The document investigates the effect of different internal structures for parts fabricated using fused deposition modeling. Finite element analysis and experiments were conducted to validate the accuracy of the simulation. Topology optimization was used to design improved internal structures. Results showed that for low pressure, sparse double dense structure had higher displacement than solid, while topology optimization was closer to solid. For high pressure, topology optimization had much lower stress than other structures, though it had longer build time. The study validated the simulation accuracy and provided guidance on choosing internal structures.

1. Effect of Sparse-build Internal Structure
on the Performance of Fused Deposition
Modeling Parts
SHIXUAN MENG
GRADUATE COMMITTEES MEMBERS:
Dr. MING C. LEU
Dr. K CHANDRASHEKHARA
Dr. HAILUNG TSAI

2. Objectives
• Investigate the effect of pressure environment on deformation,
stiffness for different internal structure of an autoclave molding tool
• Compare finite element analysis and experiment results to validate
the accuracy of SolidWorks FEA simulation solver
• Predict model performance in pressurized environment after the
FEA solver accuracy is proved

3. Outline
• Introduction
 Background
• Validation model optimization
 Model specification
 Design of sparse double dense pattern
 Topology Optimization
o Volume constraint topology optimization
o Improved Design
• Finite element analysis with partial pressure
• Experimental validate with partial pressure
 Test results
 Experiment verification
• Full pressure model optimization and finite element analysis
 Topology optimization
 Finite element
• Result and Conclusion

4. Outline
• Introduction
 Background
• Validation model optimization
 Model specification
 Design of sparse double dense pattern
 Topology Optimization
o Volume constraint topology optimization
o Improved Design
• Finite element analysis with partial pressure
• Experimental validate with partial pressure
 Test results
 Experiment verification
• Full pressure model optimization and finite element analysis
 Topology optimization
 Finite element
• Result and Conclusion

5. Background
• 0 - 0.689 MPa (0-100 psi)
• 25 – 177 oC (77-350 F)
3. After elevated temperature curing
cycle, resin is harden and part is ready
to use
1. Soft composite
fabric and uncured
resin are placed on
the mold
2. A vacuum is
used to keep the
composite fabric
and resin close to
the molding tool

6. Fused Deposition Modeling
1. CAD 2. Slice and generate toolpath
3. Fabrication 4. Finished part
• Three Top Cap Layers
• One Contour Layer with Internal Structure
• Three Bottom Cap Layers
Build
material
Support
material
Liquefier
Extrusion tip
Feed
motor
X
Z

7. Stratasys Fortus 400mc
• Accuracy: +/-.127mm or Up to +/- .0381 per mm
Tip cleaning station
Dual extrusion print head
(Build, support)
Heated chamber
Vacuumed print bed
Model material canister
Support material canister
40.6cm
35.6cm

8. Outline
• Introduction
 Background
• Validation model optimization
 Model specification
 Design of sparse double dense pattern
 Topology Optimization
o Volume constraint topology optimization
o Improved Design
• Finite element analysis with partial pressure
• Experimental validate with partial pressure
 Test results
 Experiment verification
• Full pressure model optimization and finite element analysis
 Topology optimization
 Finite element
• Result and Conclusion

9. Validation Model Optimization (mm)
Radius: 263.12
Radius: 263.12
A partial pressure testing tool is designed based on autoclave molding tool and
make it possible to experimentally verified the effectiveness of this method
Base load
head
Pressure
Top load
head

10. Design of Sparse Double Dense
Pattern
1 Contour @ 0.6604 mm (0.026 in)
Y-axis
X-axis
Raster width
@ 0.6096 mm
(0.024 in)
Raster angle
45 degree
SDD only

11. Topology Optimization
• Topology optimization is an effective methods to reduce weight while reduce the maximum
von Mises stress
• This method filter out mesh that has the lowest von Mises stress until objective is met after
FEA
• Possible objectives are: Volume constraint, maximum displacement constraint, or factor of
safety constraint
von
Mises
stress

12. Validation Model Topology Optimization
1. Initial model
2. Define boundary
conditions and design space
6. Finite element validation
3. Filter out the lowest local
Von Mises stress nodes until
requirement is met
4. Finalize topology optimization
to match material usage to
sparse double dense
5. Smoothing and generation
of FEA validation file
?

