Identification of constitutive material model parameters for high-strain rate metal cutting conditions using evolutionary computational algorithms

Materials and Manufacturing Processes

Volumn 22, Issue 5, 2007, Pages 659-667

  Özel, Tuǧrul ^a   Karpat, Yiǧit ^a  

^a DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING   (United States)

Author keywords

Constitutive material models; High strain rate plasticity; Metal cutting; Particle swarm optimization

Indexed keywords

COMPUTATIONAL METHODS; EVOLUTIONARY ALGORITHMS; FINITE ELEMENT METHOD; MATHEMATICAL MODELS; PLASTICITY; STRAIN RATE;

CONSTITUTIVE MATERIAL MODELS; HIGH-STRAIN RATE PLASTICITY; JOHNSON-COOK (JC) CONSTITUTIVE MODELS; PARTICLE SWARM OPTIMIZATION;

METAL CUTTING;

EID: 34249899976     PISSN: 10426914     EISSN: 15322475     Source Type: Journal    
DOI: 10.1080/10426910701323631     Document Type: Article

References (22)

1. Oxley, P.L.B. Mechanics of Machining, An Analytical Approach to Assessing Machinability; Ellis Horwood Limited: Chichester, UK, 1989.
2. Childs, T.H.C.; Maekawa, K.; Obikawa, T.; Yamane, Y. Metal Machining: Theory and Applications; Arnold: London, U.K., 2000.
3. Özel, T.; Altan, T. Determination of workpiece flow stress and friction at the chi-tool contact for high speed cutting. International Journal of Machine Tool and Manufacture 2000, 40, 1333-1352.
4. Sartkulvanich, P.; Altan, T.; Abdullah, G. Effects of flow stress and friction models in finite element simulation of orthogonal cutting - a sensitivity analysis. Machining Science and Technology 2005, 9, 1-26.
5. Jaspers, S.P.F.C.; Dautzenberg, J.H. Material behaviour in metal cutting: strains, strain rates and temperatures in chip formation. Journal of Materials Processing Technology 2002, 121, 123-135.
6. Maekawa, K.; Shirakashi, T.; Usui, E. Flow stress of low carbon steel at high temperature and strain rate (Part 2). Bulletin, Japanese Society of Precision Engineering 1983, 17/3, 167-172.
7. Bammann, D.J.; Chiesa, M.L.; Johnson, G.C. Modeling large deformation and failure in manufacturing processes. Theoretical and Applied Mechanics 1996, 359-376.
8. Lennon, A.M.; Ramesh, K.T. A technique for measuring the dynamic behavior of materials at high temperatures. International Journal of Plasticity 1998, 14/12, 1279-1292.
9. Johnson, G.R.; Cook, W.H. A constitutive model and data for metals subjected to large strains, high strain rates and high temperatures. Proceedings of the 7th International Symposium on Ballistics, The Hague, The Netherlands, 1983; 541-547.
10. Zerilli, F.J.; Armstrong, R.W. Dislocation mechanics based constitutive relations for material dynamics calculations. Journal of Applied Physics 1987, 57/5, 1816-1825.
11. Jaspers, S.P.F.C; Dautzenberg, J.H. Material behavior in conditions similar to metal cutting: flow stress in the primary shear zone. Journal of Materials Processing Technology 2002, 122, 322-330.
12. Lee, W.S.; Lin, C.F. High-temperature deformation behavior of Ti6Al4V alloy evaluated by high strain-rate compression tests. Journal of Materials Processing Technology 1998, 75, 127-136.
13. Gray, G.T.; Chen, S.R.; Wright, W.; Lopez, M.F. Constitutive equations for annealed metals under compression at high strain rates and high temperatures. Los Alamos National Laboratory Report; LA-12669-MS, 1994.
14. Meyer H.W. Jr.; Kleponis, D.S. Modeling the high strain rate behavior of titanium undergoing ballistic impact and penetration. International Journal of Impact Engineering 2001, 26, 509-521.
15. Özel, T.; Zeren, E. A methodology to determine work material flow stress and tool-chip interfacial friction properties by using analysis of machining. ASME Journal of Manufacturing Science and Engineering 2006, 128, 119-129.
16. Eberhart, R.C.; Kennedy, J. Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, 1995; 942-1948.
17. Van der Bergh, F.; Engelbrecht, A.P. A cooperative approach to particle swarm optimization. IEEE Transactions on Evolutionary Computation 2004, 8 (3), 225-239.
18. Shi, Y.; Eberhart, R.C. Parameter selection in particle swarm optimization. Proceedings of 7th Annual Conference on Evalutionary Programming, San Diego, 1998; 591-600.
19. Clerc, M. The swarm and the queen: toward a deterministic and adaptive particle swarm optimization. In Proceedings of 1999 Congress on Evolutionary Computation, Washington, DC, 1999; 1951-1957.
20. Eberhart, R.C.; Shi, Y. Comparing inertia weights and constriction factors in particle swarm optimization. In Proceedings of 2000 Congress on Evolutionary Computation, La Jolla, CA, 2000; 84-88.
21. Kennedy, J.; Eberhart, R.C. A discrete binary version of the particle swarm algorithm. In Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, Computational Cybernetics and Simulation, Orlando, FL, 1997; 5, 4104-4108.
22. Angeline, P. Using selection to improve particle swarm optimization. In Proceedings of 1999 Congress on Evolutionary Computation, Washington, DC, 1999; 84-89.