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TRANSCRIPT
Falcon Fever
Submitted in Response to the Real World Design Challenge
Submitted by Falcon Fever
On 4/5/13 Davenport West High School
3505 W Locust St. Davenport, IA 52804
Objective Function Value: 576,826.6 Team Member Names
Amber Sawvell: [email protected] (Business Specialist) 563-579-3116, 11th grade, age 17 Carina Grady: [email protected] (Mission Specialist) 563-517-7876, 10th grade, age 16
Eli Shellabarger: [email protected] (Project Manager) 563-508-0053, 12th grade, age 17 James Larson: [email protected] (Communications Specialist) 563-940-9495, 10th grade, age 15
Pardeep Saini: [email protected] (Flight Specialist) 563-579-4979, 11th grade, age 17 Tuyen Nguyen: [email protected] (Mission Specialist) 563-940-1867, 10th grade, age 16
Coaches and Mentors
Jason Franzenburg, Coach: [email protected] Greg Smith, Coach: [email protected]
Alexander Richardson, Aerospace Engineering, Sophomore at Iowa State University: [email protected] Ben Pickering, Sr. Aircraft Mechanic, Rockwell Collins: [email protected]
Chris Miser, CEO of the Falcon UAV: [email protected] Crist A. Rigotti, Sr. Engineering Manager, Rockwell Collins: [email protected]
Derek Attwood, Structural Engineer, Boeing: [email protected] Jeramie Vens, Electrical Engineering, Senior at Iowa State University: [email protected]
Jim Voytilla, Aerospace Engineer, FAA: [email protected] John Goorsky, Aerospace Engineering, Sophomore at Iowa State University [email protected]
Julie Kim, Mechanical Engineer, Exelon Nuclear: [email protected] Matthew Geraghty, Systems Engineer, Rockwell Collins: [email protected] Pat Sheehey, Language Arts Teacher, West high School: [email protected]
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I. Abstract
The project goal for this challenge is to design a UAS which will fly under the given constraints to
save a missing person while considering mission time and cost. The UAV is designed based on
component dimensions, material selection, and challenge requirements. The sensor payload was
selected based on resolution, altitude, and search radius. The search pattern and sensor information
determined altitude. The ground equipment and search pattern was selected based on optimizing
flight time and minimizing cost.
Falcon Fever designed a UAS which operates two UAVs simultaneously in order to effectively
search the given area in the least amount of time. The first of the UAVs is larger and operates using a
glowfuel powered GL-25 engine with 7 pounds of fuel. The fuselage has a surface area of just under
440 in2 which weighs 9.24 pounds. The wings have a planform of 450 in2, a wingspan of 64 inches,
and weigh 5.21 pounds. The tail design is a V-tail with a dihedral angle of 32 degrees, planform area
of 86 in2, and weight of 1.22 pounds. The total weight of the first UAV is 28 pounds including fuel and
components.
The second UAV is smaller and operates using a glowfuel powered GL-12 engine with 2.5 pounds
of fuel. The fuselage has a surface area of just 367 in2 which weighs 7.17 pounds. The wings on this
UAV are identical to that of the larger design. The tail design is a V-tail with the same dihedral angle,
but a surface area of 62 in2 and a weight of 0.91 pounds. The total weight of the second UAV is 21
pounds including fuel and components.
The first UAV flies at an altitude of 800 ft above ground with a flight speed of 80 mph while
scanning Zones 1 and 2. The second UAV flies at an altitude of 885 with a flight speed of 64 mph
while scanning Zone 3 and a small section of Zones 1 and 2. Both UAVs are equipped with an
X1000 sensor for detection and X3000 sensor for identification. The total flight time to scan the entire
area is 59.9 minutes, resulting in a total operational time of 9 hours.
The total initial cost of the first UAV is $50,074.35 and the second is $49,862.86. The ground
station has a total cost of $39,039.58, bringing the initial cost to $139,039.58. The cost of fuel per
mission is $100.32 and the hourly operating cost for personnel is $925. This brings the cost of
performing 50 missions $577,789.58, resulting in an objective function 576,826.6.
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II. Table of Contents
I.Abstract ............................................................................................................................................. ii
II.Table of Contents ............................................................................................................................ iii
III.List of Tables .................................................................................................................................. vi
IV.List of Figures ............................................................................................................................... vii
1.Team Engagement ........................................................................................................................... 9
1.1. Team Formation and Project Operation ................................................................................... 9
1.2. Acquiring and Engaging Mentors ........................................................................................... 10
1.2.1 Coaches .......................................................................................................................... 11
1.2.2 Near Peers ...................................................................................................................... 12
1.2.3 Local Mentors .................................................................................................................. 12
1.2.4 Long Distance Mentors ................................................................................................... 13
1.3. Project Goal ........................................................................................................................... 13
1.4. Tool Set Up/ Learning ............................................................................................................ 14
1.5. Impact on STEM .................................................................................................................... 15
V.Document the System Design ...................................................................................................... 19
1.6. Design Phases ....................................................................................................................... 19
1.2.5 Conceptual Design: Many Candidates ............................................................................ 19
1.2.6 Preliminary Design: Few Candidates .............................................................................. 20
1.2.7 Detailed Design: One Final Solution ................................................................................ 29
1.2.8 Lessons Learned (Learning Curve) ................................................................................. 32
1.2.9 Project Plan ..................................................................................................................... 32
1.7. Detailed Aerodynamic Characterization ................................................................................. 33
1.2.10 AeroData Characterization ........................................................................................... 33
1.2.11 Airfoil Validation ........................................................................................................... 35
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1.8. Selection of System Components .......................................................................................... 36
1.2.12 Propulsion System ....................................................................................................... 36
1.2.13 Sensor Payload ............................................................................................................ 37
1.2.14 Ground Station Equipment ........................................................................................... 43
1.2.15 Additional UAV/UAS Equipment .................................................................................. 46
1.9. Aircraft Geometric Details ...................................................................................................... 47
1.2.16 Wing Configuration ...................................................................................................... 47
1.2.17 Tail Configuration ......................................................................................................... 48
1.2.18 Fuselage ...................................................................................................................... 48
1.10. System and Operational Conditions ................................................................................... 49
1.11. Components Flight Vehicle Weights and Balance .............................................................. 50
1.12. Maneuver Analysis ............................................................................................................. 52
1.13. CAD Models ....................................................................................................................... 52
1.2.19 UAV 1 CAD Models...................................................................................................... 52
1.2.20 UAV 2 CAD Models...................................................................................................... 53
1.14. Three Views of Final Design ............................................................................................... 55
1.2.21 UAV 1 Dimensions ....................................................................................................... 55
1.2.22 UAV 2 Dimensions ....................................................................................................... 56
VI.Document the Mission Plan ......................................................................................................... 57
1.15. Camera Footprint ................................................................................................................ 58
1.16. Search Pattern .................................................................................................................... 60
1.17. System Detection and Identification ................................................................................... 64
1.18. Example Mission ................................................................................................................ 65
1.19. Mission Time and Resource Requirements ........................................................................ 67
1.2.23 Manpower Requirements: Ground Crew ...................................................................... 67
1.2.24 Calculated Time ........................................................................................................... 69
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VII.Documents the Business Case .................................................................................................. 71
1.20. Identify Target Commercial Applications ............................................................................ 71
1.2.25 Determine Other Uses for the UAS .............................................................................. 71
1.2.26 What Could Be Achieved if Regulatory Restrictions Were Eased? .............................. 71
1.21. Amortized System Costs .................................................................................................... 72
1.2.27 Initial Cost of System ................................................................................................... 72
1.2.28 Direct Operational Costs per Mission ........................................................................... 74
1.2.29 Amortization ................................................................................................................. 74
1.22. Market Assessment ............................................................................................................ 75
1.23. Cost/Benefits Analysis and Justification ............................................................................. 76
VIII.References .................................................................................................................................. 77
IX.List of Symbols, Abbreviations, and Acronyms ........................................................................ 79
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III. List of Tables
Table 1 - Material Decision Matrix ............................................................................................ 28
Table 2 - AeroData Worksheet ................................................................................................. 35
Table 3 - Propulsion ................................................................... Error! Bookmark not defined.
Table 4 - Sensors Selection ..................................................................................................... 41
Table 5 - Shelter/Trailer ............................................................................................................ 45
Table 6 - Ground Crew Equipment ........................................................................................... 46
Table 7 - Ground Crew Components........................................................................................ 47
Table 8 - UAV 1 Weight Balance .............................................................................................. 51
Table 9 - UAV 2 Weight Balance .............................................................................................. 51
Table 10 - Ground Crew Personnels ........................................................................................ 69
Table 11 - Initial Cost ............................................................................................................... 73
Table 12 Direct Operational Cost ............................................................................................. 74
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IV. List of Figures
Figure 1 - Falcon Fever Interviewing Chris Miser ..................................................................... 11
Figure 2 - Falcon Fever Visiting Rockwell Collins .................................................................... 11
Figure 3 - Zone Diagram .......................................................................................................... 13
Figure 4 - Swept Blend Error Figure 5 - Swept Blend Fixed................................................ 15
Figure 6 - Eppler Airfoil FloEFD Results ................................................................................... 22
Figure 7 - E216, NACA 6412, and NACA 6416 Airfoil Comparison .......................................... 23
Figure 8 - Fuselage Modular Casing Top View ........................................................................ 24
Figure 9 - Fuselage Modular Casing Bottom View ................................................................... 24
Figure 10 - Sketching Around Modular System ........................................................................ 25
Figure 11 - Solid Front End Section (inner components shown in red) .................................... 26
Figure 12 - Sketching for Tail Section ...................................................................................... 26
Figure 13 - Completed Preliminary Fuselage Design ............................................................... 26
Figure 14 - Material Properties ................................................................................................. 27
Figure 15 - E216 AoA of 0 Degrees ......................................................................................... 30
Figure 16 - PMI Foam .............................................................................................................. 31
Figure 17 - Gantt Chart ............................................................................................................ 33
Figure 18 - Eppler 216 Cl vs Cd ............................................................................................... 34
Figure 19 - Eppler 216 Cl vs AoA ............................................................................................. 34
Figure 21 - Sensor.................................................................................................................... 37
Figure 22 - Sensor Resolution .................................................................................................. 38
Figure 23 - X1000 .................................................................................................................... 40
Figure 24 - X3000 .................................................................................................................... 42
Figure 25 - Infrared Comparison .............................................................................................. 43
Figure 26 - Ground Station ....................................................................................................... 45
Figure 27 - UAV Comparison ................................................................................................... 49
Figure 28 - UAV 1 Isometric View ............................................................................................ 52
Figure 29 - UAV 1 Front View .................................................................................................. 52
Figure 30 - UAV 1 Top View ..................................................................................................... 53
Figure 31 - UAV 1 Side View .................................................................................................... 53
Figure 32 - UAV 2 Isometric View ............................................................................................ 53
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Figure 33 - UAV 2 Front View .................................................................................................. 54
Figure 34 - UAV 2 Top View ..................................................................................................... 54
Figure 35 - UAV 2 Side View .................................................................................................... 54
Figure 36 - UAV 1 Front Dimensions........................................................................................ 55
Figure 37 - UAV 1 Top Dimensions .......................................................................................... 55
Figure 38 - UAV 1 Side Dimensions ......................................................................................... 55
Figure 39 - Zone Comparison .................................................................................................. 57
Figure 40 - Zones 1 and 2 Footprint ......................................................................................... 58
Figure 41 - Zone 3 Footprint ..................................................................................................... 59
Figure 42 - Flight Path Brainstorm............................................................................................ 60
Figure 43 - Spiral ...................................................................................................................... 61
Figure 44 - Butterfly .................................................................................................................. 61
Figure 45 - Lawnmower ............................................................................................................ 61
Figure 46 - "Zamboni" .............................................................................................................. 62
Figure 47 - “Zamboni” Before-After .......................................................................................... 62
Figure 48 - Complete "Zamboni" .............................................................................................. 63
Figure 49 - Modified "Zamboni" ................................................................................................ 63
Figure 50 - Two UAVs .............................................................................................................. 64
Figure 51 - Falcon UAV ............................................................................................................ 75
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1. Team Engagement
1.1. Team Formation and Project Operation
Amber, the business specialist, has taken many business and engineering classes
which have proved useful when optimizing the Objective Function. She worked as a
researcher for materials, tails, and propulsion systems. This is Amber’s second year as
a Falcon Fever team member. She helped manage the team’s dynamics and organized
meetings with mentors.
