Uncertainty quantification for the drag reduction of microbubble-laden fluid flow in a horizontal channel

IF 3.6 2区 工程技术 Q1 MECHANICS International Journal of Multiphase Flow Pub Date : 2024-11-16 DOI:10.1016/j.ijmultiphaseflow.2024.105059
Byeong-Cheon Kim , Kyoungsik Chang , Sang-Wook Lee , Jaiyoung Ryu , Minjae Kim , Jaemoon Yoon
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Abstract

Over three decades, much research has proven the bubble drag reduction (BDR) technique. Recently, the improvement of computing performance has enabled the simulation of multi-phase flows. The present work simulated the microbubble-laden turbulent horizontal channel flow by Nek5000 code, which is based on the spectral element method. To resolve the microbubble dynamics, the 2-way coupling Euler–Lagrange approach was combined with Nek5000 code. Furthermore, for high accuracy, high-order Lagrange interpolation was adopted to track the microbubble's location and velocity in this code. All microbubbles were assumed as non-deformable, spherical, and immiscible. For the investigation of the drag reduction effect of microbubble size and the number of microbubbles, the uncertainty quantification (UQ) method was adopted with the non-intrusive polynomial chaos method. The Latin hypercube sampling method was used to obtain precision with lesser number of samples than the Monte Carlo method. The distribution of random variables was assumed to be Gaussian and generalized polynomial chaos expansion (gPC) was applied to build the surrogate model. The mean value (μ) of random variables was 110 µm, 6,345 each, while the standard deviation (σ) was ± 0.33 μ. As a result, the uncertainty propagation of velocity, second-order turbulence statistics, and drag reduction were achieved.

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水平通道中含微气泡流体流动阻力减小的不确定性量化
30 多年来,大量研究证实了气泡阻力减小(BDR)技术。最近,计算性能的提高使得多相流的模拟成为可能。本研究利用基于谱元法的 Nek5000 代码模拟了含有微气泡的湍流水平通道流。为了解决微气泡动力学问题,将双向耦合欧拉-拉格朗日方法与 Nek5000 代码相结合。此外,为了获得高精度,该代码还采用了高阶拉格朗日插值法来跟踪微气泡的位置和速度。所有微气泡均假定为不可变形、球形和不溶解。为了研究微泡大小和数量对降低阻力的影响,采用了不确定性量化(UQ)方法和非侵入式多项式混沌方法。与蒙特卡罗法相比,采用拉丁超立方采样法以较少的样本数获得精度。假设随机变量的分布为高斯分布,并采用广义多项式混沌扩展(gPC)建立代用模型。随机变量的平均值(μ)为 110 µm,每个随机变量为 6,345 μm,标准偏差(σ)为 ± 0.33 μ。因此,实现了速度的不确定性传播、二阶湍流统计和阻力减小。
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来源期刊
CiteScore
7.30
自引率
10.50%
发文量
244
审稿时长
4 months
期刊介绍: The International Journal of Multiphase Flow publishes analytical, numerical and experimental articles of lasting interest. The scope of the journal includes all aspects of mass, momentum and energy exchange phenomena among different phases such as occur in disperse flows, gas–liquid and liquid–liquid flows, flows in porous media, boiling, granular flows and others. The journal publishes full papers, brief communications and conference announcements.
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