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A RNG k-epsilon model with application to diesel combustion modeling

机译:一种RNG K-EPSILON模型,适用于柴油燃烧建模

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A modified RNG k-epsilon turbulence model has been implemented in the KIVA-II computer code and applied to diesel combustion computations. The modifications account for effects of non-zero velocity dilatation on turbulence dissipation for density-variable engine flows. Computations were made of the in-cylinder processes in a Caterpillar engine and a Tacom engine with the use of both the modified RNG k-epsilon model and a traditional k-epsilon model. The RNG approach produces smaller turbulent voscosity than the traditional k-epsilon model does, which was found to be important for accurate predictions of spray combustion. Large scale flow structures with higher local gas temperatures were predicted with the use of the present turbulence model. With the improvement of flow modeling, better rates and soot and NOx emissions were obtained over the range of injection timings and load considered. Quantitatively improved predictions of NOx formation in both the engines were also achieved due to the extreme sensitivity of NOx to the local gas temperatures.
机译:已经在Kiva-II计算机代码中实现了一种改进的RNG K-EPSILON湍流模型,并应用于柴油燃烧计算。用于非零速度扩张对密度可变发动机流动湍流耗散的影响的修改。使用改性的RNG K-EPSILON模型和传统的K-EPSILON模型,在毛毛虫发动机和TACOM发动机中的缸内工艺制成计算。 RNG方法产生比传统的K-EPSILON模型更小的湍流效果,这对于准确的喷雾燃烧预测是重要的。利用本湍流模型预测具有较高局部气体温度的大型流动结构。随着流动建模的提高,在考虑的注射时间和负荷范围内获得了更好的速率和烟灰和NOx排放。由于NOx对局部气温的极端敏感性,也实现了在两个发动机中的NOx形成预测的定量改进。

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