Optimization of In-Cylinder Flow and Swirl Generation Analysis for a Naturally Aspirated Diesel Genset Engine for Emission Reduction through Intake Port Design

Tikar, S. S.; Malkhede, Dileep; Nandgaonkar, Milankumar

doi:10.4271/2019-28-0024

Cited by 1 publication

(2 citation statements)

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“…4,13 However, it should be noted that the database used for training the ANN is commonly built by the numerical simulation results due to the cost, thus the accuracy of the numerical simulation is critical to the results of ports optimization, so a lot of research work on port simulation has been done by researchers. Table 1 gives the accuracy of the simulation results in the past decade, [30][31][32][33][34][35][36] in which the T-port means tangential port and the H-port means helical port. In the previous work, 30,31 the simulation of intake ports mainly aimed to predict the flow coefficient, and the predicted result of swirl ratio was only used to reflect the changing trends along with the increased valve lifts.…”

Section: Introductionmentioning

confidence: 99%

“…In the previous work, 30,31 the simulation of intake ports mainly aimed to predict the flow coefficient, and the predicted result of swirl ratio was only used to reflect the changing trends along with the increased valve lifts. In the later work, [32][33][34][35][36] the prediction accuracy of the swirl ratio was improved under the medium and high valve lifts, but the prediction accuracy of the flow coefficient still cannot be accurately predicted. Besides, the same numerical simulation strategy had a great difference in the simulation results of different ports.…”

Section: Introductionmentioning

confidence: 99%

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The full-parametric development of the intake ports by using genetic algorithm in a four-valve diesel engine

Gao

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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In-cylinder flow characteristics, which are mainly determined by the intake ports, have a decisive influence on the mixture formation and combustion process of internal combustion (IC) engines. To develop the optimum intake ports in a four-valve diesel engine, the full-parametric design method coupled with genetic algorithm (GA) and artificial neural network (ANN) was adopted in this study. Different from previous studies, the full-parametric templates for the tangential and helical ports were established. Then, to improve the precision of the CFD result which was used to train the ANN, the near-wall region affected by viscosity was resolved by the “enhanced wall treatment” during the simulation process. Besides, considering the interaction between the outlets of adjacent intake ports in the four-valve engine, the ANN was divided into three parts to better predict the flow performance of the combined intake ports. Finally, the developed intake ports based on ANN and GA were machined to the flow box and validated by the steady flow test. The low deviation of 4.71% in swirl ratio between the design target and the experiment result confirms that this method can be well applied to the development of the intake ports in a four-valve diesel engine.

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