Jianchun Mi

7.8k total citations
196 papers, 6.4k citations indexed

About

Jianchun Mi is a scholar working on Computational Mechanics, Aerospace Engineering and Fluid Flow and Transfer Processes. According to data from OpenAlex, Jianchun Mi has authored 196 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 157 papers in Computational Mechanics, 70 papers in Aerospace Engineering and 54 papers in Fluid Flow and Transfer Processes. Recurrent topics in Jianchun Mi's work include Combustion and flame dynamics (89 papers), Fluid Dynamics and Turbulent Flows (77 papers) and Aerodynamics and Acoustics in Jet Flows (58 papers). Jianchun Mi is often cited by papers focused on Combustion and flame dynamics (89 papers), Fluid Dynamics and Turbulent Flows (77 papers) and Aerodynamics and Acoustics in Jet Flows (58 papers). Jianchun Mi collaborates with scholars based in China, Australia and Hong Kong. Jianchun Mi's co-authors include Graham J. Nathan, Ravinesh C. Deo, Pengfei Li, Feifei Wang, Bassam B. Dally, Minyi Xu, R. A. Antonia, David S. Nobes, Sujan Ghimire and Nawin Raj and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Journal of Fluid Mechanics.

In The Last Decade

Jianchun Mi

186 papers receiving 6.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jianchun Mi China 47 4.6k 2.0k 1.8k 1.7k 1.0k 196 6.4k
G. D. Raithby Canada 35 5.9k 1.3× 1.3k 0.7× 2.0k 1.1× 451 0.3× 2.2k 2.2× 118 8.6k
A. A. Mohamad Canada 42 4.7k 1.0× 622 0.3× 3.1k 1.7× 558 0.3× 2.6k 2.6× 197 7.1k
Weeratunge Malalasekera United Kingdom 21 2.3k 0.5× 1.1k 0.6× 689 0.4× 631 0.4× 1.0k 1.0× 105 4.5k
Bassam B. Dally Australia 44 5.6k 1.2× 1.5k 0.7× 1.6k 0.9× 3.7k 2.2× 546 0.5× 224 6.7k
R. J. Moffat United States 30 5.4k 1.2× 3.2k 1.6× 2.3k 1.2× 649 0.4× 7.9k 7.7× 129 12.1k
Thomas Sattelmayer Germany 41 5.3k 1.1× 2.3k 1.2× 603 0.3× 3.5k 2.0× 486 0.5× 445 6.6k
Zhaohui Liu China 39 2.6k 0.6× 455 0.2× 2.1k 1.2× 945 0.6× 1.0k 1.0× 288 5.1k
Wenming Yang Singapore 64 6.8k 1.5× 2.0k 1.0× 5.0k 2.7× 7.8k 4.6× 1.6k 1.6× 321 12.4k
Wei Zuo China 43 1.8k 0.4× 770 0.4× 1.0k 0.6× 1.6k 0.9× 1.1k 1.1× 84 4.8k
A. Oliva Spain 42 3.4k 0.7× 950 0.5× 834 0.5× 178 0.1× 2.2k 2.2× 298 6.0k

Countries citing papers authored by Jianchun Mi

Since Specialization
Citations

This map shows the geographic impact of Jianchun Mi'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 Jianchun Mi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianchun Mi more than expected).

Fields of papers citing papers by Jianchun Mi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jianchun Mi. 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 Jianchun Mi. The network helps show where Jianchun Mi may publish in the future.

