Role of scan strategies on thermal gradient and solidification rate in electron beam powder bed fusion

Abstract Local microstructure control in electron beam powder bed fusion (EB-PBF) is of great interest to the additive manufacturing community to realize complex part geometry with targeted performance. The local microstructure control relies on having a detailed understanding of local melt pool physics (e.g., 3-D melt pool shape as well as spatial and temporal variations of thermal gradient (G) and solidification rate (R)). In this research, a new scan strategy referred to as ghost beam is numerically evaluated as a candidate to achieve the targeted G and R of IN718 alloy. The boundary conditions for simulations, including the speed (490 mm/s) and spatial locations of the beam within a given layer, are obtained by using series of snapshot images, recorded at 12,000 frames per second, using a high-speed camera. The heat transfer simulations were performed using TRUCHAS an open-source software deployed within a high-performance computational infrastructure. The simulation results showed that reheating at short beam on-time and time delay decreases both G and R. Local variation of R at the center of the melt pool trailing edge showed periodic temporal fluctuations. Finally, the ghost beam scan strategy was compared to other existing raster and spot scan strategies.

[1]  Ryan R. Dehoff,et al.  Strategy for Texture Management in Metals Additive Manufacturing , 2017 .

[2]  Wei Zhang,et al.  Modeling of temperature field and solidified surface profile during gas–metal arc fillet welding , 2003 .

[3]  S. Pannala,et al.  The metallurgy and processing science of metal additive manufacturing , 2016 .

[4]  D. Farson,et al.  Effect of magnetic stirring on grain structure refinement: Part 1 – Autogenous nickel alloy welds , 2010 .

[5]  Tatiana V. Olshanskaya,et al.  Electron beam welding of aluminum alloy AlMg6 with a dynamically positioned electron beam , 2017 .

[6]  D. Appleyard.  Powering up on powder technology , 2015 .

[7]  Iain Todd,et al.  Dimensional accuracy of Electron Beam Melting (EBM) additive manufacture with regard to weight optimized truss structures , 2016 .

[8]  Radovan Kovacevic,et al.  Numerical Modeling of Heat Distribution in the Electron Beam Melting® of Ti-6Al-4V , 2013 .

[9]  Lin Li,et al.  Modelling of the Melt Pool Geometry in the Laser Deposition of Nickel Alloys Using the Anisotropic Enhanced Thermal Conductivity Approach , 2011 .

[10]  D. Korzekwa,et al.  Truchas – a multi-physics tool for casting simulation , 2009 .

[11]  Feng Lin,et al.  Direct metal part forming of 316L stainless steel powder by electron beam selective melting , 2006 .

[12]  Feng Lin,et al.  Multiscale modeling of electron beam and substrate interaction: a new heat source model , 2015 .

[13]  C. Emmelmann,et al.  Additive Manufacturing of Metals , 2016 .

[14]  Ryan R. Dehoff,et al.  Site specific control of crystallographic grain orientation through electron beam additive manufacturing , 2015 .

[15]  Ryan R. Dehoff,et al.  Numerical modeling of heat-transfer and the influence of process parameters on tailoring the grain morphology of IN718 in electron beam additive manufacturing ☆ , 2016 .

[16]  Lonnie J. Love,et al.  Additive manufacturing of materials: Opportunities and challenges , 2015 .

[17]  E. Toyserkani,et al.  3-D finite element modeling of laser cladding by powder injection: effects of laser pulse shaping on the process , 2004 .

[18]  Robert F. Singer,et al.  Grain structure evolution in Inconel 718 during selective electron beam melting , 2016 .

[19]  W. Sames,et al.  Additive Manufacturing of Inconel 718 using Electron Beam Melting: Processing, Post-Processing, & Mechanical Properties , 2015 .

[20]  D. Farson,et al.  Reducing hot cracking tendency of dissimilar weld overlay by magnetic arc oscillation , 2014 .

[21]  Michael F. Zäh,et al.  Modelling and simulation of electron beam melting , 2010, Prod. Eng..

[22]  Iain Todd,et al.  XCT analysis of the influence of melt strategies on defect population in Ti?6Al?4V components manufactured by Selective Electron Beam Melting , 2015 .

[23]  Michael F. Zäh,et al.  The effect of scanning strategies on electron beam sintering , 2009, Prod. Eng..

[24]  S. Al-Bermani.  An investigation into microstructure and microstructural control of additive layer manufactured Ti-6Al-4V by electron beam melting , 2011 .

[25]  Leilei Wang,et al.  A pathway to microstructural refinement through double pulsed gas metal arc welding , 2017 .

[26]  T. DebRoy,et al.  Heat and fluid flow in complex joints during gas metal arc welding—Part II: Application to fillet welding of mild steel , 2004 .

[27]  C. Körner,et al.  Additive manufacturing of metallic components by selective electron beam melting — a review , 2016 .

[28]  Ryan R. Dehoff,et al.  Computational modeling of residual stress formation during the electron beam melting process for Inconel 718 , 2015 .

[29]  J. W. Park,et al.  Stray grain formation, thermomechanical stress and solidification cracking in single crystal nickel base superalloy welds , 2004 .

[30]  Robert F. Singer,et al.  Influence of the Scanning Strategy on the Microstructure and Mechanical Properties in Selective Electron Beam Melting of Ti–6Al–4V , 2015 .

[31]  Dominic Cuiuri,et al.  A tool-path generation strategy for wire and arc additive manufacturing , 2014, The International Journal of Advanced Manufacturing Technology.

[32]  D. Farson,et al.  Effect of magnetic stirring on grain structure refinement Part 2 – Nickel alloy weld overlays , 2010 .

[33]  Daniel Dřímal.  Electron Beam Welding of Gear Wheels by Splitted Beam , 2014 .

[34]  Bo Cheng,et al.  On Process Temperature in Powder-Bed Electron Beam Additive Manufacturing: Process Parameter Effects , 2014 .

[35]  N. Raghavan,et al.  Microstructure Development in Electron Beam-Melted Inconel 718 and Associated Tensile Properties , 2016 .