Carina, the team's mission specialist, collaborated and communicated with Tuyen
and Pardeep to determine the most efficient search pattern. Once the pattern was
chosen, she helped Pardeep refine the waypoints to reach the lowest and most practical
time possible. Carina worked on the example mission, and with the help of Tuyen, laid
out mission plans that the Unmanned Aerial Systems (sUAS) would perform to save the
missing child. Carina was responsible for creating visual aids to illustrate a conceptual
understanding of the mission.
Eli, the project manager, earned his role because of his performance during the
2011-2012 RWDC competition. Over the course of the challenge, Eli kept members on
task while assigning roles where team members expressed interest. In addition to being
the project manager, Eli spent a large amount of time working with the aerodynamic
aspects under the guidance of his mentor, Boeing engineer, Derek Attwood. Eli’s
calculations confirmed the plane had ample lift and that the fuselage would hold all the
components while remaining aerodynamic.
James, the communications specialist, facilitated communication between the
mentors and the team members. He focused research on basic aeronautics, structural
design, Unmanned Aerial Vehicles (UAVs), and sensor payloads. James played a major
role when making decisions related to the selection of an airfoil. He utilized Falcon
Fever's mentors by sending out weekly emails letting mentors and coaches know what
the team had accomplished in the previous week.
Pardeep, the flight specialist, worked with Tuyen to determine a final camera
footprint for the flight mission. With help from the team, Pardeep tested possible search
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patterns. After collaborating with James to determine the formation of a final search
pattern, Pardeep concentrated his time laying out waypoints for a flight path that would
successfully work to save the missing child. Teaming up with Carina, he helped
optimize mission time to be as low as possible.
Tuyen, the mission specialist, is part of the flight planning team that included finding
information about sensor capabilities and selecting a sensor payload. Tuyen was in
charge of the ground crew selection and helped Carina with planning a complete
mission. She was responsible for the tables that went along with the sensors and
ground crew.
Team: While Falcon Fever has recognized individual accomplishments, the team
took flight. On average, the team met four times a week including Saturdays, totaling 10
to 12 hours per week for each team member. Over the holiday break and spring break,
the team met as a group for approximately 25 to 30 hours per week. Recommended by
Mr. Smith, the team scheduled “mandatory fun” to bowl, eat, and ice skate. The team
took time to get to know one another outside the workplace so they could develop a
strong bond.
1.2. Acquiring and Engaging Mentors
Falcon Fever worked continuously with local, state, and national mentors. The team
coaches, Mr. Smith and Mr. Franzenburg, helped initiate contact with mentors. As the
challenge progressed, coaches turned communications over to team members.
Local mentors Julie Kim, Jeramie Vens, and Matthew Geragthy visited the team in
person. At the state kick-off event, Falcon Fever team members were introduced to and
worked with Iowa State University “Near Peers”. Near Peers, who are undergraduate
aerospace engineering students at Iowa State University, were assigned to teams in
Iowa. The team’s Near Peers traveled to Davenport for a design review with the team.
At the national level, Derek Attwood mentored the team from his home in Philadelphia.
Julie Kim, Derek Attwood, and Jeramie Vens returned as mentors from last year’s
competition.
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The team pursued many new mentors and used Skype, email, phone, Windchill, and
Skydrive to communicate problems, concepts, and solutions. The Gantt chart, created
by members, helped engage mentors by focusing on deliverables and milestones.
Frequency of communication varied from mentor to mentor. Coaches and mentors were
contacted daily, weekly, or bi-weekly.
The team investigated real life UAVs by calling
Chris Miser, the manufacturer of the Falcon UAV
that was featured in Time Magazine, February 13th.
Chris Miser’s UAV has a similar design to Falcon
Fever’s state UAV. Drawing on his experience, the
team developed a conceptual understanding of how
the UAV would work in real life.
With the help of the coaches, the team also had
an opportunity to visit Rockwell Collins where
aviation innovation is in development every day.
The team met with Crist Rigotti and Ben Pickering
for a tour of the test hanger. Crist Rigotti then
showed the team his recreational UAV that he
assembled himself. It gave the team a chance to
look at a fully operational UAV.
1.2.1. Coaches
Greg Smith is the newest addition to the Project Lead the Way (PLTW) engineering
staff at West High School. He is in his eighth year of teaching Technology Education
and he has coached RWDC for two years. Besides being the coach and mentor, he
helped organize the team and has provided resources to accomplish tasks.
Jason Franzenburg is the senior member of the PLTW engineering staff at West
High School. He is in his eleventh year of teaching Technology Education and this is his
second year coaching RWDC. Besides being the coach and mentor, he recruited all of
the team members from his PLTW Engineering classes. He helped the team brainstorm
and use the design process effectively.
Figure 1 - Falcon Fever Interviewing Chris Miser
Figure 2 - Falcon Fever Visiting Rockwell Collins
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1.2.2. Near Peers
Alexander Richardson helped the team brainstorm ideas for a conceptual design.
He explained the importance of conceptual design and how it affects the design
process. Skype was used to discuss the technical report, and he provided useful
feedback.
John Goorsky came to West High School to help work on the project. He provided
advice on team management and engineering notebook standards.
1.2.3. Local Mentors
Crist Rigotti is the manager of installation design at Rockwell Collins. As a hobby,
Crist builds and flies UAVs and once held the world record for flight distance, flying a
recreational UAV over 106,000 feet and back without incident. He provided the team
valuable information on UAV performance, structural integrity, parts interaction, and
data interpretation provided during flight. Crist invited the team back to fly his UAV.
Jeramie Vens is a senior at Iowa State University studying electrical engineering.
He helped determine the most efficient Objective Function and helped with math
equations to determine engine efficiencies. Jeramie assisted the team when selecting
software that allowed multiple users to update and edit the same document
simultaneously without compromising page layout.
Julie Kim, a mechanical engineer at Exelon Nuclear, was the most active mentor
and helped out with the complex flight pattern equations for the UAV. Along with
Jeramie, Julie helped with the equations for determining engines and unit conversions.
Julie was there for the whole team via email if anyone had any questions with math or
any conceptual understanding relating to the UAV. She met with the team every
Saturday.
Matthew Geraghty works as a systems engineer at Rockwell Collins and is the
RWDC Iowa state coordinator. Matthew took part in editing the team’s tech report and
organized feedback from the judges at the state competition.
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Pat Sheehey, a language arts teacher at Davenport West High School, provided
major editing support. After her recommended corrections, the team read through the
technical report and collaborated on revisions.
1.2.4. Long Distance Mentors
Chris Miser, the owner/designer of Falcon UAV, provided feedback to the team
about UAV design. Chris gained his experience in the Air Force as a UAV design
specialist. The team contacted Chris after reading a Time Magazine article in which his
search and rescue UAV was featured. The team noticed his design was similar to their
state design, and thus conducted a phone interview with him as to why he chose the
features offered in the Falcon UAV. Chris was able to give input on the process of
selecting an airfoil for a small UAV as well as verifying several design choices.
Derek Attwood, a structural design engineer at Boeing in Philadelphia, is currently
working on the 787-project where he coordinates, redesigns, and handles problems the
parts supplier may have with the design. He provided an abundant amount of input in
determining a proper airfoil for the team to use as well as figuring a proportionate size
for the UAV.
Jim Voytilla, an aerospace engineer at the Federal Aviation Administration (FAA),
helped review the team's design progress. Jim provided feedback assisting in airfoil
selection and helped simplify complicated equations for flight planning.
1.3. Project Goal
The project goal for this challenge is to design an
Unmanned Aerial System (UAS) which would perform
a Search and Rescue (SAR) mission under the given
constraints to locate a missing child with the smallest
rescue mission time and cost possible. The UAS is
designed to be used for surveillance; no warfare of
any kind will be performed in relation to this design.
Constraints for this challenge must follow all FAA
guidelines. Those guidelines pertaining to UAVs were Figure 3 - Zone Diagram
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provided as part of the challenge. The search area is divided into three zones which
have various tree heights offering different complications. Zone 1 has no trees and no
line of sight restrictions. Zone 2 has medium-height trees, with the line of sight
restriction of a cone with 30 degree off vertical. Zone 3 has tall trees and has the line of
sight restriction of a cone with 15 degree off vertical.
The flight altitude for the UAV must be between 150 and 1,000 feet above ground
level (AGL), assuming ground level is 8,000 feet above sea level. The maximum take-
off weight must be less than 55 pounds. When taking off at the starting position, the
UAV must be able to clear a 50 foot obstacle (vertical) within 300 feet (linear). Any
antennas on the UAV must be placed at least eighteen inches apart to avoid destructive
interference. All options for control hardware, sensor payloads, and video datalinks
were given in the provided detailed background material. The team had to choose the
hardware and components based on what is needed to operate their UAV.
Each team is required to submit an Objective Function value. The Objective
Function equation is shown below.
T is the total time in hours to find the missing child given the worst case scenario
where the child is found in the last area scanned during an example mission. It takes
into account refueling time, but not the time it takes to return to base when the mission
is over.
C is the fully loaded cost of building the system and completing the example mission
fifty times.
1.4. Tool Set Up/ Learning
Mentors, coaches, and the district software technician helped the design team learn
to utilize the software. The coaches managed the process and communicated with the
district software technician about software installation. The team is satisfied with the
completion of the software simulations. This success means more to the team as they
had to overcome difficult challenges dealing with software. Troubleshooting is a very
important skill in engineering, and it was used heavily during software issues. Last year,
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Gear Up provided Falcon Fever with two efficient laptops to run the advanced programs
such as MathCAD, Creo, and FloEFD.
This year, Falcon Fever had little trouble with MathCAD. In general, the worksheet
performed as it was supposed to with few problems. The only major problem the team
encountered with MathCAD was installation. Because of the school district’s security
and firewall system, MathCAD was only usable when the school’s network was
connected to the computer being used. When the team occasionally had to go to their
local public library, the laptops would not run MathCAD. The students discovered the
software had been installed incorrectly so that the program relied on the school’s
network to function. Eventually, the district software technician fixed the problem.
Creo had similar network license issues. When the team was making a new
fuselage, they encountered a problem with the swept blend feature. While attempting to
blend the sketched sections of the fuselage together, the blend feature caused the
fuselage to create randomized shapes, some resembling a drill bit as shown in Figure 4.
After trying multiple design strategies over the course of the week, the sketches blended
properly once the correct sequence was discovered.
