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Review Article

A review of constitutive models used in macroscale finite element analysis of additive manufacturing and post-processing of additively manufactured components

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Article: e2356079 | Received 28 Dec 2023, Accepted 07 May 2024, Published online: 10 Jun 2024

References

  • Roth CC, Tancogne-Dejean T, Mohr D. Plasticity and fracture of cast and SLM AlSi10Mg: high-throughput testing and modeling. Addit Manuf. 2021. doi:10.1016/j.addma.2021.101998
  • Tofail SA, Koumoulos EP, Bandyopadhyay A, et al. Additive manufacturing: scientific and technological challenges, market uptake and opportunities. Mater Today. 2018. doi:10.1016/j.mattod.2017.07.001
  • Pragana J, Sampaio R, Bragança I, et al. Hybrid metal additive manufacturing: a state–of–the-art review. Adv Ind Manuf Eng. 2021. doi:10.1016/j.aime.2021.100032
  • Li X, Roth CC, Tancogne-Dejean T, et al. Rate- and temperature-dependent plasticity of additively manufactured stainless steel 316L: characterization, modeling and application to crushing of shell-lattices. Int J Impact Eng. 2020. doi:10.1016/j.ijimpeng.2020.103671
  • Fan Y, Cheng P, Yao YL, et al. Effect of phase transformations on laser forming of Ti–6Al–4V alloy. J Appl Phys. 2005. doi:10.1063/1.1944202
  • Zhang K, Dong W, Lu S. Transformation plasticity of AF1410 steel and its influences on the welding residual stress and distortion: experimental and numerical study. Mater Sci Eng A. 2021. doi:10.1016/j.msea.2021.141628
  • Bai L, Jiang K, Gao L. The influence and mechanism of residual stress on the corrosion behavior of welded structures. Mat Res. 2018. doi:10.1590/1980-5373-mr-2018-01660
  • Yadroitsev I. Selective laser melting: direct manufacturing of 3D-objects by selective laser melting of metal powders. Saarbrucken: Lambert Academic Publishing; 2009.
  • Collins PC, Brice DA, Samimi P, et al. Microstructural control of additively manufactured metallic materials. Annu Rev Mater Res. 2016. doi:10.1146/annurev-matsci-070115-031816
  • Bariani PF, Dal Negro T, Bruschi S. Testing and modelling of material response to deformation in bulk metal forming. CIRP Ann. 2004. doi:10.1016/S0007-8506(07)60030-4
  • National Research Council (U.S.). Integrated computational materials engineering: A transformational discipline for improved competitiveness and national security. Washington: National Academies Press; 2008.
  • Schmitz GJ, Prahl U. ICMEg – the integrated computational materials engineering expert group – a new European coordination action. Integr Mater Manuf Innov. 2014. doi:10.1186/2193-9772-3-2
  • Bonifaz EA. In: Rodrigues JMF, Cardoso PJS, Monteiro J, Lam R, Krzhizhanovskaya VV, Lees MH, Dongarra JJ, Sloot PM (eds) Computational Science – ICCS 2019. Springer International Publishing, Cham, pp 647–659; 2019.
  • Francois MM, Sun A, King WE, et al. Modeling of additive manufacturing processes for metals: challenges and opportunities. Curr Opin Solid State Mater Sci. 2017. doi:10.1016/j.cossms.2016.12.001
  • Gatsos T, Elsayed KA, Zhai Y, et al. Review on computational modeling of process–microstructure–property relationships in metal additive manufacturing. JOM. 2020. doi:10.1007/s11837-019-03913-x
  • Afrasiabi M, Bambach M. Modelling and simulation of metal additive manufacturing processes with particle methods: A review. Virtual Phys Prototyp. 2023. doi:10.1080/17452759.2023.2274494
  • Hoyt J. Atomistic and continuum modeling of dendritic solidification. Mater Sci Eng: R: Rep. 2003. doi:10.1016/S0927-796X(03)00036-6
  • Moelans N, Blanpain B, Wollants P. An introduction to phase-field modeling of microstructure evolution. Calphad. 2008. doi:10.1016/j.calphad.2007.11.003
  • Kattner UR. The Calphad method and its role in material and process development. Tecnologia em metalurgia, materiais e mineracao. 2016. doi:10.4322/2176-1523.1059
  • Wei HL, Mukherjee T, Zhang W, et al. Mechanistic models for additive manufacturing of metallic components. Prog Mater Sci. 2021. doi:10.1016/j.pmatsci.2020.100703
  • Panwisawas C, Qiu C, Anderson MJ, et al. Mesoscale modelling of selective laser melting: thermal fluid dynamics and microstructural evolution. Comput Mater Sci. 2017. doi:10.1016/j.commatsci.2016.10.011
  • Afazov S, Roberts A, Wright L, et al. Metal powder bed fusion process chains: an overview of modelling techniques. Prog Addit Manuf. 2022. doi:10.1007/s40964-021-00230-1
  • Chen F, Yan W. High-fidelity modelling of thermal stress for additive manufacturing by linking thermal-fluid and mechanical models. Mater Des. 2020. doi:10.1016/j.matdes.2020.109185
  • Mathews R, Nagaraja KM, Zhang R, et al. Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing. Int J Mech Sci. 2023. doi:10.1016/j.ijmecsci.2023.108424
  • Afrasiabi M, Lüthi C, Bambach M, et al. Multi-Resolution SPH simulation of a laser powder Bed fusion additive manufacturing process. Appl Sci. 2021. doi:10.3390/app11072962
  • Lüthi C, Afrasiabi M, Bambach M. An adaptive smoothed particle hydrodynamics (SPH) scheme for efficient melt pool simulations in additive manufacturing. Comput Math Appl. 2023. doi:10.1016/j.camwa.2023.03.003
  • Cattenone A, Morganti S, Auricchio F. Basis of the Lattice Boltzmann method for additive manufacturing. Arch Computat Methods Eng. 2020. doi:10.1007/s11831-019-09347-7
  • Bayat M, Dong W, Thorborg J, et al. A review of multi-scale and multi-physics simulations of metal additive manufacturing processes with focus on modeling strategies. Addit Manuf. 2021. doi:10.1016/j.addma.2021.102278
  • Wang J, Wang Y, Shi J. On efficiency and effectiveness of finite volume method for thermal analysis of selective laser melting. EC. 2020. doi:10.1108/EC-03-2019-0106
  • Sampaio R, Pragana J, Bragança I, et al. Modelling of wire-arc additive manufacturing – A review. Adv Ind Manuf Eng. 2023. doi:10.1016/j.aime.2023.100121
  • Rosenthal D. The Theory of Moving Sources of Heat and Its Application to Metal Treatments; 1946.
