基于热阻及成本分析的高炉冷却壁多目标优化  

Multi-objective Optimization of Blast Furnace Cooling Stave Based on Thermal Resistance and Cost Analysis

作　　者：徐迅[1] 吴俐俊[2] Xu Xun;Wu Lijun(College of Xinglin,Nantong University,Nantong 226000,Jiangsu,China;College of Mechanical Engineering,Tongji University,Shanghai 20l804,China)

机构地区：[1]南通大学杏林学院,江苏南通226000 [2]同济大学机械与能源工程学院,上海201804

出　　处：《科技通报》2024年第2期19-24,29,共7页Bulletin of Science and Technology

基　　金：江苏省高校“青蓝工程”项目(2021年度)。

摘　　要：本文建立了高炉冷却壁热阻模型,冷却壁热阻包括火积耗散热阻和对流热阻,分别表征其导热性能和换热表面的对流换热性能。分析冷却壁运行过程中的各项成本,包括冷却壁材料成本、运行耗水成本、运行能耗成本以及冷却壁厚度减薄时产生的额外收益。应用遗传算法以冷却壁热阻和成本为目标函数,以冷却壁各结构参数为决策变量,对冷却壁进行多目标优化,获得了Pareto最优解集。优化后的冷却壁与初始冷却壁相比,可在传热性能相当的前提下成本下降79.9%,或在冷却成本相当的前提下,热阻下降27.3%。The thermal resistance model of blast furnace cooling stave is established.The thermal resistance of the cooling stave includes the entransy dissipation resistance and the convective thermal resistance,which characterize its thermal conductivity and the convective heat transfer performance of the heat exchange surface respectively.The costs in the operation of cooling stave are analyzed,including the cost of cooling stave material,the cost of running water consumption,the cost of running energy consumption and the additional benefits generated when the thickness of cool-ing stave is reduced.Taking the thermal resistance and cost of the cooling stave as the objective function,and the structural parameters of the cooling stave as the decision variables,the cooling stave was multi-objective optimized us-ing genetic algorithm,and the Pareto optimal solution set was obtained.Compared with the original cooling stave,the cost of the optimized cooling stave can be reduced by 79.9%with the same heat transfer performance,or the thermal resistance can be reduced by 27.3%with the same cooling cost.

关 键 词：高炉冷却壁 热阻 成本 多目标优化 遗传算法 

分 类 号：TK172[动力工程及工程热物理—热能工程]