Empirical relationship for fracture energy in machining processes: a FEM-based investigation with AISI 1045 steel
Author:
Publisher
Springer Science and Business Media LLC
Subject
Industrial and Manufacturing Engineering,Modeling and Simulation
Link
https://link.springer.com/content/pdf/10.1007/s12008-023-01596-y.pdf
Reference34 articles.
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2. Wang, B., Liu, Z., Hou, X., Zhao, J.: Influences of cutting Speed and Material Mechanical properties on Chip Deformation and Fracture during High-Speed cutting of Inconel 718. Materials. 11, 461 (2018). https://doi.org/10.3390/ma11040461
3. Bagga, P.J., Makhesana, M.A., Bhavsar, D.L., et al.: Experimental investigation of different NN approaches for tool wear prediction based on vision system in turning of AISI 1045 steel. Int. J. Interact. Des. Manuf. (2022). https://doi.org/10.1007/s12008-022-01072-z
4. Goyal, A., Kothari, B., Pathak, V.K.: Fuzzy logic and desirability-based models for predicting performance characteristics of varying concentration graphite nanoplatelets (GNPs) mixed nanofluid MQL in turning of AISI-1045 steel. Int. J. Interact. Des. Manuf. 16, 1559–1584 (2022). https://doi.org/10.1007/s12008-022-01068-9
5. Murugesan, P.D., Mohanraj, Jung, D.W.: Johnson Cook Material and failure model parameters estimation of AISI-1045 Medium Carbon Steel for Metal Forming Applications. Materials. 12, 609 (2019). https://doi.org/10.3390/ma12040609
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