  • Goldak J, Chakravarti A, Bibby M. A new finite element model for welding heat sources. MTB. 1984. doi:10.1007/BF02667333
  • Tan P, Shen F, Li B, et al. A thermo-metallurgical-mechanical model for selective laser melting of Ti6Al4V. Mater Des. 2019. doi:10.1016/j.matdes.2019.107642
  • Behúlová M, Babalová E. Heat source models for numerical simulation of laser welding processes – a short review. J Phys: Conf Ser. 2024. doi:10.1088/1742-6596/2712/1/012018
  • Kik T. Heat source models in numerical simulations of laser welding. Materials (Basel, Switzerland). 2020. doi:10.3390/ma13112653
  • Chiumenti M, Cervera M, Salmi A, et al. Finite element modeling of multi-pass welding and shaped metal deposition processes. Comput Methods Appl Mech Eng. 2010. doi:10.1016/j.cma.2010.02.018
  • Buhl J, Israr R, Bambach M. Modeling and convergence analysis of directed energy deposition simulations with hybrid implicit / explicit and implicit solutions. J Mach Eng. 2019. doi:10.5604/01.3001.0013.4086
  • Blumm J, Henderson J. Measurement of the volumetric expansion and bulk density of metals in the solid and molten regions. High Temp-High Press. 2000. doi:10.1068/htwu520
  • Zhang K, Dong W, Lu S. Residual stress and distortion in thick-plate weld joint of AF1410 steel: finite element simulations and experimental studies. Mater Res Express. 2022. doi:10.1088/2053-1591/ac4c5d
  • Perić M, Tonković Z, Garašić I, et al. An engineering approach for a T-joint fillet welding simulation using simplified material properties. Ocean Eng. 2016. doi:10.1016/j.oceaneng.2016.10.006
  • Park S-C, Bang H-S, Seong W-J. Effects of material properties on angular distortion in wire arc additive manufacturing: experimental and computational analyses. Materials (Basel, Switzerland). 2020. doi:10.3390/ma13061399
  • Babu B, Lundbäck A, Lindgren L-E. Simulation of Ti-6Al-4V additive manufacturing using coupled physically based flow stress and metallurgical model. Materials (Basel, Switzerland). 2019. doi:10.3390/ma12233844
  • Caron J, Heinze C, Schwenk C, et al. Effect of continuous cooling transformation variants on numerical calculation of welding induced residual stresses. Weld J. 2010;89(7):151–160.
  • Zhu XK, Chao YJ. Effects of temperature-dependent material properties on welding simulation. Comput Struct. 2002. doi:10.1016/S0045-7949(02)00040-8
  • Sun L, Ren X, He J, et al. Numerical investigation of a novel pattern for reducing residual stress in metal additive manufacturing. J Mater Sci Technol. 2021. doi:10.1016/j.jmst.2020.05.080
  • Zhao H, Zhang G, Yin Z, et al. Three-dimensional finite element analysis of thermal stress in single-pass multi-layer weld-based rapid prototyping. J Mater Process Technol. 2012. doi:10.1016/j.jmatprotec.2011.09.012
  • Draxler J, Edberg J, Andersson J, et al. Modeling and simulation of weld solidification cracking part III: simulation of solidification cracking in Varestraint tests of alloy 718. Weld World. 2019. doi:10.1007/s40194-019-00784-3
  • Nijhuis B, Geijselaers H, van den Boogaard AH. Efficient thermal simulation of large-scale metal additive manufacturing using hot element addition. Comput Struct. 2021. doi:10.1016/j.compstruc.2020.106463
  • Nycz A, Lee Y, Noakes M, et al. Effective residual stress prediction validated with neutron diffraction method for metal large-scale additive manufacturing. Mater Des. 2021. doi:10.1016/j.matdes.2021.109751
  • Ding D, Zhang S, Lu Q, et al. The well-distributed volumetric heat source model for numerical simulation of wire arc additive manufacturing process. Mater Today Commun. 2021. doi:10.1016/j.mtcomm.2021.102430
  • Farias RM, Teixeira P, Vilarinho LO. An efficient computational approach for heat source optimization in numerical simulations of arc welding processes. J Constr Steel Res. 2021. doi:10.1016/j.jcsr.2020.106382
  • Tran H-S, Tchuindjang JT, Paydas H, et al. 3D thermal finite element analysis of laser cladding processed Ti-6Al-4V part with microstructural correlations. Mater Des. 2017. doi:10.1016/j.matdes.2017.04.092
  • Outinen J, Mäkeläinen P. Mechanical properties of structural steel at elevated temperatures and after cooling down. Fire Mater. 2004. doi:10.1002/fam.849
