A Rate- and Temperature-Dependent Thermomechanical Internal State Variable Model of the Directed Energy Deposition Process
Source abstract
Abstract
Residual stress and distortion in additively manufactured parts contribute to build failures and reduced fatigue life, which hinders process qualification and part certification in industry. Predictive models can be used to better understand thermally induced residual stresses and distortion. This study investigated the influence of two mechanical models on simulated residual stress and distortion for the directed energy deposition additive manufacturing process by comparing the thermomechanical effects of two different scanning strategies on a Ti-6Al-4V thin wall. The Evolving Microstructural Model of Inelasticity (EMMI) and an elastic–perfectly plastic (EPP) model were chosen due to their inherent differences and use in manufacturing simulations in the literature. EMMI is a physically based strain-rate- and temperature-dependent dislocation mechanics-based internal state variable plasticity model while the EPP model is a phenomenological temperature-dependent yield strength model that does not account for hardening or thermal softening. Simulation results show significant differences in the predicted stress evolution and the as-built stress contours despite similar maximum von Mises stress. In particular, EMMI demonstrated more realistic stress evolution from cyclic thermal history and large thermal gradients while EPP showed discontinuities and larger oscillations in the evolution of multiple components in the stress tensor.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Additive Manufacturing Materials and Processes · Titanium Alloys Microstructure and Properties · Welding Techniques and Residual Stresses
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (42)
Show source-provided references
1. N. Shamsaei, A. Yadollahi, L. Bian, and S.M. Thompson, An overview of Direct Laser Deposition for Additive Manufacturing; Part II: Mechanical Behavior, Process Parameter Optimization and Control, Addit. Manuf., 2015 https://doi.org/10.1016/j.addma.2015.07.00210.1016/j.addma.2015.07.002 ↗
2. C. Qiu, G.A. Ravi, C. Dance, A. Ranson, S. Dilworth, and M.M. Attallah, Fabrication of Large Ti-6Al-4V Structures by Direct Laser Deposition, J. Alloys Compd., 2015, 629, p 351–361. https://doi.org/10.1016/j.jallcom.2014.12.23410.1016/j.jallcom.2014.12.234 ↗
3. A. Yadollahi, M.J. Mahtabi, A. Khalili, H.R. Doude, and J.C. Newman, Fatigue Life Prediction of Additively Manufactured Material: Effects of Surface Roughness, Defect Size, and Shape, Fatigue Fract. Eng. Mater. Struct., 2018, 41, p 1602–1614. https://doi.org/10.1111/ffe.1279910.1111/ffe.12799 ↗
4. B.A. Szost, S. Terzi, F. Martina, D. Boisselier, A. Prytuliak, T. Pirling, M. Hofmann, and D.J. Jarvis, A Comparative Study of Additive Manufacturing Techniques: Residual Stress and Microstructural Analysis of CLAD and WAAM Printed Ti-6Al-4V Components, Mater. Des., 2016, 89, p 559–567. https://doi.org/10.1016/j.matdes.2015.09.11510.1016/j.matdes.2015.09.115 ↗
