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Heat Transfer Research

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ISSN Print: 1064-2285

ISSN Online: 2162-6561

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.4 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.6 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00072 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.43 SJR: 0.318 SNIP: 0.568 CiteScore™:: 3.5 H-Index: 28

Indexed in

HEAT TRANSFER ENHANCEMENT−A BRIEF REVIEW OF LITERATURE IN 2020 AND PROSPECTS

Volume 52, Issue 10, 2021, pp. 65-92
DOI: 10.1615/HeatTransRes.2021038770
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ABSTRACT

This review provides a brief literature survey on enhanced heat transfer research published in the English language journals in 2020. A topic search containing either "heat transfer" or "heat transport" or "thermal transport" in the Web of Science resulted in over 28,000 papers published in 2020 and nearly 30% were relevant to heat transfer intensification, which indicates the importance and rapid development of heat transfer enhancement technologies. The chosen studies focus on various heat transfer enhancement research categorized into conduction, convection, radiation, boiling and condensation, energy storage, thermal management, and cross research involving two or more categories. Heat conduction papers are selected from the micro/nanoscale areas with a focus on interfacial phenomena. Important active, passive, and compound techniques for enhancing convective heat transfer are incorporated. Thermal radiation is concentrated on near-field radiation and solar energy. Heat transfer enhancement in boiling and condensation as well as in thermal energy storage, renewable and sustainable energy, and thermal management of electronics and high-end equipment is critical in many engineering applications. From the selected literature published in 2020, significant attempts have been made to research and development on heat transfer enhancement technology covering both conventional and emerging techniques. The prospects of the heat transfer enhancement research are reflected according to the literature survey. Research of innovative heat transfer enhancement techniques is immense, encompassing every aspect from understanding the fundamental theory and physical mechanisms of various heat transfer enhancement techniques to their applications. Research of emerging techniques using new interfacial materials, nanofluids, micro- and nanostructures, microchannels, and new compound enhancement techniques incorporating conventional and new techniques becomes popular. However, there are big challenges in understanding the mechanisms, engineering design methodology, and applications with these emerging techniques. Many aspects are urgently needed to be investigated and developed to achieve systematic theory, mechanisms, and design methodology for applications in thermal processes, energy storage, renewable energy, decarbonized heating and cooling and many industrial and civil sectors.

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  4. Hua Yue, Peng Jiang-Zhou, Zhou Zhi-Fu, Wu Wei-Tao, He Yong, Massoudi Mehrdad, Thermal Performance in Convection Flow of Nanofluids Using a Deep Convolutional Neural Network, Energies, 15, 21, 2022. Crossref

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