Figure 4 - Swept Blend Error Figure 5 - Swept Blend Fixed
1.5. Impact on STEM
Science: Basic knowledge in science and especially in physics is critical in the
design of the UAV. Without that knowledge, there would be a poor understanding of
aerodynamics, propulsion, and conceptual interpretation in takeoff, landing, flying, etc…
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Technology: Knowledge of programs such as Mathcad, Creo, Windchill, and
Microsoft Office programs is important to move to the next step of tasks. In addition, if
one did not know how to use a certain program, participating in the Aviation Challenge
provided an excellent opportunity to learn. Technology is more than just software
programs; it is making use of systems to solve a problem or to reach a goal. In the
future, more opportunities will arise where there will be a need to learn new software
and technology.
Engineering: Engineering, including the design process, is a critical part in the
Aviation Challenge. Engineering is applying science, math, and technology to solve
problems, but it applies other factors too: team effort, social skills, business skills, and
economic skills. Teamwork is important in the Aviation Challenge; the success of the
team rests on each individual’s participation and task completion. Business and
economic knowledge is important to ensure the UAV is realistic.
Mathematics: An understanding of math is important in the challenge. Formulas
and data are provided in the detailed background. Unit conversions are a large part of
the math in the challenge. Although it is easy to be overwhelmed by math, the skills
learned will be valuable in the future.
STEM has impacted everyone on the team. The RWDC challenge provided a great
opportunity to apply STEM to find a solution.
Amber: When Amber was first introduced into the PLTW courses in middle school,
she took interest because they were hands-on classes; PLTW was not about sitting
down and reading a book for an hour just to write a two page paper on it. Before this
project and Amber's civil engineering class, she was set on accounting for her career.
She enjoys math because she understands it well. After this project, Amber does not
want to forget about engineering; it incorporates all of the STEM subjects: science,
technology, engineering, and math. "There's more to just designing something, when
you create something, there will always be math involved," said Amber Sawvell. Amber
plans to go into industrial engineering and economics as a joint degree. Being a cost
engineer has crossed her mind, which incorporates both business practices and the
design aspect of engineering. Science and technology go hand-in-hand because they
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work together to make the design come alive. Amber is very grateful she has been
exposed to STEM and has had the chance to be a part of this project. She is excited
and cannot wait to have a career in engineering. Amber’s dream project is to produce
products in a cost effective environmentally friendly way.
Carina: Since sixth grade, Carina has always been interested in engineering, but it
was her teachers and parents who encouraged her to pursue the field since she was
good at both math and science. Throughout middle school, she went to many
engineering programs and learned many things about what engineers do. She has
received many opportunities to learn about different engineering fields, including civil,
industrial, genetic, mechanical, chemical, and now, after joining RWDC, aerospace
engineering. Taking PLTW courses offered in her high school helped shape her goals
and experiences. It is not an exaggeration to say that STEM really has affected her life
and will affect her future since she will definitely go into a STEM-related career. Carina’s
dream project is to create clean air solutions that would combat hazardous diseases.
Eli: Eli has always been intrigued by the aerospace industry, whether it is airplanes,
rockets, space shuttles; the list goes on. The ability to get off the ground has always
been a very interesting topic. At Eli’s school, there are no classes that cover this
subject. He first became involved with the RWDC last year when he worked with CAD
designs for the team all the way up to the national competition. He feels that his
success has helped prepare him for next year when he will leave for Iowa State
University to major in Aerospace Engineering. "It is not often that you get an opportunity
like what this challenge presents, a chance to work with real life tools to solve a real life
problem," says Eli. STEM is a very important aspect in Eli's life concerning his career
goals, and he plans to continue learning as much as he can about the wide variety of
subjects. Eli’s dream project is to design supersonic jets such as the SR-71 Blackbird
and NASA X-15.
James: Ever since James was a little kid he has always enjoyed math and science
and throughout the years he has enjoyed engineering and technology just as much.
James’s brother is a mechanical engineer who has motivated him to take a closer look
at engineering. Robotics initially piqued his interest because of mechanical aspects, and
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after the RWDC experience, James is looking into aeronautical engineering. When
James entered his sophomore year of high school he wanted to be more involved in
engineering because he planned to pursue it in college. He signed up for a PLTW class
and joined the RWDC team because he was interested in aeronautics. As he continues
through high school, James plans on taking more PLTW classes and staying on the
team. James’s dream project is to work on supersonic military jets such as the F-22
Raptor.
Pardeep: Pardeep’s interest in engineering started in his freshman year when
studying drafting and design. He decided to take PLTW classes because of the hands-
on approach to learning. Pardeep learned that STEM is important in solving problems.
He joined RWDC because he wanted to learn more about engineering in real-life
situations. Because of his experiences in RWDC, he is leaning more towards an
aerospace degree. Pardeep’s dream goal is to produce the next line of space travel.
Tuyen: Tuyen was first introduced to PLTW in middle school and was interested in
the hands-on activities that the classes offered. In her freshman year of high school, she
started taking PLTW courses and became interested in an engineering career. She
loved the hands-on activities and how the class challenged one's abilities to think of
problems and solutions in a different mindset. STEM is very important in all types of
engineering. For the future, Tuyen is going to stay in the engineering field and plans to
obtain an engineering degree in a yet-to-decided field. STEM will continue to be very
important in her future career. Tuyen hopes to apply her knowledge to develop self-
contained energy systems for third-world countries.
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2. Document the System Design
2.1. Design Phases
The design phases are categorized by parts of the UAV: wing geometry, fuselage,
material, tail. Each design phase will state and explain how decisions were made. The
report is divided into sections between conceptual, preliminary, and detailed design
phases.
2.1.1. Conceptual Design: Many Candidates
For conceptual design, a qualitative method of investigation was used where the
team focused on samples of many desired UAV characteristics. Through the design
process, mathematical problem-solving, case studies, market research, data
interpretation, interviews, mentor recommendation, and verification of ideas, the team
selected solutions that optimized criteria for UAV performance.
2.1.1.1. Wing Geometry
Initially, research was completed on the optimal airfoil. Selecting the optimal airfoil
was critical; otherwise, the UAV would not fly. The team sent an email to a mentor,
Derek Attwood, for recommendation on an airfoil. Derek recommended a high camber,
NACA 4-digit series airfoil. Chris Miser was interviewed and recommended a low
Reynold’s Number Eppler airfoil.
2.1.1.2. Fuselage
During the first week after the challenge was released, Falcon Fever brainstormed
different types of fuselages. The team considered both rotorcraft and fixed-wing
designs. Next, Falcon Fever looked at the lift required for each style of aircraft. A
rotorcraft requires more power to generate the same amount of lift when compared to a
fixed-wing design, and therefore is less efficient. It was determined that the increased
maneuverability and hovering abilities that rotorcraft provides does not outweigh the
more efficient wing design. It was decided that a fixed-wing design was the most
efficient design in terms of power consumption.
Another idea was to make the UAV easily adaptable for equipment updates. During
an interview with Chris Miser, he mentioned that cameras for UAVs will be outdated
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within about a year at today’s rates of technological innovations. For this reason, Falcon
Fever wanted to design a fuselage that would make it easy to swap out sensors for
future updating.
2.1.1.3. Material
Brainstorming was conducted on factors that would impact material selection.
Different types of external materials and internal structural components were evaluated.
Crist Rigotti, a mentor with UAV-building and flight experience, walked the team through
a UAV material orientation. Research on aluminum, carbon fiber, fiberglass, epoxy,
polyester, Kevlar, titanium, steel, and foam was performed. Although there were no
structural components or analysis in the challenge, the team wanted to be
comprehensive in their design considerations. Falcon Fever considered having one of
the following for their core structure: a rib structure, a solid core, or a hollow sheeted
core.
2.1.1.4. Tail
Falcon Fever conducted market research on numerous tails, specifically looking for
properties including stability, take-off lift, weight distribution, surface area, drag,
aerodynamics, manufacturing, and safety. The team considered tail designs such as the
V-tail, T-tail, H-tail, Y-tail, conventional tail, and the inverted V-tail.
The V-tail and T-tail have small surface area and a balanced shape. The H-tail and
Y-tail are less common tails that have more surface area, but they have unique shapes.
The H-tail tends to break air flow because of its shape. The conventional tail and
inverted V-tail are directly related to the T-tail and V-tail. They have the same amount of
surface area, only features are flipped which affects balance of the tails. After
researching six different tail designs, the V-tails and conventional tail proved to be the
most aerodynamic, easily manufactured, and safe.
2.1.2. Preliminary Design: Few Candidates
Possibilities were ruled out from the conceptual phase so that there would only be a
few candidates left for the wing geometry, fuselage, material, and tail. In the preliminary
design phase, the team compared each remaining design element to determine which
one proved to be the most suited selection relative to the desired UAV.
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2.1.2.1. Wing Geometry
The team initially decided to run two-dimensional tests on the final airfoils from the
state challenge, the NACA 6412, and another airfoil very similar to it, the NACA 6416.
Airfoil comparisons were performed that would limit the amount of unnecessary
changes to the FloEFD settings. Tests were ran at 64 MPH because that is the max
speed Falcon Fever’s UAV can fly in Zone 3, and temperature was set at 59 degrees
Fahrenheit as that is the standard daytime temperature. To fully understand each
airfoil’s limits, fourteen tests were conducted on each airfoil considered, each test
featuring a different angle of attack (AoA). Testing started with an AoA of negative six
degrees and increased the AoA by intervals of two degrees all the way to a final point of
20 degrees. In the Computational Fluid Dynamics (CFD) tests, the horizontal force
would represent drag and the vertical force would represent lift. When the tests were
completed, the team took the average value of the horizontal force and the vertical force
from each AoA and put them into an Excel worksheet in order to plot and make
analyzing the data easier. This range of tests on the NACA 6412 and 6416 provided the
team with a deep understanding of how each airfoil could perform.
After finishing the tests of the NACA airfoils, there was still time left to test even
more airfoils. When Chris Miser reported about different components of his UAV, he
explained that he used an Eppler airfoil. Interested in the new thought, the team went to
the University of Illinois at Urbana-Champaign’s (UIUC) airfoil database to look at their
Eppler airfoil selection. The team knew that their UAV had a low Reynolds Number so
they knew how to search the database for desired airfoils. The UIUC database
contained around thirty airfoils that were relevant to Falcon Fever’s UAV. Starting at the
beginning of the list, the team randomly chose about half the airfoils in order to still have
a good variety to test while not spending a large amount of time comparing all thirty
choices. In the end, sixteen low Reynolds Number Eppler airfoils were chosen.
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Figure 6 - Eppler Airfoil FloEFD Results
To manage time more efficiently while testing Eppler airfoils, an AoA of zero degrees
on all sixteen airfoils was chosen as a constant variable to compare against each other.
After the FloEFD tests were completed, the e216 airfoil was chosen because it had the
most lift out of the sixteen airfoils. To have more information on the airfoil, the team
used the same AoA test format used on the NACA airfoils on the e216. When the AoA
tests were completed, the e216 with an AoA of 0 degrees produced about 6 pounds of
force (lbf) in a two-dimensional FloEFD test, the NACA 6412 produced 5 lbf, and the
NACA 6416 produced 3.8 lbf.
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Figure 7 - E216, NACA 6412, and NACA 6416 Airfoil Comparison
2.1.2.2. Fuselage
With decisions made to create an innovative modular system in order to update
plane technologies, it was clear that to design a proper fuselage the skeleton of the
modular system had to be created first. To do this, it had to be decided which
components would need to be incorporated in this system. After deliberation, it was
decided that the components that needed to be included in the modular system were
the motor and two sensors. With this information, a case was created to hold the three
parts, as shown in Figures 8 and 9.