  • Maekawa A, Kawahara A, Serizawa H, et al. Fast three-dimensional multipass welding simulation using an iterative substructure method. J Mater Process Technol. 2015. doi:10.1016/j.jmatprotec.2014.08.004
  • Suman S, Biswas P. Thermo-mechanical study of single and multi-pass welding of CSEF steel for residual stresses and deformations considering solid state phase transformation. Mater Today Proc. 2020. doi:10.1016/j.matpr.2019.12.299
  • Zhang X, Li W, Ma J, et al. A novel temperature dependent yield strength model for metals considering precipitation strengthening and strain rate. Comput Mater Sci. 2017. doi:10.1016/j.commatsci.2016.12.005
  • Ali MH, Han YS. Effect of phase transformations on scanning strategy in WAAM fabrication. Materials (Basel, Switzerland). 2021. doi:10.3390/ma14247871
  • Montevecchi F, Venturini G, Grossi N, et al. Finite element mesh coarsening for effective distortion prediction in wire arc additive manufacturing. Addit Manuf. 2017. doi:10.1016/j.addma.2017.10.010
  • Huang H, Ma N, Chen J, et al. Toward large-scale simulation of residual stress and distortion in wire and arc additive manufacturing. Addit Manuf. 2020. doi:10.1016/j.addma.2020.101248
  • Manurung YHP, Prajadhiana KP, Adenan MS, et al. Analysis of material property models on WAAM distortion using nonlinear numerical computation and experimental verification with P-GMAW. ArchivCivMechEng. 2021. doi:10.1007/s43452-021-00189-4
  • Deng D, Zhang C, Pu X, et al. Influence of material model on prediction accuracy of welding residual stress in an austenitic stainless steel multi-pass butt-welded joint. J Mater Eng Perform. 2017. doi:10.1007/s11665-017-2626-6
  • Malmelöv A, Lundbäck A, Lindgren L-E. History reduction by lumping for time-efficient simulation of additive manufacturing. Metals. 2020. doi:10.3390/met10010058
  • Chen W, Xu L, Han Y, et al. Control of residual stress in metal additive manufacturing by low-temperature solid-state phase transformation: An experimental and numerical study. Addit Manuf. 2021. doi:10.1016/j.addma.2021.102016
  • Johnson GR, Cook WH. A constitutive model and data for materials subjected to large strains,: high strain rates, and high temperatures. Proc. 7th Inf. Sympo. Ballistics:541–547; 1983.
  • Gkatzogiannis S. Strain rate dependency of simulated welding residual stresses. J Mater Eng Perform. 2018. doi:10.1007/s11665-018-3418-3
  • Perzyna P. In: Advances in Applied Mechanics Volume 9. Elsevier, pp 243–377; 1966.
  • Chen F, Liu J, Ou H, et al. Flow characteristics and intrinsic workability of IN718 superalloy. Mater Sci Eng A. 2015. doi:10.1016/j.msea.2015.06.093
  • Antonsson T, Fredriksson H. The effect of cooling rate on the solidification of Inconel 718. Metall and Materi Trans B Volume 36B, February 2005—85; 2005.
  • High-temperature high-strength nickel-base alloys: A practical guide to the use of nickel-containing alloys. Number. 393
  • Benson M, Raynaud P, Wallace J. Weld Residual Stress Finite Element Analysis Validation: Part II-Proposed Validation Procedure”. US.NRC, NUREG-2228; 2020.
  • MRP E. Materials reliability program: welding residual stress dissimilar metal butt-weld finite element modeling handbook (MRP-317, revision 1). Electric Power Research Institute (EPRI); 2015.
  • Seshacharyulu T, Medeiros SC, Frazier WG, et al. Microstructural mechanisms during hot working of commercial grade Ti–6Al–4V with lamellar starting structure. Mater Sci Eng A. 2002. doi:10.1016/S0921-5093(01)01448-4
  • Rangaswamy P, Choo H, Prime MB, et al. High Temperature Stress Assessment in SCS-6/Ti-6A1-4V Composite Using Neutron Diffraction and Finite Element Modeling; 2000.
  • Venkatkumar D, Ravindran D. Effect of boundary conditions on residual stresses and distortion in 316 stainless steel butt welded plate. High Temp Mater Processes. 2019. doi:10.1515/htmp-2019-0048
  • Li Y, Zhou K, Tan P, et al. Modeling temperature and residual stress fields in selective laser melting. Int J Mech Sci. 2018. doi:10.1016/j.ijmecsci.2017.12.001
  • Denlinger ER. In: thermo-mechanical modeling of additive manufacturing. Elsevier; 2018. pp 183–195.
