Investigation of NO Formation and Transport in Combustion Systems using Planar Laser Induced Fluorescence

准确预测实际燃烧系统（如燃气轮机）中一氧化氮（NOx）的形成和传输的能力是减少这种有毒气体向环境中有害排放的必要步骤。NOx排放的负面环境后果包括臭氧消耗、全球变暖、烟雾形成和呼吸道疾病。随着计算能力的最新发展，可以通过使用计算流体动力学（CFD）算法以及最先进的燃烧和湍流模型作为优化设计工具来缓解这一问题。这种方法依赖于模型验证过程，其中CFD预测与实验数据集进行比较。在高压燃烧环境中，平面激光诱导荧光（PLIF）是一种理想的非侵入性实验技术，既可以可视化NOx的定性分布，又可以提取定量数据，如气体速度，温度，压力和物种浓度。然而，由于分子氧PLIF信号的干扰和来自UV光吸收的激光衰减，NO PLIF技术难以应用于高压燃烧流。主要的研究目标是了解氮氧化物的形成和运输的背景下，用于燃气涡轮机发动机，以减少氮氧化物排放的燃料分级策略。随着双驱动激波管装置的发展，NO PLIF系统将首先用于研究高温下NO的形成以及NO种子燃料射流与横流的混合。定量PLIF技术，如多普勒频移测速仪，分子标记测速仪，双线测温将被开发。将对PLIF信号方程进行建模，以产生计算流图像。这将允许模型验证所需的实验和数值PLIF图像之间的直接比较。将使用经过验证的燃烧模型作为研究工具，以研究当前用于燃气涡轮机燃烧室的低NOx燃料分级策略。

The ability to accurately predict the formation and transport of nitric oxide (NOx) in practical combustion systems, such as gas turbines, is a necessary step to reduce the harmful emission of this toxic gas into the environment. Negative environmental consequences of NOx emission include ozone depletion, global warming, smog formation, and respiratory illnesses. With recent advances in computing power, it is possible to mitigate this problem by using computational fluid dynamics (CFD) algorithms with state-of-the-art combustion and turbulence models as an optimization design tool. This approach relies on a model validation process in which CFD predictions are compared against experimental data sets. In high pressure combustion environments, planar laser induced fluorescence (PLIF) is an ideal non-intrusive, experimental technique to both visualize qualitative distributions of NOx and to extract quantitative data such as gas velocity, temperature, pressure, and species concentrations. However, the application of NO PLIF techniques to high pressure combustion flows is difficult due to the interference of the molecular oxygen PLIF signal and laser attenuation from UV light absorption. The main research object is to understand NOx formation and transport in the context of fuel staging strategies used in gas turbine engines to reduce NOx emissions. With the development of a dual-driver shock tube facility, an NO PLIF system will initially be used to study the formation of NO at high temperatures and mixing of an NO seeded fuel jet into a crossflow. Quantitative PLIF techniques such as Doppler shift velocimetry, molecular tagging velocimetry, and two-line thermometry will be developed. Modeling of the PLIF signal equation will be undertaken to produce computational flow images. This will allow direct comparisons between the experimental and numerical PLIF images needed for model validation. Validated combustion models will be used as investigative tools to study current low-NOx fuel-staging strategies used in gas turbine combustors.