Reliability Analysis of the Freeze–Thaw Cycle of Aeolian Sand Concrete Based on a Dual Neural Network in Series Structure Failure Mode

Abstract

Aeolian sand is a low-quality natural resource widely distributed in Inner Mongolia, China. Aeolian sand concrete has been developed as a primary raw material and tested to determine its frost resistance durability. In this study, the mechanism of concrete durability damage and deterioration was determined through the use of relative dynamic elastic modulus and mass loss ratio macroscopic evaluation indices, scanning electron microscopy (SEM), and X-ray diffraction (XRD). According to the mathematical statistics method, the marginal statistical distribution of each damage parameter was obtained, and the Copula method of series structural failure mode was proposed to construct the joint probability density function of concrete structural damage parameters. Structural reliability was analyzed via the dual neural network method, and the reliability of aeolian sand concrete was calculated in order to accurately predict the number of freeze–thaw cycles involved in structural failure. The findings of the present study indicate that the relative dynamic elastic modulus decreases progressively while mass loss increases gradually during an increasing number of freeze–thaw cycles. This result effectively illustrates the degradation pattern of the aeolian sand concrete specimens’ frost resistance. The reliability analysis model developed in the present study can effectively capture the correlation between structural reliability and freeze–thaw cycles in concrete structures, enabling accurate prediction of the remaining lifespan of aeolian sand concrete.