  • Wu X, Zhu W, He Y. Deformation prediction and experimental study of 316L stainless steel thin-walled parts processed by additive-subtractive hybrid manufacturing. Materials (Basel, Switzerland). 2021. doi:10.3390/ma14195582
  • Vishwanath MM, Lakshamanaswamy N, Ramesh GK. Numerical simulation of heat transfer behavior of dissimilar AA5052-AA6061 plates in fiction stir welding: An experimental validation. Strojnícky casopis – J Mech Eng. 2019. doi:10.2478/scjme-2019-0011
  • El-Sayed MM, Shash AY, Abd-Rabou M. Finite element modeling of aluminum alloy AA5083-O friction stir welding process. J Mater Process Technol. 2018. doi:10.1016/j.jmatprotec.2017.09.008
  • Sedighi M, Afshari D, Nazari F. Investigation of the effect of sheet thickness on residual stresses in resistance spot welding of aluminum sheets. Proc Inst Mech Eng, Part C: J Mech Eng Sci. 2018. doi:10.1177/0954406216685124
  • DebRoy T, Wei HL, Zuback JS, et al. Additive manufacturing of metallic components – Process, structure and properties. Prog Mater Sci. 2018. doi:10.1016/j.pmatsci.2017.10.001
  • Baykasoğlu C, Akyildiz O, Tunay M, et al. A process-microstructure finite element simulation framework for predicting phase transformations and microhardness for directed energy deposition of Ti6Al4V. Addit Manuf. 2020. doi:10.1016/j.addma.2020.101252
  • Zhang Q, Xie J, Gao Z, et al. A metallurgical phase transformation framework applied to SLM additive manufacturing processes. Mater Des. 2019. doi:10.1016/j.matdes.2019.107618
  • Zhang D, Sun S, Qiu D, et al. Metal alloys for fusion-based additive manufacturing. Adv Eng Mater. 2018. doi:10.1002/adem.201700952
  • Harrison PL, Farrar RA. Application of continuous cooling transformation diagrams for welding of steels. Int Mater Rev. 1989. doi:10.1179/imr.1989.34.1.35
  • Zhang K, Wang S, Liu W, et al. Characterization of stainless steel parts by laser metal deposition shaping. Mater Des. 2014. doi:10.1016/j.matdes.2013.09.006
  • Pegues JW, Shao S, Shamsaei N, et al. Fatigue of additive manufactured Ti-6Al-4V, Part I: the effects of powder feedstock, manufacturing, and post-process conditions on the resulting microstructure and defects. Int J Fatigue. 2020. doi:10.1016/j.ijfatigue.2019.105358
  • Lindgren L-E, Lundbäck A, Fisk M, et al. Simulation of additive manufacturing using coupled constitutive and microstructure models. Addit Manuf. 2016. doi:10.1016/j.addma.2016.05.005
  • Fiocchi J, Tuissi A, Biffi CA. Heat treatment of aluminium alloys produced by laser powder bed fusion: a review. Mater Des. 2021. doi:10.1016/j.matdes.2021.109651
  • Senthamarai Kannan C, Sai Sree Chandra S, Punith Krishnan G, et al. A review on additive manufacturing of AA2024 and AA6061 alloys using powder bed fusion. IOP Conf Ser: Mater Sci Eng. 2020. doi:10.1088/1757-899X/988/1/012002
  • Lu X, Li MV, Yang H. Simulation of precipitates evolution driven by non-isothermal cyclic thermal history during wire and arc additive manufacturing of IN718 superalloy. J Manuf Process. 2021. doi:10.1016/j.jmapro.2021.03.032
  • Gao Y, Zhang D, Cao M, et al. Effect of δ phase on high temperature mechanical performances of Inconel 718 fabricated with SLM process. Mater Sci Eng A. 2019. doi:10.1016/j.msea.2019.138327
  • Ahn J, He E, Chen L, et al. Prediction and measurement of residual stresses and distortions in fibre laser welded Ti-6Al-4V considering phase transformation. Mater Des. 2017. doi:10.1016/j.matdes.2016.11.078
  • Crespo A. In: Ahsan A (ed) Convection and Conduction Heat Transfer. InTech; 2011.
  • Celleri HM, Portela IV, Passarella DN. Comparison of metallurgical models during quenching using open source software. Asociación Argentina de Mecánica Computacional; 2014.
  • Leblond JB, Devaux J. A new kinetic model for anisothermal metallurgical transformations in steels including effect of austenite grain size. Acta Metall. 1984. doi:10.1016/0001-6160(84)90211-6
  • Deepu MJ, Phanikumar G. ICME framework for simulation of microstructure and property evolution during gas metal arc welding in DP980 steel. Integrating Materials and Manufacturing Innovation. 2020. doi:10.1007/s40192-020-00182-4
  • Jimenez X, Dong W, Paul S, et al. Residual stress modeling with phase transformation for wire arc additive manufacturing of B91 steel. JOM. 2020. doi:10.1007/s11837-020-04424-w
  • Murgau C, Lundbäck A, Åkerfeldt P, et al. Temperature and microstructure evolution in gas tungsten arc welding wire feed additive manufacturing of Ti-6Al-4V. Materials (Basel, Switzerland). 2019. doi:10.3390/ma12213534
  • Tchuindjang JT, Paydas H, Tran H-S, et al. A New concept for modeling phase transformations in Ti6Al4V alloy manufactured by directed energy deposition. Materials (Basel, Switzerland). 2021. doi:10.3390/ma14112985
  • Irwin J. In: thermo-mechanical modeling of additive manufacturing. Elsevier; 2018. pp 117–135.
  • Salsi E, Chiumenti M, Cervera M. Modeling of microstructure evolution of Ti6Al4V for additive manufacturing. Metals. 2018. doi:10.3390/met8080633
  • Vastola G, Zhang G, Pei QX, et al. Modeling the microstructure evolution during additive manufacturing of Ti6Al4V: A comparison between electron beam melting and selective laser melting. JOM. 2016. doi:10.1007/s11837-016-1890-5
  • Xie J, Oancea V, Hurtado J. Phase transformations in metals during additive manufacturing processes. NAFEMS World Congress 2017; 2017.
  • Costa L, Vilar R, Reti T, et al. Rapid tooling by laser powder deposition: process simulation using finite element analysis. Acta Mater. 2005. doi:10.1016/j.actamat.2005.05.003
  • Depradeux L, Robitaille C, Duval G, et al. Numerical simulation of Rapid Additive Forging (RAF) process. MATEC Web Conf. 2020. doi:10.1051/matecconf/202032103036
  • Crespo A, Vilar R. Finite element analysis of the rapid manufacturing of Ti–6Al–4V parts by laser powder deposition. Scr Mater. 2010. doi:10.1016/j.scriptamat.2010.03.036
  • Coret M, Combescure A. A mesomodel for the numerical simulation of the multiphasic behavior of materials under anisothermal loading (application to two low-carbon steels). Int J Mech Sci. 2002. doi:10.1016/S0020-7403(02)00053-X
  • Murgau CC, Pederson R, Lindgren LE. A model for Ti–6Al–4V microstructure evolution for arbitrary temperature changes. Modelling Simul Mater Sci Eng. 2012. doi:10.1088/0965-0393/20/5/055006
  • Klusemann B, Bambach M. In: Author(s), p 140012; 2018.
