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Modeling of ThermodynamicPhenomena with Lattice BoltzmannMethod for Additive ManufacturingProcessesRegina Ammer†,Matthias Markl∗, Carolin Körner∗, Ulrich Rüde†July 31th, 2014†Chair for System Simulation (LSS),∗Chair for Metal Science and Technology (WTM)
Outline
1 Additive Manufacturing
2 Mathematical and Numerical Models
3 Validation Experiments
4 Improvements for EBM Process
5 Evaporation - Condensation Problem
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 2
Additive Manufacturing
AdditiveManufacturing
Methods
ElectronBeam
Melting
SelectiveLaser
Melting
SelectiveLaser
SinteringEB free
formfabrication
StereoLithog-raphy
DirectMetal
DepositionFusedLayer
Modeling
LayerLaminate
Manu-facturing
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 3
Our target application: Electron Beam Melting
2. Melting of thecross section
3. Lowering of theprocess platform
1. Preheating of thepowder layer
4. Application of anew powder layer
powderhopper
powder
start plate
vacuumchamber
ele
ctr
on
beam
gu
n
powderhopper
rake
buildingtank
processplatform
a) b)
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 4
From Mathematical Model to Numerical Discretization
Incompressible Navier-Stokes Equations
∇ · u = 0∂u∂t
+ (u · ∇) u = −∇p + ν∆u + f
∂E∂t
+∇ · (uE) = ∇ · (k∇E) + φ
Numercial Discretization Methods:% Finite Volume Methods% Finite Element Methods" Lattice Boltzmann Method
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 5
Thermal 3D LBM
Multi-distribution approach for thermal LBM
fi (x + ei, t + ∆t) = fi(x, t) +∆tτf
(f eqi (x, t)− fi(x, t)
)+ Fi(x, t)
hi (x + ei, t + ∆t) = hi(x, t) +∆tτh
(heq
i (x, t)− hi(x, t))
+ Φi(x, t)
0 1
2
3
4
5
6
78
9 10
11
12
13
14
1516
17 18
f eqi (ρ,u) = ωiρ
1 +ei · uc2
s+
(ei · u)2
2c2s− u2
2c4s
heqi (E,u) = ωiE
1 +ei · uc2
s
• Macroscopic quantities: ρ = ∑ifi ρu = ∑
ieifi E = ∑
ihi
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 6
Free Surface Treatment1
Liquid Liquid Interface
Solid Solid Interface
Gas – Free Surface
Wall ·· Phase Transition
Volume of Fluid Approach• Fill level for interface cells is defined byϕ, 0 ≤ ϕ ≤ 1
• Simulate only liquid phase andneglect the gas phase
→ Reconstruct unknown fi,hi values fromthe gas phase in the interface layer
→ Convert interface cells due to thedynamic melt pool surface
1Körner et al., 2005
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 7
Implemenation
collision detectioncollision response
update of fluid nodescalculation of hydrodynamic forcescalculation of free surface
rigid bodies act as obstacles
create new powder layer
after solidification process
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 8
Summary of Numerical Model
" Parallelized and optimized 3D model"Wetting effects" Free surface treatment" Different absorption types" Realistic metal powder distribution
% Evaporation model /% Temperature dependent surface tension
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 9
Validation – Experimental Setting
• Line energy
EL =uBIbeam
vscan=
Pbeam
vscan
kJm
with• acceleration voltage uB in V• beam current Ibeam in A• scan velocity vscan is scan
velocity in ms
• Examination of a sampleregarding• porosity• swelling
• Hatching of a cuboidconsidering
15mm 15mm
10m
m
simulated powder bedhatching lines
beam offset
• Simulation domain:(1.44x0.64x0.24)·10−3 m3
• One powder layer with0.05 mm thickness
• Define porosity/swellingnumerically!
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 10
Categorization of Test Settings
Porosity Good Surface Swelling
Line Energy
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 11
Hatching one Layer (6.4ms , 200 kJ
m)
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 12
Comparison of experimental and numerical processwindow2
0 1 2 3 4 5 6 7
Scan velocity [m/s]
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Line
ener
gy[k
J/m
]
porousgoodswelling
Figure: Experimental process window.
0 1 2 3 4 5 6 7
Scan velocity [m/s]
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Line
ener
gy[k
J/m
]
swellingporousgood
Figure: Numerical process window.2Ammer et al. 2014
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 13
Comparison of experimental and numerical processwindow
F Experimental and simulation values are highly concordant!(especially for mid-scan-velocity and all porous values areequal)
F Small differences for low and high scan velocities→ numerical EB focus constant, experimentallythe focus spreads out
F $$$ Time is money - can it be "faster"???
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 14
Advanced Hatching Strategies - achieved bynumerical simulations3
F Numerical extension of the process window up to 30 ms
I Numerical simulations show a decrease of "window" height up to aclosing at 30 m
sI Sharp temperature/evaporation border→ Small statistical variance
for the maximum temperature on the melt pool surfaceI Rough porosity border→ High statistical variance for the powder
distribution in one layerF Decrease of line offset (100µm→ 50µm)
I Increase of beam power and scan velocity→ faster production rate!
