DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Thermal modeling of directed energy deposition additive manufacturing using graph theory

Abstract

Purpose: The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach: Here, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings: The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications: This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermalmore » camera data from large parts. Practical implications: The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value: This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.« less

Authors:
 [1];  [2];  [2];  [2];  [2];  [1]
  1. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Univ. of Nebraska, Lincoln, NE (United States)
  2. Univ. of Nebraska, Lincoln, NE (United States)
Publication Date:
Research Org.:
Univ. of Nebraska, Lincoln, NE (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1907973
Grant/Contract Number:  
SC0021136
Resource Type:
Accepted Manuscript
Journal Name:
Rapid Prototyping Journal
Additional Journal Information:
Journal Volume: 29; Journal Issue: 2; Journal ID: ISSN 1355-2546
Publisher:
Emerald Group Publishing
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING; Thermal Modeling; Directed Energy Deposition; Titanium Alloy; Graph Theory

Citation Formats

Riensche, Alex, Severson, Jordan, Yavari, Reza, Piercy, Nicholas L., Cole, Kevin D., and Rao, Prahalada. Thermal modeling of directed energy deposition additive manufacturing using graph theory. United States: N. p., 2022. Web. doi:10.1108/rpj-07-2021-0184.
Riensche, Alex, Severson, Jordan, Yavari, Reza, Piercy, Nicholas L., Cole, Kevin D., & Rao, Prahalada. Thermal modeling of directed energy deposition additive manufacturing using graph theory. United States. https://doi.org/10.1108/rpj-07-2021-0184
Riensche, Alex, Severson, Jordan, Yavari, Reza, Piercy, Nicholas L., Cole, Kevin D., and Rao, Prahalada. Fri . "Thermal modeling of directed energy deposition additive manufacturing using graph theory". United States. https://doi.org/10.1108/rpj-07-2021-0184. https://www.osti.gov/servlets/purl/1907973.
@article{osti_1907973,
title = {Thermal modeling of directed energy deposition additive manufacturing using graph theory},
author = {Riensche, Alex and Severson, Jordan and Yavari, Reza and Piercy, Nicholas L. and Cole, Kevin D. and Rao, Prahalada},
abstractNote = {Purpose: The purpose of this paper is to develop, apply and validate a mesh-free graph theory–based approach for rapid thermal modeling of the directed energy deposition (DED) additive manufacturing (AM) process. Design/methodology/approach: Here, the authors develop a novel mesh-free graph theory–based approach to predict the thermal history of the DED process. Subsequently, the authors validated the graph theory predicted temperature trends using experimental temperature data for DED of titanium alloy parts (Ti-6Al-4V). Temperature trends were tracked by embedding thermocouples in the substrate. The DED process was simulated using the graph theory approach, and the thermal history predictions were validated based on the data from the thermocouples. Findings: The temperature trends predicted by the graph theory approach have mean absolute percentage error of approximately 11% and root mean square error of 23°C when compared to the experimental data. Moreover, the graph theory simulation was obtained within 4 min using desktop computing resources, which is less than the build time of 25 min. By comparison, a finite element–based model required 136 min to converge to similar level of error. Research limitations/implications: This study uses data from fixed thermocouples when printing thin-wall DED parts. In the future, the authors will incorporate infrared thermal camera data from large parts. Practical implications: The DED process is particularly valuable for near-net shape manufacturing, repair and remanufacturing applications. However, DED parts are often afflicted with flaws, such as cracking and distortion. In DED, flaw formation is largely governed by the intensity and spatial distribution of heat in the part during the process, often referred to as the thermal history. Accordingly, fast and accurate thermal models to predict the thermal history are necessary to understand and preclude flaw formation. Originality/value: This paper presents a new mesh-free computational thermal modeling approach based on graph theory (network science) and applies it to DED. The approach eschews the tedious and computationally demanding meshing aspect of finite element modeling and allows rapid simulation of the thermal history in additive manufacturing. Although the graph theory has been applied to thermal modeling of laser powder bed fusion (LPBF), there are distinct phenomenological differences between DED and LPBF that necessitate substantial modifications to the graph theory approach.},
doi = {10.1108/rpj-07-2021-0184},
journal = {Rapid Prototyping Journal},
number = 2,
volume = 29,
place = {United States},
year = {Fri Aug 12 00:00:00 EDT 2022},
month = {Fri Aug 12 00:00:00 EDT 2022}
}

Works referenced in this record:

Correlation of Microstructure and Mechanical Properties of Metal Big Area Additive Manufacturing
journal, February 2019

