords: Bayesian theorem; nanometre modified concrete; durability life; damage mechanics theory; regression analysis.

DOI: 10.1504/IJMPT.2023.132192

International Journal of Materials and Product Technology, 2023 Vol.67 No.1, pp.26 - 37

Received: 17 Oct 2022
Accepted: 08 Feb 2023
Published online: 12 Jul 2023 *

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