13. Redesign Based on Topology
Optimization
• Since length is fixed, width is adjusted to make volume identical to sparse double dense
• Redesigned geometry is generated with the help of probe coordination trend lines
• Build time reduced from 92 minutes to 73 minutes, maximum displacement was improved by
4.1 % according to FEA, Maximum von Mises is reduced by 2.3% due to force concentration
improvement
• Better appearance where interior is visible
Raw
topology
optimization
Redesign
based on
raw TO
model
Redesign
?

14. Cross Section Comparison
Raw:
Redesign:
36th layer36th layer 27th layer 18th layer 9th layer 1st layer
36th layer 27th layer 18th layer 9th layer 1st layer

15. Outline
• Introduction
 Background
• Validation model optimization
 Model specification
 Design of sparse double dense pattern
 Topology Optimization
o Volume constraint topology optimization
o Improved Design
• Finite element analysis with partial pressure
• Experimental validate with partial pressure
 Test results
 Experiment verification
• Full pressure model optimization and finite element analysis
 Topology optimization
 Finite element
• Result and Conclusion

16. SolidWorks FEA Validation
Rigid load head
1 degree of freedom in
Z direction
Rigid fix bottom
load head
Evenly distributed pressure field on load head
Maximum displacement @ 30 MPa
(mm)
Maximum von Mises Stress @ 30 MPa
(MPa)
Solid 2.19E-01 14.651
Sparse double dense 2.67E-01 59.136
Topology optimization 2.24E-01 18.064
X-axis
Z-axis

17. Outline
• Introduction
 Background
• Validation model optimization
 Model specification
 Design of sparse double dense pattern
 Topology Optimization
o Volume constraint topology optimization
o Improved Design
• Finite element analysis with partial pressure
• Experimental validate with partial pressure
 Test results
 Experiment verification
• Full pressure model optimization and finite element analysis
 Topology optimization
 Finite element
• Result and Conclusion

18. Partial Pressure Experiment Results
Solid
Sparse Double Dense
Topology Optimization
• Since tolerances during fabrication, and
measurement exists, the displacement
point starts slightly different for each
part
• Linear data is needed to make results
more comparative
Displacement (mm)
Pressure(MPa)Pressure(MPa)Pressure(MPa)
Displacement (mm)
Displacement (mm)
Average slope of 5 linear portion
of solid compression test
New 0 for Strain and
Displacement
Pressure(MPa)
Displacement (mm)

19. Geometry Validation
Before compression
(mm)
After compression
(mm)
Percent difference
Average Width Height Width Height Width Height
Solid 76.42 9.20 76.50 9.15 0.09% -0.50%
Sparse double dense 76.42 9.25 76.43 9.23 0.00% -0.22%
Topology optimization 76.29 9.22 76.37 9.16 0.10% -0.66%
• A coordinate measuring machine is used
to measure the dimension before and
after partial pressure experiment
• A small plastic deformation occurred @
30 MPa, Therefore a smaller plastic
deformation is expected @ 0.689 MPa
• The results are based on the average
reading of 5 specimens

20. Partial Pressure Verification
The accuracy of the FEA solver is proved by the Partial Pressure Experiment
0
0.05
0.1
0.15
0.2
0.25
0.3
Solid SDD TO
FEA
Experiment
FEA displacement @ 30 MPa
Displacement(mm)
Maximum displacement (mm)
FEA Experiment Difference
Solid 0.219 0.2002 9.34%
SDD 0.267 0.2483 7.49%
TO 0.224 0.2114 5.92%
Percentage increased in maximum displacement
compare with Solid
FEA Experiment
SDD TO SDD TO
21.92% 2.28% 24.01% 5.58%

21. Outline
• Introduction
 Background
• Validation model optimization
 Model specification
 Design of sparse double dense pattern
 Topology Optimization
o Volume constraint topology optimization
o Improved Design
• Finite element analysis with partial pressure
• Experimental validate with partial pressure
 Test results
 Experiment verification
• Full pressure model optimization and finite element analysis
 Topology optimization
 Finite element
• Result and Conclusion

22. Full pressure Topology Optimization
1. TO result with low mesh density
Max. Disp.: 0.73 mm
3. Medium mesh density
Max. Disp.: 0.18 mm
5. High mesh density
Max. Disp.: 0.046 mm
4. Mid-high mesh density
Max. Disp.: 0.05 mm
?
6. Numerical analysis
2. Mid-low mesh density
Max. Disp.: 0.25 mm
Topology optimization study with different mesh size shows mesh
size dependency, therefore a numerical study is needed to find out
all possibilities
Maximum deformation

