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Thermal Modeling of Electron Beam Additive Manufacturing Process–Powder Sintering Effects

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Thermal Modeling of Electron Beam Additive Manufacturing Process–Powder Sintering Effects

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Thermal Modeling of Electron Beam Additive Manufacturing Process–Powder Sintering Effects

  1. 1. THERMAL MODELING OF ELECTRON BEAM ADDITIVE MANUFACTURING PROCESS – POWDER SINTERING EFFECTS Ninggang (George) Shen Dr. Kevin Chou 6/6/2012The University of Alabama-Mechanical Engineering 1
  2. 2. Outline of the contents1. Introduction & research objectives2. Heat transfer and heat source modeling3. Material properties & state changes4. FE mode configuration5. Model validation6. Simulation results7. Conclusions8. Future workThe University of Alabama-Mechanical Engineering 2
  3. 3. 1. Introduction and research objectivesThe University of Alabama-Mechanical Engineering 3
  4. 4. 1. Introduction and research objectives Fig. 1 Melt ball formation [2] Fig. 2 Delamination [2] 4The University of Alabama-Mechanical Engineering
  5. 5. 1. Introduction and research objectives Fig. 3 SEM picture of Ti-6Al-4V powder Fig 4. SEM picture of sintered Ti-6Al-4V powderThe University of Alabama-Mechanical Engineering 5
  6. 6. 2. Heat transfer and heat source modelingAssumption: Negligible molten flow within molten pool Temperature distribution given by heat conduction within process domain Radiation considered as boundary condition No convection between part and surroundings due to vacuum T - Temperature 2 2 2  Q Q T T T T x, y,z T T x , y , z - Absorbed heat flux 2 2 2 vs c - Specific heat capacity c x y z c t x T T T T ρ - Density λ - Thermal conductivity vs - Constant speed of the moving heat sourceLatent heat of fusion 0 T TS , ΔHf - latent heat of fusion T TS H T cd T Lf f f TS T TL , Tl - liquidus temperature TL TS Ts - solidus temperature T TL 1 fs - solid fractionThe University of Alabama-Mechanical Engineering 6
  7. 7. 2. Heat transfer and heat source modeling• The cross sectional geometry of keyhole is usually idealized as a cone• The intensity distribution is considered as a conical source:  Horizontal – Gaussian distribution  Vertical – Decaying with increasing of penetration depth Fig. 5 Actual keyhole example and idealization [3]The University of Alabama-Mechanical Engineering 7
  8. 8. 2. Heat transfer and heat source modelingHeat source equation used in our study [4]: 2 2 8 UIb 8 x xs y ys 2 zS x, y, z f z 2 exp 2 with f z 1 E E h h Max. density = 306 W/mm2 U 6 0 kV Ib 2mA If E 2mm 1 h 2mm z 0 Fig. 6 Horizontal intensity distribution @ z = 0The University of Alabama-Mechanical Engineering 8
  9. 9. 3. Material properties & state changes Fig. 7 Temperature dependent material properties of Ti-6Al-4V [5]The University of Alabama-Mechanical Engineering 9
  10. 10. 3. Material properties & state changesEmissivity [6]: Thermal Conductivity [7]: AH H 1 AH S 2 k kr kc 1 S 2 3 .0 8 2 2 0.908 16 AH 2 H 2 kc l T 3 kr k b u lk x 1.908 2 1 1 1 3 .0 8 2 1 3 S εS – Emissivity of solid material εH – Emissivity of the hole among adjacent powder particles f – Fraction of total cavity surface AH – The area fraction of the surface that is occupied by the radiation emitting holes d – Mean pore diameter D – Particle size φ – Fractional porosity of the bed l – Mean photon free path between scattering events, the particle diameter in this study σ – Stefan-Boltzmann constant, T – Temperaturex = b/R – Ratio of neck radius to particle radius Λ – Normalized contact conductivity for the three packing structures. The University of Alabama-Mechanical Engineering 10
  11. 11. 3. Material properties & state changes Tab. 1 Truth table of material determination DTemp > 0 DTemp < 0 Temp < Tmelting 0 0 Temp > Tmelting 0 1 †0 – powder, 1 – solid Fig. 8 Flow chart of the user subroutineThe University of Alabama-Mechanical Engineering 11
  12. 12. 4. FE model configuration Tab. 2 Parameters in the simulation Parameters Values Solidus temperature, TS ( C) 1605 [8] Liquidus temperature, TL ( C) 1665 [8] Latent heat of fusion, Lf (kJ/Kg) 440 [8] Electron beam diameter, Φ (mm) 0.2, 0.4, 0.7, 1.0 Absorption efficiency, η 0.9 [2] Scan speed, v (mm/sec) 400 [2] Acceleration voltage, U (kV) 60 [2] Beam current, Ib (mA) 0.002 [2] Powder layer thickness, t-layer (mm) 0.1 [2] Porosity, φ 0, 0.3, 0.45,0.6 Beam penetration depth, dP (mm) 0.1[2] Fig. 9 New FE model configuration Preheat temperature, Tpreheat ( C) 760 [2]The University of Alabama-Mechanical Engineering 12
  13. 13. 5. Model validation Fig. 10 Model geometry, ICs and BCs [9] Fig. 11 Simulation results comparison with Wang et al [9]: a) Temperature contour; b) Temperature distribution along beam center scan passThe University of Alabama-Mechanical Engineering 13
  14. 14. 6. Simulation results Fig. 12 Temperature fields and molten pool geometries of solid and powder top layerThe University of Alabama-Mechanical Engineering 14
