Flerskalig modellering av arbetsmaterialet vid skärandebearbetning
The main goal is to provide the proper finite element and experimental based technology that allows for direct fast predictions of the cutting parameters and tool wear. Our vision is to provide machining operators with online assist in the cutting process decision making based on machinability predictions.
The computational machinability assessments must be made fast, and the predictions cannot be waited upon for hours. A novel feature is the exploitation of computational micromorphic homogenization of a rigid viscoplastic Stokes flow model. Here, the choice of long-distance fluctuation of the material shear flux is crucial in order to capture the behavior of the primary shear zone in the cutting. To find the proper resolution of cutting zone, investigations are made to explore the long range- and micro-fluctuation fields with respect to computational cost efficiency and accuracy. Fast predictions are achieved via closed form homogenization based on the well-suited long-range fluctuation of the cutting zone. The model framework is validated against cutting experiments for a range of workpiece materials, where 2D orthogonal cutting conditions are monitored. Preliminary investigations concerning the shear flow distribution are available for continuous chip formation. The project is planned as a four-year fulltime project involving one PhD student and two senior researchers, working together with modeling, simulation and cutting experiments at Chalmers.
Ragnar Larsson (contact)
Chalmers, Industrial and Materials Science, Material and Computational Mechanics
Chalmers, Industrial and Materials Science, Materials and manufacture
Swedish Research Council (VR)
Project ID: 2021-05583
Funding Chalmers participation during 2022–2025