The issue of multi-scale modeling of the filament-based material extrusion has received considerable critical attention for three-dimensional (3D) printing, which involves complex physicochemical phase transitions and thermodynamic behavior. The lack of a multi-scale theoretical model poses significant challenges for prediction in 3D printing processes driven by the rapidly evolving temperature field, including the nonuniformity of tracks, the spheroidization effect of materials, and inter-track voids. Few studies have systematically investigated the mapping relationship and established the numerical modeling between the physical environment and the virtual environment. In this paper, we develop a multi-scale system to describe the fused deposition process in the 3D printing process, which is coupled with the conductive heat transfer model and the dendritic solidification model. The simulation requires a computational framework with high performance because of the cumulative effect of heat transfer between different filament layers. The proposed system is capable of simulating the material state with the proper parameter at the macro- and micro-scale and is directly used to capture multiple physical phenomena. The main contribution of this paper is that we have established a totally integrated simulation system by considering multi-scale and multi-physical properties. We carry out several numerical tests to verify the robustness and efficiency of the proposed model.

1.
J. G.
Michopoulos
,
A. P.
Iliopoulos
,
J. C.
Steuben
,
A. J.
Birnbaum
, and
S. G.
Lambrakos
, “
On the multiphysics modeling challenges for metal additive manufacturing processes
,”
Addit. Manuf.
22
,
784
799
(
2018
).
2.
D.
Gu
,
C.
Ma
,
M.
Xia
,
D.
Dai
, and
Q.
Shi
, “
A multiscale understanding of the thermodynamic and kinetic mechanisms of laser additive manufacturing
,”
Engineering
3
,
675
684
(
2017
).
3.
Q.
Chen
,
X.
Liang
,
D.
Hayduke
,
J.
Liu
,
L.
Cheng
,
J.
Oskin
,
R.
Whitmore
, and
A. C.
To
, “
An inherent strain based multiscale modeling framework for simulating part-scale residual deformation for direct metal laser sintering
,”
Addit. Manuf.
28
,
406
418
(
2019
).
4.
F.
Liou
,
J.
Newkirk
,
Z.
Fan
,
T.
Sparks
,
X.
Chen
,
K.
Fletcher
,
J.
Zhang
,
Y.
Zhang
,
K. S.
Kumar
, and
S.
Karnati
, “
Multiscale and multiphysics modeling of additive manufacturing of advanced materials
,” NASA Langley Research Center Technical Report No. NASA/CR-2015-218691, 2015.
5.
H.
Xia
,
J.
Lu
, and
G.
Tryggvason
, “
A numerical study of the effect of viscoelastic stresses in fused filament fabrication
,”
Comput. Methods Appl. Mech. Eng.
346
,
242
259
(
2019
).
6.
Q.
Xia
,
J.
Yang
, and
Y.
Li
, “
On the conservative phase-field method with the N-component incompressible flows
,”
Phys. Fluids
35
,
012120
(
2023
).
7.
Q.
Xia
,
J.
Kim
, and
Y.
Li
, “
Modeling and simulation of multi-component immiscible flows based on a modified Cahn-Hilliard equation
,”
Eur. J. Mech. B
95
,
194
204
(
2022
).
8.
Y.
Li
,
R.
Liu
,
Q.
Xia
,
C.
He
, and
Z.
Li
, “
First- and second-order unconditionally stable direct discretization methods for multi-component Cahn-Hilliard system on surfaces
,”
J. Comput. Appl. Math.
401
,
113778
(
2022
).
9.
W.
Yan
,
J.
Smith
,
W.
Ge
,
F.
Lin
, and
W. K.
Liu
, “
Multiscale modeling of electron beam and substrate interaction: A new heat source model
,”
Comput. Mech.
56
,
265
276
(
2015
).
10.
W.
Yan
,
W.
Ge
,
J.
Smith
,
S.
Lin
,
O. L.
Kafka
,
F.
Lin
, and
W. K.
Liu
, “
Multi-scale modeling of electron beam melting of functionally graded materials
,”
Acta Mater.
115
,
403
412
(
2016
).
11.
W.
Yan
,
W.
Ge
,
Y.
Qian
,
S.
Lin
,
B.
Zhou
,
W. K.
Liu
,
F.
Lin
, and
G. J.
Wagner
, “
Multi-physics modeling of single/multiple-track defect mechanisms in electron beam selective melting
,”
Acta Mater.
134
,
324
333
(
2017
).
12.
W.
Yan
,
S.
Lin
,
O. L.
Kafka
,
Y.
Lian
,
C.
Yu
,
Z.
Liu
,
J.
Yan
,
S.
Wolff
,
H.
Wu
,
E.
Ndip-Agbor
 et al, “
Data-driven multi-scale multi-physics models to derive process–structure–property relationships for additive manufacturing
,”
Comput. Mech.
61
,
521
541
(
2018
).
13.
Z.
Wang
,
W.
Yan
,
W. K.
Liu
, and
M.
Liu
, “
Powder-scale multi-physics modeling of multi-layer multi-track selective laser melting with sharp interface capturing method
,”
Comput. Mech.
63
,
649
661
(
2019
).
