Comparative analysis of heat transfer enhancement in vortex generators using nanofluids under turbulent flow conditions
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Yanfang Yu
,
Zhiying Han
Abstract
To address industrial challenges in thermal efficiency equipment, current research emphasizes optimizing system designs and employing efficient heat transfer fluids. In this paper, the turbulent heat transfer performance of nanofluids in a TG-type vortex generator is investigated by numerical simulations using the mixture model at Re = 2,600–17,000 operating conditions. Gap-Diameter ratio (G/D) are investigated in order to select a vortex generator structure with the optimal performance (Best performance when G/D = 1.2). Then the impact of nanofluid type, concentration, and CNT diameter on heat transfer was quantified. It was found that the Nusselt number of Vortex generators was by 1.75–2.44 times higher than that of the empty tube. The nanofluids Al2O3–H2O, SiC–H2O and CNT–H2O achieved Nuavg increases of 1.04–1.17, 1.30–1.46 and 5.36–5.98 times over water, respectively. By increasing the Fc and suppressing the ST, CNT can reduce total irreversible losses while achieving efficient heat transfer. In addition, the comprehensive heat transfer performance of single-walled carbon nanotubes (SWCNT) is better than that of multi-walled carbon nanotubes (MWCNT). MWCNT = 50 nm, MWCNT < 10 nm and SWCNT exhibited PEC enhancements of 4.03–5.07, 4.48–5.70, and 6.92–9.07 times over water, respectively. This study provides valuable insight into the optimization of heat exchangers and other industrial thermal systems.
Funding source: Qingdao Science and Technology for Public Welfare Demonstration Project
Award Identifier / Grant number: 25-1-5-xdny-10-nsh
Funding source: Innovation Projects of University Students
Award Identifier / Grant number: 202507016CX
Funding source: Natural Science Foundation of Liaoning Province
Award Identifier / Grant number: 2024-MS-132
Funding source: Research Start-up Fund of China University of Petroleum (East China)
Award Identifier / Grant number: R20220113
Funding source: Shandong Provincial Natural Science Foundation
Award Identifier / Grant number: ZR2024ME067
Funding source: the Scientific Research Project of Education Department of Liaoning Province
Award Identifier / Grant number: LJ212510149023
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. YF Yu: Conceptualization, Supervision, Methodology, Writing – original draft. MQ Zhang: Investigation, Formal analysis, Software, Validation. HB Meng: Writing – review & editing, Project administration, Supervision, Funding acquisition. ZY Han: Software, JN Wang: Data curation.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: This research was supported by the following funds: Qingdao Science and Technology for Public Welfare Demonstration Project (25-1-5-xdny-10-nsh), Research Start-up Fund of China University of Petroleum (East China) (R20220113), Shandong Provincial Natural Science Foundation (ZR2024ME067), Natural Science Foundation of Liaoning Province (2024-MS-132), the Scientific Research Project of Education Department of Liaoning Province (LJ212510149023), and Innovation Projects of University Students (202507016CX).
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Data availability: Not applicable.
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