23. • Redesign was done imitating the raw
topology optimization and considered the
manufacturability
• FEA is studied using different numbers of
stiffener
• The higher number of stiffener does not
necessary mean improvement in
performance
• In this case 10 Stiffeners is the optimal
design
5 stiffeners 10 stiffeners
15 stiffeners 20 stiffeners
Topology Optimization Numerical Study
0
5
10
15
20
0 5 10 15 20 25
Maximum von Mises stress with
different number of stiffners
MaximumVonMisesstress(MPa)
Number of stiffners
0
0.01
0.02
0.03
0.04
0.05
0 5 10 15 20 25
Maximum displacement with
different number of stiffners
Maximumdisplacement(mm)
Number of stiffners

24. FEA Resultant Displacement @
.689476 MPa
• In autoclave full pressure
environment the displacement
difference is more significant
• Although sparse double dense
has less displacement, topology
optimization has a higher safety
factor

25. FEA Z-direction Displacement @
.689476 MPa

27. Dimples Close Look
• Dimples occurs in the center of air
gap due to the lack of support
behind the shell
• The deformation is maximized at the
edge where lack of horizontal and
vertical direction support

28. -5.2E-3 mm
-5.8E-3 mm -6.2E-3 mm

29. Full size model local deformation
Maximum z-direction local deformation= B – A
= -0.00533 – (-0.00420)
= -0.00113 mm
A B
SDD
TO
Maximum z-direction local deformation= B – A
= -0.00576 – (-0.00361)
= -0.00215 mm
A B
Y-axis
Z-axis
Y-axis
Z-axis

30. Outline
• Introduction
 Background
• Validation model optimization
 Model specification
 Design of sparse double dense pattern
 Topology Optimization
o Volume constraint topology optimization
o Improved Design
• Finite element analysis with partial pressure
• Experimental validate with partial pressure
 Test results
 Experiment verification
• Full pressure model optimization and finite element analysis
 Topology optimization
 Finite element
• Result and Conclusion

31. Partial Pressure FEA Comparison
• Topology optimization has a
small displacement that is
close to solid built
• Sparse double dense is the
fastest internal structure to
build for the same amount
of material
• If stiffness and material
usage are the main concern,
topology optimization is the
best internal structure for
compression application

32. Full Pressure FEA Comparison
• At 25oC (77 F), solid has the
best mechanical performance
• Sparse double dense is the
fastest internal structure to
fabricate in three designs, it
has a 3.3% less maximum
displacement compare to
redesigned topology
optimization.
• Redesigned topology
optimization offers 35.5% less
maximum Von Mises stress
than sparse double dense.

33. Conclusions
In the partial pressure FEA model @ 30MPa:
• Design with sparse double dense internal structure has 21.92% higher maximum
displacement compare to solid.
• Redesigned topology optimization only has 2.38% higher.
• In the partial pressure experiment @ 30 MPa:
• Parts with sparse double dense internal structure have an average of 24.01% higher
maximum displacement compare to solid.
• Redesigned topology optimization parts only have an average of 5.58% higher.
In the full pressure FEA model @ 0.689 MPa:
• Redesign topology optimization model has 26.25% higher maximum displacement compare
to design with sparse double dense internal structure and 981.08% higher maximum
displacement compare to solid design.
• Design with sparse double dense internal structure has a maximum von Mises stress that is
87.71% higher than Redesign topology optimization, and 7784% compare to solid.
• In partial pressure FEA model, the build time of redesigned topology optimization is 53%
longer than solid, and 102% longer than model with sparse double dense internal structure.
• In full pressure FEA model, the build time of redesigned topology optimization is 131%
longer than solid, and 217% longer than model with sparse double dense internal structure.