Co-authorship network of co-authors of Jianchun Mi

This figure shows the co-authorship network connecting the top 25 collaborators of Jianchun Mi. A scholar is included among the top collaborators of Jianchun Mi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jianchun Mi. Jianchun Mi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Si, Jicang, Yulian Wang, Farhan Hanif, et al.. (2025). Ensemble-Empirical-Mode-Decomposition (EEMD) on SWH prediction: The effect of decomposed IMFs, continuous prediction duration, and data-driven models. Ocean Engineering. 324. 120755–120755. 10 indexed citations
2.
Ahmad, Akhlaq, et al.. (2025). The Solar AI Nexus: Reinforcement Learning Shaping the Future of Energy Management. Wiley Interdisciplinary Reviews Energy and Environment. 14(3). 1 indexed citations
3.
Metwaly, Mohamed, et al.. (2025). Towards Sustainable Construction: Experimental and Machine Learning-Based Analysis of Wastewater-Integrated Concrete Pavers. Sustainability. 17(15). 6811–6811. 1 indexed citations
4.
5.
Wang, Guochang, Xiangtao Liu, Pengfei Li, et al.. (2024). Influence of the H2 proportion on NH3/H2/air combustion in hot and low-oxygen coflows. International Journal of Hydrogen Energy. 63. 480–490. 18 indexed citations
6.
Liu, Xiangtao, et al.. (2024). On a premixed NH3/O2 jet flame in hot coflow of gaseous H2O versus N2. International Journal of Hydrogen Energy. 72. 588–600. 7 indexed citations
7.
Hanif, Muhammad Fainan & Jianchun Mi. (2024). Harnessing AI for solar energy: Emergence of transformer models. Applied Energy. 369. 123541–123541. 20 indexed citations
8.
9.
Hanif, Muhammad Fainan, Mohamed Metwaly, Imran Iqbal, et al.. (2024). Leveraging advanced AI algorithms with transformer-infused recurrent neural networks to optimize solar irradiance forecasting. Frontiers in Energy Research. 12. 9 indexed citations
10.
Wu, Mengwei, Chuanqing Zhu, Hao Wang, et al.. (2024). Recent advances in nanogenerators driven by flow-induced vibrations for harvesting energy. Materials Today Energy. 41. 101529–101529. 13 indexed citations
11.
Wang, Guochang, Xiangtao Liu, Pengfei Li, et al.. (2023). MILD combustion of a premixed NH3/air jet flame in hot coflow versus its CH4/air counterpart. Fuel. 355. 129523–129523. 29 indexed citations
12.
Cheong, Kin-Pang, et al.. (2023). Operational condition and furnace geometry for premixed C3H8/Air MILD combustion of high thermal-intensity and low emissions. Energy. 288. 129905–129905. 14 indexed citations
13.
Wu, Mengwei, Chuanqing Zhu, Jicang Si, et al.. (2023). Recent Progress in Flow Energy Harvesting and Sensing Based on Triboelectric Nanogenerators. Advanced Materials Technologies. 8(19). 13 indexed citations
14.
Wu, Mengwei, Minyi Xu, Jianchun Mi, & Ravinesh C. Deo. (2020). Mixing characteristics of a film-exciting flapping jet. International Journal of Heat and Fluid Flow. 82. 108532–108532. 6 indexed citations
15.
Jiang, Xudong, Pengfei Li, Junjun Guo, et al.. (2018). Detailed investigation of NO mechanism in non-premixed oxy-fuel jet flames with CH4/H2 fuel blends. International Journal of Hydrogen Energy. 43(17). 8534–8557. 30 indexed citations
16.
Wang, Feifei, Pengfei Li, Jianchun Mi, & Jinbo Wang. (2018). A refined global reaction mechanism for modeling coal combustion under moderate or intense low-oxygen dilution condition. Energy. 157. 764–777. 29 indexed citations
17.
Wang, Feifei, et al.. (2018). Particle deposition in ventilation duct with convex or concave wall cavity. Journal of Central South University. 25(11). 2601–2614. 4 indexed citations
18.
Cheong, Kin-Pang, Guochang Wang, Jianchun Mi, et al.. (2018). Premixed MILD Combustion of Propane in a Cylindrical Furnace with a Single Jet Burner: Combustion and Emission Characteristics. Energy & Fuels. 32(8). 8817–8829. 39 indexed citations
19.
Mi, Jianchun. (2011). Effect of Large Turbulence Intensity on Airfoil Load and Flow. Acta Aeronautica Et Astronautica Sinica. 3 indexed citations
20.
Mi, Jianchun, Fei Wang, & Pengfei Li. (2010). Effects of Reactant Injection Conditions on Diffusion Combustion of Natural Gas in a Laboratory-scale Combustor. 1573. 1 indexed citations

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.

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