  15. 15. 6. Simulation resultsFig. 13 Temperature fields and molten pool Fig. 14 Temperature histories and heating or coolinggeometries of powder bed of various levels of porosity rates of center point for various levels of porosityThe University of Alabama-Mechanical Engineering 15
  16. 16. 6. Simulation results Fig. 15 Temperature fields and molten pool geometries of various beam sizesThe University of Alabama-Mechanical Engineering 16
  17. 17. 6. Simulation results Tab. 3 The simulated conditions and molten pool sizes Φ (mm) Material Length (µm) Width (µm) Depth (µm) Solid 750 300 100 φ = 30% 850 400 123 0.4 φ = 45% 800 400 127 φ = 60% 750 400 134 0.2 - - 130 0.7 φ = 30% - - 80 1.0 - - 68The University of Alabama-Mechanical Engineering 17
  18. 18. 7. Conclusions• Higher molten pool temperature is caused by to the high thermal resistance of powder materials. The higher the porosity is, the higher molten pool temperature will be and molten pool becomes deeper but shorter. The width of molten pool has less correlation with porosity.• A longer, wider and deeper melt pool with the powder top layer applied.• Heat is generally trapped in the scanned region even if powder materials are changed to solid after solidification,• Cooling rate increases drastically due to greater temperature gradients around the melt pool, even the thermal conductivity is low.• A larger electron beam diameter → shallower molten pool, less the temperature gradients, and a lower cooling rate. For the tested electron beam power level, the beam size around 0.4 mm could be an adequate choice.The University of Alabama-Mechanical Engineering 18
  19. 19. 8. Future work Fig. 17 Contour melting Fig. 18 Hatch meltingFig. 16 IR camera – MCS640 from Mikron Fig. 20 Measurement setup of building a 1 in3 cube Fig. 21 Comparison of measurement and simulation for Hatch meltingThe University of Alabama-Mechanical Engineering 19
  20. 20. 8. Future work Fig. 22 Measured preheating Fig. 23 Simulated preheatingThe University of Alabama-Mechanical Engineering 20
  21. 21. 8. Future work• Thermal process of manufacturing a part with overhang structure (i.e. two kinds of substrate under a unique scan, both solid and powder substrate)• Effects of the solid/powder interface in substrate on thermal process• Thermo-mechanical analysis Fig. 24 Molten pool geometries of solid substrate part and powder substrate partThe University of Alabama-Mechanical Engineering 21
  22. 22. AcknowledgementSponsor: NASA, No. NNX11AM11ACollaborator: Marshall Space Flight Center (Huntsville, AL), Advanced Manufacturing Team. The University of Alabama-Mechanical Engineering 22
  23. 23. Q&A Thank you! Any Question?The University of Alabama-Mechanical Engineering 23
  24. 24. Reference[1] Available from: http://www.arcam.com/.[2] Zaeh, M. F., and Lutzmann, S., 2010, "Modelling and simulation of electron beam melting," Production Engeering. Research and Development, 4, pp. 15-23.[3] Lampa, C., Kaplan, A. F. H., Powell, J., and Magnusson, C., 1997, "An analytical thermodynamic model of laser welding," Journal of Physics D: Applied Physics, 30(9), p. 1293.[4] Rouquette, S., Guo, J., and Le Masson, P., 2007, "Estimation of the parameters of a Gaussian heat source by the Levenberg-Marquardt method: Application to the electron beam welding," International Journal of Thermal Sciences, 46(2), pp. 128-138.[5] Yang, J., Sun, S., Brandt, M., and Yan, W., 2010, "Experimental investigation and 3D finite element prediction of the heat affected zone during laser assisted machining of Ti6Al4V alloy," Journal of Materials Processing Technology, 210(15), pp. 2215-2222.[6] Sih, S. S., and Barlow, J. W., 2004, "The prediction of the emissivity and thermal conductivity of powder beds," Particulate Science and Technology, 22, pp. 291-304.[7] Kolossov, S., Boillat, E., Glardon, R., Fischer, P., and Locher, M., 2004, "3D FE simulation for temperature evolution in the selective laser sintering process," International Journal of Machine Tools and Manufacture, 44(2-3), pp. 117-123.[8] Boyer, R., Welsch, G., and Collings, E. W., 1998, "Materials Properties Handbook: Titanium Alloys," ASM InternationalMaterials Park, OH, USA, pp. 483-636.[9] Wang, L., Felicelli, S., Gooroochurn, Y., Wang, P. T., and Horstemeyer, M. F., 2008, "Optimization of the LENS process for steady molten pool size," Materials Science & Engineering A (Structural Materials: Properties, Microstructure and Processing), 474, pp. 148-156.[10] Hofmeister, W., Wert, M., Smugeresky, J., Philliber, J. A., Griffith, M., and Ensz, M. T., 1999, "Invesitigation of solidification in the Laser Engineered Net Shaping (LENS) process," JOM, 51(7). The University of Alabama-Mechanical Engineering 24
  25. 25. Appendix IThe University of Alabama-Mechanical Engineering 25
  26. 26. Appendix II Other selected conditions comparisonThe University of Alabama-Mechanical Engineering 26

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