论文标题
用于模拟n $ _2 $ -CH $ _4 $震惊流量的物理上一致的化学数据集t = 100,000k
A Physically-Consistent Chemical Dataset for the Simulation of N$_2$-CH$_4$ Shocked Flows Up to T=100,000K
论文作者
论文摘要
在先前在\ emph（验证重新输入应用的验证空气热化学模型的范围）的范围内进行的工作中，已证实Gökçen化学数据集提供了与实验相差越来越大的结果，因为一种考虑的冲击速度超过了5米\米\米\ per \ secone。也就是说，对于每\ 7至9 \ kilo \ meter \ s的冲击速度，与实验相矛盾的模型可以通过模型预测CN紫辐射中的一个以上的时间峰。这暗示了数据集中的几个速率不直接适用于此类应用的感兴趣范围，通常超过10,000 \ kelvin。确实，已经发现，来自Gökçen化学数据集的几个宏观速率在非常高的温度下达到了非物理值。此外，已经发现许多电离速率是不足以模拟高温n $ _ {2} $ - ch $ _ {4} $震惊的流量。在这里，我们对Gökçen化学数据集进行了广泛的更新，目的是至少在整个T = 100-100,000 \ kelvin \ kelvin \温度范围内达到身体一致的速率。尽管不能真正声称在如此延长的温度范围内对这种改进的数据集进行了验证（由于这种高温范围几乎无法提供的实验数据），但与Gökçen化学数据集相比，它能够为该混合物提供更准确的高速冲击流量模拟。
In the previous work carried out in the scope of the \emph{Validation of Aerothermochemistry Models for Re-Entry Applications}, it was verified that the Gökçen chemical dataset provided increasingly diverging results from experiments, as one considered shock speeds in excess of 5\kilo\metre\per\second. Namely, for shock velocities between 7 and 9\kilo\metre\per\second, more than one temporal peak in CN Violet radiation were predicted by models considering this kinetic dataset, in contradiction with experiments. This hinted at several of the rates from the dataset not being directly applicable in the temperature range of interest for such applications, often in excess of 10,000\kelvin. Indeed, it has been found that several macroscopic rates from the Gökçen chemical dataset reached unphysical values at very high temperatures. Furthermore, many of the ionization rates have been found to be inadequate for the simulation of high-temperature N$_{2}$--CH$_{4}$ shocked flows. Here, we have carried an extensive update of the Gökçen chemical dataset, with the aim of at least reaching physically consistent rates for the whole T=100-100,000\kelvin\ temperature range. While it cannot really be claimed that such improved dataset is validated in such an extended temperature range (due to the scarcely available experimental data for such high temperature ranges), it is capable of providing more accurate simulations of high-speed shocked flows for this mixture, when compared to the Gökçen chemical dataset.
