journal article·2010-12

Temperature and stress fields evolution during spark plasma sintering processes

S. Muñoz, U. Anselmi-Tamburini

Journal of Materials Science· Volume 45· Issue 23
Publisher page

Abstract

Numerical modelling of Spark Plasma Sintering (SPS) processes is essential to evaluate temperature and stress distributions that can result in sample inhomogeneities. Most of the available literature, however, produced analysis in static conditions. In this work, we focused our attention on the time evolution of current density, temperature and stress distribution during a SPS process using a new approach that includes a PID control in the algorithm, allowing a realistic simulation of experiments performed using a temperature controller. Controlled temperature experiments have been simulated and discussed, with special interest focused on the time evolution of the process. The results showed that stress gradients inside the samples (~40%) are much greater than the temperature gradients (~2%), suggesting that heterogeneities in the microstructure can also be caused by the stress gradient. During the evolution of the process, a peak in stresses is experienced by the alumina sample at the beginning of the cooling stage, caused by differences in contraction between the sample and the die. It has been proved that, using a controlled cooling stage, these peaks in the stresses can be easily eliminated.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced ceramic materials synthesis · Advanced materials and composites · Aluminum Alloys Composites Properties

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References (18)

Show source-provided references
1. Groza JR (1998) In: ASM Handbook, vol 7, Powder metallurgy, pp 583
2. Orrù R, Licheri R, Locci A, Cincotti A, Cao G (2009) Mater Sci Eng R 63:127–28710.1016/j.mser.2008.09.003 ↗
3. Munir ZA, Anselmi-Tamburini U, Ohyanagi M (2006) J Mater Sci 41:763–777. doi: 10.1007/s10853-006-6555-210.1007/s10853-006-6555-2 ↗
4. Anselmi-Tamburini U, Garay JE, Munir ZA (2006) Scr Mater 54:823–82810.1016/j.scriptamat.2005.11.015 ↗
5. Zavaliangos A, Zhang J, Krammer M, Groza JR (2004) Mater Sci Eng A 379:218–22810.1016/j.msea.2004.01.052 ↗
6. Vanmeensel K, Laptev A, Hennicke J, Vleugels J, Van der Biest O (2005) Acta Mater 53:4379–438810.1016/j.actamat.2005.05.042 ↗
7. Anselmi-Tamburini U, Gennari S, Garay JE, Munir ZA (2005) Mater Sci Eng A 394:139–14810.1016/j.msea.2004.11.019 ↗
8. McWilliams B, Zavaliangos A, Cho KC, Dowding RJ (2006) JOM 58(4):67–7110.1007/s11837-006-0218-2 ↗
9. McWilliams B, Zavaliangos A (2008) J Mater Sci 43(14):5031–5503. doi: 10.1007/s10853-008-2744-5s10.1007/s10853-008-2744-5 ↗
10. Antou G, Mathieu G, Trolliard G, Maitre A (2009) J Mater Res 24(2):404–41210.1557/JMR.2009.0039 ↗
11. Wang X, Casolco SR, Xu G, Garay JE (2007) Acta Mater 55:3611–362210.1016/j.actamat.2007.02.022 ↗
12. ANSYS 11.0 Coupled-field analysis guide (2007)
13. ANSYS 11.0 Contact technology guide (2007)
14. Åstrom KJ, Hagglund T (1995) PID controllers: theory, design and tuning, 2nd edn. ISA Research Triangle Park, NC
15. Ziegler J, Nichols N (1942) Trans ASME 64:759–768
16. Matsugi K, Kuramoto H, Hatayama T, Yanagisawa O (2004) J Mater Process Technol 146:274–28110.1016/j.jmatprotec.2003.11.002 ↗
17. Tomino H, Watanabe H, Kondo Y (1997) J Jpn Soc Powder Metall 44:974–97910.2497/jjspm.44.974 ↗
18. Khoei A (2005) Computational plasticity in powder forming processes, Elsevier Sci, Oxford