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Abstract: chip morphology predictions in metal cutting have always been challenging because of the complexity of the various multiphysical phenomena that occur across the tool-chip interface. An accurate prediction of chip morphology is a key factor in the assessment of a particular machining operation with regard to both tool performance and workpiece quality. Although finite element (FE) models are being developed over the last two decades, their capabilities in modeling correct material flow around the tool tip with shear localization are very limited. FE models with an arbitrary Lagrangian Eulerian () approach are able to simulate correct material flow around the tool tip. However, these models are unable to predict any shear localization based on material flow criteria. On the other hand, FE models with a Lagrangian formulation can simulate shear localization in the chip segments; they need to make use of a mesh-based chip separation criterion that significantly affects material flow around the tool tip. In this study a mesh-free method viz. smoothed particles hydrodynamics (SPH) is implemented to simulate shear localization in the chip while machining hardened steel. Unlike other SPH models developed by some researchers, this model is based on a renormalized formulation that can consider frictional stresses along the tool-chip interface giving a realistic chip shape and material flow. SPH models with different cutting parameters are compared with the traditional FE models and it has been found that the SPH models are good for predicting shear localized chips and do not need any geometric or mesh-based chip separation criteria.

基于有限元和光滑粒子流体动力学的硬质工具钢切屑形貌预测方法研究

[1]ABAQUS Analysis User Manual, 2010. ABAQUS Documentation, V6.10. Dassault Systemes, France.

[2]Arrazola, P.J., Villar, A., Ugarte, D., et al., 2007. Serrated chip prediction in finite element modeling of the chip formation process. Machining Science and Technology, 11: 367-390.

[3]Atlati, S., Haddag, B., Nouari, M., et al., 2011. Analysis of a new segmentation intensity ratio “SIR” to characterize the chip segmentation process in machining ductile metals. International Journal of Machine Tools and Manufacture, 51(9):687-700.

[4]Calamaz, M., Coupard, D., Girot, F., 2008. A new material model for 2D numerical simulation of serrated chip formation when machining titanium alloy Ti–6Al–4V. International Journal of Machine Tools and Manufacture, 48(3-4):275-288.

[5]Calamaz, M., Limido, J., Nouari, M., et al., 2009. Toward a better understanding of tool wear effect through a comparison between experiments and SPH numerical modelling of machining hard materials. International Journal of Refractory Metals and Hard Materials, 27(3):595-604.

[6]Ceretti, E., Lucchi, M., Altan, T., 1999. FEM simulation of orthogonal cutting: serrated chip formation. Journal of Materials Processing Technology, 95(1-3):17-26.

[7]Cockcroft, M.G., Latham, D.J., 1968. Ductility and the workability of metals. Journal of the Institute of Metals, 96(1):33-39.

[8]Dodd, B., 1992. Adiabatic Shear Localization: Occurrence, Theories, and Applications. Pergamon Press, Oxford, UK.

[9]Gu, L.Y., Wang, M.J., Duan, C.Z., 2013. On adiabatic shear localized fracture during serrated chip evolution in high speed machining of hardened AISI 1045 steel. International Journal of Mechanical Sciences, 75:288-298.

[10]Guo, Y.B., Yen, D.W., 2004. A FEM study on mechanisms of discontinuous chip formation in hard machining. Journal of Materials Processing Technology, 155-156:1350-1356.

[11]Heisel, U., Zaloga, W., Krivoruchko, D., et al., 2013. Modelling of orthogonal cutting processes with the method of smoothed particle hydrodynamics. Production Engineering, 7(6):639-645.

[12]Hou, Z.B., Komanduri, R., 1997. Modeling of thermomechanical shear instability in machining. International Journal of Mechanical Sciences, 39(11):1273-1314.

[13]Hua, J., Shivpuri, R., 2004. Prediction of chip morphology and segmentation during the machining of titanium alloys. Journal of Materials Processing Technology, 150(1-2):124-133.

[14]Johnson, G.R., Cook, W.H., 1983. 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, Hague, The Netherlands, 21:541-547.

[15]Komanduri, R., Schroeder, T., Hazra, J., et al., 1982. On the catastrophic shear instability in high-speed machining of an AISI 4340 steel. Journal of Engineering for Industry, 104(2):121-131.

[16]Kouadri, S., Necib, K., Atlati, S., et al., 2013. Quantification of the chip segmentation in metal machining: application to machining the aeronautical aluminium alloy AA2024-T351 with cemented carbide tools WC-Co. International Journal of Machine Tools and Manufacture, 64:102-113.

[17]Limido, J., Espinosa, C., Salaün, M., et al., 2007. SPH method applied to high speed cutting modelling. International Journal of Mechanical Sciences, 49(7):898-908.

[18]Liu, M.B., Liu, G.R., 2010. Smoothed particle hydrodynamics (SPH): an overview and recent developments. Archives of Computational Methods in Engineering, 17(1):25-76.

[19]Madaj, M., Píška, M., 2013. On the SPH orthogonal cutting simulation of A2024-T351 alloy. Procedia CIRP, 8:152-157.

[20]Ng, E.G., Aspinwall, D.K., 2002a. The effect of workpiece hardness and cutting speed on the machinability of AISI H13 hot work die steel when using PCBN tooling. Journal of Manufacturing Science and Engineering, 124(3):588-594.

[21]Ng, E.G., Aspinwall, D.K., 2002b. Modelling of hard part machining. Journal of Materials Processing Technology, 127(2):222-229.

[22]Ng, E.G., Aspinwall, D.K., Brazil, D., et al., 1999. Modelling of temperature and forces when orthogonally machining hardened steel. International Journal of Machine Tools and Manufacture, 39(6):885-903.

[23]Randles, P.W., Libersky, L.D., 1996. Smoothed particle hydrodynamics: some recent improvements and applications. Computer Methods in Applied Mechanics and Engineering, 139(1-4):375-408.

[24]Rhim, S.H., Oh, S.I., 2006. Prediction of serrated chip formation in metal cutting process with new flow stress model for AISI 1045 steel. Journal of Materials Processing Technology, 171(3):417-422.

[25]Sartkulvanich, P., Koppka, F., Altan, T., 2004. Determination of flow stress for metal cutting simulation–a progress report. Journal of Materials Processing Technology, 146(1):61-71.

[26]Shaw, M.C., 1984. Metal Cutting Principles. Clarendon Press, Oxford, UK.

[27]Sima, M., Özel, T., 2010. Modified material constitutive models for serrated chip formation simulations and experimental validation in machining of titanium alloy Ti–6Al–4V. International Journal of Machine Tools and Manufacture, 50(11):943-960.

[28]Umbrello, D., Rizzuti, S., Outeiro, J.C.C., et al., 2008. Hardness-based flow stress for numerical simulation of hard machining AISI H13 tool steel. Journal of Materials Processing Technology, 199(1-3):64-73.

[29]Vila, J., 2005. SPH renormalized hybrid methods for conservation laws: applications to free surface flows. Lecture Notes in Computational Science & Engineering,

[30]43:207-229.

[31]Xi, Y., Bermingham, M., Wang, G., et al., 2014. SPH/FE modeling of cutting force and chip formation during thermally assisted machining of Ti6Al4V alloy. Computational Materials Science, 84:188-197.

[32]Xie, J.Q., Bayoumi, A.E., Zbib, H.M., 1998. FEA modeling and simulation of shear localized chip formation in metal cutting. International Journal of Machine Tools and Manufacture, 38(9):1067-1087.

[33]Zorev, N.N., 1963. Inter-relationship between shear processes occurring along tool face and shear plane in metal cutting. International Research in Production Engineering, 49:143-152.