摘要
燃机在贫燃工况下易出现燃烧不稳定,分析和预测不稳定燃烧特性对保证燃烧室正常工作具有重要意义。通过数值仿真得到燃烧室的火焰描述函数(flame describing function,FDF),并结合低阶热声网络模型预测了燃烧室的热声不稳定特性。首先,通过模型旋流燃烧室自激振荡实验,得到振荡燃烧发生时的工况和主频;其次,利用大涡模拟(large eddy simulation,LES),得到火焰燃烧热释放率对不同入口扰动的响应特征,通过拟合得到FDF;最后,建立了燃烧室低阶热声网络模型,并分析了燃烧室不稳定特性。结果表明:模型预测的振荡特性与实验数据相符,说明该模型能够从机理上预测燃烧不稳定特性。
Combustion instability is easy to occur under lean combustion of gas turbine.Analyzing and predicting the characteristics of unstable combustion is of great significance to ensure the normal operation of combustion chamber.The flame describing function(FDF)of combustion chamber was obtained by numerical simulation,and the thermoacoustic instability characteristics of combustion chamber were predicted by combining the low-order thermoacoustic network model.Firstly,the operating conditions and main frequency of oscillating combustion were obtained through the self-excited oscillation experiment of model swirler combustor.Secondly,by using large eddy simulation(LES),the response characteristics of heat release rate of flame combustion under different inlet disturbances were obtained,and the FDF was fitted.Finally,the low-order thermoacoustic network model of the combustion chamber was established,and the instability characteristics of the combustion chamber were analyzed.The results show that the oscillation characteristics predicted by the model are consistent with the experimental data,indicating that the model can predict the combustion instability characteristics from the mechanism.
作者
郝建刚
贡文明
丁阳
郑丹伟
刘勇
HAO Jiangang;GONGWenming;DING Yang;ZHENG Danwei;LIU Yong(Huadian Electric Power Research Institute Co.,Ltd.,Hangzhou 310030,Zhejiang Province,China;Jiangsu Huadian Qishuyan Power Generation Co.,Ltd.,Changzhou 213011,Jiangsu Province,China;Aero-engine Thermal Environment and Structure Key Laboratory of Ministry of Industry and Information Technology(College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics),Nanjing 210016,Jiangsu Province,China)
出处
《发电技术》
2022年第6期927-934,共8页
Power Generation Technology
基金
国家自然科学基金项目(91741118)。