34. The Fortus 400mc machine successfully manufactured all testing tools with a tolerance between -0.17% and +0.5%; the testing tools are fabricated
with ULTEM 9085 material to validate the mechanical properties with FEA study results. The performance differences between the FEA solver and
experimentation are from 5.92% to 9.34%. The accuracy of the solver has been proven with different internal structure through validation process,
therefore the predictions of the parts’ performance are made for a full pressure environment at room temperature.
In the partial pressure FEA model at 30MPa:
The sparse double dense internal structure has an average of 21.92% higher maximum displacement compared to the solid internal structure.
The redesigned topology optimization has an average of 2.38% higher maximum displacement compared to the solid internal structure.
In the partial pressure experiment at 30 MPa:
The sparse double dense internal structure has an average of 24.01% higher maximum displacement compared to the solid internal structure.
The redesigned topology optimization has an average of 5.58% higher maximum displacement compared to the solid internal structure.
In the full pressure FEA model at 0.689 MPa:
The redesigned topology optimized internal structure has a 32.20% higher maximum displacement compared to the sparse double dense internal
structure and 905.40% higher maximum displacement compared to the solid internal structure.
The sparse double dense internal structure has a maximum von Mises stress that is 21.89% higher than the redesigned topology optimized
internal structure, and 501.33% higher von Mises stress than the solid internal structure.
Fabrication performance is predicted using Stratasys Insight 10.2. Since topology optimization software does not include designing for additive
manufacturing, the build time and amount of support material are larger than the sparse double dense internal structure. Even though the
redesigned topology optimization uses the same amount of build material as the sparse double dense internal structure, the build time is much
longer among different designs.
In the full pressure FEA model, the build time of the redesigned topology optimization is 53% longer than the solid internal structure, and 102%
longer than the sparse double dense internal structure.
In the full pressure FEA model, the build time of the redesigned topology optimization is 131% longer than the solid internal structure, and 217%
longer than the sparse double dense internal structure.

35. Reference
[1] Chua C. K., Leong K. F. and LIM C. S., "Rapid prototyping: Principles and Applications," Vol. 1, page 124-129
[2] Stratasys: http://usglobalimages.stratasys.com/Main/Files/Best%20Practices_BP/BP_FDM_VariableDensity.pdf?v=635817995040925513,
2015
[3] O. Iyibilgin, M. C. Leu, G. Taylor, H. Li, and K. Chandrashekhara, " Investigation of Sparse-Build Rapid Tooling by Fused Deposition
Modeling," Solid Freeform Fabrication Symposium, 2014
[4] Philip A. Browne, "Topology Optimization of Linear Elastic Structures," University of Bath Department of Mathematical Sciences, 2013
[5] INSTRON: http://www.instron.us/en-us/our-company/library/glossary/c/compression-test, 2015
[6] Adhiyamaan Arivazhagan, S.H. Masood, “Dynamic Mechanical Properties of ABS Material Processed by Fused Deposition Modeling, 2012
[7] INSPIRE SolidThinking:
http://resources.altair.com/hyperworks/pdfs/product_brochures/HW13_sT_Inspire.pdf?__hstc=240259932.d9c42b3867ab6a1a10104805f986bf5
c.1435775566918.1435775566918.1441045887752.2&__hssc=240259932.1.1441045887752&__hsfp=2415725232&_ga=1.242785602.139175
4687.1435775584 , 2015
[8] Stratasys: http://www.stratasys.com/materials/fdm/~/media/83DA2BBEE7DE4A669CFEF6B1FCA118AA.ashx, 2015
[9] Stratasys:
http://usglobalimages.stratasys.com/Main/Files/White%20Papers/WP_FDM_Fortus360mc400mcAccuracyStudy.pdf?v=635787005291964002,
2015
[10] Renishaw: http://www.renishaw.com/en/first-metal-3d-printed-bicycle-frame-manufactured-by-renishaw-for-empire-cycles--24154, 2015
[11] Ming C. Leu, K. Chandrashekhara, "SPARSE-BUILD RAPID TOOLING BY FUSED DEPOSITION MODELING FOR COMPOSITE
MANUFACTURING AND HYDROFORMING," 2014
[12] SolidWorks: http://help.solidworks.com/2014/english/solidworks/cworks/c_analysis_solvers.htm, 2015
[13] H. Li, G. Taylor, V. Bheemreddy, O. Iyibilgin, M. Leu, K. Chandrashekhara, "Modeling and characterization of fused deposition modeling
tooling for vacuum assisted resin transfer molding process", 2015
[14] Sigmund, M.P., "Topology Optimization: Theory, Methods and Applications, Springer.", 2002

36. Questions?