线管式相变材料热交换器传热的数值研究

IF 1.5 4区 物理与天体物理 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Devendra Dandotiya, Nitin. D. Banker, Anil Jaiswal, Naveen G. Patil
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引用次数: 0

摘要

潜热储存装置具有能量密度高和等温传热的特点,利用潜热储存装置可以提高热能系统的性能。本研究旨在通过数值模拟,研究翅片位置对线管式相变材料(PCM)热交换器熔化时间的影响。研究为热交换器引入了一种新的复杂几何形状,并在 Ansys Fluent 软件中使用已建立的凝固和熔化模型对传热进行了数值分析。数值结果与实验数据进行了验证,发现管和鳍片的位置对 PCM 内部的热传递有重大影响。该模型能够预测温度数据,最大偏差为 3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Numerical investigation of heat transfer in wire and tube-based phase change material heat exchanger

The utilization of latent heat storage units with their high energy density and isothermal heat transfer behavior can enhance the performance of thermal energy systems. This study aims to investigate the effect of fin placement on the melting time of a wire and tube-based Phase Change Material (PCM) heat exchanger using numerical simulations. The study introduces a new complex geometry for the heat exchanger, and numerical analysis of heat transfer was conducted in Ansys Fluent software using an established solidification and melting model. The numerical results were validated against experimental data, and it was found that the position of the tubes and fins had a significant impact on heat transfer within the PCM. The model was able to predict temperature data with a maximum discrepancy of 3%.

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来源期刊
International Journal of Modern Physics C
International Journal of Modern Physics C 物理-计算机:跨学科应用
CiteScore
3.00
自引率
15.80%
发文量
158
审稿时长
4 months
期刊介绍: International Journal of Modern Physics C (IJMPC) is a journal dedicated to Computational Physics and aims at publishing both review and research articles on the use of computers to advance knowledge in physical sciences and the use of physical analogies in computation. Topics covered include: algorithms; computational biophysics; computational fluid dynamics; statistical physics; complex systems; computer and information science; condensed matter physics, materials science; socio- and econophysics; data analysis and computation in experimental physics; environmental physics; traffic modelling; physical computation including neural nets, cellular automata and genetic algorithms.
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