  • Shassere, Benjamin; Nycz, Andrzej; Noakes, Mark
  • Applied Sciences, Vol. 9, Issue 4
  • DOI: 10.3390/app9040787

Invited review article: Metal-additive manufacturing—Modeling strategies for application-optimized designs
journal, August 2018


Computational heat transfer with spectral graph theory: Quantitative verification
journal, July 2020


Thermo-mechanical model development and validation of directed energy deposition additive manufacturing of Ti–6Al–4V
journal, January 2015


Benchmarking build simulation software for laser powder bed fusion of metals
journal, December 2020


A new physics-based model for laser directed energy deposition (powder-fed additive manufacturing): From single-track to multi-track and multi-layer
journal, January 2019


Simulation of metallic powder bed additive manufacturing processes with the finite element method: A critical review
journal, August 2016

  • Schoinochoritis, Babis; Chantzis, Dimitrios; Salonitis, Konstantinos
  • Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 231, Issue 1
  • DOI: 10.1177/0954405414567522

Anisotropic properties of directed energy deposition (DED)-processed Ti–6Al–4V
journal, October 2016


Multi-sensor investigations of optical emissions and their relations to directed energy deposition processes and quality
journal, May 2018


Toward the digital twin of additive manufacturing: Integrating thermal simulations, sensing, and analytics to detect process faults
journal, January 2020


Temperature distribution in laser-clad multi-layers
journal, August 2004

  • Jendrzejewski, R.; Kreja, I.; Śliwiński, G.
  • Materials Science and Engineering: A, Vol. 379, Issue 1-2
  • DOI: 10.1016/j.msea.2004.02.053

Application of Directed Energy Deposition-Based Additive Manufacturing in Repair
journal, August 2019

  • Saboori, Abdollah; Aversa, Alberta; Marchese, Giulio
  • Applied Sciences, Vol. 9, Issue 16
  • DOI: 10.3390/app9163316

Thermal Modeling in Metal Additive Manufacturing Using Graph Theory: Experimental Validation With Laser Powder Bed Fusion Using In Situ Infrared Thermography Data
journal, September 2020

  • Reza Yavari, M.; Williams, Richard J.; Cole, Kevin D.
  • Journal of Manufacturing Science and Engineering, Vol. 142, Issue 12
  • DOI: 10.1115/1.4047619

Modeling forced convection in the thermal simulation of laser cladding processes
journal, February 2015

  • Gouge, Michael F.; Heigel, Jarred C.; Michaleris, Panagiotis
  • The International Journal of Advanced Manufacturing Technology, Vol. 79, Issue 1-4
  • DOI: 10.1007/s00170-015-6831-x

Experimental comparison of residual stresses for a thermomechanical model for the simulation of selective laser melting
journal, October 2016


Residual Strain Predictions for a Powder Bed Fusion Inconel 625 Single Cantilever Part
journal, July 2019

  • Yang, Yangzhan; Allen, Madie; London, Tyler
  • Integrating Materials and Manufacturing Innovation, Vol. 8, Issue 3
  • DOI: 10.1007/s40192-019-00144-5

Additive manufacturing of metallic components – Process, structure and properties
journal, March 2018


Graph characteristics from the heat kernel trace
journal, November 2009


Understanding the Microstructure Formation of Ti-6Al-4V During Direct Laser Deposition via In-Situ Thermal Monitoring
journal, January 2016


Modeling metal deposition in heat transfer analyses of additive manufacturing processes
journal, September 2014


Residual Stress Measurement of Laser-Engineered Net Shaping AISI 410 Thin Plates Using Neutron Diffraction
journal, October 2008

  • Pratt, P.; Felicelli, S. D.; Wang, L.
  • Metallurgical and Materials Transactions A, Vol. 39, Issue 13
  • DOI: 10.1007/s11661-008-9660-9

Heat and fluid flow in additive manufacturing—Part I: Modeling of powder bed fusion
journal, July 2018


3D spatial reconstruction of thermal characteristics in directed energy deposition through optical thermal imaging
journal, July 2015


An improved prediction of residual stresses and distortion in additive manufacturing
journal, January 2017


Graph spectral image smoothing using the heat kernel
journal, November 2008


Microstructural evolution in laser-deposited multilayer Ti-6Al-4V builds: Part II. Thermal modeling
journal, June 2004


Distortion minimization of laser‐processed components through control of laser scanning patterns
journal, December 2002


Thermal Modeling in Metal Additive Manufacturing Using Graph Theory
journal, May 2019