  • Buhl J, Klöppel T, Merten M, et al. Numerical prediction of process-dependent properties of high-performance Ti6Al4 in LS-DYNA. ESAFORM 2021; 2021. doi:10.25518/esaform21.1496
  • Promoppatum P, Taprachareon K, Chayasombat B, et al. Understanding size-dependent thermal,: microstructural, mechanical behaviors of additively manufactured Ti-6Al-4V from experiments and thermo-metallurgical simulation. J Manuf Process. 2022. doi:10.1016/j.jmapro.2022.01.068
  • Yang X, Barrett RA, Tong M, et al. Prediction of microstructure evolution for additive manufacturing of Ti-6Al-4V. Procedia Manuf. 2020. doi:10.1016/j.promfg.2020.04.170
  • Nitzler J, Meier C, Müller KW, et al. A novel physics-based and data-supported microstructure model for part-scale simulation of laser powder bed fusion of Ti-6Al-4V. Adv Model and Simul in Eng Sci. 2021. doi:10.1186/s40323-021-00201-9
  • Zhang Q, Xie J, London T, et al. Estimates of the mechanical properties of laser powder bed fusion Ti-6Al-4V parts using finite element models. Mater Des. 2019. doi:10.1016/j.matdes.2019.107678
  • Yang X, Barrett RA, Tong M, et al. Towards a process-structure model for Ti-6Al-4V during additive manufacturing. J Manuf Process. 2021. doi:10.1016/j.jmapro.2020.11.033
  • Johnson WA, Mehl RF. Reaction kinetics in processes of nucleation and growth. American Institute of Mining and Metallurgical Engineers Technical publication No. 1089; 1939.
  • Avrami M. Kinetics of phase change. I general theory. J Chem Phys. 1939. doi:10.1063/1.1750380
  • Gil Mur FX, Rodríguez D, Planell JA. Influence of tempering temperature and time on the α′-Ti-6Al-4V martensite. J Alloys Compd. 1996. doi:10.1016/0925-8388(95)02057-8
  • Krauss G. Steels: heat treatment and processing principles. Materials Park (Ohio): ASM International; 1990.
  • Réti T, Gergely M, Tardy P. Mathematical treatment of non-isothermal transformations. Mater Sci Technol. 1987. doi:10.1179/mst.1987.3.5.365
  • Costa L, Deus AM, Reti T, et al. Simulation of layer overlap tempering in steel parts produced by laser cladding. RPD 2002-Advanced Solutions and Development; 2002.
  • Lindgren L-E, Lundbäck A. Additive manufacturing and high performance applications. Nanyang Technological University; 2018.
  • Wen D, Gao C, Zheng Z, et al. Hot tensile behavior of a low-alloyed ultrahigh strength steel: fracture mechanism and physically-based constitutive model. J Mater Res Technol. 2021. doi:10.1016/j.jmrt.2021.05.100
  • Wu H, Xu W, Wang S, et al. A cellular automaton coupled FEA model for hot deformation behavior of AZ61 magnesium alloys. J Alloys Compd. 2020. doi:10.1016/j.jallcom.2019.152562
  • Babu B, Lindgren L-E. Dislocation density based model for plastic deformation and globularization of Ti-6Al-4V. Int J Plast. 2013. doi:10.1016/j.ijplas.2013.04.003
  • Fisk M, Lundbäck A. Simulation and validation of repair welding and heat treatment of an alloy 718 plate. Finite Elem Anal Des. 2012. doi:10.1016/j.finel.2012.04.002
  • Seeger A. The mechanism of glide and work hardening in FCC and HCP metals. In: Fisher J, Johnston WG, Thomson R, Vreeland TJ, editors. Dislocations and mechanical properties of crystals. New York, NY: Wiley; 1956. (65). p. 243–655.
  • Orowan E. Problems of plastic gliding. Proc Phys Soc. 1940. doi:10.1088/0959-5309/52/1/303
  • Mecking H, Kocks UF. Kinetics of flow and strain-hardening. Acta Metall. 1981. doi:10.1016/0001-6160(81)90112-7
  • Holt DL. Dislocation cell formation in metals. J Appl Phys. 1970. doi:10.1063/1.1659399
  • Militzer M, Sun WP, Jonas JJ. Modelling the effect of deformation-induced vacancies on segregation and precipitation. Acta Metall Mater. 1994. doi:10.1016/0956-7151(94)90056-6
  • Sandström R, Lagneborg R. A model for hot working occurring by recrystallization. Acta Metall. 1975. doi:10.1016/0001-6160(75)90132-7
  • Mecking H, Estrin Y. The effect of vacancy generation on plastic deformation. Scr Metall. 1980. doi:10.1016/0036-9748(80)90295-1
  • Sargent GA, Zane AP, Fagin PN, et al. Low-Temperature coarsening and plastic flow behavior of an alpha/beta titanium billet material with an ultrafine microstructure. Metall Mat Trans A. 2008. doi:10.1007/s11661-008-9650-y
  • Semiatin SL, Stefansson N, Doherty RD. Prediction of the kinetics of static globularization of Ti-6Al-4V. Metall Mat Trans A. 2005. doi:10.1007/s11661-005-0229-6
  • Thomas J, Semiatin S. Mesoscale Modeling of the Recrystallization of Waspaloy and application to the simulation of the ingot-cogging process; 2006.
