Youngdon Kwon

925 citations
59 papers · 749 · h-index 14

Impact in

Papers in

Youngdon Kwon

57 papers receiving 668 citations

Peers

Youngdon Kwon
Comparison fields: 5 of 56
  • Fluid Flow and Transfer Processes 277
  • Polymers and Plastics 327
  • Computational Mechanics 152
  • Mechanics of Materials 167
  • Biomedical Engineering 207
Replace С. А. Патлажан with:
С. А. Патлажан Russia
K. A. Narh United States
D. P. Jones United Kingdom
D. A. Caulk United States
J.J. Benbow United Kingdom
Susumu Kase Japan
Yaozong Li China
I. J. Rao United States
Stephen H. Spiegelberg United States
Erik Andreassen Norway
Youngdon Kwon relative to С. А. Патлажан Russia С. А. Патлажан's profile →
Citations per field
00.5×1.5×2.2×
С. А. Патлажан · 1×
Citations per year

Countries citing papers authored by Youngdon Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Youngdon Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Youngdon Kwon, 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 Youngdon Kwon Line = papers co-authored together Youngdon Kwon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201393
2 199491
3 199558
4 197757
5 199433
6
Finite element analysis of planar 4:1 contraction flow with the tensor-logarithmic formulation of differential constitutive equations
200427
7 200422
8 199121
9 200118
10 197718
11 201618
12 202115
13 198013
14 199213
15 199413
16 201213
17 197612
18 201712
19 197712
20 199312

About Youngdon Kwon

Youngdon Kwon is a scholar working on Fluid Flow and Transfer Processes, Polymers and Plastics, Computational Mechanics, Biomedical Engineering and Mechanics of Materials, having authored 59 papers that have together received 749 indexed citations. Recurring topics across this work include Rheology and Fluid Dynamics Studies (32 papers), Polymer crystallization and properties (15 papers), Elasticity and Material Modeling (11 papers), Mechanical Behavior of Composites (9 papers), Polymer Nanocomposites and Properties (7 papers), Fluid Dynamics and Turbulent Flows (7 papers), Textile materials and evaluations (7 papers) and Force Microscopy Techniques and Applications (4 papers). The work is most often cited by research in Fluid Flow and Transfer Processes (277 citations), Polymers and Plastics (327 citations), Computational Mechanics (152 citations), Mechanics of Materials (167 citations) and Biomedical Engineering (207 citations). Youngdon Kwon has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include D. C. Prevoršek, A. I. Leonov, Abhishek Sharma, Yumi Matsumiya, Hiroshi Watanabe, Sung Soo Kim, Un Young Kim, Jae‐Jin Kim, H. B. Chin and Cheolmin Park. Their work appears in journals such as Rheologica Acta, Macromolecules, Journal of Applied Polymer Science, Journal of Rheology and Journal of Non-Newtonian Fluid Mechanics.

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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