Exhaust plume flow visualization for qualitative analysis of engine combustion Performance

M. Khan, H. Sherazi
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引用次数: 1

Abstract

This work explores use of Thermal Infrared Image based Flow Visualization (TITFV) for qualitative analysis of gasoline engine combustion performance. It proposes determining engine combustion performance through analysis of the exhaust plume turbulence and radiation extinction patterns. The employed methodology requires estimating the point spread function (PSF) prevailing in a LWTR image and using the PSF estimates for enhancing the engine exhaust plume LWIR images. Influence of exhaust plume composition on the plume flow characteristics, made evident by the turbulence and radiation extinction patterns, is then ascertained. The observed plume flow characteristics and underlying flow patterns are used to qualitatively determine the engine combustion performance. Results suggest that engine exhaust flow visualization can help in qualitative analysis of combustion performance from a distance and our reliance on photochemical-based analysis of gasoline engine combustion efficiency can be reduced. Thus a time consuming and untidy process, difficult to be carried out in real life situations, may be replaced with a swift and cleaner one.
用于发动机燃烧性能定性分析的排气羽流可视化
本研究探索了基于热红外图像的流动可视化(TITFV)在汽油机燃烧性能定性分析中的应用。提出通过分析排气羽流湍流和辐射消光模式来确定发动机的燃烧性能。所采用的方法需要估计LWTR图像中普遍存在的点扩展函数(PSF),并使用PSF估计来增强发动机排气羽流LWIR图像。排气羽流组成对羽流特性的影响,通过紊流和辐射消光模式得到了证实。观测到的羽流特性和底层流型用于定性地确定发动机的燃烧性能。结果表明,发动机排气流可视化有助于从远处对燃烧性能进行定性分析,可以减少我们对基于光化学的汽油发动机燃烧效率分析的依赖。因此,在现实生活中难以进行的耗时和不整洁的过程可能会被一个快速而干净的过程所取代。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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