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锅炉水冷壁节流孔板结构对结垢的影响分析与结构优化
Impact Analysis of the Orifice’s Structure on its Fouling Problem and Structure Optimization of the Orifices
【Author】 YU Lan-lan,ZHOU Ke-yi,TANG Yan (School of Energy and Environment,Southeast University,Nanjing 210096,Jiangsu Province,China)
【机构】 东南大学能源与环境学院；
【摘要】 针对超超临界锅炉水冷壁节流孔板结垢问题,建立了节流孔板的数值模型,分析了结垢的主要原因,确定了影响结垢程度的孔板结构参数。在大量数值计算的基础上,采用BP人工神经网络,建立了孔板结构参数与结垢程度之间关系的模型。基于此模型,采用遗传算法进行结构优化,所得结构尺寸下的节流孔板的结垢程度有所减轻。研究结果为进一步优化节流孔板的结构设计提供了一种有效的方法。
【Abstract】 Fouling of orifices installed at the entrance of waterwalls may lead to overheating and tube failure problems.Therefore,in this study numerical models of orifices are developed based on the computational fluid dynamics(CFD) method to identify the principal causes of the orifice fouling,and then determine the orifice’s structure parameters that have impacts on its fouling issue.Based on the numerical calculation,the relationship between the orifice’s structure and its fouling problem is developed by using the Artificial Neural Network.The Genetic Algorithm is subsequently employed to search for the best structure which can minimize the orifice fouling.The results can provide an effective method for further study on structure optimization of the orifices.
【Key words】 ultra-supercritical； orifice； fouling； numerical calcaulation； BP Neural Network； Genetic Algorithm；
- 【会议录名称】 中国动力工程学会锅炉专业委员会2011年学术研讨会论文集
- 【会议名称】中国动力工程学会锅炉专业委员会2011年学术研讨会
- 【会议时间】2011-09-17
- 【会议地点】中国北京
- 【分类号】TK223.31
- 【主办单位】中国动力工程学会锅炉专业委员会