Bayesian based durability life prediction method of nano-modified concrete
Source abstract
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.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Concrete Corrosion and Durability
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References
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