Optimization of Sulfate Resistance Performance of Concrete under Dry-Wet Cycles Based on PSO Algorithm

This article focuses on examining how algorithm optimization enhances concrete's resistance to sulfate corrosion, with empirical validation. Addressing the issue of concrete's susceptibility to sulfate corrosion under dry-wet cycling, the Particle Swarm Optimization (PSO) algorithm is employed to refine the concrete mix proportions. For the experimental study, standard Portland cement, natural river sand, and crushed stone serve as raw materials, while a sodium sulfate solution of specific concentration acts as the corrosive agent. Comparative analysis is conducted on the concrete's corrosion resistance pre-and post-optimization through dry-wet cycle tests and performance assessments. Results indicate a notable improvement in sulfate corrosion resistance with the optimized mix, evidenced by reduced corrosion depth and sustained strength. Furthermore, the study reveals a pattern: as dry-wet cycles increase, concrete's corrosion resistance gradually diminishes. Ultimately, it is evident that algorithm optimization substantially boosts concrete's sulfate corrosion resistance, and concrete performance under such cycling exhibits predictable trends.