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Data for a simulation of metal cutting with cutting fluid using the Finite-Pointset-Method
Eckart Uhlmann1,2, Enrico Barth1, Tobias Seifarth3
1Institute for Machine Tools and Factory Management (IWF), Technische Universität Berlin, Pascalstr. 8 - 9, Berlin 10587, Germany.
Data in Brief
|September 24, 2021
Summary
This study details metal cutting simulations using the Finite-Pointset-Method (FPM), providing accessible experimental and simulation data for validation. Researchers can replicate and extend these simulations for metal cutting process analysis.
Area of Science:
- Manufacturing Engineering
- Computational Mechanics
Background:
- Orthogonal cutting simulations require accurate experimental data for validation.
- The Finite-Pointset-Method (FPM) offers a robust approach for simulating complex material behaviors.
- Previous research has explored metal cutting simulations, but comprehensive data sharing is often limited.
Purpose of the Study:
- To present detailed measurement and simulation data for wet and dry metal cutting.
- To provide the simulation setup and adaptable software for the Finite-Pointset-Method (FPM).
- To enable independent validation and further research in metal cutting simulation.
Main Methods:
- Conducting wet and dry turning experiments to gather process forces and chip morphology data.
- Developing and adapting the MESHFREE software for FPM-based simulations.
- Collaboratively validating the orthogonal cutting simulation model between research institutes.
Main Results:
- Detailed preparation methods for process forces, chip morphology images, and tool rake face contact lengths are documented.
- Experimental and simulation data are published on the Mendeley Data repository.
- Complete simulation model files are also available for replication and further analysis.
Conclusions:
- The published data and models facilitate transparent and reproducible research in metal cutting simulation.
- Open access to simulation data and models promotes further validation and exploration of process parameters.
- This work supports the advancement of computational methods in manufacturing processes.
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