Seog-Young Han

555 total citations
43 papers, 441 citations indexed

About

Seog-Young Han is a scholar working on Civil and Structural Engineering, Computational Theory and Mathematics and Mechanics of Materials. According to data from OpenAlex, Seog-Young Han has authored 43 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Civil and Structural Engineering, 18 papers in Computational Theory and Mathematics and 17 papers in Mechanics of Materials. Recurrent topics in Seog-Young Han's work include Topology Optimization in Engineering (24 papers), Advanced Multi-Objective Optimization Algorithms (18 papers) and Composite Structure Analysis and Optimization (11 papers). Seog-Young Han is often cited by papers focused on Topology Optimization in Engineering (24 papers), Advanced Multi-Objective Optimization Algorithms (18 papers) and Composite Structure Analysis and Optimization (11 papers). Seog-Young Han collaborates with scholars based in South Korea. Seog-Young Han's co-authors include Jae-Yong Park, Kwangsun Yoo, Ji‐Yong Park, Jae‐Eung Oh, Dong‐Won Kim, Jin-Su Kim, Jae Hyung Park, Sookyoung Lee, Young June Yoon and Yong‐Ho Kim and has published in prestigious journals such as Journal of Biomechanics, Sensors and Actuators B Chemical and Journal of Theoretical Biology.

In The Last Decade

Seog-Young Han

40 papers receiving 410 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seog-Young Han South Korea 12 227 155 101 97 81 43 441
Bouchaïb Radi France 12 99 0.4× 129 0.8× 95 0.9× 144 1.5× 129 1.6× 75 453
David J. Munk Australia 14 327 1.4× 183 1.2× 188 1.9× 34 0.4× 152 1.9× 31 561
Mehmet A. Akgün Türkiye 10 429 1.9× 140 0.9× 301 3.0× 166 1.7× 105 1.3× 27 652
Woo-Seok Choi South Korea 9 290 1.3× 75 0.5× 159 1.6× 92 0.9× 131 1.6× 42 508
Thang Le-Duc Vietnam 13 201 0.9× 91 0.6× 61 0.6× 38 0.4× 79 1.0× 18 477
G. J. Park South Korea 7 198 0.9× 118 0.8× 111 1.1× 84 0.9× 92 1.1× 16 364
Terence Macquart United Kingdom 11 198 0.9× 74 0.5× 195 1.9× 43 0.4× 78 1.0× 32 432
Silvana M. B. Afonso Brazil 16 225 1.0× 98 0.6× 141 1.4× 78 0.8× 304 3.8× 48 596
Kai Long China 16 320 1.4× 96 0.6× 209 2.1× 27 0.3× 145 1.8× 47 597
Senthil Murugan India 12 299 1.3× 50 0.3× 213 2.1× 147 1.5× 68 0.8× 30 523

Countries citing papers authored by Seog-Young Han

Since Specialization
Citations

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

Fields of papers citing papers by Seog-Young Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seog-Young Han. 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 Seog-Young Han. The network helps show where Seog-Young Han may publish in the future.

Co-authorship network of co-authors of Seog-Young Han

This figure shows the co-authorship network connecting the top 25 collaborators of Seog-Young Han. A scholar is included among the top collaborators of Seog-Young Han 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 Seog-Young Han. Seog-Young Han 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.
Han, Seog-Young, et al.. (2019). A Modified Big Bang–Big Crunch Algorithm for Structural Topology Optimization. International Journal of Precision Engineering and Manufacturing. 20(12). 2193–2203. 2 indexed citations
2.
Kim, Yong‐Ho & Seog-Young Han. (2018). Topological Shape Optimization Scheme for Nonlinear Structures Based on Artificial Bee Colony Algorithm. Journal of The Korean Society of Manufacturing Technology Engineers. 27(4). 329–338. 1 indexed citations
3.
Kim, Yong‐Ho & Seog-Young Han. (2017). Topological shape optimization scheme based on the artificial bee colony algorithm. International Journal of Precision Engineering and Manufacturing. 18(10). 1393–1401. 6 indexed citations
4.
Lee, Seungmin & Seog-Young Han. (2016). Topology optimization scheme for dynamic stiffness problems using harmony search method. International Journal of Precision Engineering and Manufacturing. 17(9). 1187–1194. 5 indexed citations
5.
Han, Seog-Young, et al.. (2015). Topology optimum design of compliant mechanisms using modified ant colony optimization. Journal of Mechanical Science and Technology. 29(8). 3321–3327. 15 indexed citations
6.
Han, Seog-Young, et al.. (2014). Mechanism for reducing stress concentrations in bolt-nut connectors. International Journal of Precision Engineering and Manufacturing. 15(7). 1337–1343. 8 indexed citations
7.
Park, Ji‐Yong & Seog-Young Han. (2013). Application of artificial bee colony algorithm to topology optimization for dynamic stiffness problems. Computers & Mathematics with Applications. 66(10). 1879–1891. 19 indexed citations
8.
Kim, Se-Chan, et al.. (2012). Development of Modified Ant Colony Optimization Algorithm for Compliant Mechanisms. 152–157. 5 indexed citations
9.
Yoon, Young June, et al.. (2012). The speed of sound through trabecular bone predicted by Biot theory. Journal of Biomechanics. 45(4). 716–718. 5 indexed citations
10.
Park, Jae Hyung, et al.. (2012). A modeling approach to energy savings of flying Canada geese using computational fluid dynamics. Journal of Theoretical Biology. 320. 76–85. 25 indexed citations
11.
Park, Jae-Yong, et al.. (2012). Dynamic topology optimization based on ant colony optimization. 2. 763–766. 2 indexed citations
12.
Park, Jaeku, et al.. (2012). Application of artificial bee colony algorithm for structural topology optimization. 1023–1025. 4 indexed citations
13.
Park, Jae-Yong, et al.. (2011). Optimum design of an active micro-mixer using successive Kriging method. International Journal of Precision Engineering and Manufacturing. 12(5). 849–855. 18 indexed citations
14.
Yoo, Kwangsun, et al.. (2011). Reliability-based topology optimization using successive standard response surface method. Finite Elements in Analysis and Design. 47(7). 843–849. 29 indexed citations
15.
Yoo, Kwangsun, et al.. (2010). Reliability-based topology optimization using a standard response surface method for three-dimensional structures. Structural and Multidisciplinary Optimization. 43(2). 287–295. 91 indexed citations
16.
Han, Seog-Young, et al.. (2010). Reliability-Based Topology Optimization Based on Bidirectional Evolutionary Structural Optimization. 19(4). 529–538. 1 indexed citations
17.
Yi, Byung-Ju, et al.. (2008). Comparison of Impulses Experienced on Human Joints Walking on the Ground to Those Experienced Walking on a Treadmill. International Journal of Control Automation and Systems. 6(2). 243–252. 7 indexed citations
18.
Park, Jae-Yong, et al.. (2007). Study on a Spatial 3-Degree-of-Freedom Micromanipulator Employing Displacement Magnifying Four-Revolute-Flexure Hinges. Journal of the Korean Physical Society. 51(4). 1419–1419. 1 indexed citations
19.
Han, Seog-Young. (2000). Shape optimization for general two-dimensional structures. Acta Mechanica. 145(1-4). 117–125. 7 indexed citations
20.
Han, Seog-Young, et al.. (1997). Effects of Extreme Pressure Additives on Lubricity and Anti-seizure Property of Lubricants.. ISIJ International. 37(5). 498–503. 3 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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