Optimisation and comparison of performance parameters of a double pipe heat exchanger with dimpled twisted tapes using CFD and ANN

Jatoth Heeraman, Ravinder Kumar, P. Chaurasiya, T. Verma, Davendra Kumar Chauhan
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Abstract

Double pipe heat exchanger (DPHE) is a key component of a wide variety of fields where heat trans-mission is a necessity. The numerical simulation was carried out using ANSYS 16.0 within the operating Reynolds number ( Re) 6000 to 14,000 to explore and estimate the thermal performance of the heat exchangers (HEs). Computational fluid dynamic (CFD) analysis was performed for the tube tailored with tape twisted (TT) with dimples of Día = 6 mm, D/H Ratio = 1.5, 3 and 4.5, with twist ratio is 5.5. The gathered datasets were subsequently employed validate an artificial neural network (ANN) model, aiming to forecast Nusselt numbers and friction factor within a tube containing dimpled twisted tape inserts. The mean relative errors (MRE) between the predicted results, experimental data and numerical results for the Nusselt numbers and the friction factor were less than 3.30, 0.08 and 2.1 percentage, respectively. Consequently, the study suggests employing the combination of CFD and ANN models as a means to forecast the effectiveness of thermal systems in diverse engineering applications. The efficiency of heat transmission, frictional loss, flow rates and heat transfer rate were all determined using these quantitative simulations.
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利用 CFD 和 ANN 优化和比较带凹陷扭曲带的双管热交换器的性能参数
双管热交换器(DPHE)是各种热传输领域的关键部件。使用 ANSYS 16.0 在工作雷诺数(Re)6000 至 14000 范围内进行了数值模拟,以探索和估计热交换器(HEs)的热性能。计算流体动力学(CFD)分析针对的是用胶带扭曲(TT)定制的管子,其凹陷为 Día = 6 毫米,D/H 比 = 1.5、3 和 4.5,扭曲比为 5.5。收集的数据集随后被用于验证人工神经网络(ANN)模型,该模型旨在预测含有凹陷扭曲胶带插入物的管道内的努塞尔特数和摩擦因数。在努塞尔特数和摩擦因数方面,预测结果、实验数据和数值结果之间的平均相对误差(MRE)分别小于 3.30%、0.08% 和 2.1%。因此,该研究建议采用 CFD 和 ANN 模型相结合的方法来预测各种工程应用中热力系统的有效性。热传递效率、摩擦损失、流速和传热率都是通过这些定量模拟确定的。
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