PSI - Issue 46

Nithin Konda et al. / Procedia Structural Integrity 46 (2023) 87–93 Nithin Konda et al. / Structural Integrity Procedia 00 (2019) 000–000

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the following conclusions are made based on the present work.  XGB has explained 82% of the variance in the dataset as R2 score of the train data is 0.82, whereas RF is able to explain 78% of the variance in the dataset.  Among the two chosen algorithms, XGB has performed better in predicting the Fatigue life of L-PBF fabricated Ti6Al4V alloy. References Cain, V. et al. 2015. “Crack Propagation and Fracture Toughness of Ti6Al4V Alloy Produced by Selective Laser Melting.” Additive Manufacturing 5: 68–76. http://dx.doi.org/10.1016/j.addma.2014.12.006. Chastand, Victor, Philippe Quaegebeur, Wilson Maia, and Eric Charkaluk. 2018. “Comparative Study of Fatigue Properties of Ti-6Al-4V Specimens Built by Electron Beam Melting (EBM) and Selective Laser Melting (SLM).” Materials Characterization 143(February): 76– 81. https://doi.org/10.1016/j.matchar.2018.03.028. Du, Leiming, Guian Qian, Liang Zheng, and Youshi Hong. 2021. “Influence of Processing Parameters of Selective Laser Melting on High-Cycle and Very-High-Cycle Fatigue Behaviour of Ti-6Al-4V.” Fatigue and Fracture of Engineering Materials and Structures 44(1): 240–56. Fotovvati, Behzad, Navid Namdari, and Amir Dehghanghadikolaei. 2019. “Fatigue Performance of Selective Laser Melted Ti6Al4V Components: State of the Art.” Materials Research Express 6(1). Kamble, Rohit G., N. R. Raykar, and D. N. Jadhav. 2020. “Machine Learning Approach to Predict Fatigue Crack Growth.” Materials Today: Proceedings 38: 2506–11. https://doi.org/10.1016/j.matpr.2020.07.535. Liu, Shunyu, and Yung C. Shin. 2019. “Additive Manufacturing of Ti6Al4V Alloy: A Review.” Materials and Design 164: 107552. https://doi.org/10.1016/j.matdes.2018.107552. Mythreyi, O. V., M. Rohith Srinivaas, Tigga Amit Kumar, and R. Jayaganthan. 2021. “Machine-Learning-Based Prediction of Corrosion Behavior in Additively Manufactured Inconel 718.” Data 6(8). Pegues, Jonathan, Michael Roach, R. Scott Williamson, and Nima Shamsaei. 2018. “Surface Roughness Effects on the Fatigue Strength of Additively Manufactured Ti-6Al-4V.” International Journal of Fatigue 116(April): 543–52. https://doi.org/10.1016/j.ijfatigue.2018.07.013. Raja, Allavikutty, Sai Teja Chukka, and Rengaswamy Jayaganthan. 2020. “Prediction of Fatigue Crack Growth Behaviour in Ultrafine Grained Al 2014 Alloy Using Machine Learning.” Metals 10(10): 1–13. Vayssette, Bastien et al. 2018. “Surface Roughness of Ti-6Al-4V Parts Obtained by SLM and EBM: Effect on the High Cycle Fatigue Life.” Procedia Engineering 213: 89–97. https://doi.org/10.1016/j.proeng.2018.02.010. Xie, Yong et al. 2021. “Effect of Microstructure on Fatigue Crack Growth of Wire Arc Additive Manufactured Ti–6Al–4V.” Materials Science and Engineering: A 826(July): 141942. https://doi.org/10.1016/j.msea.2021.141942.

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