additive manufacturing simulation on the...
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Additive Manufacturing Simulation on the GPU
Krishnan Suresh
ProfessorMechanical Engineering
Overview
2
1.AM: What & Why?
2.AM Simulation
3.Computational Bottlenecks
4. Ideas for Fast Simulation
Manufacturing
3
Traditional (Subtractive) Additive Manuf. (AM)
(3D printing)
AM Methods
4
Why AM?
5
Design Freedom!
Cool designs Fewer parts CustomizationBetter designs
AM Market
6
Where is the catch?
Additive manufacturing (AM) is an art!
The Real Truth
8
CAD Model (torture test)Our attempt
Vendor Print
AM Issues
[Ref: Cheng 2014]
[ma3jic, OSU]
Warping
Micro-defects
DelaminationBurning
[Ref: Mertens 2014]
Surface Finish
[Ref: NASA techbrief]
Voids
[Apriso]
[Ref: UMTech 2012]
AM Price Tag
10
Material cost:$ per gram!
Can’t afford playing around
Unless you are GE
> $500K
GE Success Story
11
Additive manufacturing is an art
AM Simulation
13
AM Simulation
14
Identify relevant physics
Discretization
Numerical solution
Results
Experiments
Errors
Relevant Physics?
15
• Thermal analysis• Elasticity/plasticity analysis
• Thermal analysis• Viscous/flow modeling
[Ref: Thomson 2015]
• Particle dynamics• Laser absorption• Melt pool formation• Thermal transfers• Macro-structural loads• Micro-structural evolution• …
Mathematical Model
( ) ( )( )i i
i i p i i
u h u Hh k E HQ
t x x x t xc
Energy Equation
Transient Term
Flow Term
Conductivity Term
Latent Heat Terms
Internal Energy Source
Double Ellipsoidal Volumetric Heat Source
http://www.ams.org.cn/EN/10.11900/0412.1961.2013.00832
AM Simulation
17
Identify relevant physics
Discretization
Numerical methods
Simulation Results
Experiments
Errors
Discretization
18
Discretization(Mesh)
Printing resolution ~ 20 microns
Hand-sized part ~ 125 billion elements!
AM Issues
[Ref: Cheng 2014]
[ma3jic, OSU]
Warping
Micro-defects
DelaminationBurning
[Ref: Mertens 2014]
Surface Finish
[Ref: NASA techbrief]
Voids
[Apriso]
[Ref: UMTech 2012]
Resolution Map for AM
201 element ~ 3 degrees of freedom
4 20 50 150 500
#ELEMENTS (MILLION)
#Elements for 10x10x10 cm
Discretization & Solver
21
Discretization(Mesh)
Kd = fPhysics
AM Simulation Bottleneck
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Kd f
AM Simulation
23
Identify relevant physics
Discretization
Numerical methods
Simulation Results
Experiments
Errors
24
Kd = f (GTC Topics)
Fine-grained Parallel Preconditioners
CULA
MAGMA
Accelerating Iterative Linear Solvers
Efficient AMG on Hybrid GPU Clusters
Preconditioning for Large-Scale Linear Solvers
…
AM Simulation: Highly Nonlinear
Transient
Phase change
Radiation non-linearity
Material non-linearity
Typical Discretization
[ANSYS]
Distinctly shaped elements
AM Discretization
Voxelization: Identical elements~ microns to mm
‘Identical’ element stiffness Ke
Implication: SpMV
28
1
Classic: N
ei
Kd K d
: Sparse Matrix-Vector Multiplication (SpMV)
Critical operation in ALL iterative solvers
Kd
1
Assembly-free: N
e ei
Kd K d
Store a single Ke (4 kB)
Assembly-Free SpMV
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Million Elements
0
200
400
600
800
1000
Assembled AF-CPU AF-GPU
SpMV; Kd (msec)
770
37
CPU
Assembly-free Kd
Classic Kd
Challenge
How to construct pre-conditioner for K, without assembling K?
Assembly-free deflation
(Agglomeration + rigid body)
Yadav, P., Suresh, K., “Large Scale Finite Element Analysis via Assembly Free Deflated Conjugate Gradient,” Journal of Computing and Information Science in Engineering, Volume 14, Number 4, December 2012
Example
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3.15 million DOF
Multi-core/GPU Friendly
AM Simulation
32
Identify relevant physics
Discretization
Numerical methods
Simulation Results
Experiments
Errors
Preliminary Results
CPU:
– Xeon E5-2620, 2.2 GHz, 8 core
– 32 GB
– C/C++ Code (OpenMP)
GPU:
– GP 100
– 16 GB
– CUDA
Double-precision
Timings include CPU-GPU transfer
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0
200
400
600
800
1000
0 50000 100000 150000 200000 250000 300000 350000 400000 450000 500000
Tim
e(s)
Number of Elements
ANSYS 14.5 Direct
ANSYS 14.5 CGiterative
PareTO FSW
Transient Thermo-Elastic Simulation
34
Friction Stir Welding (only CPU)
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Friction Stir Welding: Accuracy
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0.0E+00
5.0E+06
1.0E+07
1.5E+07
2.0E+07
2.5E+07
0 10 20 30 40 50
Str
ess
(Pa)
Distance from center line
ANSYS 14.5
PareTO FSW
0
100
200
300
400
500
600
0 10 20 30 40 50
Tem
per
atu
re (
Deg
C)
Distance from center line
ANSYS 14.5
PareTO FSW
Temperature Stress
GPU Speed-up
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0
20
40
60
80
100
120
0 10 20 30 40 50 60
Tim
e in
Min
ute
s
Millions of elements
Clock time in minutes
Xeon E5-2620
Nvidia GP100
0
2
4
6
8
10
12
14
16
0 10 20 30 40 50 60
Sp
eed
-up
Millions of elements
GP100 Speed-up
Deflated Assembly-free Kd = f
1 million elements ~ 3 million degrees of freedom
Resolution Map for AM
371 element ~ 3 degrees of freedom
4 20 50 150 500
#ELEMENTS (MILLION)
#Elements for 10x10x10 cm
Single-GPU limit
FDM: Thermal + Phase Change
AM Simulation
39
Identify relevant physics
Discretization
Numerical methods
Simulation Results
Experiments
Errors
40
Friction Stir Welding: Accuracy
[Fehrenbacher, 2014]
ParametersExperimental Parameters used:Force = 3500 NFriction coeff = 0.4
525
530
535
540
545
550
555
50 52 54 56 58 60 62
Experimental Numerical
AM:Verification
LENS (Metal) Process
Technology Transfer
www.sciartsoft.com
AM simulation on the desktop!
Conclusions
1. Strong need for AM simulation
2. Complexity of AM Simulation
3. Assembly-free methods on GPU
4. Current focus on Multi-GPU
Acknowledgements
Praveen Yadav Shiguang Deng Amir M. Mirzendehdel Chaman Singh Alireza Taheri Bian Xiang
Anirudh Krishnakumar Anirban Niyogi Victor Cavalcanti Cameron Gilanshah Yibo Hu Alex Buehler
Funding NSF Air-force Luvata Autodesk Sandia National Lab NVidia