Sangjo Kim

515 total citations
38 papers, 374 citations indexed

About

Sangjo Kim is a scholar working on Aerospace Engineering, Mechanical Engineering and Global and Planetary Change. According to data from OpenAlex, Sangjo Kim has authored 38 papers receiving a total of 374 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Aerospace Engineering, 18 papers in Mechanical Engineering and 10 papers in Global and Planetary Change. Recurrent topics in Sangjo Kim's work include Turbomachinery Performance and Optimization (22 papers), Refrigeration and Air Conditioning Technologies (13 papers) and Advanced Aircraft Design and Technologies (10 papers). Sangjo Kim is often cited by papers focused on Turbomachinery Performance and Optimization (22 papers), Refrigeration and Air Conditioning Technologies (13 papers) and Advanced Aircraft Design and Technologies (10 papers). Sangjo Kim collaborates with scholars based in South Korea, United States and China. Sangjo Kim's co-authors include Changmin Son, Kuisoon Kim, Myung‐Ho Kim, Jung-Hoe Kim, Dong‐Hyun Kim, Guillermo Gallego, Dong-Hyun Kim, Naksoo Kim, Dong-In Han and Byung Chul Kim and has published in prestigious journals such as Energy, Applied Thermal Engineering and Production and Operations Management.

In The Last Decade

Sangjo Kim

31 papers receiving 353 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sangjo Kim South Korea 11 191 142 97 92 73 38 374
W. P. J. Visser Netherlands 12 203 1.1× 126 0.9× 81 0.8× 141 1.5× 97 1.3× 32 451
Cleverson Bringhenti Brazil 12 218 1.1× 221 1.6× 48 0.5× 56 0.6× 136 1.9× 73 456
Zhiping Song China 11 74 0.4× 82 0.6× 192 2.0× 78 0.8× 43 0.6× 42 346
Hakan Aygün Türkiye 13 204 1.1× 176 1.2× 40 0.4× 147 1.6× 79 1.1× 49 494
Luca Marinai United Kingdom 7 109 0.6× 56 0.4× 139 1.4× 50 0.5× 28 0.4× 13 305
Joachim Kurzke Germany 16 407 2.1× 164 1.2× 70 0.7× 147 1.6× 158 2.2× 27 593
Jeffryes W. Chapman United States 13 269 1.4× 66 0.5× 131 1.4× 134 1.5× 49 0.7× 46 486
Mitch Wolff United States 13 376 2.0× 189 1.3× 106 1.1× 89 1.0× 318 4.4× 88 619
Jonathan DeCastro United States 8 77 0.4× 55 0.4× 255 2.6× 49 0.5× 33 0.5× 15 421

Countries citing papers authored by Sangjo Kim

Since Specialization
Citations

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

Fields of papers citing papers by Sangjo Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sangjo Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Sangjo Kim. A scholar is included among the top collaborators of Sangjo Kim 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 Sangjo Kim. Sangjo Kim 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.
Kim, Kuisoon, et al.. (2025). Analysis of the Effect of Leading Edge Damage Caused by FOD on the Aerodynamic Performance of Aircraft Fan Blades. Journal of the Korean Society of Propulsion Engineers. 29(5). 1–11.
2.
Kim, Sangjo. (2025). Prediction-focused machine learning-based visualization of compressor flow in a gas turbine engine digital twin. Applied Thermal Engineering. 278. 127154–127154.
3.
Kim, Sangjo. (2025). Hybrid aero-engine performance modeling to enable real-time capability using physics-based analysis and machine learning. Engineering Applications of Artificial Intelligence. 156. 111288–111288.
4.
Kim, Sangjo. (2025). A novel approach to self-adaptive digital twin performance model of turbofan engines for in-flight application. Aerospace Science and Technology. 166. 110620–110620.
5.
Kim, Sangjo. (2025). Prediction-focused machine learning for performance adaptation of aero gas turbines through steady-state and transient simulation. Applied Thermal Engineering. 267. 125732–125732. 6 indexed citations
6.
Kim, Sangjo, et al.. (2024). Suitability of performance adaptation methods for updating the thermodynamic cycle model of a turboprop engine. Applied Thermal Engineering. 242. 122408–122408. 5 indexed citations
7.
Kim, Sangjo. (2024). Application of machine learning and its effectiveness in performance model adaptation for a turbofan engine. Aerospace Science and Technology. 147. 108976–108976. 11 indexed citations
8.
Kim, Sangjo, et al.. (2023). Diagnostics using a physics-based engine model in aero gas turbine engine verification tests. Aerospace Science and Technology. 133. 108102–108102. 39 indexed citations
9.
10.
Kim, Sangjo, et al.. (2023). A study on one-dimensional model correction for axial-flow compressors based on measurement data. Aerospace Science and Technology. 133. 108139–108139. 8 indexed citations
11.
Kim, Sangjo, et al.. (2021). Diagnostics Using First-Principles Based Digital Twin and Application for Gas Turbine Verification Test. SSRN Electronic Journal. 3 indexed citations
12.
Kim, Sangjo, Kuisoon Kim, & Changmin Son. (2019). A new transient performance adaptation method for an aero gas turbine engine. Energy. 193. 116752–116752. 38 indexed citations
13.
Kim, Sangjo. (2018). Meanline Analysis Method for Performance Analysis of a Multi-stage Axial Turbine in Choking Region. Journal of the Korean Society of Propulsion Engineers. 22(2). 20–28. 2 indexed citations
14.
Kim, Sangjo, Kuisoon Kim, & Changmin Son. (2018). Adaptation Method for Overall and Local Performances of Gas Turbine Engine Model. International Journal of Aeronautical and Space Sciences. 19(1). 250–261. 17 indexed citations
15.
Kim, Sangjo, Kuisoon Kim, & Changmin Son. (2016). Optimum arrangements of guide vanes in a combining header and its effect on the performance of a tubular heat exchanger. Applied Thermal Engineering. 103. 1145–1155. 6 indexed citations
16.
Kim, Sangjo, Changmin Son, & Kuisoon Kim. (2016). Combining effect of optimized axial compressor variable guide vanes and bleed air on the thermodynamic performance of aircraft engine system. Energy. 119. 199–210. 25 indexed citations
17.
18.
Kim, Sangjo, et al.. (2015). Study on Variable Systems for Compressor and Turbine and its Control Scheme. Journal of the Korean Society of Propulsion Engineers. 19(5). 1–14.
19.
Kim, Sangjo, et al.. (2013). A study on the bearingless switched reluctance rotation motor with improved motor performance. Journal of Mechanical Science and Technology. 27(5). 1407–1414. 3 indexed citations
20.
Kim, Sangjo. (2008). The Influence of Online Experimental Value on Affect and Trust, and re-visit Intention. 10(1). 117–135. 4 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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