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Influence of the turbulence model for channel flows with strong transverse temperature gradients

机译:湍流模型对横向温度梯度较大的河道水流的影响

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The effects of a strong transverse temperature gradient on a turbulent Poiseuille flow are studied numerically using Reynolds-averaged Navier-Stokes (BANS) models. Such a situation is very common for numerous industrial applications. Since a large majority of industrial computations are based on the BANS approach, the aim of the present work is to investigate the ability of different BANS models to reproduce the main physical phenomena at the origin of the asymmetry of the flow and thermal fields. Comparison are performed with available direct numerical simulations (DNS) or large eddy simulation (LES) databases. With the prospect of future application of the models in the industrial context, models based on the widely used eddy-viscosity and simple gradient diffusion (SGDH) hypotheses are compared to more elaborate second-moment closures for the Reynolds stress and turbulent heat flux. The aim is to determine the closure level necessary to reproduce the influence of strong temperature gradients on the turbulent flow, for a wide range of wall-temperature ratios. Eddy-viscosity models prove able to correctly reproduce the asymmetry of the flow and the tendency toward relaminarization close to the hot wall, which are mainly due to the strong variations of the physical properties (namely the molecular viscosity and the density). Discrepancies in the predictions of the different closure levels only appear for the highest temperature ratios. Unfortunately, reliable reference data are lacking for these configurations, which calls for future DNS or refined LES studies.
机译:使用雷诺平均Navier-Stokes(BANS)模型以数值方式研究了强烈的横向温度梯度对湍流Poiseuille流的影响。对于许多工业应用来说,这种情况非常普遍。由于大多数工业计算都基于BANS方法,因此本研究的目的是研究不同BANS模型在流场和热场不对称性的起源上再现主要物理现象的能力。使用可用的直接数值模拟(DNS)或大型涡流模拟(LES)数据库进行比较。随着模型在工业环境中的未来应用前景的发展,将基于广泛使用的涡流粘度和简单梯度扩散(SGDH)假设的模型与针对雷诺应力和湍流热通量的更为精细的第二矩闭合进行了比较。目的是针对大范围的壁温比,确定再现强温度梯度对湍流的影响所必需的闭合度。涡粘性模型证明能够正确地再现流动的不对称性以及靠近热壁的再层化趋势,这主要是由于物理性质(即分子粘度和密度)的强烈变化所致。仅在最高温度比的情况下,才会出现对不同封闭度的预测差异。不幸的是,这些配置缺少可靠的参考数据,这要求将来进行DNS或完善的LES研究。

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