14.
M.
Liu
and
G.
Liu
,
Particle Methods for Multi-Scale and Multi-Physics
(
World Scientific
,
2015
).
15.
M.
Markl
and
C.
Körner
, “
Multiscale modeling of powder bed–based additive manufacturing
,”
Annu. Rev. Mater. Sci.
46
,
93
123
(
2016
).
16.
R.
Geng
,
J.
Du
,
Z.
Wei
,
G.
Zhao
, and
J.
Ni
, “
Multiscale modeling of microstructural evolution in fused-coating additive manufacturing
,”
J. Mater. Eng. Perform.
28
,
6544
6553
(
2019
).
17.
Y.
Li
,
Q.
Xia
,
C.
Lee
,
S.
Kim
, and
J.
Kim
, “
A robust and efficient fingerprint image restoration method based on a phase-field model
,”
Pattern Recognit.
123
,
108405
(
2022
).
18.
Q.
Xia
,
G.
Sun
,
Q.
Yu
,
J.
Kim
, and
Y.
Li
, “
Thermal-fluid topology optimization with unconditional energy stability and second-order accuracy via phase-field model
,”
Commun. Nonlinear Sci. Numer. Simul.
116
,
106782
(
2023
).
19.
S.
Vyavahare
,
S.
Teraiya
,
D.
Panghal
, and
S.
Kumar
, “
Fused deposition modelling: A review
,”
Rapid Prototyping J.
26
,
176
201
(
2020
).
20.
O. A.
Mohamed
,
S. H.
Masood
, and
J. L.
Bhowmik
, “
Optimization of fused deposition modeling process parameters: A review of current research and future prospects
,”
Adv. Manuf.
3
,
42
53
(
2015
).
21.
H.
Xia
,
J.
Lu
,
S.
Dabiri
, and
G.
Tryggvason
, “
Fully resolved numerical simulations of fused deposition modeling—Part I: Fluid flow
,”
Rapid Prototyping J.
24
,
463
476
(
2018
).
22.
T.
Rahim
,
A.
Abdullah
, and
H.
Akil
, “
Recent developments in fused deposition modeling-based 3D printing of polymers and their composites
,”
Polym. Rev.
59
,
589
624
(
2019
).
23.
A.
Sheoran
and
H.
Kumar
, “
Fused deposition modeling process parameters optimization and effect on mechanical properties and part quality: Review and reflection on present research
,”
Mater. Today
21
,
1659
1672
(
2020
).
24.
S.
Wasti
and
S.
Adhikari
, “
Use of biomaterials for 3D printing by fused deposition modeling technique: A review
,”
Front. Chem.
8
,
315
(
2020
).
25.
Q.
Yu
,
Q.
Xia
, and
Y.
Li
, “
A phase field-based systematic multiscale topology optimization method for porous structures design
,”
J. Comput. Phys.
466
,
111383
(
2022
).
26.
H.
Huang
,
N.
Ma
,
J.
Chen
,
Z.
Feng
, and
H.
Murakawa
, “
Toward large-scale simulation of residual stress and distortion in wire and arc additive manufacturing
,”
Addit. Manuf.
34
,
101248
(
2020
).
27.
S.
Nelaturi
,
W.
Kim
, and
T.
Kurtoglu
, “
Manufacturability feedback and model correction for additive manufacturing
,”
CIRP J. Manuf. Sci. Technol.
137
,
021015
(
2015
).
28.
D.
Wang
and
X.
Chen
, “
Closed-loop high-fidelity simulation integrating finite element modeling with feedback controls in additive manufacturing
,”
J. Dyn. Syst. Meas. Control
143
,
021006
(
2021
).
29.
A.
Nasirov
,
S.
Hasanov
,
I.
Fidan
 et al, “
Prediction of mechanical properties of fused deposition modeling made parts using multiscale modeling and classical laminate theory
,” in
Proceedings of the 30th Annual International Solid Freeform Fabrication Symposium—An Additive Manufacturing Conference,
Austin, TX
(
2019
), Vol.
1376
.
30.
L.
Sánchez-Balanzar
,
F.
Velázquez-Villegas
,
L.
Ruiz-Huerta
, and
A.
Caballero-Ruiz
, “
A multiscale analysis approach to predict mechanical properties in fused deposition modeling parts
,”
Int. J. Adv. Manuf. Technol.
115
,
2269
2279
(
2021
).
31.
H.
Xia
,
J.
Lu
, and
G.
Tryggvason
, “
Simulations of fused filament fabrication using a front tracking method
,”
Int. J. Heat Mass Transfer
138
,
1310
1319
(
2019
).
32.
H.
Xia
,
J.
Lu
, and
G.
Tryggvason
, “
Fully resolved numerical simulations of fused deposition modeling—Part II: Solidification, residual stresses and modeling of the nozzle
,”
Rapid Prototyp. J.
24
,
973
987
(
2018
).
33.
Q.
Xia
,
Q.
Yu
, and
Y.
Li
, “
A second-order accurate, unconditionally energy stable numerical scheme for binary fluid flows on arbitrarily curved surfaces
,”
Comput. Methods Appl. Mech. Eng.