  • Yavari, M. Reza; Cole, Kevin D.; Rao, Prahalada
  • Journal of Manufacturing Science and Engineering, Vol. 141, Issue 7
  • DOI: 10.1115/1.4043648

Mechanistic models for additive manufacturing of metallic components
journal, February 2021


On thermal modeling of Additive Manufacturing processes
journal, January 2018

  • Foteinopoulos, Panagis; Papacharalampopoulos, Alexios; Stavropoulos, Panagiotis
  • CIRP Journal of Manufacturing Science and Technology, Vol. 20
  • DOI: 10.1016/j.cirpj.2017.09.007

The metallurgy and processing science of metal additive manufacturing
journal, March 2016


Modelling of metal deposition
journal, October 2011


Process Maps for Predicting Residual Stress and Melt Pool Size in the Laser-Based Fabrication of Thin-Walled Structures
journal, March 2006

  • Vasinonta, Aditad; Beuth, Jack L.; Griffith, Michelle
  • Journal of Manufacturing Science and Engineering, Vol. 129, Issue 1
  • DOI: 10.1115/1.2335852

Laser powder bed fusion additive manufacturing of metals; physics, computational, and materials challenges
journal, December 2015

  • King, W. E.; Anderson, A. T.; Ferencz, R. M.
  • Applied Physics Reviews, Vol. 2, Issue 4
  • DOI: 10.1063/1.4937809

Residual stresses in LENS-deposited AISI 410 stainless steel plates
journal, November 2008

  • Wang, Liang; Felicelli, Sergio D.; Pratt, Phillip
  • Materials Science and Engineering: A, Vol. 496, Issue 1-2
  • DOI: 10.1016/j.msea.2008.05.044

Heat diffusion: Thermodynamic depth complexity of networks
journal, March 2012


Modelling of temperatures and heat flow within laser sintered part cakes
journal, October 2016


In-situ monitoring of melt pool images for porosity prediction in directed energy deposition processes
journal, March 2018


Metal additive manufacturing: Technology, metallurgy and modelling
journal, September 2020


Distortion prediction and compensation in selective laser melting
journal, October 2017


Process-structure relationship in the directed energy deposition of cobalt-chromium alloy (Stellite 21) coatings
journal, January 2021


Impact of Interlayer Dwell Time on Microstructure and Mechanical Properties of Nickel and Titanium Alloys
journal, June 2017

  • Foster, B. K.; Beese, A. M.; Keist, J. S.
  • Metallurgical and Materials Transactions A, Vol. 48, Issue 9
  • DOI: 10.1007/s11661-017-4164-0

A pragmatic part scale model for residual stress and distortion prediction in powder bed fusion
journal, August 2018


Temperature and composition profile during double-track laser cladding of H13 tool steel
journal, December 2009


Numerical Analysis of Residual Stresses in Parts Produced by Selective Laser Melting Process
journal, January 2020


Review on Computational Modeling of Process–Microstructure–Property Relationships in Metal Additive Manufacturing
journal, November 2019


Heterogeneous sensor-based condition monitoring in directed energy deposition
journal, December 2019


The development of temperature fields and powder flow during laser direct metal deposition wall growth
journal, May 2004

  • Pinkerton, A. J.; Li, L.
  • Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, Vol. 218, Issue 5
  • DOI: 10.1243/095440604323052319

A framework to link localized cooling and properties of directed energy deposition (DED)-processed Ti-6Al-4V
journal, June 2017


Thermal Behavior and Microstructural Evolution during Laser Deposition with Laser-Engineered Net Shaping: Part I. Numerical Calculations
journal, June 2008

  • Zheng, B.; Zhou, Y.; Smugeresky, J. E.
  • Metallurgical and Materials Transactions A, Vol. 39, Issue 9
  • DOI: 10.1007/s11661-008-9557-7

Review on thermal analysis in laser-based additive manufacturing
journal, October 2018


Heat-flow simulation of laser remelting with experimenting validation
journal, February 1991

  • Hoadley, A. F. A.; Rappaz, M.; Zimmermann, M.
  • Metallurgical Transactions B, Vol. 22, Issue 1
  • DOI: 10.1007/BF02672531

Thermal and microstructural analysis of laser-based directed energy deposition for Ti-6Al-4V and Inconel 625 deposits
journal, February 2018


A new finite element model for welding heat sources
journal, June 1984

  • Goldak, John; Chakravarti, Aditya; Bibby, Malcolm
  • Metallurgical Transactions B, Vol. 15, Issue 2
  • DOI: 10.1007/bf02667333