Open Access
| Issue |
MATEC Web Conf.
Volume 417, 2025
2025 RAPDASA-RobMech-PRASA-AMI Conference: Bridging the Gap between Industry & Academia - The 26th Annual International RAPDASA Conference, joined by RobMech, PRASA and AMI, co-hosted by CSIR and Tshwane University of Technology, Pretoria
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| Article Number | 08004 | |
| Number of page(s) | 16 | |
| Section | Product Design and Development | |
| DOI | https://doi.org/10.1051/matecconf/202541708004 | |
| Published online | 25 November 2025 | |
- Gleeble 3800 GTC. (accessed https://gleeble.com/products/gleeble-systems/gleeble-3800.html). [Google Scholar]
- J. Yang, S. Sung, C. Chen, and A. Tan, Study of microstructural and mechanical properties of weld heat affected zones of 2024-T3 aluminium using Gleeble simulation. Mater. Sci. Technol. 27, 357-365 (2011) [Google Scholar]
- M. van Rooyen, T. H. Becker, J. E. Westraadt, and G. Marx, J, Measurement of creep deformation of ex-service 12% Cr steel using digital image correlation. Strain Anal. Eng. Des. 55, 71-85 (2020) [Google Scholar]
- M. van Rooyen and T. H. Becker, High-temperature tensile property measurements using digital image correlation over a non-uniform temperature field. J. Strain Anal. Eng. Des. 53, 117-129 (2018) [Google Scholar]
- J. Qin, D. Racine, K. Liu, and X. Chen, Strain-controlled thermo-mechanical fatigue testing of aluminum alloys using the Gleeble 3800 system in Proceedings of the 16th International Aluminum Alloys Conference (ICAA 16), Canadian Institute of Mining, Metallurgy & Petroleum, Montreal, QC, Canada, 17-21, (2018) [Google Scholar]
- Y. Gajalappa, A. Krishnaiah, K. B. Kumar, K. K. Saxena, and P. Goyal, Flow behaviour kinetics of Inconel 600 superalloy under hot deformation using gleeble 3800. Mater. Today Proc. 45, 5320-5322 (2021) [Google Scholar]
- M. Blackwell, M. Vos, S. George, M. Neaves, and T. Becker, Temperature Dependant Mechanical Property Characterisation Using Digital Image Correlation and Infrared Thermography. R&D J. 40, 27-32 (2024) [Google Scholar]
- B. Pan, K. Qian, H. Xie, and A. Asundi, Robust full-field measurement considering rotation using digital image correlation. Meas. Sci. Technol. 20, 062001 (2009) [NASA ADS] [CrossRef] [Google Scholar]
- E. M. Jones and M. A. Iadicola, A Good Practices Guide for Digital Image Correlation. Int. Dig. Image Correl. Soc. 10, 1-110 (2018) [Google Scholar]
- V. Belloni, R. Ravanelli, A. Nascetti, M. Di Rita, D. Mattei, and M. Crespi, Digital image correlation from commercial to FOS software: a mature technique for full-field displacement measurements. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci. 42, 91-95 (2018) [Google Scholar]
- D. Atkinson and T. Becker, A 117 line 2D digital image correlation code written in MATLAB. Remote Sens. 12, 2906 (2020) [Google Scholar]
- L. Yu and B. Pan, Overview of high-temperature deformation measurement using digital image correlation. Exp. Mech. 61, 1121-1142 (2021) [CrossRef] [Google Scholar]
- MatchID. (accessed https://www.matchid.eu/). [Google Scholar]
- M. A. Blackwell, High-temperature mechanical property characterisation of additively manufactured Inconel 718. MSc thesis, Stellenbosch University (2024) [Google Scholar]
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