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Figure 8 - Fuselage Modular Casing Top View
Figure 9 - Fuselage Modular Casing Bottom View
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Once the casing had been designed, design efforts were concentrated on the
surrounding fuselage. It was decided that it would be more manageable to design the
rest of the fuselage in Creo instead of using OpenVSP. Using Creo would allow the
team to view the aerodynamics of their design using FloEFD, whereas objects created
in OpenVSP are unable to be simulated in a wind tunnel test. From there it was on to
deciding the shape of the fuselage. At first, there was confusion as to how to go about
shaping the front of the UAV as the desired engine, the GL-12, stuck out oddly and was
not symmetrical. However, after looking at some other designs used in real life, the
team noticed that many UAVs have a bulbous front end in order to store needed
components. With this in mind, sketches were created that would become the outside
shell. Once these sketches were completed, they were blended together into the final
fuselage shape.
Figure 10 - Sketching Around Modular System
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Figure 11 - Solid Front End Section (inner components shown in red)
Figure 12 - Sketching for Tail Section
Figure 13 - Completed Preliminary Fuselage Design
2.1.2.3. Material
With the help of Julie Kim, research was done on the materials for the outer shell
and found the definition of longitudinal, transverse, tensile, and compressive strength.
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Longitudinal strength is the vertical strength as if it were pulled apart. The transverse
strength would be the horizontal strength. The difference between tensile and
compressive strength is that tensile strength pulls apart, and compressive strength
pushes inward.
Figure 14 - Material Properties
The deciding factors in choosing the outer shell material were structural strength,
cost, and weight. Steel and titanium were eliminated from the preliminary design phase
due to the fact that they are heavy and expensive materials. Kevlar can withstand
extreme temperatures and chemicals, but carried a high price and was more than the
team needed. Fiberglass was not chosen since its strength-to-weight ratio is not
efficient for this application. Using any type of foam for the outer shell was also a
concern in the case that the UAV would be handled or used in rough conditions. The
aluminum alloy and carbon fiber both have a similar structural strength, but ultimately
the aluminum alloy was chosen since carbon fiber is approximately four times the cost.
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A hollow core with a rib structure and a solid core were compared to structural
aspects. A hollow core with a rib structure and a solid core were compared to view
structural aspects. In comparison to the solid core, the hollow core provides space for
UAV components and has the same structural strength. Considering the small size of
the wings, it was decided that there would be no true benefit to a rib structure as it
would nearly be a solid by the time it was constructed. Components could still be placed
in the wing as long as it was properly reinforced in those sections.
The team then looked into different types of materials that could be used as a solid
interior, but they kept in mind that the UAV could not be too heavy or expensive. There
was, however, a list of properties that were necessary to consider: high strength, light
weight, flexibility, and density. The fact that foam is used in many remote controlled
(RC) aircraft and thus well-known helped make this decision. After reassessing, only
three materials were left: polymethacrylimide foam (PMI), polyurethane foam, and
ethafoam.
When looking at having a hollow core with a rib structure, Falcon Fever did not want
the UAV to be minimally supported on areas such as the wings or tail nor worry about
pinch-points where they connected to the fuselage, having a low weight but strong solid
core would eliminate these concerns. The team looked into different types of materials
that could be used as a solid, but they kept in mind that the UAV could not be too heavy
or expensive. There was, however, a list of properties that were necessary to consider:
high strength, light weight, flexibility, and density. The fact that foam is used in many
remote controlled (RC) aircraft and thus well-known helped make this decision.
After reassessing polymethacrylimide foam (PMI), polyurethane foam, and ethafoam
were the only three left to compare and contrast. Comparing the three foams, the team
acquired the following information as shown in Table 1.
Table 1 - Material Decision Matrix
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2.1.2.4. Tail
The team placed more weight on the V-tail over the conventional tail after using the
following criteria: aerodynamics and manufacturing.
Reducing drag is a key aerodynamic property. The V-tails produce less drag
because of less surface area. In contrast, the conventional tail produces more drag
because there is more surface area. V-tails are well balanced, aerodynamic, and take
advantage of the Pythagorean Theorem. The Pythagorean Theorem is A2 + B2 = C2,
where A, B, and C represent sides of a right triangle. Sides A and B represent the
vertical and horizontal surfaces of a conventional tail, while side C represents a wing
with a dihedral angle that replaces sides A and B, in this case being the V-tail.
Takeoff and landing with a V-tail is less stable when compared to a conventional tail,
which is why it is not seen more often on larger aircraft. However, with a catapult
launch mechanism, take off is reduced to a fraction of the time it would take for an
aircraft using a runway, thus making this a negligible effect.
In an interview with Chris Miser, the team asked why he chose the V-tail over the
conventional tail for his UAV. He stated that the V-tail has less parts and less assembly,
which results in cost savings and the performance is not sacrificed. The V-tail removes
one element from the conventional tail, resulting in cost effectiveness through an easier
manufacturing process. With all these factors considered, selection was narrowed down
to the two V-tail designs.
2.1.3. Detailed Design: One Final Solution
To refine the selected solutions, the team went into detail and received a valuable
insight to how the solution would work in relation to wing Geometry, fuselage, materials,
and tail selection. For the detailed design, one final solution was selected after
optimizing considerations in the preliminary design.
2.1.3.1. Wing Geometry
After all the FloEFD testing was completed, the test results showed that the Eppler
216 (e216) had the most lift while not having an excessive amount of drag. The e216’s
main competitor was the NACA 6412 which was the airfoil used for the state challenge.
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Initially, the team wanted to stick with the NACA 6412 because they knew of its
reliability. However, after running the FloEFD tests on the e216 twice, the better choice
for their desired UAV was the NACA 6412 because it had more lift while still having the
same amount of drag.
Figure 15 - E216 AoA of 0 Degrees
As seen in Figure 15, the blue streamlines above the airfoil is fast moving air which
creates a low pressure bubble. The green streamlines beneath and to the rear of the
airfoil is slow moving air which creates a high pressure bubble. Having fast moving air
above the airfoil and slow moving air below the airfoil are important to having a high lift
airfoil for a relatively slow moving aircraft.
2.1.3.2. Fuselage
When the time came to finalize the fuselage, a few factors were left to consider.
Since there are two UAVs with two separate flight paths (refer to section 2.5 and 3.2),
the design had to be viable for both flight paths. After some initial testing, they soon
discovered that while the fuselage worked for the UAV destined to fly through Zone 3
(UAV 2), it was not adequate for the UAV which had to fly through Zones 1 and 2 (UAV
1). The problems encountered included not having enough fuel and the engine not
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being powerful enough. To solve this, the engine size had to be increased on UAV 1
from the GL-12 to the GL-25 and the fuel capacity had to be doubled. This then resulted
in the fuselage needing to be resized in order to fit a larger engine and store extra fuel.
To do this, the team rolled back the Creo model to the initial modular system design.
They increased the engine box sizing so that the new engine would fit and made other
necessary changes to sketches to complete the similar but refined design for UAV 1.
2.1.3.3. Material
Taking price and weight into consideration, aluminum was selected as the exterior
material. Aluminum alloy 7001-T6X is a strong, light weight, cost effective, and
commonly used in aerospace industry.
The interior material selection is a solid core filled with PMI foam. PMI is high density
foam which causes it to be stronger as it molds together. PMI foam is chemical
resistant, dense, lightweight and holds its shape when low amounts of heat are present.
Having a solid core is beneficial because it makes the UAV structurally sound. PMI
foam only fills the area that does not have any type of components present. Areas such
as the wings and tail are filled with PMI foam.
Falcon Fever decided that the fuselage would house the engine and parts of the
sensors. Two out of the three antennas are mounted to the wings, and the fuel tank is
contained inside the wings. Figure 16 is a cross-section view of what the tail may look
like with foam material added. The gray top sheet represents the aluminum outer shell
on the UAV, and the inner material is PMI foam.
Figure 16 - PMI Foam
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2.1.3.4. Tail
During their interview with Chris Miser, Falcon Fever had discovered that the
inverted V-tail has a few downfalls. The tail may produce large drag if it does not fit with
the aerodynamics of the UAV. Also, when landing with an inverted V-tail there is a risk
of a tail strike which would damage the tail wings. However, the standard V-tail does not
have these issues. Falcon Fever thus ruled out the inverted V-tail and selected the
standard V-tail for its safety, aerodynamics and manufacturing cost.
2.1.4. Lessons Learned (Learning Curve)
Because there were only three returning members, Falcon Fever’s biggest learning
curve for this year was time management. All team members either had part-time jobs
or played sports. For that reason, having all team members present at the same time for
a meeting was difficult. During the beginning of the challenge, three members left the
team; however, another two members joined in their absence. The team used Windchill
to store files for organization purposes. The team learned to hit the save button often
because of the possibility of computers crashing. Rewriting work is never fun and is not
being time efficient.
There were a number of technical challenges the team had to overcome. The team
had frequent Internet connection issues at school and had to work around it. There was
the challenge of learning how to use programs such as FloEFD and Creo in a fast and
efficient manner. The team learned through the design phase that trial and error is
needed to find successful data, to know how things works, to know what is practical and
impractical, and how improvement could always be brought into a design. The team
learned how to evaluate components from dozens of choices to a few and how to
evaluate components to choose the best one.
2.1.5. Project Plan
Since the beginning of the challenge, each team member was assigned specific
tasks to work on different components of the challenge. The team had a calendar of
meeting times that was updated frequently to make sure all of the members would show
up on time and know when to come. Every week, the team coaches would sit down with
the team to discuss goals and kept the team on track.
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Falcon Fever used many different methods to stay on schedule with the design
phases, including writing weekly goals the team wanted to accomplish, and following
the Gantt chart to stay on task. James sent weekly emails to mentors that would include
what Falcon Fever had been doing the entire week and any questions the team had.
Figure 17 - Gantt Chart
2.2. Detailed Aerodynamic Characterization
2.2.1. AeroData Characterization
The Eppler 216 was chosen for its ability to perform well at the low Reynold
Number that the UAV would be operating at. This was confirmed when Falcon Fever
used the airfoil analysis software JavaFoil to find the Coefficients of Lift and Drag. The
results, shown below, were quite pleasing to the team.
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Figure 18 - Eppler 216 Cl vs Cd
Figure 19 - Eppler 216 Cl vs AoA
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Table 2 - AeroData Worksheet
2.2.2. Airfoil Validation
This year, selecting the correct airfoil was essential to completing the challenge.
Falcon Fever went through 18 airfoils to identify the one that matched their UAV the
best. Out of those 18 airfoils chosen, there were 16 Eppler airfoils and 2 NACA airfoils.
The team ran AoA tests on three airfoils that Falcon Fever felt had promising results,
the E216, the NACA 6412, and the NACA 6416. Ultimately, the Eppler 216 proved to be
the best airfoil as described during the design process.
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2.3. Selection of System Components
Research was conducted on UAS components to determine which features are
desired for the SAR mission. System components are key when finding the missing
child in a timely manner. The design process was used to select the propulsion system,
sensor payload, and ground station equipment.
2.3.1. Propulsion System
Examination of the detailed background showed propulsion system performance
options. Gas powered engines and electric engines were the two main options. The GL-
6, GL-12, and GL-25 were gas powered run by glow fuel. The GA-55 and GA-110 were
gas powered run by octane. The E-6, E-20, and E-70 were electrical powered. Power,
practicality, efficiency, and cost were used as criteria to narrow down the propulsion
candidates to a selected few.
First considerations pointed to the electrical engine due to the benefit of not having
to refuel, little vibrations, and battery power. However, after further research on the
UAV's capabilities, it was determined that the power from one battery would not be
enough. The UAV will require multiple batteries to sustain the flight mission.
Consequently, the team looked into the gasoline powered engine. Gas has a better
power-to-weight ratio, meaning that the engine can get a lot more power out of a pound
of gas in comparison to how much power the engine can get from a pound of batteries.