5. P.J. Withers, Residual Stress and its Role in Failure, Rep. Prog. Phys., 2007, 70, p 2211–2264. https://doi.org/10.1088/0034-4885/70/12/R0410.1088/0034-4885/70/12/R04 ↗
6. K. Carpenter and A. Tabei, On Residual Stress Development, Prevention, and Compensation in Metal Additive Manufacturing, Materials (Basel), 2020 https://doi.org/10.3390/ma1302025510.3390/ma13020255 ↗
7. M. Megahed, H.-W. Mindt, N. N’Dri, H. Duan, and O. Desmaison, Metal Additive-Manufacturing Process and Residual Stress Modeling, Integr. Mater. Manuf. Innov., 2016 https://doi.org/10.1186/s40192-016-0047-210.1186/s40192-016-0047-2 ↗
8. G. Vastola, G. Zhang, Q.X. Pei, and Y.W. Zhang, Controlling of Residual Stress in Additive Manufacturing of Ti6Al4V by Finite Element Modeling, Addit. Manuf., 2016, 12, p 231–239. https://doi.org/10.1016/j.addma.2016.05.01010.1016/j.addma.2016.05.010 ↗
9. W.E. Frazier, Metal Additive Manufacturing: A Review, J. Mater. Eng. Perform., 2014, 23, p 1917–1928. https://doi.org/10.1007/s11665-014-0958-z10.1007/s11665-014-0958-z ↗
10. A.S. Wu, D.W. Brown, M. Kumar, G.F. Gallegos, and W.E. King, An Experimental Investigation into Additive Manufacturing-Induced Residual Stresses in 316L Stainless Steel, Metall. Mater. Trans. A Phys. Metall. Mater. Sci., 2014, 45, p 6260–6270. https://doi.org/10.1007/s11661-014-2549-x10.1007/s11661-014-2549-x ↗
11. N. Shamsaei, A. Yadollahi, L. Bian, and S.M. Thompson, An Overview of Direct Laser Deposition for Additive Manufacturing; Part II: Mechanical Behavior, Process Parameter Optimization and Control, Addit. Manuf., 2015, 8, p 12–35. https://doi.org/10.1016/j.addma.2015.07.00210.1016/j.addma.2015.07.002 ↗
12. P. Mercelis and J.P. Kruth, Residual Stresses in Selective Laser Sintering and Selective Laser Melting, Rapid Prototyp. J., 2006, 12, p 254–265. https://doi.org/10.1108/1355254061070701310.1108/13552540610707013 ↗
13. M.J. Matthews, G. Guss, S.A. Khairallah, A.M. Rubenchik, P.J. Depond, and W.E. King, Denudation of Metal Powder Layers in Laser Powder Bed Fusion Processes, Acta Mater., 2016, 114, p 33–42. https://doi.org/10.1016/j.actamat.2016.05.01710.1016/j.actamat.2016.05.017 ↗
14. C. Teng, D. Pal, H. Gong, K. Zeng, K. Briggs, N. Patil, and B. Stucker, A Review of Defect Modeling in Laser Material Processing, Addit. Manuf., 2017, 14, p 137–147. https://doi.org/10.1016/j.addma.2016.10.00910.1016/j.addma.2016.10.009 ↗
15. M. Masoomi, J.W. Pegues, S.M. Thompson, and N. Shamsaei, A Numerical and Experimental Investigation of Convective Heat Transfer during Laser-Powder Bed Fusion, Addit. Manuf., 2018, 22, p 729–745. https://doi.org/10.1016/j.addma.2018.06.02110.1016/j.addma.2018.06.021 ↗
16. S.M. Hashemi, S. Parvizi, H. Baghbanijavid, T. Alvin, L. Tan, M. Nematollahi, A. Ramazani, and N.X. Fang, Computational Modelling of Process – Structure – Property – Performance Relationships in Metal Additive Manufacturing: A Review, Int. Mater. Rev., 2021 https://doi.org/10.1080/09506608.2020.186888910.1080/09506608.2020.1868889 ↗
