Combined Model Based on the Finite Element Method and Artificial Neural Networks for Modeling Laser Shock Peening of Titanium–Niobium Implants
Author:
Publisher
Pleiades Publishing Ltd
Subject
Industrial and Manufacturing Engineering,Mechanical Engineering,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1134/S1052618823070208.pdf
Reference10 articles.
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2. Pavan, M., Furfari, D., Ahmad, B., Gharghouri, M.A., and Fitzpatrick, M.E., Fatigue crack growth in a laser shock peened residual stress field, Int. J. Fatigue, 2019, vol. 123, pp. 157–165. https://doi.org/10.1016/j.ijfatigue.2019.01.020
3. Sathiya, P., Paaneerselvam, K., and Soundararajan, R., Optimal design for laser beam butt welding process parameter using artificial neural networks and genetic algorithm for super austenitic stainless steel, Opt. Laser Technol., 2012, vol. 44, no. 6, pp. 1905–1914. https://doi.org/10.1016/j.optlastec.2012.01.025
4. Hfaiedh, N., Peyre, P., Song, H., Popa, I., Ji, V., and Vignal, V., Finite element analysis of laser shock peening of 2050–T8 aluminum alloy, Int. J. Fatigue, 2015, vol. 70, pp. 480–489. https://doi.org/10.1016/j.ijfatigue.2014.05.015
5. Rahimi, M.H., Shayganmanesh, M., Noorossana, R., and Pazhuheian, F., Modelling and optimization of laser engraving qualitative characteristics of Al-SiC composite using response surface methodology and artificial neural networks, Opt. Laser Technol., 2019, vol. 112, pp. 65–76. https://doi.org/10.1016/j.optlastec.2018.10.058
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1. A Comprehensive Review on Finite Element Analysis of Laser Shock Peening;Materials;2024-08-23
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