基于粒子群算法的火力发电厂粉煤灰高性能混凝土配合比优化

The Optimization of Mixture Proportion for Fly Ash High-performance Concrete in Thermal Power Plant Based on Particle Swarm Optimization Algorithm

当前火力发电厂粉煤灰混凝土配合比计算常基于单一环境,文章提出基于粒子群算法的粉煤灰高性能混凝土配合比优化方案,明确材料基础掺量,增强多环境计算的可靠性,构建优化模型,采用抗渗测定优化配合比。实验结果表明,经过三个配合比优化阶段的测定,测试构件的抗压强度均可以达到30 MPa以上,说明在粒子群算法的辅助下,优化方法的针对性更高。

At present,the mixture proportion calculation of fly ash concrete in thermal power plants is often based on a single environment.This paper proposes a mixture proportion optimization scheme of fly ash high-performance concrete based on Particle Swarm Optimization algorithm,clarifies the basic content of materials,enhances the reliability of multi-environment calculation,constructs an optimization model,and optimizes the mixture proportion by impermeability measurement.The experimental results show that the compressive strength of the tested components can reach more than 30 MPa after the determination of the three mixture proportion optimization stages,indicating that the optimization method is more targeted with the assistance of the Particle Swarm Optimization algorithm.