Experimental and numerical study of water sprayed turbulent combustion: Proposal of a neural network modeling for five-dimensional flamelet approach  

作　　者：Takafumi Honzawa Reo Kai Kotaro Hori Makoto Seino Takayuki Nishiie Ryoichi Kurose 

机构地区：[1]Department of Mechanical Engineering and Science,Graduate School of Engineering,Kyoto University,Kyoto daigaku-Katsura,Nishikyo-ku,Kyoto 615-8540,Japan [2]Tokyo Gas Co.,Ltd.,1-7-7 Suehiro-cho,Tsurumi-ku,Yokohama,Kanagawa 230-0045,Japan [3]Numerical Flow Designing Co.,Ltd.,1-10-10,Higashi-Gotanda,Shinagawa-ku,Tokyo 141-0022,Japan

出　　处：《Energy and AI》2021年第3期316-324,共9页能源与人工智能（英文）

基　　金：The temperature measurements and PIA were supported by Prof.M.Nishioka of University of Tsukuba and Prof.K.Nishino of Yokohama National University,respectively.This work was partially supported by MEXT as"Program for Promoting Researches on the Supercomputer Fu-gaku"(Digital Twins of Real World’s Clean Energy Systems with Inte-grated Utilization of Super-simulation and AI).

摘　　要：Owing to the increasing worldwide demand for natural gas,the development of a large submerged combustion vaporizer is required.Its burner is equipped with a water spray nozzle to reduce nitrogen oxides,and a practi-cal simulation method is required for the optimal design.The non-adiabatic flamelet approach can predict the combustion emissions and is useful for reducing simulation costs.However,as the number of control variables increases,the database requires larger memory and cannot be dealt with by general computers.In this study,an artificial neural network(ANN)model based on a five-dimensional flamelet database,which includes the effects of heat loss and vapor concentration by sprayed water evaporation,is developed.Furthermore,large eddy sim-ulations(LESs)for turbulent combustion fields with and without water spray are conducted employing flamelet generated manifold(FGM)approach with this ANN model,and the validity is investigated.For comparison,a lab-scale burner equipped with a water spray nozzle is manufactured,and combustion experiments with and without water spray are conducted.The results show that CO,NO,temperature,and reaction rate of progress variable predicted by the present ANN model are in good agreement with those of a five-dimensional flamelet database.In the condition without water spray,the flame behavior predicted by the LES employing the FGM/ANN ap-proach is in good agreement with that employing the conventional FGM approach,while indicating much lower memory,although there appeared some quantitative discrepancies in the temperature against the experiment probably partially because of the insufficiency of the FGM approach for the present complex flame structure.In the condition with water spray,the LES employing the FGM/ANN approach is able to capture the effect of the water spray on the flame behavior in the experiment,such that the water spray decreases the temperature,which causes the decrease in NO but increase in CO.

关 键 词：Neural network modeling Five-dimensional flamelet approach Water spray Large eddy simulation 

分 类 号：TB3[一般工业技术—材料科学与工程]