Weight management is a big gain when compared to batteries that have to be replaced
or recharged often. Because of this important fact, the team agreed that using a gas
powered engine would be the best choice to use for the desired UAV.
After eliminating the electric engine, attention was given to types of gas engines.
There were a total of five choices for gas engines, three of which were GL engines that
uses glow fuel and two GA engines that uses octane gas.
During the design process, testing started with the GA-55 engine, but after the size
of the UAV was reduced, UAV power needs was cut down. Through the mission
analysis worksheets, engine performance is calculated, and after several trial and error
calculations, it was determined that the GL-12 engine met the mission power needs.
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When the team finished their search pattern (refer to section 3.2), the UAV needed a
higher power gas engine if they wanted to keep their time to under an hour. To achieve
the desired time, either the search pattern or a different engine would need to be
selected to keep the Objective Function low.
Since there would be two UAVs (refer to section 2.5) the engine for each UAV would
have to be considered. The team decided that UAV 2, the one flying over Zone 3 would
have the GL-12 engine with 2.5 pounds of fuel. The amount of fuel is calculated using
the mission analysis worksheet. The UAV flying over Zones 1 and 2, however, would
need to have more power since the UAV will go faster. The team decided to have the
UAV in Zones 1 and 2 would have the GL-25 engine with 6 pounds of fuel. Selecting
gas engines that do not need to refuel with a flight mission time of under one hour and
achieve desired speeds in different zones allowed the UAVs to reach optimal
performance.
2.3.2. Sensor Payload
There are five sensor payloads provided in
the sensor payload catalog in the detailed
background. They range from the X1000 sensor
to the X5000 sensor. The sensors are all daylight
electro-optical, gyro-stabilized cameras which
allow the sensors to dampen motor vibrations.
This permits lower shutter speeds so that the
longer lenses can provide greater clarity and an
improved range of recognition. The vibrations would not be a problem if the sensor is
placed next to an engine. Daylight imaging allows the sensor to have a high-resolution
colored camera.
Figure 20 - Sensor
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The video camera inside the
sensor payload views objects as
pixels on a computer monitor. A pixel
is a square of color that, when
bunched together, makes an image.
An object's appearance depends on
how far away they are from the
camera. Figure 22 illustrates the
viewing of computer images by
ground crew.
The object has to be able to reach a
specific number of pixels before it could be recognized by the sensors. Figure 22 letter
(c) shows that the object has to be eight pixels wide in order to reach the minimum
detection resolution. If the object is not wide enough, the sensors would not be able to
register the image. If the sensor is equipped with the video scanning software, it could
register the object with the width of just 4 pixels, as shown in Figure 22 letter (d). This
allows the UAV to fly at a higher altitude and still achieve detection. For identification,
the confirmation resolution is 20 pixels. If the cluster of pixels does not reach the
minimum requirement for the resolution, the sensor would not be able to register an
object.
Different sensor payloads favor different altitudes. Some payloads could easily
detect at a high altitude while others are not able to reach the minimum detection
resolution. Other things that distinguish the payloads apart from each other are the
range of their field of view, which is the degree in which the camera can pan.
2.3.2.1. One Sensor vs. Two Sensors
Each sensor provided in the detailed background favors specific ranges of flight
altitudes and speeds that would influence the design of the UAV. The team wanted to
design the UAV around the selected sensors to maximize the ability of the sensor
payloads since the selection of sensor(s) would directly influence the mission flight plan.
Figure 21 - Sensor Resolution
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With only one sensor, after possibly detecting the missing child in a mission
scenario, the UAV would have to circle back to where the sensors had detected an
object and run through that area again to confirm the finding. With one sensor, the UAV
would have to fly at a lower altitude as well as with a lower flight speed to be able to
achieve confirmation. Confirmation can occur after detection, so then the UAV would
have to circle back to the same coordinate of the detection to be able to start the
identification scan.
With two sensors, the UAV is theoretically able to detect and confirm if an object is
the missing child or a false detection while maintaining its course and speed. The
detection sensor would be able to detect an object at a high altitude, and after detection
has occurred, the second “identification” sensor can pitch and roll throughout the
detection radius of sensor one while maintaining altitude to either confirm the missing
child or determine if it was a false detection. It is assumed that sensor one, after
achieving detection, will instantaneously communicate with sensor two to start
confirming.
With the two sensor scenario, the identification sensor requires a large identification
radius. Since the UAV maintains altitude and speed, the area that the sensor detected
the missing child will rapidly move out of frame. While traveling at high speeds and
altitudes, the identification sensor has a large enough radius to pitch and roll back to the
detection circle and still be able to identify. To achieve this, the identification sensor
would have to have a low Telescopic Field of View (TFOV) which ultimately affects cost.
One sensor versus two sensors could represent one of the most important questions
in the challenge: should cutting down time be higher priority than cutting cost? With one
sensor, the initial cost will be lower since there is only the cost of one sensor. However,
one sensor sacrifices time since the UAV would have to fly back to the coordinates in
which it had detected an object for confirmation. Before the UAV could confirm, it has to
lower its altitude and speed. When a false detection occurs, the UAV takes time to climb
to the desired altitude. While gaining and losing altitude, the footprint of the sensor
changes and it leaves spots in the search pattern that has not yet been searched.
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Decisions were ultimately made to have two sensors rather than one because the
time outweighed cost in the challenge. With two sensors, cost is greater; however,
having two sensors for the UAV would have the capability to detect and confirm almost
simultaneously after detection, helping the UAV to maintain altitude and flight speed.
2.3.2.2. Detection sensor
With the thought of two sensors in mind, the team split up into groups, each working
with the Excel sheet provided by RWDC to pick two cost effective sensors that could
detect and identify at relatively high altitudes.
After thoroughly researching the information about sensors in the detailed
background, the team decided to fly at an altitude of 800 feet AGL. The baseline altitude
was selected because of optimal performance for the X2000. Testing through Excel
worksheets needed to take place on all sensors to find the most suitable sensor for the
mission. Through experimentation, it was discovered that the X1000 sensor can perform
as well as the X2000 and other sensors at an 800 feet altitude with a field of view of 40
degrees.
It was an important piece of information since the X1000 was only $8,000 and the
X2000 was $25,000. The deciding factor for choosing the X1000 over the X2000 was
cost.
Figure 22 - X1000
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2.3.2.3. Identification Sensor
The criteria for the identification sensor were similar to the detection sensor. A flying
altitude of 800 feet and a large identification radius (more than 1000 feet) was
recognized as a need. Cost was another factor in picking an identification sensor.
For the identification sensor, there was a choice between the X2000, X3000, X4000,
and the X5000 sensors. The X1000 was not a part of the identification sensor selection
because it could not zoom to meet the identification radius that was desired. The X2000
was eliminated as an identification sensor because the Telescopic Field of View (TFOV)
at a full zoom was 40 degrees which resulted in a maximum altitude of 183 feet to
achieve identification, subsequently following in an identification radius of 11 feet.
The X3000 sensor could fly at an 800 feet altitude and still be able to identify. The
TFOV of the X3000 sensor is 5.5 degrees. With this, the identification radius on the
ground would be 1067 feet. Although the X3000 met the criteria, more testing was
needed. Continuing to investigate the other sensors, the team found the results in Table
4 with the desired altitude of 800 feet.
Table 3 - Sensors Selection
All three sensors met desired requirements, and cost became a determining factor.
The X4000 and X5000 were eliminated because of the cost-to-identification ratio. The
identification radius needs to be close to 1000 feet to be able to identify an object from
the altitude of 800 feet, and the X4000 and X5000 have a larger identification radius,
which is not needed. All of the sensors have the capability to identify at the altitude of
800 feet, but the X3000 is the most cost effective. As a result, the X3000 was chosen to
be the identification sensor.
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Figure 23 - X3000
2.3.2.4. Innovation
For innovation, Julie Kim helped brainstorm sensors not found in the detailed
background. Possible ideas included a color-filter sensor and an infrared sensor. The
color-filter sensor idea came about from how a green screen works in television. The
idea behind it was that the boy was wearing a blue jacket, and using a blue color filter,
all colors with the exception of blue will be filtered.
Infrared sensors were thought to be the most practical for research. Heat can be
detected by infrared sensors and could be used to help the confirmation of the missing
child. If the child is under a tree, the infrared sensor can detect the child, reducing the
chance of error of skipping over the child.
Infrared sensors would assist the X3000 in the confirmation of the missing child. In a
mission scenario, the X1000 detects the missing child. Communicating instantaneously
with the X3000 and an infrared sensor, confirmation occurs. No additional cost would be
needed for crew; the only cost involved with adding in an infrared sensor is the actual
sensor itself and a total of $1200 for suited equipment.
The idea of using an infrared sensor was a good thought; but it presents many
complications. Besides picking up the heat signature from the missing child, the infrared
sensor could also pick up heat signatures from animals.
A critical decision process is needed to distinguish between heat signatures too
small and too large to be the child. There is no data given in research found about
altitude and speed versus footprint for the infrared sensor. Future integration of an
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infrared sensor seems possible with more research and data. In the meantime, it is
better to go with the given optical sensors than to risk the life of a child.
Figure 24 - Infrared Comparison
The main innovation with the UAVs is the fuselage modular sensor system that
contains interchangeable sensor adaptation, meaning when new sensor technology
comes to market, Falcon Fever’s UAVs can change out old sensors with updated
technology (refer to 2.1.2.2 and Figures 8 to 13).
2.3.3. Ground Station Equipment
Ground station equipment for the ground crew is essential to perform and complete
a SAR mission. This equipment helps program the flight path of the UAV, detect the
child, and gives confirmation. The ground station equipment sends and receives data
from the UAV during the mission.
Safety Pilot Flight Box: [$200] The Safety Pilot uses the flight box to directly
manipulate the control surfaces of a single UAV during an emergency. This device
transmits data via command datalink.
Operational Pilot Workstation Computer: [$1,500] The Operational Pilot’s
workstation includes a laptop computer with software to configure, manage, and update
waypoints for a single UAV. Flight altitudes and speeds, coordinated turns, loiter points,
and directions of travel can be commanded through the workstation. The UAV sends
information through the command datalink including its position, orientation, and
velocity.
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Sensor Payload Workstation Computer Version A: [$2,000] Workstation Version
A includes a laptop computer and software to display video data to the Sensor Payload
Operator. The Operator can manually modify the pan, tilt, and zoom of a single sensor
payload through the workstation. The data is transmitted through the video datalink to
the workstation. Only one sensor payload can be used with this workstation.
Sensor Payload Workstation Computer Version B: [$12,000] Workstation
Version B includes an advanced laptop computer with software capable of displaying
video data from up to four sensor payloads. It is capable of having automatic and
manual control of pan, tilt, and zoom. The workstation displays feedback information on
the orientation of the sensor payload. When the video scanning software has
automatically detected an object, the Sensor Payload Operator is alerted and must take
manual action to confirm the detection of the object. Sensor payload commands are
transmitted through command datalink and receive video data from up to four separate
video datalinks.
Command Datalink Ground Transceiver: [$300] The transceiver sends and
receives signals from the UAV during flight via the command datalink. The transceiver is
mounted on a tripod and has an omni-directional antenna that sends and receives data
up to three miles. The datalinks transmits data to one safety pilot box, one operational
pilot workstation computer, and up to ten Sensor Payload Operator workstation
computers that are communicating with the same UAV.
Video Datalink Ground Receiver: [$400] The receiver obtains video datalinks from
the UAV while in flight. The receiver is mounted on a tripod and has an omni-directional
antenna which receives data up to three miles.
