Investigation on suitable swirl ratio and spray angle of a large-bore marine diesel engine using genetic algorithm

被引:7
|
作者
Lu, Tianlong [1 ]
Lu, Zhen [1 ]
Gao, Yuchuan [1 ]
Shi, Lei [1 ]
Wang, Huaiyin [1 ]
Wang, Tianyou [1 ]
机构
[1] Tianjin Univ, State Key Lab Engines, Tianjin, Peoples R China
基金
中国国家自然科学基金;
关键词
Suitable swirl ratio; Fuel -air matching; Artificial neural network; Genetic algorithm; Large -bore marine diesel engine; OPTIMIZATION; COMBUSTION; FUEL; FLOW; CYLINDER;
D O I
10.1016/j.fuel.2023.128187
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The swirl flow and spray angle are crucial to the organization of the combustion process in marine engines. In this work, to explore the suitable swirl ratio and corresponding spray angle for large-bore marine diesel engines, the artificial neural network (ANN) coupled with the genetic algorithm (GA) was used. At the same time, to increase the swirl ratio without affecting the scavenging efficiency, the cylinder gas recirculation (CGR) strategy was adopted in this manuscript. Compared with the original design, results indicate that the optimal swirl ratio is about 10 for the large-bore marine diesel engine when applying the CGR strategy. Due to the improved fuel-air mixing process and combustion process, the thermal efficiency and the output power of the optimal case increased by 4.86% and 5.2%, respectively. The present results are helpful for the design and optimization of the fuel-air mixing and combustion processes for large-bore marine diesel engines.
引用
收藏
页数:15
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