The Design Visualization (DV) group supports work at the Kennedy Space Center by utilizing metrology data with Computer-Aided Design (CAD) models and simulations to provide accurate visual representations that aid in decision-making. The capability to measure and simulate objects in real time helps to predict and avoid potential problems before they become expensive in addition to facilitating the planning of operations. I had the opportunity to work on existing and new models and simulations in support of DV and NASAs Exploration Ground Systems (EGS)

Hemsworth, Paul J.

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NASA KSC – Internship Final Report 
KSC 1 13 04 2018 
 
 
 
 
 
 
 
Learning Reverse Engineering and Simulation with Design 
Visualization 
Paul J. Hemsworth 
John F. Kennedy Space Center 
Major: Aerospace Engineering 
Reverse Engineering and Simulation Spring Session 
Date:  13 04 2018 
 
 
 
  
https://ntrs.nasa.gov/search.jsp?R=20180002689 2019-08-29T18:07:39+00:00Z
NASA KSC – Internship Final Report 
KSC 2 13 04 2018 
Learning Reverse Engineering and Simulation with Design 
Visualization 
Paul J. Hemsworth1 
Embry-Riddle Aeronautical University, Daytona Beach, FL, 32114 
 
Abstract 
The Design Visualization (DV) group supports work at the Kennedy Space Center by utilizing 
metrology data with Computer-Aided Design (CAD) models and simulations to provide 
accurate visual representations that aid in decision-making. The capability to measure and 
simulate objects in real time helps to predict and avoid potential problems before they become 
expensive in addition to facilitating the planning of operations. I had the opportunity to work 
on existing and new models and simulations in support of DV and NASA’s Exploration 
Ground Systems (EGS). 
 
I. Introduction 
The world is too complex for any school to teach students everything they need to know before graduating. 
Therefore, it is beneficial to gain real-world experience through internships and projects. From January to May 2018, 
I had the opportunity to enhance my learning as an intern with the Design Visualization (DV) group at the John F. 
Kennedy Space Center. It has been an incredible experience not only for the hands-on learning but for the chance to 
support Exploration Ground Systems (EGS) as NASA readies the Space Launch System (SLS) and Orion spacecraft 
to carry human explorers farther than ever before. This report outlines several examples of how my learning has gone 
outside of the classroom as I completed tasks involving existing models and the creation of new models.  
II. Working with Existing Models 
This internship provided me the opportunity to deal with models far more complex than anything I had previously 
seen. All the CAD models I dealt with were in a program called CATIA V5, where CATIA is an abbreviation for 
Computer-Aided Three-Dimensional Interactive Application. The Interim Cryogenic Propulsion Stage (ICPS) and the 
Mobile Launcher (ML) are two examples of CATIA models that I worked on. 
A. ICPS    
One of the first tasks assigned to me was to apply materials to a model of the ICPS.  This model was obtained from 
United Launch Alliance (ULA) and contained details down to the screws, nuts, and washers holding the ICPS together. 
These thousands of parts came in all colors of the rainbow and needed to have materials applied to them so that a 
presentable model could be used for planning in meetings. 
While working with the ICPS model, I learned to use the product selection mode to select products and then apply 
materials from a material library that I was given. One of the challenges was to navigate to select internal parts and 
parts in tight spaces. To address this, I moved parts to the hidden space after texturing them so that they would not be 
an obstacle to selecting un-textured parts. Using this approach, I could more easily select parts to apply materials and 
ensure that all parts were being textured. This work also showed me a problem with CATIA V5 that I had not 
previously experienced or known about. It takes time to apply materials and when selecting parts by the hundreds or 
thousands, it took several minutes to complete the operation. For example, applying a material to 300 or more screws, 
washers and bolts could easily take 10 minutes and when I had over a thousand parts selected, I could expect it to take 
around 20 minutes or more. I later found that some sets of screws were contained under the same product and that 
texturing only the highest product level containing those parts could be done in a couple of seconds. Another 
adjustment I made while working with large CATIA models was using the save management feature. When I learned 
CATIA at school, the models were simple, and I did not have to worry about accidentally overwriting parts. Due to 
                                                          