Shelter/Trailer: The shelter/trailer is a mobile office which carries the workstations,
aircrafts, tools, fuel, generators, and other ancillary equipment. There are three types of
shelters provided in the detailed background. The shelter chosen depends on the
number of UAVs needed.
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Table 4 - Shelter/Trailer
Catapult/ Snag Line: [$7,502.37] The catapult launches the UAV to start the flight.
At the end of the flight, the UAV will be caught by a snag line, an alternative to landing
gear.
Figure 25 - Ground Station
The safety pilot box is necessary for any emergency situations in which the safety
pilot needs to take over the UAV. Two safety pilot boxes are required for the two UAVs
needed to complete the mission (refer to section 2.5 for explanations of two UAVs).
There are two Operational Pilot workstation computers for each of the Operational
Pilots. Each pilot is responsible for one UAV, and need a separate workstation (refer to
3.5.1 for details on the personnel). The ground station needs one sensor payload
workstation computer version B. Version B would be able to support the four sensor
payloads that the UAV needs. Two command datalink ground transceivers are required
to receive data sent from the UAVs. The ground transceiver sends data to the Safety
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and Operational Pilots for interpretation. Four video datalink ground receivers are
needed for the four sensor payloads.
Two UAVs require a fleet shelter. The fleet shelter could hold two UAVs and is more
cost effective than having two streamline shelters.
Table 5 - Ground Crew Equipment
2.3.4. Additional UAV/UAS Equipment
Specific equipment is required for the sUAS to be able to perform a SAR mission.
During a SAR, the equipment performs important tasks essential to mission safety and
success. The additional UAV equipment can support multiple UAVs in a fleet shelter,
reducing the overall cost.
Video Datalink UAV Transmitter: [$200] The video datalink transmits video
captured by sensor payloads to the Ground Control Station. The transmitter connects
with a single sensor and communicates with a single video datalink ground receiver. To
minimize interference, antennas are placed eighteen inches apart.
Command Datalink UAV Transceiver: [$300] The command datalink sends and
receives communication signals from the ground station. The device communicates with
a single command datalink ground transceiver. Keeping with requirements, antennas
are placed eighteen inches apart.
Onboard Video Recorder: [$600] The onboard video recorder logs video received
from the sensor payload. The UAV must first land before the Data Analyst could review
the recorded video from the UAV to go back to the detection coordinates. This is an
alternative to the video datalink.
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Flight Control System: [$2,000] The flight control system communicates with the
Operational Pilot in the ground station. The system is capable of GPS navigation and
has the ability to relay sensor payload commands from the ground control station. It is
capable of autonomous flight which is a preprogrammed flight path that the operational
pilot can update throughout the mission.
Fuel Tank: [$12.50] The tank holds fuel for the UAV. The size and shape of the fuel
tank is determined by the team to fit within the airframe and hold sufficient fuel.
Batteries: [$40] Light-weight batteries are needed to supply enough energy to the
various UAV components included in the sUAS design.
The two UAVs in the mission (refer to section 2.5) are equipped with two sensor
payloads which totals into four video datalink transmitters. There needs to be two
command datalink UAV transceivers, one transceiver per UAV. Because two UAVs are
used in the mission, two flight control systems are required. Both UAVs need 0.6
pounds of batteries (0.3 pounds of batteries per UAV) to fly the mission.
Table 6 - Ground Crew Components
2.4. Aircraft Geometric Details
After selection the system components, the aircraft’s geometric details were focused
upon next. These details include the wing configuration, tail configuration, and fuselage.
2.4.1. Wing Configuration
Falcon Fever designed both UAVs with the same set of wings. The wings’ two-
dimensional shape is designed using an Eppler 216 airfoil. The wing itself is optimized
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in its three dimensional shaping to create the best wing for the UAVs. The wings have a
total planform area of 450 in². This produces enough lift for both UAVs to clear a 50 feet
tall object within 300 feet of takeoff flying at determined speeds. Other defining
conditions of the wing include an aspect ratio of 8, a taper ratio of 0.8, a dihedral angle
of one degree, a sweep of one degree, and a wing incidence angle of two degrees. The
team contemplated using a different airfoil shape for the tip chord in order to create
more favorable stall conditions, but after a conversation with Derek Attwood, they
learned that this method was impractical to produce and that the same effect could be
gained by applying a twist angle to the end of the wing. For this reason, a twist of three
degrees was added on the wings. The weight of the wings on UAV 1 is 5.21 pounds and
the weight of the wings on UAV 2 is 4.45 pounds. UAV 2 is lighter because it needed
less structural support.
2.4.2. Tail Configuration
The V-tail design on UAV 1 features a planform area of 86.056 in². This amount
was determined by the V-tail definition worksheet provided by Mark Beyer. Other
features of the wing include an aspect ratio of four, a taper ratio of 0.7, a sweep angle of
20 degrees, and a dihedral angle of 32.513 degrees. The incidence and washout angles
are both left at zero degrees. The tail wing weighs in at 1.22 pounds, an amount
determined by the Configurator Excel Worksheet.
Meanwhile, the V-tail design on UAV 2 features a planform area of 62.039 in².
The definition of the aspect and taper ratio as well as the sweep, dihedral, incidence
and washout angles all remains the same as that on UAV 1. The tail wing weighs in at
0.91 pounds, also determined by the Configurator Excel Worksheet.
2.4.3. Fuselage
The UAV’s fuselage shaping was based on a modular components system to
make repairs easier. The fuselage is designed to minimize surface area and be
aerodynamic while still holding all the necessary components. Once completely
designed, UAV 1 had a surface area of 439.94 in², causing it to weigh in at 9.24 pounds.
UAV 2 had a surface area of 366.89 in², causing its weight to be 7.17 pounds. Both of
these weights were determined using the Configurator Excel Worksheet.
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2.5. System and Operational Conditions
In determining the mission plan, the decision had to be made of either using one
UAV or two UAVs. This decision dramatically affects the Objective Function depending
on which option was chosen.
To help determine which method is best for the Objective Function, an experiment
was completed. Using the accurate times for the mission plan as the independent
variable (refer to section 3.2), the team selected a low and high initial price to calculate
the Objective Function for one and two UAVs using MathCAD. This is not the actual
Objective Function, but rather an experiment with numbers to find whether using one
UAV was more effective than using two UAVs.
Figure 26 - UAV Comparison
In experiment one, having two UAVs is better for the Objective Function than just
one. If the initial cost is $50,000, two UAVs would cut the Objective Function by almost
in. To make sure that this observation is constant, the team proceeded with experiment
two that included a larger number for the initial cost. In experiment two, the end result
was that two UAVs were more cost effective than one UAV. With a larger initial cost, the
Objective Function is not quite half, but it is still clear that two UAVs are better than just
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one. Because of this observation, the team agreed that the mission would use two
UAVs to save the missing child.
But then the team had to take into consideration the different zones since the line of
sight restriction changes throughout the course of the mission. It is time consuming for
one UAV to be scanning the entire search area.
When using two UAVs, it is time effective but would sacrifice cost since the initial
cost would be doubled in the Objective Function. There is the initial cost of the two
UAVs, but in addition, all of the other components on the UAS would have to be
doubled, such as the ground crew and sensors.
2.6. Components Flight Vehicle Weights and Balance
One of the most important things in an aircraft is balancing the weight. The closer
the total balanced weight is to the center of lift, the less effort is required for the aircraft
to control its flight. With the aerodynamic of each plane being at a position of 16 inches,
it was essential to position the center of gravity as close to this point as possible. The
closer these two points are to each other, the less power the UAV has to use to balance
itself during flight. The tables below show the component positioning of each UAV.
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Table 7 - UAV 1 Weight Balance
Table 8 - UAV 2 Weight Balance
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2.7. Maneuver Analysis
Referring to section 3.2 for the flight pattern, UAV 1 will be flying in speed ranges of
60 to 80 MPH for Zone 1 and 2—as low as 60 MPH when flying in a relatively sharp turn
with a steeper bank, and as high as 80 MPH when flying in a relatively wider curve with
less bank. In Zone 3, however, UAV 2 will be flying between 60 and 64 MPH due to its
smaller camera footprint. A smaller footprint results in sharper turns, which results in
steeper banking and slower speeds.
2.8. CAD Models
2.8.1. UAV 1 CAD Models
Figure 27 - UAV 1 Isometric View
Figure 28 - UAV 1 Front View
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Figure 29 - UAV 1 Top View
Figure 30 - UAV 1 Side View
2.8.2. UAV 2 CAD Models
Figure 31 - UAV 2 Isometric View
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Figure 32 - UAV 2 Front View
Figure 33 - UAV 2 Top View
Figure 34 - UAV 2 Side View
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2.9. Three Views of Final Design
2.9.1. UAV 1 Dimensions
Figure 35 - UAV 1 Front Dimensions
Figure 36 - UAV 1 Top Dimensions
Figure 37 - UAV 1 Side Dimensions
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2.9.2. UAV 2 Dimensions
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3. Document the Mission Plan
Due to the differentiating tree heights, the search area is divided into three zones,
each one having a line of sight limitation. In Zone 1, there are no restrictions to the line
of sight on the sensor because there are no trees blocking the sensors. In Zone 2, there
are medium-height trees that restrict the sensor’s line of sight by 30 degrees or less
from vertical. Zone 3 has tall trees that restrict the sensor’s line of sight to 15 degrees or
less from vertical. Due to the different line of sight restrictions on all of the zones, the
UAV would need to handle each zone differently. The camera footprint has to be within
the line of sight limitation or the sensors will not be able to detect with the line of sight
view being cut off by the trees. The camera footprint is dependent on the line of sight,
and the waypoints for flight planning are dependent on the footprint. Figure 39 is a
sketch that shows the length of the line of sight restriction. The line of sight varies
depending on the altitude.
Figure 38 - Zone Comparison
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3.1. Camera Footprint
After the selection of sensors, the camera footprint must be determined next
since the footprint of a specific sensor is what the flight plan is based on. Therefore,
before anything can be done for flight planning, the footprint has to be carefully thought
out and chosen first. Because Zone 1 has no restrictions, the team combined it together
with Zone 2 due to the convenience of a constant camera footprint.
When flying at an 800 foot altitude with a line of sight radius restriction of 30 degrees
for Zones 1 and 2, there is a line of sight radius of 462 feet (924 feet diameter). When
flying at the desired altitude of 800 feet, the X1000, the detection sensor for Zones 1
and 2, would have a camera footprint length of 602 feet (301 feet from center to the
outer edge). These calculations are made in the sensor footprint Excel sheet provided in
the design kit. The X1000 would have a 40 degree horizontal field of view (HFOV) and
would be positioned at zero pitch and roll. The 602 feet (approximately the length of two
football fields) camera footprint is what all of the calculations for flight patterns would be
based on for Zone 1 and 2.
Figure 39 - Zones 1 and 2 Footprint
For Figure 40, the blue rectangle represents the camera footprint, the green line
represents the maximum detection distance circle, the dotted purple circle represents
the Zone 2 line of sight, and the dotted blue circle represents the Zone 3 line of sight.
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The sensor would be positioned straight down while searching. The team took into
consideration that, while the UAV would be banking, the camera would not be pointed
straight down; the sensor payloads would have the ability to pan and tilt, whereas the
sensor itself could move to adjust with the banking angle. While the UAV is banking, the
sensors could pan and tilt to maintain the rectangular footprint pattern.
For Zone 3, a separated UAV containing identical cameras would be used. This UAV
would fly at an altitude of 885 feet above ground level in order to maximize the detection
radius of the X1000 sensor. At this altitude with the 15 degree viewing angle limitation,
the Zone 3 line-of-sight radius is 237 feet. Meanwhile, the X1000’s detection radius at
this height is 239 feet, ensuring that detection can occur within the entire footprint of the
viewable area.
