Sam Coppieters

2.1k total citations
105 papers, 1.7k citations indexed

About

Sam Coppieters is a scholar working on Mechanical Engineering, Mechanics of Materials and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sam Coppieters has authored 105 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Mechanical Engineering, 74 papers in Mechanics of Materials and 32 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sam Coppieters's work include Metal Forming Simulation Techniques (69 papers), Metallurgy and Material Forming (50 papers) and Optical measurement and interference techniques (32 papers). Sam Coppieters is often cited by papers focused on Metal Forming Simulation Techniques (69 papers), Metallurgy and Material Forming (50 papers) and Optical measurement and interference techniques (32 papers). Sam Coppieters collaborates with scholars based in Belgium, Japan and Portugal. Sam Coppieters's co-authors include Dimitri Debruyne, Pascal Lava, Steven Cooreman, Toshihiko Kuwabara, P. Van Houtte, H. Sol, Maarten De Strycker, Y. Wang, A. Andrade‐Campos and Dimitri Debruyne and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Materials Processing Technology and International Journal of Solids and Structures.

In The Last Decade

Sam Coppieters

98 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sam Coppieters Belgium 21 1.2k 915 499 294 280 105 1.7k
F.A. Díaz Spain 24 707 0.6× 893 1.0× 531 1.1× 178 0.6× 670 2.4× 116 1.7k
Marco Rossi Italy 21 685 0.6× 632 0.7× 344 0.7× 274 0.9× 322 1.1× 52 1.2k
Steven Cooreman Belgium 13 600 0.5× 467 0.5× 322 0.6× 181 0.6× 200 0.7× 51 941
David Lecompte Belgium 20 593 0.5× 480 0.5× 546 1.1× 330 1.1× 770 2.8× 63 1.6k
Sébastien Mistou France 13 503 0.4× 1.3k 1.4× 410 0.8× 292 1.0× 931 3.3× 43 1.9k
B. Wattrisse France 13 365 0.3× 423 0.5× 544 1.1× 162 0.6× 324 1.2× 19 1.1k
Marina Fazzini France 13 459 0.4× 396 0.4× 472 0.9× 87 0.3× 314 1.1× 29 1.2k
Jin Yan China 12 399 0.3× 276 0.3× 373 0.7× 123 0.4× 244 0.9× 25 876
Zejia Liu China 20 407 0.3× 184 0.2× 246 0.5× 190 0.6× 290 1.0× 80 1.1k
Xiaomin Deng United States 25 989 0.8× 1.2k 1.3× 186 0.4× 426 1.4× 640 2.3× 89 2.0k

Countries citing papers authored by Sam Coppieters

Since Specialization
Citations

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

Fields of papers citing papers by Sam Coppieters

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sam Coppieters

This figure shows the co-authorship network connecting the top 25 collaborators of Sam Coppieters. A scholar is included among the top collaborators of Sam Coppieters 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 Sam Coppieters. Sam Coppieters 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.
Starman, Bojan, et al.. (2025). Characterising Through-Thickness Shear Anisotropy Using the Double-Bridge Shear Test and Finite Element Model Updating. Materials. 18(10). 2220–2220. 1 indexed citations
2.
Starman, Bojan, et al.. (2025). Inverse calibration of out-of-plane shear anisotropy parameters of sheet metal. International Journal of Solids and Structures. 313. 113313–113313. 2 indexed citations
3.
Zhong, Shengping, Qimin Shi, Jeroen Van Dessel, et al.. (2025). Biomechanics of Manual-Bent Versus Patient-Specific Mandibular Implants. Journal of Biomechanical Engineering. 147(12). 1 indexed citations
4.
Coppieters, Sam. (2024). Plasticity experiments on heavy gauge S700 steel. Materials research proceedings. 41. 1135–1143.
5.
Starman, Bojan, et al.. (2023). Confidence intervals of inversely identified material model parameters: A novel two-stage error propagation model based on stereo DIC system uncertainty. Optics and Lasers in Engineering. 174. 107958–107958. 5 indexed citations
6.
Chen, Bin & Sam Coppieters. (2023). Unified digital image correlation under meshfree framework. Strain. 60(1). 8 indexed citations
7.
Ivens, Jan, et al.. (2022). The Effect of the Setting Force on the Fatigue Resistance of a Blind Rivet Nut Set in CFRP. Key engineering materials. 926. 1498–1504. 2 indexed citations
8.
Rossi, Marco, et al.. (2022). Testing methodologies for the calibration of advanced plasticity models for sheet metals: A review. Strain. 58(6). 33 indexed citations
9.
Henriques, João, et al.. (2022). Parameter Identification of Swift Law Using a FEMU-Based Approach and an Innovative Heterogeneous Mechanical Test. Key engineering materials. 926. 2238–2246. 3 indexed citations
10.
Andrade‐Campos, A., et al.. (2022). Identification of Anisotropic Yield Functions Using FEMU and an Information-Rich Tensile Specimen. Key engineering materials. 926. 2162–2173. 2 indexed citations
11.
Coppieters, Sam, et al.. (2018). Mechanical Behaviour of Clinched Joints in Configurations. SHILAP Revista de lepidopterología. 414–414. 1 indexed citations
12.
Denys, K., et al.. (2016). Identification of a 3D Anisotropic Yield Surface of X70 Pipeline Steel Using a Multi-DIC Setup. Lirias (KU Leuven). 1 indexed citations
13.
Coppieters, Sam, et al.. (2014). Identification of Post-Necking Hardening Behaviour of Sheet Metal: Influence of the Yield Function. Lirias (KU Leuven). 1 indexed citations
14.
Coppieters, Sam, et al.. (2013). Advances in post-necking flow curve identification of sheet metal through standard tensile testing. AIP conference proceedings. 632–635. 2 indexed citations
15.
Coppieters, Sam, Pascal Lava, Steven Cooreman, et al.. (2012). Numerical and experimental study of the multi-axial quasi-static strength of clinched connections. International Journal of Material Forming. 6(4). 437–451. 44 indexed citations
16.
Lava, Pascal, et al.. (2012). Impact of lens distrortions on strain measurements obtained with digital image correlation. Ghent University Academic Bibliography (Ghent University). 1–6. 2 indexed citations
17.
Coppieters, Sam, Steven Cooreman, H. Sol, Paul Van Houtte, & Dimitri Debruyne. (2011). Identification of post-necking hardening behaviour of sheet metal.
18.
Coppieters, Sam, Pascal Lava, H. Sol, et al.. (2010). Determination of the flow stress and contact friction of sheet metal in a multi-layered upsetting test. Journal of Materials Processing Technology. 210(10). 1290–1296. 20 indexed citations
19.
Coppieters, Sam, et al.. (2009). Inverse identification of flow curves and interface friction for FE simulations of clinch forming. Lirias (KU Leuven). 2 indexed citations
20.
Cooreman, Steven, David Lecompte, H. Sol, Dimitri Debruyne, & Sam Coppieters. (2007). Elasto-plastic material parameter identification by inverse methods. Lirias (KU Leuven). 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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