1 NIFS Intern, NE-L1, Kennedy Space Center, Embry-Riddle Aeronautical University. 
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the complexity of the ICPS model and the possibility of overwriting another person’s work, I had to use the save 
management feature to ensure I was only modifying the top-level product. 
B. ML 
Updating an existing model of the Mobile Launcher (ML) was easily 
the most time-consuming project I worked on this spring, but it was 
interesting learning about the ML systems as I worked. Starting with a 
class 5 model (A low detail model omitting things like screws and bolts 
and not as detailed as a class 3 or lower model) containing over 10,000 
parts, I was tasked with applying materials and selection sets to the model. 
This is necessary so that an up-to-date model can easily be used to plan 
processes or solve problems in the future. 
To recreate selection sets, I attempted to use DV’s custom CATIA tool 
to export selection sets from an older model and import them into the 
current one, but this failed due to the renaming of parts between models. 
This meant that I had to manually apply materials and selection sets. I 
found that the search tool helped to some extent after I learned how to use 
it, but I abandoned this approach after realizing that I was selecting parts 
and products that I did not want. It was also challenging at times to know 
what to deactivate when duplicate parts were present because some 
duplicates had matching part and instance names meaning that both would 
be deactivated at the same time even if only one was selected. Deactivated 
parts also caused errors when trying to export selection sets as CGRs 
(lightweight visual representations of objects). To fix this, the selection 
sets affected had to be recreated, which was done quickly by isolating parts 
in the visible or hidden space, selecting them, and making a new set. With all modifications done, the final model 
(figure 1) shows 7,903 parts grouped into 47 selection sets.  
III. Creating Models through Reverse Engineering 
There are several occasions when a model is needed, but an accurate model does not exist. This is when reverse 
engineering using laser scanners is useful.  
A. Hydraulic Pressure Cart (HPC) 
One such reverse engineering task was to create a model of an HPC that is in High Bay 3 of the Vehicle Assembly 
Building (VAB). The Surphaser was used to scan the cart. To do this, scan targets were positioned on tripods and 
magnets around the cart before the scanner could be used to scan the cart from various positions. Scan targets are 
white spheres of known size that can be identified by software when processing the scan data later. I learned that it is 
important for each scan to include at least 3 targets from the previous scan so that the scans can be registered later. 
Another consideration is that a scan should not start facing a target because a slight overlap occurs when the scanner 
rotates, and the target data might not be 
recognizable if the overlap is not clean. The 
Surphaser, like other scanners, has a setting to 
determine the scan resolution in scan lines per 
degree. Resolution affects the time required for 
a scan, so the user must decide how to trade-off 
the level of detail in a scan with the time it takes 
to scan. For the HPC scan, each scan took 
around 12 minutes. We also took photos of the 
HPC cart to help with modeling and texturing. 
 After scanning, the data was processed and 
given to me in the form of an E57 file. This file 
stored the point cloud, which I imported into 
CATIA V5 using one of Design Visualization’s 
custom tools (see figure 2). At first, I was not 
certain of the level of detail needed, but I learned 
Figure 1. The updated class 5 ML with 
materials and selection sets 
Figure 2. Point cloud of HPC scan that has been processed in 
RealWorks and imported into CATIA 
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to focus on overall dimensions of the object in addition to outlets and controls. I also learned to use the compass to 
move parts (The compass is not a tool I needed when modeling objects for assignments at school.). 
 After creating the geometry, I learned how to apply image textures to the model from the pictures taken earlier. I 
learned on my own that CATIA V5’s Photo Studio workbench includes a sticker tool that allows images to be mapped 
to the surface of a model. I thought this was how to apply image textures to models for DV, but I was told that it 
breaks on large models when I asked about using it. Instead, DV showed me the method they use for adding image 
textures. It involves creating a thin new part that is snapped to the model surface and given a material with an image 
texture. The final model is shown in figure 3. 
 