Figure 40 - Zone 3 Footprint
For identification in Zone 3, the UAV would use the onboard X3000 sensor to track
the detected object. At the flight altitude, this sensor would have an identification radius
of 997 feet. However, given the line-of-sight restrictions, there is only a 237 foot radius
for the sensor to identify within. With the object being required to stay in the camera
footprint for five seconds to be identified, this means that the distance traveled during
the identification time must be less than 474 feet. By setting the flight speed at 64 MPH,
the distance traveled during identification time is 469 feet. By making this the maximum
flight speed, the team was able to accurately scan Zone 3 in the shortest amount of time
possible.
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Once the footprints had been finalized, the team then decided to break the two
UAVs into two sections: one UAV would search Zone 3 due to the smaller footprint, and
another UAV would search Zones 1 and 2 due their identical footprints.
3.2. Search Pattern
A search pattern for the UAV is crucial to minimizing the mission time. To reduce
time searching the area, the team had to avoid excessive overlapping in an area that
has already been searched while minimizing the total distance traveled. The search
pattern had to be practical; for example, sharp turns or extreme banking had to be
avoided because it would make it more difficult for the sensor payloads to detect and
identify objects since the UAV would not be pointing directly at the ground.
Figure 41 - Flight Path Brainstorm
The team took several possibilities for flight paths into consideration. Regardless of
feasibility, all ideas were written down in brainstorming sessions until the search could
be narrowed down. The selection was based on three criteria: feasibility, efficiency, and
time. Since Zones 1 and 2 had the same camera footprint and covered nearly two-thirds
of the search area, it was convenient to use a trial and error method on the two zones to
plug in waypoints and analyze which pattern was the best.
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Because of the previous experience in the state
challenge, the first idea the team brainstormed was a
spiral configuration. The UAV circles around the middle
to gain the 800 feet of altitude, and after the UAV gains
speed it begins the spiral pattern. As shown in Figure
43, there are large blind spots and excessive overlap in
sharp turns. On the final turn, the UAV’s turning radius
becomes too tight to curve, therefore eliminating the
feasibility and reliability of the spiral pattern.
The team moved on to the next pattern to which was
nicknamed the “butterfly.” The UAV flies north and
makes a loop outside of the search area with a space
the size of the camera footprint left out in the middle to
avoid sharp turning, then the UAV flies south to make a
similar loop. The UAV would repeat the process, flying
between each loop to cover the entire area. However,
the UAV is unable to cover the entire area, and in
addition, has excess overlap coming back to the middle.
As shown in Figure 44, the turns get much too sharp in
the middle, restricting the UAV from finishing the
pattern and therefore making the pattern impractical.
The next pattern the team considered was the
lawnmower, as shown in Figure 45. The UAV first flies
north to the edge and then flies around the perimeter
to the other side. The UAV then turns and does the
same motion (similar to what one would do mowing
their lawn), but reversed and in a shrinking circular
fashion. The idea is very efficient because there is not
any excessive overlap, and the pattern is able to cover
the entire area. However, it is not very feasible due to
Figure 42 - Spiral
Figure 43 - Butterfly
Figure 44 - Lawnmower
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the tight turns that exceed the normal turning radius. To make the turns, the UAV has to
bank at an unreasonably high angle, rendering the turns unrealistic.
Although the lawnmower configuration was not
practical, the team wanted to keep its successful result of
searching the whole area. After brainstorming and
researching possible solutions to how the UAV could make
the turns, a new idea was formed from the idea of
resurfacing an ice rink: the “Zamboni” pattern. The
“Zamboni” is basically the same as the lawnmower pattern,
but instead of flying into an adjacent tight turn, the UAV
would skip an area the size of the camera footprint, then
turn. The UAV will continue to skip these spaces until it
comes to the middle, as shown in Figure 47, then loop back around to search the
skipped spaces.
Figure 46 - “Zamboni” Before-After
Figure 45 - "Zamboni"
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The team successfully determined the waypoints,
adjusted the angles, and covered every last bit of area
in the two zones. Afterwards, the pattern was
implemented in Zone 3 with its separate camera
footprint to complete the search pattern that covers the
two-mile search radius as shown in Figure 48. There is
a constant two foot overlap throughout the flight to cover
the lack of absolute precision.
Although the successful results surpassed the team’s standards for a search pattern,
there was always more room for improvement. The total time for Zones 1 and 2 was
66.4 minutes (1.1 hours), and despite it being a little over one hour, it would have to be
rounded up to 2.0 hours for the ground crew payment. After realizing this, the team
considered what they could do to fix the problem. They noticed that the time to search
Zone 3 was 49.9 minutes (0.8 hours), which is a low enough time to be able to search
an additional amount of area and still be under one hour. Taking this thought into
consideration, the team experimented by taking away a section of the flight path from
the UAV flying over Zones 1 and 2 and added it to the flight path of the UAV flying over
Zone 3, as shown in Figure 49. Because both UAVs use the same type of sensors, the
UAV that covers Zone 3 is adequate enough to cover part of Zones 1 and 2 as long as
the altitudes and speed match up to the correct footprint requirements.
Figure 48 - Modified "Zamboni"
Figure 47 - Complete "Zamboni"
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Satisfied with the outcome the modified pattern produced, it was ultimately decided that
this would be the final search pattern for the UAVs. The total time to search Zones 1
and 2 with an altitude of 800 feet is 59.9 minutes with a total distance of 76.5 miles. The
total time to search Zone 3 with an altitude of 885 feet is 57.6 minutes with a total
distance of 63.1 miles. Figure 50 (Family) shows where both UAVs would travel during
the course of the mission; refueling stops are not needed.
Figure 49 - Two UAVs
3.3. System Detection and Identification
While the UAV is flying at its search altitude and speed, the sensors send back live
image to the Payload Operator for the identification sensor. The detection sensor
(X1000) is equipped with the video scanning software which allows it to detect an object
mid-flight with half the number of pixels required. A trained Payload Operator needs at
least eight pixels to be able to detect a child during a mission while the video scanning
software only requires 4 pixels to achieve detection.
After a successful detection by the video scanning software, a confirmation needs to
be made by the Payload Operator. The Payload Operator will be sitting in front of a
computer that shows a live image of the identification sensor (X3000). The minimum
identification sensor resolution is 20 pixels. Using the image, the Payload Operator can
determine if the object spotted by the detection sensor is the missing child and then
relay the information back to the ground personnel. This all happens when the UAV is
still maintaining its search altitude. The UAV is equipped with a Global Positioning
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System (GPS) that tracks the UAV in flight. This is how the latitude and longitude will be
determined and be relayed back to the ground crew.
While the UAV is flying, the identification sensor is able to pan and tilt to cover the
smaller search radius of the detection sensor and is able to confirm whether anything
detected is the missing child or a decoy. A benefit of having two sensors is that the UAV
will not have to slow down or change altitude, but will rather continue its course
throughout the search area without interruptions.
3.4. Example Mission
A search and rescue (SAR) crew receives a call from Philmont Ranch, New Mexico
regarding a lost and potentially injured child missing in the wilderness of a two-mile
radius. Because of the size of the area, the number of trees, and the crucial constraint
to locate the lost child as soon as possible, it is ultimately decided to conduct the
mission by using two UAVs. These UAVs are designed and constructed to perform SAR
missions just like the one they have laid out for them: to effectively save a missing
person in the lowest time and cost possible.
As soon as the SAR crew readies their UAVs and plans, they set out from their
headquarters in Colorado Springs to the designated ranch in New Mexico. During the
drive to the ranch, they broke up the search area into three different zones dependent
on its terrain. UAV 1 will search Zones 1 and 2, Zone 1 with no trees and Zone 2 with
the medium trees. UAV 2 will search Zone 3, the zone with the tallest trees. The crew
preprogrammed a “Zamboni” search pattern for both UAVs. Both UAVs will be fueled
and the mission will be completed in less than one hour.
The crew arrives and immediately sets up the equipment in the search center.
Because it was calculated that UAV 1 will take longer to search the two zones
containing two-thirds of the area, the Range Safety Officer prioritizes preparation of
UAV 1 for launch. The launch system for the UAVs is a powerful catapult that propels
the UAV on takeoff. UAV 1 clears a 50 foot obstacle in 149 feet on its way to an altitude
of 800 feet AGL after being launched from the center by heading north to the edge of
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the search area to gain altitude. The speed for UAV 1 ranges from 60 MPH when
banking to 80 MPH when cruising along with the efficient “Zamboni” search pattern.
After UAV 1 is launched, UAV 2 will be the Range Officer’s next priority while
keeping a careful and observant eye on UAV 1 in flight. UAV 2 is launched the same
way as UAV 1, and clears a 50 foot obstacle in 207 feet on its way to an altitude of 885
feet AGL. UAV 2 has a minimum speed of 60 MPH and maximum speed of 64 MPH.
Because both UAVs fly at different altitudes, they will not interfere with each other when
the flight paths are interlocking.
As both UAVs fly simultaneously in the “Zamboni” search pattern with GPS
waypoints, the sensors, which are two electro-optical cameras oriented with zero pitch
and roll to maximize the detection capability, will send live video back to the ground
crew. There are two types of datalinks: a command datalink, and a video datalink. The
command datalink transmitters on the UAVs send back navigation data to the command
datalink ground transceivers. The data will be analyzed by the Operational Pilot and
Safety Pilot to make sure the UAVs are at the right altitudes and speeds. The Range
Safety Officer will make sure that the UAVs are following FAA regulations and will verify
that the airspace is clear. The video datalink transmitters will be positioned on the UAVs
and will send back live video to the video datalink transceivers to be analyzed by the
Sensor Payload Operator.
The sensors will be pointed straight down and are equipped with a software
scanning program that will detect an object within half a second. Once the software
detects an object that is potentially the missing child, it sends the coordinates and all of
the data back to the Sensor Payload Operator while simultaneously alerting the
identification sensor to start its scan. The software automatically logs the geographic
location and image frame of the time of detection. The Payload Operator can observe
the image in live video feed and identify the object as a false detection or the missing
child.
If it is a false detection, the UAV will maintain its altitude and continue the search. If
the child has successfully been identified, the Payload Operator will announce the news
to the Operational Pilot by sending out geographical coordinates. The Operational Pilots
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will then reprogram the both UAVs flight route to return to base and be caught by a snag
line. If anything goes wrong with the landing sequence, the Safety Pilots will be
available to manually take over the UAVs and land them safely.
The Payload Operator will notify the rescue squad, known as the Ground Search
Personnel, of the child’s coordinates so the child will be brought back to safety. The
Payload Operator will keep radio contact with the squad to assist them through the
rough terrain. The Range/Safety Officer will ready the UAVs for deportation, and the
entire ground crew will then make the trip back to Colorado Springs while celebrating
the successful mission of saving the child.
3.5. Mission Time and Resource Requirements
Consideration of manpower requires operation of the sUAS equipment via Payload
Operator, Operational Pilot, Safety Pilot, Range and Safety Pilot, and Ground Crew
Personnel. The team would have to consider the manpower requirement to operate
their sUAS. This would include anyone who operates equipment and how much they
would be paid. The team calculates the total time of their search mission. Search
mission include travel time, setup time, flight time, and tear down time.
3.5.1. Manpower Requirements: Ground Crew
For a sUAS to be able to perform a SAR mission, a ground crew is required. During
a SAR, there are a variety of roles that the ground personnel have to perform in order to
ensure that the mission is successful. The cost per hour of each person includes
expenses for transportation, salary, fringe benefits, labor overhead, and supplies.