384
,
113987
(
2021
).
34.
Y.
Li
,
K.
Wang
,
Q.
Yu
,
Q.
Xia
, and
J.
Kim
, “
Unconditionally energy stable schemes for fluid-based topology optimization
,”
Commun. Nonlinear Sci. Numer. Simul.
111
,
106433
(
2022
).
35.
Y.
Li
,
L.
Zhang
,
Q.
Xia
,
Q.
Yu
, and
J.
Kim
, “
An unconditionally energy-stable second-order time-accurate numerical scheme for the coupled Cahn-Hilliard system in copolymer/homopolymer mixtures
,”
Comput. Mater. Sci.
200
,
110809
(
2021
).
36.
C.
Mcllroy
and
R.
Graham
, “
Modelling flow-enhanced crystallisation during fused filament fabrication of semi-crystalline polymer melts
,”
Addit. Manuf.
24
,
323
340
(
2018
).
37.
M.
Francois
,
A.
Sun
,
W.
King
,
N.
Henson
,
D.
Tourret
,
C.
Bronkhorst
,
N.
Carlson
,
C.
Newman
,
T.
Haut
,
J.
Bakosi
,
J.
Gibbs
,
V.
Livescu
,
S.
Wiel
,
A.
Clarke
,
M.
Schraad
,
T.
Blacker
,
H.
Lim
,
T.
Rodgers
,
S.
Owen
,
F.
Abdeljawad
,
J.
Madison
,
A.
Anderson
,
J.
Fattebert
,
R.
Ferencz
,
N.
Nodge
,
S.
Khairallah
, and
O.
Walton
, “
Modeling of additive manufacturing processes for metals: Challenges and opportunities
,”
Curr. Opin. Solid State Mater. Sci.
21
,
198
206
(
2017
).
38.
Y.
Li
,
K.
Qin
,
Q.
Xia
, and
J.
Kim
, “
A second-order unconditionally stable method for the anisotropic dendritic crystal growth model with an orientation-field
,”
Appl. Numer. Math.
184
,
512
526
(
2023
).
39.
J.
Langer
, “
Models of pattern formation in first-order phase transitions
,” in
Directions in Condensed Matter Physics: Memorial Volume in Honor of Shang-Keng Ma
(
World Scientific
,
1986
), pp.
165
186
.
40.
H. G.
Lee
and
J.
Kim
, “
An efficient and accurate numerical algorithm for the vector-valued Allen–Cahn equations
,”
Comput. Phys. Commun.
183
,
2107
2115
(
2012
).
41.
Y.
Li
and
J.
Kim
, “
Phase-field simulations of crystal growth with adaptive mesh refinement
,”
Int. J. Heat Mass Transfer
55
,
7926
7932
(
2012
).
42.
X.
Tong
,
C.
Beckermann
,
A.
Karma
, and
Q.
Li
, “
Phase-field simulations of dendritic crystal growth in a forced flow
,”
Phys. Rev. E
63
,
061601
(
2001
).
43.
X.
Huang
,
X.
Tian
,
Q.
Zhong
,
S.
He
,
C.
Huo
,
Y.
Cao
,
Z.
Tong
, and
D.
Li
, “
Real-time process control of powder bed fusion by monitoring dynamic temperature field
,”
Adv. Manuf.
8
,
380
391
(
2020
).
44.
M.
Jamshidinia
,
F.
Kong
, and
R.
Kovacevic
, “
Numerical modeling of heat distribution in the Electron Beam Melting® of Ti-6Al-4V
,”
J. Manuf. Sci. Eng.
135
,
061010
(
2013
).
45.
A.
Karma
and
W.
Rappel
, “
Phase-field method for computationally efficient modeling of solidification with arbitrary interface kinetics
,”
Phys. Rev. E
53
,
R3017
(
1996
).
46.
A.
Barbieri
and
J.
Langer
, “
Predictions of dendritic growth rates in the linearized solvability theory
,”
Phys. Rev. A
39
,
5314
(
1989
).
47.
A.
Karma
and
W.
Rappel
, “
Quantitative phase-field modeling of dendritic growth in two and three dimensions
,”
Phys. Rev. E
57
,
4323
(
1998
).
48.
M.
Dodd
and
A.
Ferrante
, “
A fast pressure-correction method for incompressible two-fluid flows
,”
J. Comput. Phys.
273
,
416
434
(
2014
).
49.
X.
Yang
, “
Efficient linear, stabilized, second-order time marching schemes for an anisotropic phase field dendritic crystal growth model
,”
Comput. Methods Appl. Mech. Eng.
347
,
316
339
(
2019
).
50.
Y.
Li
,
Q.
Xia
,
S.
Yoon
,
C.
Lee
,
B.
Lu
, and
J.
Kim
, “
Simple and efficient volume merging method for triply periodic minimal structures
,”
Comput. Phys. Commun.
264
,
107956
(
2021
).
51.
A.
Brown
and
D.
Beer
, “
Development of a stereolithography (STL) slicing and G-code generation algorithm for an entry level 3-D printer
,” in
2013 Africon
(
IEEE
,
2013
), pp.
1
5
.
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