 
      Figure 3. Model of a HPC cart from scan data 
B. Laser Tracker 
Another scanning and modeling task came to me from a customer’s need to position a laser tracker on the High 
Bay 3 platforms. The laser tracker is used to determine the initial coordinates of Space Launch System when it is in 
the VAB. This information is necessary for an avionics box inside the rocket to calculate the position of the rocket 
internally, so the rocket can know where it is even if external tracking is lost. A model of the tracker was needed to 
decide on the tracker’s positioning so that the laser 
could shoot through a service hatch in the vehicle.  
First, the tracker was scanned by the Surphaser 
from 3 positions. Figure 4 shows the scan setup. Each 
scan took around 12 minutes. After scanning, the raw 
scan data was processed in RealWorks. I relied on 
documentation and other DV members to process the 
data as this job was my first time using RealWorks. 
The process started by importing all the scan files and 
then registering the targets with the “Auto Extract 
Targets” tool. This prompted for the type of target 
used (200mm spherical) and a reference scan station. 
RealWorks then found the targets in each scan and 
matched them, which resulted in all 3 point-clouds 
being aligned and placed in the same coordinate 
system with the reference scan station serving as the 
origin. From here, points were extracted from the 
scans using the “Scan Explorer” window. The easiest 
way to select the needed points for extraction was with 
Figure 4. The laser tracker is in the middle surrounded by 
spherical white scan targets. I was standing out of the way as 
the Surphaser on the right was scanning. Behind the camera 
is Devin Swanson who helped me with this scan. 
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a “Key Plan,” which is a top-down view of the scan. After 
extracting the area that included the tracker, more points 
were removed by selection until only the tracker’s point 
cloud remained. A new coordinate system centered on the 
tracker was made by fitting shapes to the point cloud. This 
simplified modeling later. The processed point cloud is 
depicted in figure 5. 
 The tracker was modeled from the point cloud like the 
HPC, but this time kinematics were applied. I learned how 
to use kinematics from a book during week 2 of this 
internship. This provided me with an understanding of 
joint types, degrees of freedom and how to constrain parts 
so they can only move in desirable ways. Even with this 
working knowledge, a couple of problems were 
encountered. After applying geometry-based joints to the 
tracker, I realized I could not move parts in the product 
tree without breaking joints and needing to re-create 
them. This is when I was told to use axis-based joints, 
which I had not encountered in the textbook I read 
earlier. Also, the handles that are created to jog a 
mechanism were reversed so that clicking and dragging 
the arrows to move a joint one way only made it move 
the opposite direction. After experimenting with joint 
creation for a while, I found that the order of geometry 
or axis systems selection affects the handle direction. 
For example, the tracker needed to rotate horizontally 
on the tripod. From the frame of reference of the tripod, 
the tracker should rotate and so the tripod’s reference 
geometry or axis system should be selected first in the 
creation of a revolute joint. When these problems were 
solved, the final model (figure 6) was used to help the 
customer determine where to place the tracker on the 
VAB High Bay 3 platforms. 
C. Man Lift 
More experience in reverse engineering was made by modeling a man lift 
that will be used in the processing of the SLS core stage. I used a TX-8 to scan 
the man lift in an extended and then retracted position. Four targets were 
placed on tripods around the lift and several others were magnetically attached 
to the lift itself. The lift was retracted for 6 scans after conducting 6 scans with 
the lift fully extended. A small problem resulted from retracting the lift 
because the vehicle and the spheres attached to it shook violently in the process 
leading to higher fitting errors in RealWorks when registering the scan later. 
For this reason, I unmatched the targets on the vehicle and used only the 4 
tripod-mounted ones. I performed a station-based extraction of points so that 
the resulting point clouds could be merged into two separate ones for the 
retracted and extended lift positions as shown in figure 7. 
 I encountered difficulty when creating kinematics for the man lift because 
a piston-arm mechanism that raises the basket caused a build error when 
jogging the mechanism. To solve this, I tried to check the alignment of the 
axis systems, experiment with joint combinations and create a simple model 
in another CATIA session to show that the joint combinations worked. None 
of this solved the problem. Kinematic relationships were used to drive other 
joints in the model and so I decided that the same might need to be done for 
the piston and arm. A discussion about the problem with DV revealed that 
CATIA’s chain link solver function stopped working as soon as kinematic 
Figure 7. Man lift scan data in 
RealWorks with both the extended and 
retracted lift point clouds. The green 
plane was fitted to the lift arm and 
used to create a user-defined 
coordinate system. 
Figure 5. Processed point cloud of the laser tracker in 
RealWorks. The orange triangles represent the scanner 
locations. 
Figure 6. Completed laser tracker model with image 
textures and kinematics 
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relationships were made to keep the lift’s basket level. This was the cause of the build error and the solution was to 
add kinematic relationships to all joints without commands. Defining the kinematic relationships for the piston and 
arm was not difficult because the parts make a triangle. That said, I had some confusion involving angle units for 
kinematic relationships because CATIA’s documentation does not clearly state that radians are used regardless of the 
user setting all angle units to degrees. All these issues were solved after a while and the completed model is seen in 
figure 8. The lessons I learned while creating this model will help me in the future, and I hope they help others as well. 
 