  • Nembach E, Neite G. Precipitation hardening of superalloys by ordered γ′-particles. Prog Mater Sci. 1985. doi:10.1016/0079-6425(85)90001-5
  • Mirkoohi E, Mahdavi M, Li D, et al. Microstructure affected residual stress prediction based on mechanical threshold stress in direct metal deposition of Ti-6Al-4V. Int J Adv Manuf Technol. 2021. doi:10.1007/s00170-020-06526-w
  • Lundbäck A, Lindgren L-E. Modelling of metal deposition. Finite Elem Anal Des. 2011. doi:10.1016/j.finel.2011.05.005
  • Eskandari Sabzi H, Rivera-Díaz-del-Castillo PE. Composition and process parameter dependence of yield strength in laser powder bed fusion alloys. Mater Des. 2020. doi:10.1016/j.matdes.2020.109024
  • Babu B, Lundäck A. Physically based constitutive model for Ti-6Al-4V used in the simulation of manufacturing chain. X International Conference on Computational Plasticity COMPLAS X; 2009.
  • Kale AB, Alluri P, Singh AK, et al. The deformation and fracture behavior of 316L SS fabricated by SLM under mini V-bending test. Int J Mech Sci. 2021. doi:10.1016/j.ijmecsci.2021.106292
  • Tao P, Zhong J, Li H, et al. Microstructure, mechanical properties, and constitutive models for Ti–6Al–4V alloy fabricated by selective laser melting (SLM). Metals. 2019. doi:10.3390/met9040447
  • Motoyama Y, Tokunaga H, Kajino S, et al. Stress–strain behavior of a selective laser melted Ti-6Al-4V at strain rates of 0.001–1/s and temperatures 20–1000 °C. J Mater Process Technol. 2021. doi:10.1016/j.jmatprotec.2021.117141
  • Saboori A, Abdi A, Fatemi SA, et al. Hot deformation behavior and flow stress modeling of Ti–6Al–4V alloy produced via electron beam melting additive manufacturing technology in single β-phase field. Mater Sci Eng A. 2020. doi:10.1016/j.msea.2020.139822
  • Niu Y, Sun Z, Wang Y, et al. Phenomenological constitutive models for Hot deformation behavior of Ti6Al4V alloy manufactured by directed energy deposition laser. Metals. 2020. doi:10.3390/met10111496
  • Motallebi R, Savaedi Z, Mirzadeh H. Additive manufacturing – A review of hot deformation behavior and constitutive modeling of flow stress. Curr Opin Solid State Mater Sci. 2022. doi:10.1016/j.cossms.2022.100992
  • Bambach M, Sizova I. In: Author(s), p 170001; 2018.
  • Bambach M, Sizova I, Szyndler J, et al. On the hot deformation behavior of Ti-6Al-4V made by additive manufacturing. J Mater Process Technol. 2021. doi:10.1016/j.jmatprotec.2020.116840
  • Gao P, Yang H, Fan X, et al. Unified modeling of flow softening and globularization for hot working of two-phase titanium alloy with a lamellar colony microstructure. J Alloys Compd. 2014. doi:10.1016/j.jallcom.2014.02.110
  • Galindo-Fernández MA, Mumtaz K, Rivera-Díaz-del-Castillo P, et al. A microstructure sensitive model for deformation of Ti-6Al-4V describing cast-and-wrought and additive manufacturing morphologies. Mater Des. 2018. doi:10.1016/j.matdes.2018.09.028
  • Hayes BJ, Martin BW, Welk B, et al. Predicting tensile properties of Ti-6Al-4V produced via directed energy deposition. Acta Mater. 2017. doi:10.1016/j.actamat.2017.05.025
  • Yang X, Barrett RA, Harrison NM, et al. A physically-based structure-property model for additively manufactured Ti-6Al-4V. Mater Des. 2021. doi:10.1016/j.matdes.2021.109709
  • Obiukwu O, Nwafor M, Okafor B, et al. The effect of surface finish on the low cycle fatigue of low and medium carbon steel. International Conference on Mechanical and Industrial Engineering (ICMIE'15) (Harare(Zimbabwe), (2015); 2015.
  • Salonitis K, D'Alvise L, Schoinochoritiris B, et al. Additive manufacturing and post-processing simulation: laser cladding followed by high speed machining. Int J Adv ManufTechnol. 2016;85:2401–2411.
