Published in Archives of Computational Methods in Engineering, Vol. 31(3), pp. 1611-1658, 2024, Open Access
DOI: 10.1007/s11831-023-10026-x
https://link.springer.com/article/10.1007/s11831-023-10026-x
Conventional machining still represents a predominant manufacturing process for the production of metal parts. During the last few decades, extensive research has been conducted to develop predictive models to capture complex material response during the machining process. Understanding the plastic behavior of the metals and alloys during machining operations has a great significance for researchers and engineers in both academia and industry. This paper thoroughly reviews the constitutive material models that have been employed thus far in the conventional machining studies. The aim of the paper is to present all significant constitutive models focusing the discussion on the most frequently used. First, we introduce the phenomenological models that depend on the deformation variables including strain, strain rate and temperature. Several extended versions proposed in the literature of these types of models will be reviewed. The techniques to identify the material constant parameters will also be discussed. Second, the proposed physical-based models, a kind of model that relies on the evolution of internal state variables, including dislocation density and grain size, will be addressed. Following that, novel data-driven based constitutive models are briefly debated to highlight their capabilities in order to be exploited in machining analysis. Finally, a concise overview and perspectives for future research efforts are outlined.
Published on 01/01/2024
DOI: 10.1007/s11831-023-10026-x
Licence: CC BY-NC-SA license
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