17. M.M. Francois, A. Sun, W.E. King, N.J. Henson, D. Tourret, C.A. Bronkhorst, N.N. Carlson, C.K. Newman, T. Haut, J. Bakosi, J.W. Gibbs, V. Livescu, S.A. Vander Wiel, A.J. Clarke, M.W. Schraad, T. Blacker, H. Lim, T. Rodgers, S. Owen, F. Abdeljawad, J. Madison, A.T. Anderson, J. Fattebert, R.M. Ferencz, N.E. Hodge, S.A. Khairallah, and O. Walton, Modeling of Additive Manufacturing Processes for Metals: Challenges and Opportunities, Curr. Opin. Solid State Mater. Sci., 2017, 21, p 1–9. https://doi.org/10.1016/j.cossms.2016.12.00110.1016/j.cossms.2016.12.001 ↗
18. X. Liang, L. Cheng, Q. Chen, Q. Yang, and A.C. To, A Modified Method for Estimating Inherent Strains From Detailed Process Simulation for Fast Residual Distortion Prediction of Single-Walled Structures Fabricated by Directed Energy Deposition, Addit. Manuf., 2018, 23, p 471–486. https://doi.org/10.1016/j.addma.2018.08.02910.1016/j.addma.2018.08.029 ↗
19. E.R. Denlinger, Thermo-Mechanical Modeling of Large Electron Beam Builds, 1st ed. Elsevier Inc., Amsterdam, 2017. https://doi.org/10.1016/B978-0-12-811820-7.00012-410.1016/B978-0-12-811820-7.00012-4 ↗
20. P. Promoppatum and A.D. Rollett, Influence of Material Constitutive Models on Thermomechanical Behaviors in the Laser Powder Bed Fusion of Ti-6Al-4V, Addit. Manuf., 2020 https://doi.org/10.1016/j.addma.2020.10168010.1016/j.addma.2020.101680 ↗
21. R.K. Ganeriwala, M. Strantza, W.E. King, B. Clausen, T.Q. Phan, L.E. Levine, D.W. Brown, and N.E. Hodge, Evaluation of a Thermomechanical Model for Prediction of Residual Stress during Laser Powder Bed Fusion of Ti-6Al-4V, Addit. Manuf., 2019, 27, p 489–502. https://doi.org/10.1016/j.addma.2019.03.03410.1016/j.addma.2019.03.034 ↗
22. A. Nycz, Y. Lee, M. Noakes, D. Ankit, C. Masuo, S. Simunovic, J. Bunn, L. Love, V. Oancea, A. Payzant, and C.M. Fancher, Effective Residual Stress Prediction Validated with Neutron Diffraction Method for Metal Large-Scale Additive Manufacturing, Mater. Des., 2021, 205, p 109751. https://doi.org/10.1016/j.matdes.2021.10975110.1016/j.matdes.2021.109751 ↗
23. P. Promoppatum and A.D. Rollett, Physics-Based and Phenomenological Plasticity Models for Thermomechanical Simulation in Laser Powder Bed Fusion Additive Manufacturing: A Comprehensive Numerical Comparison, Mater. Des., 2021, 204, p 109658. https://doi.org/10.1016/j.matdes.2021.10965810.1016/j.matdes.2021.109658 ↗
24. K.L. Johnson, T.M. Rodgers, O.D. Underwood, J.D. Madison, K.R. Ford, S.R. Whetten, D.J. Dagel, and J.E. Bishop, Simulation and Experimental Comparison of the Thermo-Mechanical History and 3D Microstructure Evolution of 304L Stainless Steel Tubes Manufactured Using LENS, Comput. Mech., 2018, 61, p 559–574. https://doi.org/10.1007/s00466-017-1516-y10.1007/s00466-017-1516-y ↗
25. X. Lu, X. Lin, M. Chiumenti, M. Cervera, Y. Hu, X. Ji, L. Ma, H. Yang, and W. Huang, Residual Stress and Distortion of Rectangular and S-Shaped Ti-6Al-4V Parts by Directed Energy Deposition: Modelling and Experimental Calibration, Addit. Manuf., 2019, 26, p 166–179. https://doi.org/10.1016/j.addma.2019.02.00110.1016/j.addma.2019.02.001 ↗
26. E.R. Denlinger and P. Michaleris, Effect of Stress Relaxation on Distortion in Additive Manufacturing Process Modeling, Addit. Manuf., 2016 https://doi.org/10.1016/j.addma.2016.06.01110.1016/j.addma.2016.06.011 ↗
