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Title: Milling Process FEM Simulation for Identification of Material Parameters Directly from Experiments

Abstract

An identification procedure for the determination of material parameters that are used for the FEM simulation of milling processes is proposed. This procedure is based on the coupling of a numerical identification procedure and FEM simulations of milling operations. The experimental data result directly from measurements performed during milling experiments. A special device has been instrumented and calibrated to perform force and torque measurements, directly during machining experiments in using a piezoelectric dynamometer and a high frequency charge amplifier. The forces and torques are stored and low pass filtered if necessary, and these data provide the main basis for the identification procedure which is based on coupling 3D FEM simulations of milling and optimization/identification algorithms. The identification approach is mainly based on the Surfaces Response Method in the material parameters space, coupled to a sensitivity analysis. A Moving Least Square Approximation method is used to accelerate the identification process. The material behaviour is described from Johnson-Cook law. A fracture model is also added to consider chip formation and separation. The FEM simulations of milling are performed using explicit ALE based FEM code. The inverse identification method is here applied on a 304L stainless steel and the first results are presented.

Authors:
; ; ; ;  [1]
  1. FEMTO-ST Institute / Applied Mechanics Laboratory, ENSMM, 26 rue de l'Epitaphe, 25000 Besancon (France)
Publication Date:
OSTI Identifier:
21057389
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 908; Journal Issue: 1; Conference: NUMIFORM '07: 9. international conference on numerical methods in industrial forming processes, Porto (Portugal), 17-21 Jun 2007; Other Information: DOI: 10.1063/1.2740820; (c) 2007 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; A CODES; ALGORITHMS; APPROXIMATIONS; COMPUTERIZED SIMULATION; COUPLING; FINITE ELEMENT METHOD; FRACTURES; LEAST SQUARE FIT; MILLING; OPTIMIZATION; PIEZOELECTRICITY; SENSITIVITY ANALYSIS; STAINLESS STEEL-304L; SURFACES; TORQUE

Citation Formats

Maurel, A., Fontaine, M., Thibaud, S., Michel, G., and Gelin, J. C. Milling Process FEM Simulation for Identification of Material Parameters Directly from Experiments. United States: N. p., 2007. Web. doi:10.1063/1.2740820.
Maurel, A., Fontaine, M., Thibaud, S., Michel, G., & Gelin, J. C. Milling Process FEM Simulation for Identification of Material Parameters Directly from Experiments. United States. doi:10.1063/1.2740820.
Maurel, A., Fontaine, M., Thibaud, S., Michel, G., and Gelin, J. C. Thu . "Milling Process FEM Simulation for Identification of Material Parameters Directly from Experiments". United States. doi:10.1063/1.2740820.
@article{osti_21057389,
title = {Milling Process FEM Simulation for Identification of Material Parameters Directly from Experiments},
author = {Maurel, A. and Fontaine, M. and Thibaud, S. and Michel, G. and Gelin, J. C.},
abstractNote = {An identification procedure for the determination of material parameters that are used for the FEM simulation of milling processes is proposed. This procedure is based on the coupling of a numerical identification procedure and FEM simulations of milling operations. The experimental data result directly from measurements performed during milling experiments. A special device has been instrumented and calibrated to perform force and torque measurements, directly during machining experiments in using a piezoelectric dynamometer and a high frequency charge amplifier. The forces and torques are stored and low pass filtered if necessary, and these data provide the main basis for the identification procedure which is based on coupling 3D FEM simulations of milling and optimization/identification algorithms. The identification approach is mainly based on the Surfaces Response Method in the material parameters space, coupled to a sensitivity analysis. A Moving Least Square Approximation method is used to accelerate the identification process. The material behaviour is described from Johnson-Cook law. A fracture model is also added to consider chip formation and separation. The FEM simulations of milling are performed using explicit ALE based FEM code. The inverse identification method is here applied on a 304L stainless steel and the first results are presented.},
doi = {10.1063/1.2740820},
journal = {AIP Conference Proceedings},
number = 1,
volume = 908,
place = {United States},
year = {Thu May 17 00:00:00 EDT 2007},
month = {Thu May 17 00:00:00 EDT 2007}
}