  • Koenis T, van den Brink W, Bosman M. Full process chain simulation of the (wire-based) laser metal deposition process towards fatigue life prediction. Procedia Structural Integrity. 2021. doi:10.1016/j.prostr.2021.12.034
  • Afazov S, Ceesay L, Larkin O, et al. A methodology for precision manufacture of a nozzle using hybrid laser powder-bed fusion: A case study. Proc Inst Mech Eng, Part B: J Eng Manuf. 2021. doi:10.1177/0954405420958856
  • He Y, Wei J, Peng Y, et al. Deformation prediction and experimental investigation on alternating additive-subtractive hybrid manufacturing of 316L stainless steel thin-walled parts. Int J Adv Manuf Technol. 2023. doi:10.1007/s00170-023-12592-7
  • Luo Y, Zheng K, Zhao P, et al. Machining characteristics of 316L stainless steel in hybrid manufacturing via a three-dimensional thermal-mechanical coupled model. J Manuf Process. 2023. doi:10.1016/j.jmapro.2023.06.021
  • Novotný L, Béreš M, Abreu Hd, et al. Thermal analysis and phase transformation behaviour during additive manufacturing of Ti–6Al–4V alloy. Mater Sci Technol. 2019. doi:10.1080/02670836.2019.1593669
  • Spierings AB, Starr TL, Wegener K. Fatigue performance of additive manufactured metallic parts. Rapid Prototyp J. 2013. doi:10.1108/13552541311302932
  • Bronkhorst CA, Mayeur JR, Livescu V, et al. Structural representation of additively manufactured 316L austenitic stainless steel. Int J Plast. 2019. doi:10.1016/j.ijplas.2019.01.012
  • Riemer A, Leuders S, Thöne M, et al. On the fatigue crack growth behavior in 316L stainless steel manufactured by selective laser melting. Eng Fract Mech. 2014. doi:10.1016/j.engfracmech.2014.03.008
  • Palanivel S, Dutt AK, Faierson EJ, et al. Spatially dependent properties in a laser additive manufactured Ti–6Al–4V component. Mater Sci Eng A. 2016. doi:10.1016/j.msea.2015.12.021
  • Nalli F, Cortese L, Concli F. Ductile damage assessment of Ti6Al4V, 17-4PH and AlSi10Mg for additive manufacturing. Eng Fract Mech. 2021. doi:10.1016/j.engfracmech.2020.107395
  • Tancogne-Dejean T, Roth CC, Mohr D. Rate-dependent strength and ductility of binder jetting 3D-printed stainless steel 316L: experiments and modeling. Int J Mech Sci. 2021. doi:10.1016/j.ijmecsci.2021.106647
  • Wilson-Heid AE, Qin S, Beese AM. Anisotropic multiaxial plasticity model for laser powder bed fusion additively manufactured Ti-6Al-4V. Mater Sci Eng A. 2018. doi:10.1016/j.msea.2018.09.077
  • Wilson-Heid AE, Qin S, Beese AM. Multiaxial plasticity and fracture behavior of stainless steel 316L by laser powder bed fusion: experiments and computational modeling. Acta Mater. 2020. doi:10.1016/j.actamat.2020.08.066
  • Wilson-Heid AE, Beese AM. Fracture of laser powder bed fusion additively manufactured Ti–6Al–4V under multiaxial loading: calibration and comparison of fracture models. Mater Sci Eng A. 2019. doi:10.1016/j.msea.2019.05.097
  • Yang X, Li Y, Duan M, et al. An investigation of ductile fracture behavior of Ti6Al4V alloy fabricated by selective laser melting. J Alloys Compd. 2022. doi:10.1016/j.jallcom.2021.161926
  • Qin S, Novak TC, Vailhe MK, et al. Plasticity and fracture behavior of Inconel 625 manufactured by laser powder bed fusion: comparison between as-built and stress relieved conditions. Mater Sci Eng A. 2021. doi:10.1016/j.msea.2021.140808
  • Paul SK, Tarlochan F, Hilditch T. Fatigue life prediction of the additively manufactured specimen. Model Simul Mater Sci Eng. 2022. doi:10.1088/1361-651X/ac11b9
  • Yadollahi A, Shamsaei N. Additive manufacturing of fatigue resistant materials: challenges and opportunities. Int J Fatigue. 2017. doi:10.1016/j.ijfatigue.2017.01.001
  • Blinn B, Krebs F, Ley M, et al. Determination of the influence of a stress-relief heat treatment and additively manufactured surface on the fatigue behavior of selectively laser melted AISI 316L by using efficient short-time procedures. Int J Fatigue. 2020. doi:10.1016/j.ijfatigue.2019.105301
  • Fotovvati B, Namdari N, Dehghanghadikolaei A. Fatigue performance of selective laser melted Ti6Al4 V components: state of the art. Mater Res Express. 2019. doi:10.1088/2053-1591/aae10e
  • Molaei R, Fatemi A, Sanaei N, et al. Fatigue of additive manufactured Ti-6Al-4V,: part II: The relationship between microstructure, material cyclic properties, and component performance. Int J Fatigue. 2020. doi:10.1016/j.ijfatigue.2019.105363
  • Torries B, Imandoust A, Beretta S, et al. Overview on microstructure- and defect-sensitive fatigue modeling of additively manufactured materials. JOM. 2018. doi:10.1007/s11837-018-2987-9
  • Lindström T, Nilsson D, Simonsson K, et al. Constitutive model for thermomechanical fatigue conditions of an additively manufactured combustor alloy. Mech Mater. 2022. doi:10.1016/j.mechmat.2022.104273
  • Mooney B, Agius D, Kourousis KI. Cyclic plasticity of the As-built EOS maraging steel: preliminary experimental and computational results. Applied Sciences. 2020. doi:10.3390/app10041232
  • Kourousis IK, Agius D, Wang C, et al. Constitutive modeling of additive manufactured Ti-6Al-4V cyclic elastoplastic behaviour. Technische Mechanik. 2016;36(1–2):57–72.
  • Lindström T, Ewest D, Simonsson K, et al. Constitutive model of an additively manufactured ductile nickel-based superalloy undergoing cyclic plasticity. Int J Plast. 2020. doi:10.1016/j.ijplas.2020.102752
  • Zhang J, Wang X, Paddea S, et al. Fatigue crack propagation behaviour in wire+arc additive manufactured Ti-6Al-4V: effects of microstructure and residual stress. Mater Des. 2016. doi:10.1016/j.matdes.2015.10.141
  • Huynh L, Rotella J, Sangid MD. Fatigue behavior of IN718 microtrusses produced via additive manufacturing. Mater Des. 2016. doi:10.1016/j.matdes.2016.05.032
  • Li P, Warner DH, Phan N. Predicting the fatigue performance of an additively manufactured Ti-6Al-4V component from witness coupon behavior. Addit Manufa. 2020. doi:10.1016/j.addma.2020.101230
  • Arbeiter F, Trávníček L, Petersmann S, et al. Damage tolerance-based methodology for fatigue lifetime estimation of a structural component produced by material extrusion-based additive manufacturing. Addit Manuf. 2020. doi:10.1016/j.addma.2020.101730
  • Torries B, Sterling AJ, Shamsaei N, et al. Utilization of a microstructure sensitive fatigue model for additively manufactured Ti-6Al-4V. RPJ. 2016. doi:10.1108/RPJ-11-2015-0168
  • Rutherford BA, Avery DZ, Phillips BJ, et al. Effect of thermomechanical processing on fatigue behavior in solid-state additive manufacturing of Al-Mg-Si alloy. Metals. 2020. doi:10.3390/met10070947
  • Pröbstle M, Neumeier S, Hopfenmüller J, et al. Superior creep strength of a nickel-based superalloy produced by selective laser melting. Mater Sci Eng A. 2016. doi:10.1016/j.msea.2016.07.061
  • Kim Y-K, Park S-H, Yu J-H, et al. Improvement in the high-temperature creep properties via heat treatment of Ti-6Al-4V alloy manufactured by selective laser melting. Mater Sci Eng A. 2018. doi:10.1016/j.msea.2017.12.085
  • Uzan NE, Shneck R, Yeheskel O, et al. High-temperature mechanical properties of AlSi10Mg specimens fabricated by additive manufacturing using selective laser melting technologies (AM-SLM). Additive Manufacturing. 2018. doi:10.1016/j.addma.2018.09.033
  • Cardon A, Mareau C, Ayed Y, et al. In: PROCEEDINGS OF THE 22ND INTERNATIONAL ESAFORM CONFERENCE ON MATERIAL FORMING: ESAFORM 2019. AIP Publishing, p 150018; 2019.