27. J. Goldak and M. Akhlagi, Computational Welding Mechanics, Springer, Berlin, 2005.
28. D.J. Bammann, An Internal Variable Model of Viscoplasticity, Int. J. Eng. Sci., 1984, 22, p 1041–1053.10.1016/0020-7225(84)90105-8 ↗
29. M.E. Stender, L.L. Beghini, J.D. Sugar, M.G. Veilleux, S.R. Subia, T.R. Smith, C.W.S. Marchi, A.A. Brown, and D.J. Dagel, A Thermal-Mechanical Finite Element Workflow for Directed Energy Deposition Additive Manufacturing Process Modeling, Addit. Manuf., 2018, 21, p 556–566. https://doi.org/10.1016/j.addma.2018.04.01210.1016/j.addma.2018.04.012 ↗
30. B. Babu, A. Lundbäck, and L.-E. Lindgren, Simulation of Ti-6Al-4V Additive Manufacturing Using Coupled Physically Based Flow Stress and Metallurgical Model, Materials (Basel)., 2019, 12, p 3844. https://doi.org/10.3390/ma1223384410.3390/ma12233844 ↗
31. M.F. Horstemeyer and D.J. Bammann, Historical Review of Internal State Variable Theory for Inelasticity, Int. J. Plast., 2010, 26, p 1310–1334. https://doi.org/10.1016/j.ijplas.2010.06.00510.1016/j.ijplas.2010.06.005 ↗
32. E.B. Marin, D.J. Bammann, R.A. Regueiro, and G.C. Johnson, On the Formulation, Parameter Identification and Numerical Integration of the EMMI Model: Plasticity and Isotropic Damage (2006). https://www.osti.gov/biblio/883488
33. J.J. Dike, J.A. Brooks, D.J. Bammann, M. Li, J.S. Krafcik, and N.Y.C. Yang, Predicting Weld Solidification Cracking Using Damage Mechanics -LDRD Summary Report (1997)10.2172/495695 ↗
34. J.A. Goldak and M. Akhlagi, Computational Welding Mechanics, Springer US, New York, 2005.
35. M.J. Dantin, W.M. Furr, and M.W. Priddy, Toward a Physical Basis for a Predictive Finite Element Thermal Model of the LENSTM Process Leveraging Dual-Wavelength Pyrometer Datasets, Integr. Mater. Manuf. Innov., 2022, 11, p 407–417. https://doi.org/10.1007/s40192-022-00271-610.1007/s40192-022-00271-6 ↗
36. B. Babu and L.E. Lindgren, Dislocation Density Based Model for Plastic Deformation and Globularization of Ti-6Al-4V, Int. J. Plast., 2013, 50, p 94–108. https://doi.org/10.1016/j.ijplas.2013.04.00310.1016/j.ijplas.2013.04.003 ↗
37. E.R. Denlinger, J.C. Heigel, and P. Michaleris, Residual Stress and Distortion Modeling of Electron Beam Direct Manufacturing Ti-6Al-4V, Proc. Inst. Mech. Eng. Part B J. Eng. Manuf., 2015, 229, p 1803–1813. https://doi.org/10.1177/095440541453949410.1177/0954405414539494 ↗
38. C. Li, Z.Y. Liu, X.Y. Fang, and Y.B. Guo, Residual Stress in Metal Additive Manufacturing, Procedia CIRP, 2018, 71, p 348–353. https://doi.org/10.1016/j.procir.2018.05.03910.1016/j.procir.2018.05.039 ↗
39. M.J. Dantin, Thermomechanical Modeling Predictions of the Directed Energy Deposition Process Using a Dislocation Mechanics Based Internal State Variable Model, Mississippi State University (2021)
40. X. Xu and P. Nash, Sintering Mechanisms of Armstrong Prealloyed Ti-6Al-4V Powders, Mater. Sci. Eng. A, 2014, 607, p 409–416. https://doi.org/10.1016/j.msea.2014.03.04510.1016/j.msea.2014.03.045 ↗
41. E. Alabort, P. Kontis, D. Barba, K. Dragnevski, and R.C. Reed, On the Mechanisms of Superplasticity in Ti-6Al-4V, Acta Mater., 2016, 105, p 449–463. https://doi.org/10.1016/j.actamat.2015.12.00310.1016/j.actamat.2015.12.003 ↗
42. K.C. Mills, Recommended Values of Thermophysical Properties for Selected Commercial Alloys, Woodhead Publishing Ltd., Cambridge, 2002.10.1533/9781845690144 ↗