Analysis of Separation in the Roughness Sublayer Using DNS Data and DANS/DEM Modelling of Roughness Effects

IF 2 3区 工程技术 Q3 MECHANICS
François Chedevergne, Jiasheng Yang, Alexander Stroh, Pourya Forooghi
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引用次数: 0

Abstract

From the recent DNS database (Yang in Journal of Fluid Mechanics) of channel flows with rough walls in the presence of heat transfer, the impact of the skewness of the roughness elevation map on the velocity and temperature profiles within the roughness sublayer is analysed. The separation zones observed near the wall in the sublayer are shown to play a significant role when the skewness is negative. The \(k-\omega\)-based turbulence model (Chedevergne and Forooghi in Journal of Turbulence 21:463–482, 2020); (Chedevergne in Journal of Turbulence 22:713–734, 2021, Chedevergne in Journal of Turbulence 24: 36–56, 2023), capable of capturing roughness effects and incorporating the Double Averaged Navier–Stokes (DANS) equations and the Discrete Element Method (DEM), is tested against this DNS database, showing some limitations in the description of the roughness sublayers, especially for configurations with negative skewness. To reproduce the observations made in the DNS database, the pressure gradient imposed in the simulated channel using the DANS/DEM model is adjusted based on the distance to a reference wall in the roughness sublayers. Additionally, the increase in turbulent mixing observed in the DNS database for rough configurations with negative skewness is accounted for in the DANS/DEM model by modifying the source terms in the transport equations of the turbulent scalars with respect to the skewness, improving the prediction the roughness effects.

基于DNS数据的粗糙度子层分离分析及粗糙度效应的DANS/DEM建模
利用最近的DNS数据库(Yang in Journal of Fluid Mechanics)研究了存在传热的粗糙壁面通道流动,分析了粗糙度高程图的偏度对粗糙亚层内速度和温度分布的影响。当偏度为负时,在亚层壁面附近观察到的分离区起着重要的作用。基于\(k-\omega\)的湍流模型(Chedevergne and Forooghi in Journal of turbulence, 2020:463 - 482);(Chedevergne in Journal of Turbulence, 22:713-734, 2021; Chedevergne in Journal of Turbulence, 24: 36 - 56,2023),能够捕捉粗糙度效应,并结合双平均Navier-Stokes (DANS)方程和离散元方法(DEM),对该DNS数据库进行了测试,显示了粗糙度子层描述的一些局限性,特别是对于负偏度的配置。为了重现DNS数据库中的观测结果,使用DANS/DEM模型在模拟通道中施加的压力梯度根据粗糙度子层中与参考壁的距离进行调整。此外,在DNS数据库中观测到的具有负偏度的粗糙构型的湍流混合增加,在DANS/DEM模型中可以通过修改湍流标量输运方程中相对于偏度的源项来解释,从而改善粗糙度效应的预测。
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来源期刊
Flow, Turbulence and Combustion
Flow, Turbulence and Combustion 工程技术-力学
CiteScore
5.70
自引率
8.30%
发文量
72
审稿时长
2 months
期刊介绍: Flow, Turbulence and Combustion provides a global forum for the publication of original and innovative research results that contribute to the solution of fundamental and applied problems encountered in single-phase, multi-phase and reacting flows, in both idealized and real systems. The scope of coverage encompasses topics in fluid dynamics, scalar transport, multi-physics interactions and flow control. From time to time the journal publishes Special or Theme Issues featuring invited articles. Contributions may report research that falls within the broad spectrum of analytical, computational and experimental methods. This includes research conducted in academia, industry and a variety of environmental and geophysical sectors. Turbulence, transition and associated phenomena are expected to play a significant role in the majority of studies reported, although non-turbulent flows, typical of those in micro-devices, would be regarded as falling within the scope covered. The emphasis is on originality, timeliness, quality and thematic fit, as exemplified by the title of the journal and the qualifications described above. Relevance to real-world problems and industrial applications are regarded as strengths.
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