Upstream history quantification and scale-decomposed energy analysis for weak-to-strong adverse-pressure-gradient turbulent boundary layers

IF 2.6 3区 工程技术 Q2 ENGINEERING, MECHANICAL
Atharva Mahajan , Rahul Deshpande , Taygun R. Gungor , Yvan Maciel , Ricardo Vinuesa
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引用次数: 0

Abstract

The present study delineates the effects of pressure gradient history and local disequilibration on the small and large-scale energy in turbulent boundary layers (TBLs) imposed with a broad range of adverse-pressure-gradients (APG). This is made possible by analyzing four published high-fidelity APG TBL databases, which span weak to strong APGs and cover dynamic conditions ranging from near-equilibrium to strong disequilibrium. These databases enable the development of a methodology to understand the effects of PG history and local disequilibration, the latter defined here as the local streamwise rate of change of the pressure force contribution in the force balance. The influence of PG history on TBL statistics is quantified by the accumulated PG parameter (β¯), proposed previously by Vinuesa et al. (2017) to study integral quantities, which is compared here between cases at matched local PG strength (β), Reynolds number (Re) and dβ/dRe at nominally similar orders of magnitude. Here, β denotes a general umbrella term used for pressure gradient parameters that is estimated using different scaling parameters in this study. While the effects of local disequilibration (dβ/dRe) are investigated by considering TBL cases at matched β, Re, and fairly matched β¯. This enables analysis of accumulated PG history and local disequilibration effects separately, where applicable, to highlight qualitative differences in statistical trends. It is found that β¯ cannot unambiguously capture history effects when dβ/dRe levels are significantly high, as it does not account for the delayed response of the mean flow and turbulence, nor the attenuation of the pressure gradient effect with distance. In two comparisons of APG TBLs under strong non-equilibrium, the values of β¯ and dβ/dRe expressed using Zagarola–Smits scaling were found to be consistent with the trends in mean velocity defect and Reynolds stresses noted previously for weak APG TBLs. While an increase in β¯ is associated with energization of both the small and large scales in the outer regions of APG TBLs, it affects only the large scales in the near-wall region. This confirms the ability of near-wall small scales to rapidly adjust to changes in PG strength. By attempting to provide a structured parametric methodology to isolate effects of PG history and local disequilibration, this study reports the influence of these effects on turbulent flow statistics across the widest APG strengths documented in the literature.
弱到强逆压力梯度湍流边界层上游历史量化及尺度分解能量分析
本研究描述了压力梯度历史和局部不平衡对大范围逆压力梯度(APG)作用下湍流边界层小尺度能量的影响。这是通过分析4个已发表的高保真APG TBL数据库实现的,这些数据库涵盖了弱到强APG,涵盖了从接近平衡到强不平衡的动态条件。这些数据库有助于开发一种方法来理解PG历史和局部不平衡的影响,后者在这里被定义为力平衡中压力力贡献的局部流向变化率。PG历史对TBL统计的影响通过累积PG参数(β¯)来量化,该参数先前由Vinuesa等人(2017)提出,用于研究积分量,这里比较了在名义上相似数量级的匹配局部PG强度(β),雷诺数(Re)和dβ/dRe的情况。这里,β表示在本研究中使用不同的缩放参数估计的压力梯度参数的总称。而局部不平衡(dβ/dRe)的影响则通过考虑匹配的β、Re和相当匹配的β¯的TBL情况来研究。这使得能够在适用的情况下分别分析累积的PG历史和局部不平衡效应,以突出统计趋势中的定性差异。研究发现,当dβ/dRe水平显著高时,β¯不能明确地捕捉历史效应,因为它没有考虑平均流量和湍流的延迟响应,也没有考虑压力梯度效应随距离的衰减。在两种强非平衡状态下的APG TBLs对比中,zagar罗拉- smits标度法表达的β¯和dβ/dRe值与之前在弱APG TBLs中发现的平均速度缺陷和雷诺兹应力的变化趋势一致。虽然β¯的增加与APG TBLs外区小尺度和大尺度的通电有关,但它只影响近壁区域的大尺度。这证实了近壁小尺度快速适应PG强度变化的能力。通过尝试提供一种结构化的参数方法来分离PG历史和局部不平衡的影响,本研究报告了这些影响对文献中记载的最宽APG强度的湍流统计数据的影响。
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来源期刊
International Journal of Heat and Fluid Flow
International Journal of Heat and Fluid Flow 工程技术-工程:机械
CiteScore
5.00
自引率
7.70%
发文量
131
审稿时长
33 days
期刊介绍: The International Journal of Heat and Fluid Flow welcomes high-quality original contributions on experimental, computational, and physical aspects of convective heat transfer and fluid dynamics relevant to engineering or the environment, including multiphase and microscale flows. Papers reporting the application of these disciplines to design and development, with emphasis on new technological fields, are also welcomed. Some of these new fields include microscale electronic and mechanical systems; medical and biological systems; and thermal and flow control in both the internal and external environment.
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