Wan‐Jin Chung

485 total citations
56 papers, 342 citations indexed

About

Wan‐Jin Chung is a scholar working on Mechanical Engineering, Mechanics of Materials and Computational Mechanics. According to data from OpenAlex, Wan‐Jin Chung has authored 56 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Mechanical Engineering, 37 papers in Mechanics of Materials and 22 papers in Computational Mechanics. Recurrent topics in Wan‐Jin Chung's work include Metal Forming Simulation Techniques (33 papers), Metallurgy and Material Forming (26 papers) and Laser and Thermal Forming Techniques (14 papers). Wan‐Jin Chung is often cited by papers focused on Metal Forming Simulation Techniques (33 papers), Metallurgy and Material Forming (26 papers) and Laser and Thermal Forming Techniques (14 papers). Wan‐Jin Chung collaborates with scholars based in South Korea, United States and Pakistan. Wan‐Jin Chung's co-authors include Ted Belytschko, Man Soo Joun, Mohanraj Murugesan, Ki-Hoon Shin, Sunghwan Kim, Seon Han Choi, D.Y. Yang, Tae Hoon Choi, Dong‐Yol Yang and Sungwon Lee and has published in prestigious journals such as Nucleic Acids Research, Scripta Materialia and Journal of Materials Processing Technology.

In The Last Decade

Wan‐Jin Chung

47 papers receiving 327 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wan‐Jin Chung South Korea 11 265 208 77 77 43 56 342
Y.T. Keum South Korea 11 358 1.4× 327 1.6× 65 0.8× 98 1.3× 19 0.4× 29 393
Hassane Moustabchir Morocco 11 148 0.6× 153 0.7× 47 0.6× 72 0.9× 74 1.7× 39 303
Sanjib Kumar Acharyya India 10 230 0.9× 91 0.4× 47 0.6× 44 0.6× 32 0.7× 35 298
Jay H. Phelps United States 6 232 0.9× 396 1.9× 48 0.6× 24 0.3× 31 0.7× 8 515
Munjin Kang South Korea 14 535 2.0× 140 0.7× 47 0.6× 54 0.7× 10 0.2× 42 574
Andreas Kuppert Germany 6 523 2.0× 360 1.7× 91 1.2× 170 2.2× 23 0.5× 12 562
Jean‐Loup Chenot France 11 230 0.9× 203 1.0× 34 0.4× 57 0.7× 28 0.7× 27 289
Luc Penazzi France 9 319 1.2× 256 1.2× 39 0.5× 152 2.0× 32 0.7× 21 440
Bernd Kuhfuß Germany 11 334 1.3× 207 1.0× 30 0.4× 151 2.0× 13 0.3× 69 414
Mats Sigvant Sweden 10 369 1.4× 327 1.6× 64 0.8× 91 1.2× 8 0.2× 50 391

Countries citing papers authored by Wan‐Jin Chung

Since Specialization
Citations

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

Fields of papers citing papers by Wan‐Jin Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wan‐Jin Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Wan‐Jin Chung. A scholar is included among the top collaborators of Wan‐Jin Chung 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 Wan‐Jin Chung. Wan‐Jin Chung 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.
Choi, In-Gyu, et al.. (2025). Analysis of acoustic emission signals during bending deformation of magnesium alloy sheet. Nondestructive Testing And Evaluation. 41(4). 2016–2039.
2.
Chung, Wan‐Jin, et al.. (2025). Experimental and numerical study on fillet rolling of a Ti6Al4V alloy aircraft bolt focusing on fatigue life. Journal of Manufacturing Processes. 151. 490–505.
3.
Chung, Wan‐Jin, et al.. (2025). Novel finite element analysis model for three-roller fillet rolling focusing on its strength of accuracy and practicability. Journal of Materials Research and Technology. 37. 3788–3800.
4.
Choi, In-Gyu, et al.. (2024). Analysis and Clustering of Acoustic Emission Signals in the Tensile Deformation of AZ31B. Metals and Materials International. 31(3). 676–691. 3 indexed citations
5.
Chung, Sai‐Ho, et al.. (2023). Realistic finite element analysis model of the pilgering process to deal with initial tube thickness nonuniformity. Journal of Manufacturing Processes. 95. 217–228. 5 indexed citations
6.
Murugesan, Mohanraj, et al.. (2023). Warm Deformation Behavior and Flow Stress Modeling of AZ31B Magnesium Alloy under Tensile Deformation. Materials. 16(14). 5088–5088. 2 indexed citations
7.
Murugesan, Mohanraj, et al.. (2023). Investigation of forming parameters influence on pillow defect in a new vacuum-assisted incremental sheet forming process. The International Journal of Advanced Manufacturing Technology. 127(11-12). 5531–5551. 7 indexed citations
8.
Murugesan, Mohanraj, et al.. (2023). Hybrid Artificial Neural Network-Based Models to Investigate Deformation Behavior of AZ31B Magnesium Alloy at Warm Tensile Deformation. Materials. 16(15). 5308–5308. 10 indexed citations
9.
Joun, Man Soo, et al.. (2023). Cases of multi-body mechanics in metal forming. AIP conference proceedings. 2810. 20003–20003. 1 indexed citations
10.
Murugesan, Mohanraj, et al.. (2022). Supervised Machine Learning Approach for Modeling Hot Deformation Behavior of Medium Carbon Steel. steel research international. 94(2). 14 indexed citations
11.
Murugesan, Mohanraj, et al.. (2022). Study on the Incremental sheet metal forming process using a metal foam as a die. International Journal of Material Forming. 15(6). 5 indexed citations
12.
Cho, Sung-Min, et al.. (2020). Optimization Design of Penetrator Geometry Using Artificial Neural Network and Genetic Algorithm. Journal of the Korean Society for Precision Engineering. 37(6). 429–436.
13.
Chung, Wan‐Jin, et al.. (2020). Tool Path Design of the Counter Single Point Incremental Forming Process to Decrease Shape Error. Materials. 13(21). 4719–4719. 17 indexed citations
14.
Chung, Wan‐Jin, et al.. (2020). Analysis of the Section Deflection in the Incremental Sheet Metal Forming Process of the Circular Cup Shape according to the Cup Geometry. Journal of the Korean Society for Precision Engineering. 37(9). 675–683. 2 indexed citations
15.
Chung, Sai‐Ho, et al.. (2019). Numerical and Experimental Study on Spring Back in Automatic Multi-Stage Precision Cold Forging Process of a Steering Yoke. Transactions of Materials Processing. 28(3). 115–122. 3 indexed citations
16.
Chung, Wan‐Jin, et al.. (2009). Forming Analysis of L-type Bending of Sandwich Sheet with Pyramid Core. Elastomers and Composites. 44(4). 378–383. 1 indexed citations
17.
Chung, Wan‐Jin, et al.. (2007). The Static and Dynamic Behaviour of a Very Long Shaft Made of a Composite. 1. 471–476. 1 indexed citations
18.
Guo, Jingzhong, et al.. (2004). PROSPECT-PSPP: an automatic computational pipeline for protein structure prediction. Nucleic Acids Research. 32(Web Server). W522–W525. 10 indexed citations
19.
Chung, Wan‐Jin, et al.. (2003). Shrinkage in Injection Molded Part for Operational Conditions and Resins. Elastomers and Composites. 38(4). 295–302. 2 indexed citations
20.
Chung, Wan‐Jin, et al.. (1996). Development of Fine Blanking Die with Fluid Chamber and its Application to Procuction of Circular Blanks in a Hydraulic Press. Journal of the Korean Society for Precision Engineering. 13(5). 157–163. 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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