Kaiyan Jin

412 citations
16 papers · 322 · h-index 10

Impact in

Papers in

    • Combustion and Detonation Processes 9
    • Heat and Mass Transfer in Porous Media 3
    • Heat transfer and supercritical fluids 3
    • Computational Fluid Dynamics and Aerodynamics 3
    • Combustion and flame dynamics 1

Kaiyan Jin

15 papers receiving 319 citations

Peers

Kaiyan Jin
Comparison fields: 5 of 26
  • Aerospace Engineering 218
  • Safety, Risk, Reliability and Quality 66
  • Computational Mechanics 55
  • Statistics, Probability and Uncertainty 10
  • Fluid Flow and Transfer Processes 9
Replace A. Gavrikov with:
A. Gavrikov Russia
Jianjun Xiao China
Shaojie Wan China
Vladislav V. Volodin Russia
Jeffrey L. Chaffee United States
А.А. Ефименко Russia
Keiko Chitose Japan
Shengchao Rui China
Shingo Chiba Japan
Pratikash P. Panda India
Kaiyan Jin relative to A. Gavrikov Russia A. Gavrikov's profile →
Citations per field
00.5×2×3×4.4×
A. Gavrikov · 1×
Citations per year

Countries citing papers authored by Kaiyan Jin

Since Specialization
Citations

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

Fields of papers citing papers by Kaiyan Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Kaiyan Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kaiyan Jin Line = papers co-authored together Kaiyan Jin links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 202148
2 202244
3 202043
4 202034
5 202133
6 202126
7 202321
8 202418
9 202315
10 202411
11 20239
12 20238
13 20245
14 20254
15 20253
16 20260

About Kaiyan Jin

Kaiyan Jin is a scholar working on Aerospace Engineering, Computational Mechanics, Applied Mathematics, Safety, Risk, Reliability and Quality and Statistical and Nonlinear Physics, having authored 16 papers that have together received 322 indexed citations. Recurring topics across this work include Combustion and Detonation Processes (9 papers), Heat and Mass Transfer in Porous Media (3 papers), Heat transfer and supercritical fluids (3 papers), Computational Fluid Dynamics and Aerodynamics (3 papers), Gas Dynamics and Kinetic Theory (2 papers), Hydrogen Storage and Materials (1 paper), Fire dynamics and safety research (1 paper) and Combustion and flame dynamics (1 paper). The work is most often cited by research in Aerospace Engineering (218 citations), Safety, Risk, Reliability and Quality (66 citations), Computational Mechanics (55 citations), Statistics, Probability and Uncertainty (10 citations) and Fluid Flow and Transfer Processes (9 citations). Kaiyan Jin has collaborated with scholars based in China, Germany and United Kingdom. Frequent co-authors include Yuchun Zhang, Yunji Gao, Shengnan Yang, Zhisheng Li, Yifei Han, Dongsheng Wen, Qiangling Duan, Jinhua Sun, Jin Cai Zhao and Guice Yao. Their work appears in journals such as Combustion and Flame, International Journal of Hydrogen Energy, International Journal of Heat and Mass Transfer, Journal of Computational Physics and Tunnelling and Underground Space Technology.

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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