 
Figure 8. Completed CATIA model of the man lift with the piston-arm mechanism 
defined using kinematic relationships 
D. SRB Aft Skirt 
The ROMER Absolute Arm is another metrology 
instrument that I learned to use during my internship. To 
begin, there is a mock-up solid rocket booster (SRB) based 
on those of the Space Shuttle in the VAB. Although similar 
to the Space Shuttle SRBs, the SRBs that will power SLS 
have modifications. For this reason, a group requested a 3D-
scan of the mock-up aft skirt so that an umbilical attachment 
could be printed and attached to more accurately reflect what 
SLS will have. The ROMER arm was chosen for its ability to 
scan corners and create a mesh that can be exported as a 3D-
printable Stereo Lithography (STL) file. 
 Scanning with the ROMER arm differs from scanning 
with the TX-8 and Surphaser because of the proximity to the 
object being scanned and ability to move the scan head. We 
set up the ROMER arm beneath the section of the aft skirt 
that needed to be scanned and completed the scan. Since the 
ROMER arm scanner operates at a short distance from the 
object and the part to be scanned was above our heads (see 
figure 9), it was tiring and awkward at times to move the arm. Nevertheless, we produced what the customer needed, 
and I enjoyed learning to use the ROMER arm while standing beneath a SRB. 
 
Figure 9. The author using the ROMER arm under 
the SRB aft skirt. On the left is Rich Overleese and 
behind the camera is Devin Swanson, who both helped 
me tremendously during the internship.  
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IV. Conclusion 
This internship experience has been an interesting and unique learning opportunity that is unlike anything a student 
can find at school. I encountered and overcame challenges in the work done this spring, which has made me more 
effective at CAD modeling and simulations. The methods I learned for making kinematics and texturing in CATIA 
have unique advantages that I would probably never learn at school. I received an introduction to RealWorks, which 
I was unaware of before this internship and I now understand the usefulness of 3D scanners and trackers in engineering. 
In the remaining three weeks of the internship, I hope to learn more about metrology and CAD modeling in addition 
to 3D printing, the wiring harness assembly in CATIA and inverse kinematics. I hope to use the skills gained from 
this experience in the future to contribute to solving the world’s engineering challenges and specifically America’s 
space exploration goals.  
Acknowledgments 
Thanks to Adam Luchner, Alden Pitard, Devin Swanson, Jeffrey Bonggren, Rich Overleese, Robert Edwards and 
Robert Humeniuk of the Design Visualization team. 
 
Additional thanks to David Macon for mentoring me. 
 
 


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