液态纳米燃料在船用燃气轮机中的雾化与燃烧特性研究

As a kind of special liquid-solid mixture consisting of nanoparticles and fuel base fluid, liquid nanofuel has a potential application in the fields of combustion enhancement and pollutant emission control of marine gas turbine because of its high heat transport capability, good catalytic combustion performance and low pollutant emission. However, the small size characteristic of nanoparticle makes the heat and mass transport mechanism and chemical reaction of liquid nanofuel very complex, which leads that the atomization and combustion characteristics of liquid nanofuel in marine gas turbine are still unclear. To solve this problem, the effects of different typical factors on the thermophysical parameters of liquid nanofuel are measured firstly in the present project. And the neural network models will be proposed to predict the related thermophysical parameters. Then, the initial atomization characteristics of liquid nanofuel in marine gas turbine nozzle are investigated experimentally. Besides, the numerical analysis is performed to study the coupling effects of different thermophysical parameters on the second atomization characteristics of liquid nanofuel. On this basis, the combustion characteristic and pollutant emission of liquid nanofuel under the actual working condition of marine gas turbine are discussed in detailed by using visualization experiments. The results of this project can play the important roles in promoting the improvement of liquid nanofuel combustion theory and the development of liquid nanofuel in the field of marine gas turbine.

作为一种由纳米颗粒与燃料基液组成的特殊液-固两相混合物，液态纳米燃料具有热传输能力强、催化助燃性能好、污染物排放低等特点，在船用燃气轮机高效强化燃烧与污染物排放控制领域有着重要的应用前景。然而，纳米颗粒的小尺寸特征使得液态纳米燃料的热、质输运机理与化学反应过程极其复杂，导致液态纳米燃料在船用燃气轮机中的雾化与燃烧特性至今尚不明确。为解决这一问题，本项目首先对典型因素影响下的液态纳米燃料热物性参数变化规律进行测量分析，建立基于神经网络的热物性参数预测模型；然后通过实验阐明液态纳米燃料在船用燃气轮机喷嘴中的初次雾化特性，数值模拟揭示不同热物性参数对液态纳米燃料二次雾化特性的耦合作用机制；在此基础上，结合可视化实验研究液态纳米燃料在船用燃气轮机实际工作条件下的燃烧特性与污染物排放规律。研究成果对于完善液态纳米燃料的燃烧理论和推动液态纳米燃料在船用燃气轮机领域的发展具有重要的促进作用。

液态纳米燃料是一种由纳米颗粒与燃料基液组成的特殊液-固两相混合物。本研究围绕液态纳米燃料应用于船用燃气轮机面临的雾化和燃烧基础问题，开展了柴油基液态纳米燃料制备和典型热物性参数实验研究，分析了不同因素对纳米颗粒悬浮稳定性和热物性参数的影响，建立了基于神经网络的热物性参数预测模型；结合实验与数值模拟分析了纳米颗粒作用下离心喷嘴的燃油初次雾化特性、二次雾化单液滴变形与破碎特征，掌握了不同热物性参数的耦合作用机制；数值分析了典型工况条件下纳米颗粒对船用燃气轮机环管燃烧室冷热态流场结构、火焰形态等的影响规律，设计了燃烧室多物理场在线同步测试系统，研究了CO和NOx的污染物排放规律。相关研究成果可为船用燃气轮机高效清洁燃烧室设计提供一定参考。