Reconstruction of Turbulent Swirling Flow in a Dump Combustor
Reconstruction of Turbulent Swirling Flow in a Dump Combustor作者机构：Mechanical Engineering Department College of Engineering American University of Sharjah Sharjah 26666 UAE
出 版 物：《Journal of Mechanics Engineering and Automation》 (机械工程与自动化（英文版）)
年 卷 期：2013年第3卷第7期
页 面：414-420页
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080703[工学-动力机械及工程] 08[工学] 0807[工学-动力工程及工程热物理]
主 题：Swirling flow dump combustors generalized feed forward network.
摘 要：Experimental data of the continuous evolution of fluid flow characteristics in a dump combustor is very useful and essential for better and optimum designs of gas turbine combustors and ramjet engines. Unfortunately, experimental techniques such as 2D and/or 3D LDV （Laser Doppler Velocimetry） measurements provide only limited discrete information at given points; especially, for the cases of complex flows such as dump combustor swirling flows. For this type of flows, usual numerical interpolating schemes appear to be unsuitable. Recently, neural networks have emerged as viable means of expanding a finite data set of experimental measurements to enhance better understanding of a particular complex phenomenon. This study showed that generalized feed forward network is suitable for the prediction of turbulent swirling flow characteristics in a model dump combustor. These techniques are proposed for optimum designs of dump combustors and ramjet engines.
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