TY - JOUR
T1 - Efficient thermal simulation of large-scale metal additive manufacturing using hot element addition
AU - Nijhuis, Björn
AU - Geijselaers, Bert
AU - van den Boogaard, Antonius H.
N1 - Elsevier deal
Funding Information:
The authors would like to thank Dr. Jialuo Ding from Cranfield University for providing the experimental thermal data. This research was carried out under project number P16-46/S17024K, which is part of AiM2XL program framework of the Partnership Program of the Materials innovation institute M2i (www.m2i.nl) and the Netherlands Organization for Scientific Research (www.nwo.nl). The research was conducted in collaboration with industrial partners and supported by the Rotterdam Fieldlab Additive Manufacturing BV (RAMLAB) (www.ramlab.com).
Funding Information:
The authors would like to thank Dr. Jialuo Ding from Cranfield University for providing the experimental thermal data. This research was carried out under project number P16-46/S17024K, which is part of AiM2XL program framework of the Partnership Program of the Materials innovation institute M2i ( www.m2i.nl ) and the Netherlands Organization for Scientific Research ( www.nwo.nl ). The research was conducted in collaboration with industrial partners and supported by the Rotterdam Fieldlab Additive Manufacturing BV (RAMLAB) ( www.ramlab.com ).
Publisher Copyright:
© 2020 The Authors
PY - 2021/3
Y1 - 2021/3
N2 - Directed energy deposition processes can reduce material waste and manufacturing time of large metal parts through near net-shape production at high deposition rates. However, the localised high heat input gives rise to undesired heat accumulation, residual stresses and distortions. In this work, a fast thermal model is developed to aid in predicting and preventing these drawbacks by providing insight in the relation between process settings, deposition strategy and thermal response. Material addition and heat input are efficiently combined by adding new elements at elevated temperature. Newly deposited elements are assigned an artificially enhanced heat capacity to match the process heat input. The discontinuous Galerkin finite element method is used for spatial discretisation. The resulting numerical scheme is fully explicit and can be solved element-wise. Unlike previous prescribed-temperature heat input models, the proposed method correctly captures the process heat input, irrespective of substrate temperature and element size and without calibration. Comparison with experimental data shows that the thermal history of a large additively manufactured part can be accurately predicted.
AB - Directed energy deposition processes can reduce material waste and manufacturing time of large metal parts through near net-shape production at high deposition rates. However, the localised high heat input gives rise to undesired heat accumulation, residual stresses and distortions. In this work, a fast thermal model is developed to aid in predicting and preventing these drawbacks by providing insight in the relation between process settings, deposition strategy and thermal response. Material addition and heat input are efficiently combined by adding new elements at elevated temperature. Newly deposited elements are assigned an artificially enhanced heat capacity to match the process heat input. The discontinuous Galerkin finite element method is used for spatial discretisation. The resulting numerical scheme is fully explicit and can be solved element-wise. Unlike previous prescribed-temperature heat input models, the proposed method correctly captures the process heat input, irrespective of substrate temperature and element size and without calibration. Comparison with experimental data shows that the thermal history of a large additively manufactured part can be accurately predicted.
KW - UT-Hybrid-D
KW - Discontinuous Galerkin method
KW - Wire and arc additive manufacturing (WAAM)
KW - Directed energy deposition
KW - Thermal analysis
U2 - 10.1016/j.compstruc.2020.106463
DO - 10.1016/j.compstruc.2020.106463
M3 - Article
SN - 0045-7949
VL - 245
JO - Computers & Structures
JF - Computers & Structures
M1 - 106463
ER -