Modelling fatigue life prediction of additively manufactured Ti-6Al-4V samples using machine learning approach.

MLA

Horňas, Jan, et al. “Modelling Fatigue Life Prediction of Additively Manufactured Ti-6Al-4V Samples Using Machine Learning Approach.” International Journal of Fatigue, vol. 169, Apr. 2023, p. N.PAG. EBSCOhost, https://doi.org/10.1016/j.ijfatigue.2022.107483.

APA

Horňas, J., Běhal, J., Homola, P., Senck, S., Holzleitner, M., Godja, N., Pásztor, Z., Hegedüs, B., Doubrava, R., Růžek, R., & Petrusová, L. (2023). Modelling fatigue life prediction of additively manufactured Ti-6Al-4V samples using machine learning approach. International Journal of Fatigue, 169, N.PAG. https://doi.org/10.1016/j.ijfatigue.2022.107483

Chicago

Horňas, Jan, Jiří Běhal, Petr Homola, Sascha Senck, Martin Holzleitner, Norica Godja, Zsolt Pásztor, et al. 2023. “Modelling Fatigue Life Prediction of Additively Manufactured Ti-6Al-4V Samples Using Machine Learning Approach.” International Journal of Fatigue 169 (April): N.PAG. doi:10.1016/j.ijfatigue.2022.107483.