I Lower maximum temperature for the same beam power→ less evaporation rate!
3Markl et al. 2014
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 15
Evaporation–Condensation Problem4
dense phase
fe(ρe, Ts)fifr
vapour phase
O(λ)
beam energyI Knudsen layer = boundary layer with
a thickness of a few molecular meanfree path
I Classical Hertz-Knudsen formula fornet mass flux
mHK = me − mi = ρe
√√√√√√RTs
2π− ρv
√√√√√√RTv
2πI / lack of nonlinear convective
effects, limited in the range ofevaporation, not including the backpressure problem...
4Hertz 1882 and Knudsen 1915
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 16
Flow Structure of the Vapour Plume
condensedmatter
Knudsen layer
vapour
compressedambient gas
ambient gas
contactdiscontinuity
shock wave
subsonic flow supersonic flow
rarefaction fan
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 17
Evaporation and condensation fluxes
I Net mass transport from evaporating surface
jnet = j+ − j− =
j+ − j−
j+
· j+ = φ · j+
with evaporation coefficient φI Evaporation flux
j+ = ps
√√√√√√ mA
2πkBTs
where mA is atomic mass and kB Boltzmann’s constant
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 18
Evaporation and condensation fluxes cont’d
I Condensation flux
j− = pKn
√√√√√√ mA
2πkBTKn· β · F−
where β and F− account for collisional effects in downstreamflow and require jump conditions across the Knudsen layer
I evaporation coefficient φ
φ =√2πγν ·MaKn(Ts) ·
ρKn
ρs
√√√√√√√TKn
Ts
where γν is ratio of specific heats and MaKn(Ts) is flow Machnumber of outer Knudsen layer
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 19
Back pressure
I Conservation of momentum→ expanding vapour generates aback pressure pback onto evaporating surface
I For φ = 0→ state of thermodynamic equilibrium betweenvapour and condensed phase, flux of evaporating particlesmatches these of condensing ones:
pback = 0.5ps + 0.5pKn = ps
I For higher evaporation fluxes, i.e., φ > 0:
pback =12
ps +12
(1− φ)
12
pKn +12
ps
=12
ps ·1 +
12· (1− φ) ·
1 +ρKn
ρs
TKn
Ts
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 20
Numerical transfer
F Vapour layer is neglected→ remove evaproated mass andenergy from the free surface cells!
F Update the state variables by:∆pback(xs, t) = pback(xs, t)− pa
∆mvap(xs, t) = jnet(xs, t)∆t(∆x)2
∆Evap(xs, t) = ∆mvap(xs, t) · [Lvap(Ts(xs, t)) + Lmelt+
cp,sTliquidus + cp,l(Ts(xs, t)− Tliquidus)]
F Post-evaporation quantities are:pG,post(xs, t) = pG,pre + ∆pback
mpost(xs, t) = mpre(xs, t)−∆mvap(xs, t)
hE,post(xs, t) =hE,pre(xs, t)mpre(xs, t)−∆Evap(xs, t)
mpost(xs, t)
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 21
Conclusion & Outlook
" 3D model for simulating EBM processes ," Validation experiments show highly accordance with
experimental results ," Improvement of hatching strategies by decreased line offset→ find "fastest" parameter set (EL, vscan) ,
% Including evaporation and condensation problem in theWALBERLA-framework!
% Simulate more powder layers to achieve information aboutbeam-powder-bed-interaction!
% Use static grid refinement for the melt pool!% . . .
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 22
More Powder Layers!
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 23
References & Acknowledgments
EU Grand Agreement Number 28 66 95 – FastEBM
High Productivity Electron Beam Melting Additive Manufacturing Developmentfor the Part Production Systems Market
l M. Markl, R. Ammer, U. Rüde, C. Körner:Improving Hatching Strategies for Powder Bed Based AddivitiveManufacturing with an Electron Beam by 3D Simulationssubmitted (2014)
l R. Ammer, M. Markl, V. Jüchter, C. Körner, U. Rüde:Validation experiments for LBM simulations of electron beam meltingInt. J. Mod. Phys. C 25, 1441009 (2014)
l R. Ammer, M. Markl, U. Ljungblad, C. Körner, U. Rüde:Simulating Fast Electron Beam Melting with a Parallel Thermal Free SurfaceLattice Boltzmann MethodComput. Math. Appl. 67, 318 (2014)
l M. Markl, R. Ammer, U. Ljungblad, U. Rüde, C. Körner:Electron Beam Absorption Algorithms for Electron Beam Melting ProcessesSimulated by a 3D Thermal Free Surface LBM in a Distributed and ParallelEnvironmentProcedia Comput. Sci. 18 2127 (2013)
July 31th, 2014 | Regina Ammer et al. | LSS | Simulation of Thermodynamic Phenomena by LBM 24