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Internal combustion engines in cylinder flow simulation improvement using nonlinear k-ε turbulence models

机译:使用非线性k-ε湍流模型改进气缸内流动的内燃机

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The purpose of this paper is to studying nonlinear k-ε turbulence models and its advantages in internal combustion engines, since the standard k-ε model is incapable of representing the anisotropy of turbulence intensities and fails to express the Reynolds stresses adequately in rotating flows. Therefore, this model is not only incapable of expressing the anisotropy of turbulence in an engine cylinder, but also is unable to provide good performance when computing the swirling and tumbling flows is important in engine cylinders. Thus, in this paper, the results of nonlinear k-ε model are compared with those of the linear one. Results of diesel engine simulation with linear and nonlinear k-ε models in comparison show that turbulence intensity in the nonlinear model simulation is higher than that of the linear model; also, nonlinear k-ε models predict the second peak value because of the bowl shape in expansion stroke for turbulence intensity. Gas injection results show that nonlinear turbulence models predict spray penetration accurately because of correctly turbulence intensities predicting. Also, the results demonstrate that, for high pressure gas injection, turbulence intensity is high and predicted accurately using nonlinear models. Then, its spray penetration length is predicted accurately in comparison to experimental data’s. Although CPU time spending in the nonlinear model is more than that of the linear one, the non-linear stress model is found to increase computation time by 19%.
机译:本文的目的是研究非线性k-ε湍流模型及其在内燃机中的优势,因为标准k-ε模型无法表示湍流强度的各向异性并且不能充分表达旋转流中的雷诺应力。因此,该模型不仅不能表达发动机汽缸中的湍流各向异性,而且在计算发动机汽缸中重要的涡流和翻滚流量时也不能提供良好的性能。因此,本文将非线性k-ε模型的结果与线性模型的结果进行比较。线性和非线性k-ε模型对柴油机的仿真结果比较表明,非线性模型仿真的湍流强度高于线性模型。同样,非线性k-ε模型可预测第二个峰值,这是因为湍流强度在膨胀冲程中呈碗状。气体注入结果表明,由于正确地预测了湍流强度,因此非线性湍流模型可以准确地预测喷雾渗透。此外,结果表明,对于高压气体注入,湍流强度很高,并且可以使用非线性模型准确预测。然后,与实验数据相比,可以准确预测其喷雾渗透长度。尽管非线性模型中的CPU时间花费比线性模型中的花费更多,但是发现非线性应力模型将计算时间增加了19%。

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