Sukky Jun

5.0k citations
35 papers · 4.1k indexed · 2 hit papers · h-index 18

Sukky Jun

35 papers receiving 3.9k citations

Hit Papers

Reproducing kernel particle methods2.3k199520262005201550010001.5k2.0k

Peers

Sukky Jun
Comparison fields: 5 of 81
  • Mechanics of Materials 3.3k
  • Computational Mechanics 2.0k
  • Civil and Structural Engineering 1.3k
  • Modeling and Simulation 87
  • Materials Chemistry 734
Replace Y. Krongauz with:
Y. Krongauz United States
D. Organ United States
Dongdong Wang China
I.V. Singh India
Michael J. Borden United States
John T. Foster United States
Eli Sternberg United States
Michael A. Epton United States
Martin Schanz Austria
Olaf Weckner United States
Sukky Jun relative to Y. Krongauz United States Y. Krongauz's profile →
Citations per field
00.5×3.0×
Y. Krongauz · 1×
Citations per year

Countries citing papers authored by Sukky Jun

Since Specialization
Citations

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

Fields of papers citing papers by Sukky Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20122
2 201014
3 2008113
4 200867
5 20071
6 200753
7 200732
8 20065
9
COLLOCATION MESHFREE METHODS AS A FLOW SOLVER, WHAT WE ARE DONE WITH AND WHAT WE ARE DOING NOW
20062
10 20063
11 20048
12 200311
13 200318
14 200016
15 199887
16 1998102
17 199793
18
Reproducing kernel particle methods for structural dynamicsbreakdown →
1995677
19
Reproducing Kernel Particle Methods for elastic and plastic problems
199324
20 199343

About Sukky Jun

Sukky Jun is a scholar working on Mechanics of Materials, Computational Mechanics and Ceramics and Composites, having authored 35 papers that have together received 4.1k indexed citations. Recurring topics across this work include Numerical methods in engineering (13 papers), Fluid Dynamics Simulations and Interactions (8 papers), Graphene research and applications (7 papers), Carbon Nanotubes in Composites (6 papers), Advanced Numerical Methods in Computational Mathematics (5 papers), Composite Material Mechanics (4 papers), Microstructure and mechanical properties (4 papers) and Ion-surface interactions and analysis (3 papers). The work is most often cited by research in Mechanics of Materials (3.3k citations), Computational Mechanics (2.0k citations) and Civil and Structural Engineering (1.3k citations). Sukky Jun has collaborated with scholars based in United States, South Korea and Philippines. Frequent co-authors include Wing Kam Liu, Yi Fei Zhang, Ted Belytschko, Shaofan Li, Sung Youb Kim, Seyoung Im, In‐Ho Lee, Demitris Kouris, Changwen Mi and Youngmin Lee. Their work appears in journals such as Physical Review B, International Journal for Numerical Methods in Engineering, Computer Methods in Applied Mechanics and Engineering, Optics Express and Applied Physics Letters.

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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