Payload Operator: [$150/hr.] The Payload Operator is required when the sensor
payload data is telemetered from the aircraft during the mission. This person would
typically sit at the ground station and control the payload operations using the graphical
user interface. The payload operator is in charge of monitoring the sensor payload,
steering the payload (where the sensor is pointing), and directing the aircraft operator
on where to fly the aircraft. Additionally, they monitor the search status to identify
targets of interests that may require follow-up either by the aircraft or by ground search
personnel.
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Data Analyst: [$150/hr.] The Data Analyst is required when data from the search
aircraft cannot be processed in real-time. This role is a requirement when sensor data is
recorded on the aircraft for download and analysis after recovering the aircraft. The
Data Analysis is responsible for software analysis and communicating results to other
group crew personnel.
Ground Search Personnel: [N/A] The Ground Search Personnel follows up on
ground target indicators, after the successful confirmation of the child by the aircraft is
performed by the Payload Operator. The Ground Search Personnel would be provided
by Philmont Ranch.
Range Safety/ Aircraft Launch & Recovery/ Maintenance: [$175/hr.] This person
is a highly qualified technician. Range safety includes making sure the frequency the
UAV is transmitting, does not interfere with other aircrafts in the area. This person
monitors air traffic channels to ensure that the airspace remains free during the mission,
makes sure the aircraft follows the appropriate airspace restrictions, and is responsible
for launch, maintenance between flights, and recovery operations.
Launch & Recovery Assistants: [$50/hr.] The Launch & Recovery Assistants help
when positioning the aircraft on the launch system (catapult) and help recovery of the
aircraft from the capture mechanism (snag line).
Safety Pilot: [$100/hr.] The Safety Pilot is responsible for bringing the aircraft safely
in for recovery. The Safety Pilot needs to be able to observe the aircraft at all times.
During semi-autonomous flight operations, the Safety Pilot is responsible for
immediately taking over command of the aircraft if the aircraft exhibits unanticipated
flight behaviors.
Operational Pilot: [$150/hr.] This person is responsible for monitoring aircraft
altitude, waypoint tracking, and adjusting the aircraft flight path. The Operational Pilot
will be at the ground control station monitoring the telemetry from the aircraft’s onboard
flight control computer and adjusting the aircraft’s programming as necessary.
All ground crew personnel are paid hourly and not all are needed to perform the
SAR mission. There are only a few ground personnel that are absolutely necessary to
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make sure that the ground crew is efficient. Payload Operators can handle up to four
sensor payloads and are limited to watching only one UAV; therefore, there would have
to be one Payload Operator for each UAV. There is no need for a Data Analyst since all
data being sent back to the ground station would be analyzed by the Payload Operator.
Since two UAVs will be in the air at the same time, there will have to be two
Operational Pilots to monitor each UAV. They will be in the ground control station
monitoring the telemetry of the aircraft and adjusting the programming as necessary.
Two Safety Pilots are needed to observe the UAV in flight at all times to ensure a safe
landing. If needed, the Safety Pilot can take over the UAV manually. One Safety Pilot is
needed for each UAV.
There would only need to be one Range Safety Officer since the UAVs will be taking
off at different times and will be recovered at different times. When monitoring air traffic
channels, they can monitor the search area to make sure the air traffic is clear.
A crew from Philmont Ranch will serve as the Ground Search Personnel. There is no
cost associated with the search personnel.
Table 9 - Ground Crew Personnel
3.5.2. Calculated Time
The ground crew takes 3.5 hours to travel from Colorado Springs to Philmont Ranch,
New Mexico. Once they arrive, it takes 0.5 hours to set-up equipment and prepare for
launch.
Both UAVs would fly in a “Zamboni” pattern, which is engineered to fly in under one
hour. The total time for UAV 1 to completely search Zone 1 and 2 is 0.99 hours. The
total time for UAV 2 to completely search Zone 3 is 0.96 hours. Since UAV 1 is
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launched first due to its longer time, the total time to conduct the search time is 0.99
hours.
Once the mission is over and the crew has successfully found the missing child, the
crew will prepare for departure Tear-down time takes 0.5 hours to complete, and
traveling back to the headquarters in Colorado Springs takes another 3.5 hours.
TOTAL OPERATION TIME: 8.99 hours (rounded up to 9)
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4. Documents the Business Case
4.1. Identify Target Commercial Applications
Falcon Fever’s UAVs have the potential to be used for more than just SAR missions
in the real world. UAVs could be used more freely if FAA or regulatory restrictions were
eased.
4.1.1. Determine Other Uses for the UAS
UAVs are becoming more commercialized. In February of 2012, President Barack
Obama signed the FAA Modernization and Reform Act to establish that the U.S.
airspace open for commercial use of UAVs by 2015. Once the regulation catches up to
reality, domestic UAVs are poised for widespread expansion into U.S. airspace.
One major innovation for the future could be improving surveillance for research. An
example would be forming a live Google Maps or GPS advancement to update road
construction in a timely manner. The FAA has strict policies regarding UAVs being used
for commercial utilization. Currently, some firemen use UAVs to inspect fire damage
and/or to detect wildfires. The police currently use UAVs for surveillance and are hoping
to expand the use of UAVs throughout law enforcement. One of the current plans to
expand the use of UAVs in law enforcement is to use them as mobile traffic cameras.
UAVs could be used for more than just law enforcement. Applications include aerial
mapping, hyperspectral imaging for mining exploration, volumetric survey, pipeline and
power line monitoring, land planning, disaster response, and wildlife management. The
future of UAVs to benefit society looks positive.
4.1.2. What Could Be Achieved if Regulatory Restrictions Were Eased?
The FAA has strict regulations when it comes to the licensing and registrations of
UAVs and where they can operate. Currently, the regulation provided by the FAA does
not allow the use of a UAV without a permit. The permits are only given for research
and development situations under limited circumstances. Currently, there are two ways
to legally fly a UAV in national airspace. One way is to get a Certificate of Authorization
(COA) from the FAA, a process that could take months or more; the other way is to fly a
UAV under recreational purposes.
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Due to the FAA Modernization and Reform Act, U.S. airspace will open for use of
commercial UAVs by 2015. The U.S. government is scheduled to start issuing
commercial UAV permits, which will open up airspace to the use of UAVs by both public
and private industry.
There are many potential markets for the use of UAVs. Once regulations are eased,
major league sports, film and television production, meteorological studies, and the
media could be potential customers. Teal Group, an aviation and aerospace industry
research firm, estimated that the global spending on UAVs will double over the next 10
years to nearly $90 billion. The commercial growth of UAVs in the future is set to grow
because of its low operating costs and versatility.
4.2. Amortized System Costs
Once the UAV was effectively designed with a finalized mission plan, the amortized
business cost of fifty missions was calculated. This helps determine the cost
effectiveness of the system.
4.2.1. Initial Cost of System
The initial cost is the cost to buy the UAS, including: airframe, sensors, motor,
components, and ground crew personal. Once the UAS has been bought, a second
purchase is not needed.
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Table 10 - Initial Cost
74
4.2.2. Direct Operational Costs per Mission
The direct operational cost is the price of personnel needed to fly the mission. These
items need to be repurchased after every mission flown.
Table 11 Direct Operational Cost
4.2.3. Amortization
Falcon Fever proceeded to calculate the cost of fifty missions, which was later used
to find the average cost per mission.
( ) ( ) ( )
Initial Cost without Fuel = $139,039.58
Cost for Ground Station Equipment = $39,102.37
Cost per Mission for Ground Crew = $975.00
= Cost for 50 Missions (without fuel) = $577,789.58
( )
= Average Cost per Mission (without fuel) = $11,555.79
A reasonable profit margin is 15% to 35% not including current market outlook or
customers. When a company sells a large quantity of one product, each individual
product typically has a low profit margin. Selling a large amount of a product can lower
the profit margin. But when there are a small number of sales of a product, the company
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wants a high profit margin. That way, the company can still make enough money to
support its business and/or have a net profit. For example, if the same company sold a
low quantity of product in the next month, the company's profit margin would be notably
smaller. Marketing and manufacturing were taken into consideration when pricing the
UAV for the market. Keeping into consideration, if Falcon Fever was manufacturing this
product they would also market it which hints to the profit margin increase. No fuel is
included in the final UAV cost for manufacturer.
After looking at current profit margin percentages for John Deere and Texas
Instruments, the team concluded the final percentages as a rough estimate. John Deere
is a manufacturer, and Texas Instruments is a marketer. If they were to find the profit
margin as though they were both, they estimated a 30% profit margin.
4.3. Market Assessment
Falcon Fever’s UAVs were compared
to the Falcon in terms of cost,
specifications, and components. The
Falcon was designed and engineered by
the Mesa County Sheriff's Office in
Colorado. The Falcon can conduct SAR
missions as well as assist the Colorado
State Patrol with fatal crashes or fires.
The Falcon and Falcon Fever’s UAVs are intended for SAR purposes and with no
warfare use of any kind. Both UAVs are equipped with sensor payloads which can be
used to search in a pre-programmed flight path.
Falcon Fever’s UAVs and the Falcon have contrasting differences. The Falcon can
fly for 1 hour at a time with a speed range of 25 to 55 MPH. Falcon Fever’s UAV 1 can
fly a total of 1 hour and 4 minutes while UAV 2 can fly a total of 1 hour and 15 minutes
before running out of fuel. Falcon Fever’s UAVs can fly up to 80 MPH. The Falcon
weighs 9.5 pounds compared to Falcon Fever’s UAV 1 weight of 27.8 lbs and UAV 2’s
weight of 20.6 lbs. The Falcon is launched by hand and is recovered by a parachute or
Figure 50 - Falcon UAV
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belly landing depending on the scenario. Falcon Fever’s UAVs are launched by a
catapult and caught by a snag line.
Looking at the structural design of both UAVs, the Falcon UAV has a small fuselage
that does not encase the components inside while Falcon Fever’s UAVs have a
fuselage that encases all main components. The Falcon runs on batteries while the
Falcon Fever’s UAVs run off fuel.
4.4. Cost/Benefits Analysis and Justification
Falcon Fever’s UAVs are a better buy than others because they are light weight, low
cost, and are equipped with the latest technology. The fuselages are designed to allow
the sensors and motor to be easily removed and exchanged if needed. Two sensors are
used on each UAV, one for detection and one for identification, to find the missing child
more quickly compared to using one sensor like Miser’s Falcon does. Falcon Fever’s
UAVs have a practical and efficient flight path that is programmed with two UAVs both
flying in a time under one hour. The team wanted to make sure they had a reasonable
time-to-cost ratio for their UAV since having too much of one thing would offset the
efficiency of either time or cost. For this reason, they selected their components by that
ratio.
77
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6. List of Symbols, Abbreviations, and Acronyms
AGL: Above Ground Level
AoA: Angle of Attack
ASL: Above Sea Level
CAD: Computer-Aided Design
CFD: Computational Fluid Dynamics
COA: Certificate of Authorization
e216: Eppler 216
FAA: Federal Aviation Administration
GPS: Global Positioning System
HFOV: Horizontal Field of View
lbf: Pounds of Force
PLTW: Project Lead the Way
PMI: Polymethacrylimide foam
RC: Remote Controlled
RWDC: Real World Design Challenge
SAR: Search and Rescue
STEM: Science Technology Engineering Mathematics
TFOV: Telescopic Field of View
UAS: Unmanned Aerial System
UAV: Unmanned Aerial Vehicle
UIUC: University of Illinois at Urbana-Champaign