Jun Long
Impact in
- Computational Mechanics top 5%
- Fluid Dynamics and Turbulent Flows
- Heat transfer and supercritical fluids
- Granular flow and fluidized beds
- Combustion and flame dynamics
- Fluid Dynamics and Vibration Analysis
- Soil Science top 10%
- Irrigation Practices and Water Management
Papers in
-
- Fluid Dynamics and Turbulent Flows 8
- Fluid Dynamics and Vibration Analysis 4
-
- Heat Transfer Mechanisms 6
- Co-authors
- T. H. New (7 shared papers)Xiaogang Liu (3 shared papers)Liming Yu (3 shared papers)Qiliang Yang (3 shared papers)Dong Yang (2 shared papers)Siyang Wang (1 shared paper)Shengxian Shi (1 shared paper)Bin Zang (1 shared paper)
- Journals
- Experimental Thermal and Fluid Science (2 papers)Physics of Fluids (2 papers)Experiments in Fluids (2 papers)Journal of Futures Markets (2 papers)Chemical Engineering Science (1 paper)
- Partner nations
- ChinaSingaporeUnited Kingdom
In The Last Decade
Jun Long
20 papers receiving 303 citations
Peers
Comparison fields: 5 of 48
- Computational Mechanics 191
- Soil Science 67
- Aerospace Engineering 61
- Mechanical Engineering 91
- Civil and Structural Engineering 50
Countries citing papers authored by Jun Long
This map shows the geographic impact of Jun Long's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jun Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Long more than expected).
Fields of papers citing papers by Jun Long
This network shows the impact of papers produced by Jun Long. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Long. The network helps show where Jun Long may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Long, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 50 | |
| 2 | 2015 | 41 | |
| 3 | 2018 | 31 | |
| 4 | 2015 | 28 | |
| 5 | 2018 | 27 | |
| 6 | 2020 | 26 | |
| 7 | 2015 | 26 | |
| 8 | 2018 | 22 | |
| 9 | 2015 | 13 | |
| 10 | 2020 | 9 | |
| 11 | 2016 | 9 | |
| 12 | 2022 | 7 | |
| 13 | 2018 | 6 | |
| 14 | 2024 | 3 | |
| 15 | 2023 | 3 | |
| 16 | 2024 | 2 | |
| 17 | 2023 | 2 | |
| 18 | 2024 | 2 | |
| 19 | 2015 | 2 | |
| 20 | 2012 | 1 |
About Jun Long
Jun Long is a scholar working on Computational Mechanics, Mechanical Engineering, Biomedical Engineering, Civil and Structural Engineering and Economics and Econometrics, having authored 22 papers that have together received 310 indexed citations. Recurring topics across this work include Fluid Dynamics and Turbulent Flows (8 papers), Heat Transfer Mechanisms (6 papers), Fluid Dynamics and Vibration Analysis (4 papers), Financial Markets and Investment Strategies (3 papers), Stock Market Forecasting Methods (3 papers), Market Dynamics and Volatility (3 papers), Particle Dynamics in Fluid Flows (2 papers) and Hydraulic flow and structures (2 papers). The work is most often cited by research in Computational Mechanics (191 citations), Soil Science (67 citations), Aerospace Engineering (61 citations), Mechanical Engineering (91 citations) and Civil and Structural Engineering (50 citations). Jun Long has collaborated with scholars based in China, Singapore and United Kingdom. Frequent co-authors include T. H. New, Xiaogang Liu, Liming Yu, Qiliang Yang, Dong Yang, Siyang Wang, Shengxian Shi, Bin Zang, Shiqiu Gao and Wei Wang. Their work appears in journals such as Experimental Thermal and Fluid Science, Physics of Fluids, Experiments in Fluids, Journal of Futures Markets and Chemical Engineering Science.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.