水工高性能混凝土配合比多目标智能优化设计与分析方法

高性能混凝土(HPC)在水利工程中的多元化应用对其配合比设计提出了更高要求.为实现高效、准确的配合比设计,本文结合人工智能算法和元启发式搜索技术,开发了一种综合考虑多目标需求(力学性能、经济性和环保性)的HPC配合比优化设计新方法.其主要包括:(1)建立了以配合比参数为设计变量,以抗压强度、单方生产成本和碳排放量为优化...

Multi-objective intelligent optimization design and analysis method for mix proportion of hydraulic high performance concrete

The diversified application of high performance concrete (HPC) in hydraulic engineering puts forward higher requirements for its mix proportion design. In order to achieve the efficient and accurate concrete mix, this paper combines the artificial intelligence algorithm and meta-heuristic search technique to develop a novel method for HPC mix optimization design that comprehensively considers multi-objective requirements (mechanical properties, economy and environmental protection). The developed method mainly includes that:(1) Establishing a HPC mix proportion multi-objective optimization mathematical model that takes mix parameters as design variables and takes compressive strength, unilateral production cost and carbon dioxide emissions as optimization goals; (2) Proposing a model solving method based on the random forest and adaptive evolutionary particle swarm optimization (AEPSO) algorithms, where random forest is used to characterize the complex nonlinear relationship between the mix proportion of raw materials and the compressive strength, while AEPSO for the optimal Pareto front, in order to obtain the optimal mix proportion of different biases. The proposed method has been used to optimize the mix proportion of HPC for a certain project, and the effectiveness and superiority of the proposed method are verified by comparing with the traditional method.