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Reduced Model for Microscopic Lubricated Contact in Orthogonal Cutting
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The presented work aims to develop a framework to investigate the key effects within the lubricated contact zone in orthogonal cutting on a microscopic level as well as macroscopic level. As considering macro scales in microscopic detail poses practical difficulties, the possibilities to couple reduced model of the microscopic model is considered. To this end, we explore ways to develop reduced models by formulating the problem as learning a generative model of the solution fields using neural networks.
