利用 OpenFOAM 经验闭包对高压过冷沸腾流进行 CFD 分析,以了解制冷剂属性变化的影响

IF 2.2 Q2 ENGINEERING, MULTIDISCIPLINARY
Baramee Muangput , Thet Zin , Sirawit Namchanthra , Jetsadaporn Priyadumkol , Tinnapob Phengpom , Watcharapong Chookaew , Chakrit Suvanjumrat , Machimontorn Promtong
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引用次数: 0

摘要

沸腾流动是一个重大问题,尤其是当液体超过其沸点时,有可能导致灾难性后果。本研究利用 OpenFOAM 软件中的两相代码研究流动沸腾过程中气泡的形成。根据运行条件选择了成熟的经验模型来计算壁面热量成分。研究结合了制冷剂 R-12 不同特性的高压沸腾流(10-30 巴)的实验数据。与实验结果相比,预测结果显示空隙率和液体温度的预测值偏低。值得注意的是,过冷度对空隙率行为的影响得到了强调,蒸发部分的潜在预测不足也得到了强调,尤其是靠近壁面的部分。通过气泡直径和速度数据的差异,可以明显看出气泡大小分布建模的挑战,这表明有必要进一步改进代码。总之,这项数值研究为了解高压过冷沸腾流的复杂动力学提供了宝贵的见解,尤其是在考虑到工作流体性质可变的情况下。今后的工作重点是完善成核点密度、气泡离去尺寸和升空频率模型,以提高预测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CFD elucidation of high-pressure subcooled boiling flow towards effects of variable refrigerantproperties using OpenFOAM empirical closures

Boiling flow presents a significant concern, especially when a liquid surpasses its boiling point, potentially leading to catastrophic consequences. This research utilizes a two-phase code in the OpenFOAM software to investigate bubble formation during flow boiling. The well-established empirical models for calculating wall heat components were selected based on the operating conditions. The study incorporates experimental data from high-pressure boiling flow (10–30 bars) with variable properties of refrigerant R-12. The predictions reveal underpredictions in void fraction and liquid temperature compared to experimental observations. Significantly, the impact of the subcooling degree on void fraction behaviour is emphasized, and a potential underprediction of the evaporation portion is highlighted, particularly near the wall. Challenges in modelling bubble size distribution are evident through discrepancies in bubble diameter and velocity data, indicating the necessity for further advancements in the code. In summary, this numerical study provides valuable insights into the intricate dynamics of high-pressure subcooled boiling flow, especially when considering variable working fluid properties. Future efforts will focus on refining models for nucleation site density, bubble departure size, and lift-off frequency to enhance prediction accuracy.

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来源期刊
Applications in engineering science
Applications in engineering science Mechanical Engineering
CiteScore
3.60
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审稿时长
68 days
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