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Spatial gradients of conditional averages in turbulent flames

机译:湍流火焰中条件平均值的空间梯度

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Data from the two different methane/air jet experimental databases is examined to understand the effects of spatial variations in the conditional averages of reactive scalars in the context of the Conditional Source-term Estimation (CSE) model, with particular emphasis on the double-conditional version, DCSE. Data from all spatial locations and from the four turbulent flames in the Sandia/TUD database are averaged together to generate a global, two-condition (mixture fraction and a species-based reaction progress variable) conditional average; it is found that the conditional fluctuations around this new, two-condition conditional average do not exhibit any significant dependence on either spatial location or even on Reynolds number. Furthermore, the normalized RMS of the conditional fluctuations are found to be dramatically lower than those seen using only one condition. These results indicate that the two condition conditional averages in the Sandia/TUD piloted methane/air flame series do not vary in space, nor vary with Reynolds number. In the Sydney Swirl burner data, the two-condition conditional averages exhibit modest gradients in space which are attributed to heat transfer with the bluff body in the flow; when a third condition is added - based on the total enthalpy - the spatial gradients in the conditional average of temperature a dramatically reduced. In both of the cases tested, the normalized RMS of the conditional fluctuations around both the two- and three-condition conditional averages are relatively small. These results imply that, in a simulation of these flames using DCSE, one would be better off ignoring spatial variations in the conditional averages and instead collecting all of the spatial data together for the integral equation inversion using either two or three conditioning variables in a single, global ensemble species involved in relatively slow chemistry, such as NO. The results also imply that the underlying assumptions in DCSE - that the conditional variances and the spatial gradients in the conditional averages are both negligible - are valid when sufficient conditioning variables are used, at least for the flames considered. (C) 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
机译:检查了来自两个不同甲烷/空气喷射实验数据库的数据,以了解在有条件源项估算(CSE)模型的背景下,反应性标量的条件平均值的空间变化的影响,尤其着重于双条件版本DCSE。将来自所有空间位置的数据以及来自Sandia / TUD数据库中四个湍流火焰的数据一起求平均,以生成全局的两个条件(混合物分数和基于物种的反应进度变量)条件平均值;发现新的两条件条件平均值周围的条件波动对空间位置甚至雷诺数均无显着影响。此外,发现条件波动的归一化RMS显着低于仅使用一种条件所看到的均方根RMS。这些结果表明,在Sandia / TUD引导的甲烷/空气火焰序列中的两个条件条件平均值在空间上没有变化,也没有随雷诺数变化。在Sydney Swirl燃烧器数据中,两个条件的平均数在空间上显示出适度的梯度,这归因于流动中钝体的传热。当添加第三个条件时-基于总焓-温度的条件平均值中的空间梯度将大大减小。在这两个测试案例中,围绕两个条件和三个条件平均值的条件波动的归一化RMS相对较小。这些结果表明,在使用DCSE对这些火焰进行模拟时,最好忽略条件平均值中的空间变化,而将所有空间数据收集在一起,以便在单个变量中使用两个或三个条件变量来进行积分方程反演。 ,涉及相对较慢化学反应的全球整体物种,例如NO。结果还暗示,当使用足够的条件变量时,至少对于所考虑的火焰,DCSE中的基本假设(条件均值中的条件方差和空间梯度均可以忽略)是有效的。 (C)2018年燃烧研究所。由Elsevier Inc.出版。保留所有权利。

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