利用动态高阶分解法分析气泡柱的水动力特性

IF 3.1 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Science Pub Date : 2024-05-13 DOI:10.1016/j.jocs.2024.102316
C. Mendez , F.P Santos , G.G.S. Ferreira
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引用次数: 0

摘要

气泡塔在化学和生物化学过程、石油化工和环境工程等众多行业中发挥着至关重要的作用。了解气泡塔的动态对于优化其在各种应用中的性能至关重要。本研究提出了一种分析二维气泡柱系统动力学的数据驱动方法。为此,我们进行了不同表面速度的模拟,并生成了涵盖整个速度场和压力场的综合训练数据集。然后,我们比较了快速傅立叶变换(FFT)和高阶动态模式分解(HODMD)这两种方法在表现系统动态方面的性能。我们的研究结果表明,传统的 FFT 方法无法充分捕捉分散多相流系统的复杂动态。这种局限性是由于沿域的频率分布造成的。相反,我们的工作突出了 HODMD 方法的成功之处,即仅使用域内的几个任意采样点就能准确地表示系统的动态。这项研究意义重大,因为它揭示了采用 HODMD 分析气泡柱动力学的潜在优势。利用这种方法,可以在各种应用中更有效地优化工业流程。
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Hydrodynamic characterization of bubble column using Dynamical High Order Decomposition approach

Bubble columns play a crucial role in a wide range of industries, including chemical and biochemical processes, petrochemicals, and environmental engineering. Understanding the dynamics of bubble columns is essential for optimizing their performance in various applications. This study proposes a data-driven approach for analyzing the dynamics of a two-dimensional bubble column system. We conducted simulations with varying superficial velocities and generated a comprehensive training dataset encompassing the entire velocity and pressure fields to achieve this. We then compared the performance of two approaches, the Fast Fourier Transformation (FFT) and the High-Order Dynamic Mode Decomposition (HODMD), in representing the system’s dynamics. Our findings demonstrate that the conventional FFT approach fails to adequately capture the complex dynamics of the dispersed multiphase flow system. This limitation arises due to the distribution of frequencies along the domain. Conversely, our work highlights the success of the HODMD method in accurately representing the system’s dynamics using only a few arbitrary sampling points within the domain. The implications of this study are significant, as it sheds light on the potential benefits of employing HODMD for analyzing bubble column dynamics. By utilizing this approach, industrial processes can be optimized more effectively across various applications.

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来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
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