  • He Y, Ma Y, Zhang W, et al. Effects of build direction on thermal exposure and creep performance of SLM Ti6Al4V titanium alloy. Eng Fail Anal. 2022. doi:10.1016/j.engfailanal.2022.106063
  • Paoletti C, Santecchia E, Cabibbo M, et al. Modelling the creep behavior of an AlSi10Mg alloy produced by additive manufacturing. Mater Sci Eng A. 2021. doi:10.1016/j.msea.2020.140138
  • Paoletti C, Cerri E, Ghio E, et al. Effect of low-temperature annealing on creep properties of AlSi10Mg alloy produced by additive manufacturing: experiments and modeling. Metals. 2021. doi:10.3390/met11020179
  • Kim Y-K, Yang S, Lee K-A. Compressive creep behavior of selective laser melted CoCrFeMnNi high-entropy alloy strengthened by in-situ formation of nano-oxides. Addit Manuf. 2020. doi:10.1016/j.addma.2020.101543
  • Mbang S, Haasis S. Automation of the computer-aided design–computer-aided quality assurance process chain in car body engineering. Int J Prod Res. 2004. doi:10.1080/00207540410001717119
  • Afazov SM. Modelling and simulation of manufacturing process chains. CIRP J Manuf Sci Technol. 2013. doi:10.1016/j.cirpj.2012.10.005
  • Afazov SM, Becker AA, Hyde TH. Development of a finite element data exchange system for chain simulation of manufacturing processes. Adv Eng Softw. 2012. doi:10.1016/j.advengsoft.2011.12.011
  • Wang J, Rashed S, Murakawa H. Mechanism investigation of welding induced buckling using inherent deformation method. Thin-Walled Struct. 2014. doi:10.1016/j.tws.2014.03.003
  • O’Brien JM, Montgomery S, Yaghi A, et al. Process chain simulation of laser powder bed fusion including heat treatment and surface hardening. CIRP J Manuf Sci Technol. 2021. doi:10.1016/j.cirpj.2021.01.006
  • Yaghi A, Ayvar-Soberanis S, Moturu S, et al. Design against distortion for additive manufacturing. Addit Manuf. 2019. doi:10.1016/j.addma.2019.03.010
  • Yaghi A, Afazov S, Villa M. Maturity assessment of laser powder bed fusion process chain modelling and simulation. Digital Manuf Technology. 2021. doi:10.37256/dmt.112021822
  • Bleck W, Brecher C, Herty M, et al. In: Brecher C, Özdemir D (eds) Integrative Production Technology. Springer International Publishing. Cham. 2017: 253–364.
  • Zhang XX, Lutz A, Andrä H, et al. An additively manufactured and direct-aged AlSi3.5Mg2.5 alloy with superior strength and ductility: micromechanical mechanisms. Int J Plast. 2021. doi:10.1016/j.ijplas.2021.103083
  • Zhang XX, Bauer P-P, Lutz A, et al. Microplasticity and macroplasticity behavior of additively manufactured Al-Mg-Sc-Zr alloys: In-situ experiment and modeling. Int J Plast. 2023. doi:10.1016/j.ijplas.2023.103659
  • Zhang XX, Andrä H. Crystal plasticity simulation of the macroscale and microscale stress–strain relations of additively manufactured AlSi10Mg alloy. Comput Mater Sci. 2021. doi:10.1016/j.commatsci.2021.110832
  • Zhang XX, Knoop D, Andrä H, et al. Multiscale constitutive modeling of additively manufactured Al–Si–Mg alloys based on measured phase stresses and dislocation density. Int J Plast. 2021. doi:10.1016/j.ijplas.2021.102972
  • Bambach M, Heppner S, Steinmetz D, et al. Assessing and ensuring parameter identifiability for a physically-based strain hardening model for twinning-induced plasticity. Mech Mater. 2015. doi:10.1016/j.mechmat.2015.01.019
  • Siddique S, Imran M, Rauer M, et al. Computed tomography for characterization of fatigue performance of selective laser melted parts. Mater Des. 2015. doi:10.1016/j.matdes.2015.06.063
  • Biswal R, Zhang X, Shamir M, et al. Interrupted fatigue testing with periodic tomography to monitor porosity defects in wire + arc additive manufactured Ti-6Al-4V. Additive Manufacturing. 2019. doi:10.1016/j.addma.2019.04.026
  • Grüger L, Sydow B, Woll R, et al. Design of a cost-effective and statistically validated test specification with selected machine elements to evaluate the influence of the manufacturing process with a focus on additive manufacturing. Metals. 2023. doi:10.3390/met13111900