Cryohawk
artist’s concept
Half-scale Demonstrator of a CReSIS Polar
Exploration UAV Concept
Richard Colgren – KUAE
Meeting 97, Aerospace Control and Guidance Systems Committee
Roadmap
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Background
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Intro to CReSIS
KU UAV Background
Sensor Payload
Requirements
Mission Profile
Updated Design
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½ Scale Demonstrator
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AE 721 Student Team
AE 510 Student Team
PSU Team and Others
Goals
Current Design
Challenges
Intro to CReSIS
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Science-driven technology development
Focused on mapping ice-sheet
characteristics
Antarctica and Greenland missions in
years 3 through 5
Established by NSF
For more info, go to cresis.ku.edu
UAV Lab Objectives:
Develop, test and demonstrate single and multiple Intelligent UAV concepts
and systems for use in defense, scientific and commercial applications.
Unmanned Aerial Vehicles
Rotorcraft
Kansas NASA EPSCoR Program
Kansas NSF EPSCoR Program
Autonomous Rotorcraft Project
Phase I Raptor 50 Flight Test Familiarization
Phase II RMAX Flight Test Data Collection
Phase III RMAX Autonomous Flight
Hardware Validation
Phase IV RMAX Software Validated
Phase V Cooperative Flight Demonstrated
Raptor 50 Leader/Follower, R-Max
Fixed Wing
- Edge 540 T High Alpha CFD/Test Program
- Hawkeye UAV Program/SAE Competition
- J-3 Cub Instrumentation Project
- Ultra Stick R/C Airplane Obstacle Avoidance
- Visual Based-Obstacle Avoidance Project
- NSF CReSIS Center
Phase I
- Preliminary Design Developed
Phase II
- GNC System Designed
Phase III - Flight Demonstrations
KU Fixed Wing UAVs
Polar UAV
Hawkeye
Ultra Stick
1/3 Scale J-3 Cub
Edge 540 T
SAE Heavy-Lift
KU Rotary Wing UAVs
Yamaha RMAX and Raptor 50 Helicopters
KU Hypersonic Vehicle Studies

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Generic Hypersonic Vehicle
Navy Hypersonic Vehicle Study
Supersonic Flows with Injected Streams - NASA
AST-4000 Flight Simulator
Aviation Simulation Technology Inc.
14802 W. 114th Terrace
Lenexa, KS 66215 USA
AST-4000 Flight Simulator
Specifications
KU Hypersonic Vehicle Simulation
Clb Versus a & Mach
Look-up
table
Number
Original
Graph
Trajectory
120000
Altitude
100000
80000
Accent
a
M
ClB
0
4
-0.05500
2
4
-0.05650
4
4
-0.05800
6
4
-0.05950
8
4
-0.06100
10
4
-0.06250
12
4
-0.06400
0
6
-0.03750
2
6
-0.03875
4
6
-0.04000
6
6
-0.04125
8
6
-0.04250
10
6
-0.04375
12
6
-0.04500
0
10
-0.02250
2
10
-0.02375
4
10
-0.02500
6
10
-0.02625
8
10
-0.02750
10
10
-0.02875
12
10
-0.03000
0
15
-0.01600
2
15
-0.01750
4
15
-0.01900
6
15
-0.02050
8
15
-0.02200
60000
Level flight
10
15
-0.02350
40000
Descent
12
15
-0.02500
MATLAB
Routine
(FITTER)
% This routine is written in order to find the best fitting equation for
[m,n]=size(A);
if(n<4)
% For the basic vehicle evaluation, no control surface.
newA(:,1:2) = A(:,1:2) ;
newA(:,3) = [0]
;
newA(:,4) = A(:,3) ;
A
= newA
;
end
alpha = A(:,1)
;
mach = A(:,2)
;
cs = A(:,3)
;
val = A(:,4)
;
t
= size(mach) ;
cof = size(27,10) ;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%---1st--%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%
j= 1
;
X = [ones(size(val)) (alpha) (mach) (cs) ] ;
% The first prediction for the aerodynamic equation
con = X\val
;
Cof(1:size(con),j) = con(:)
;
newval = X*con
;
Err = newval- val
;
perf(j) = sse(Err,X)
;
% The sum of squares due to error.
% This statistic measures the deviation of the responses from the fitted values of the responses.
% A value closer to 0 indicates a better fit.
% pause
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%---2nd--%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%
j = j+1
;
X = [ones(size(val)) (alpha) (mach) (cs) (alpha).^2 (mach).^2 (cs).^2 ]
;
% The 2nd prediction for the aerodynamic equation
con = X\val
;
Cof(1:size(con),j) = con(:)
;
newval = X*con
;
Analytical
Expression
Cl
b
-1
 - 1.402  10
 8.596  10
-6
 2.354  10
-6
a
 2.219  10
-4
M
3
 3.803  10
-19
a
4
-4
 3.326  10 - 2  M - 7.590  10  a
 (a  M) - 3.794  10
2
- 1.044  10
-8
- 8.964  10
M
 (a  M)
-18
 7.419  10
-3
-8
a
3
M
5
2
2
- 6.462  10
-6
- 3.353  10
M
- 21
4
a
5
20000
0
0
5
10
15
Mach Number
20
25
MATLAB Simulation
FORTRAN Simulation
UAV Sensor Payload
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Depth-sounding radar
Surface-scanning lidar
Other sensors
artist’s concept
Ice Sheet
Bedrock
UAV Sensor Payload
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Depth-sounding radar
Surface-scanning lidar
Other sensors
Ice Sheet
Radar
Bedrock
UAV Sensor Payload
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Depth-sounding radar
Surface-scanning lidar
Other sensors
Lidar
Ice Sheet
Radar
Bedrock
UAV Requirements
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175 lb payload
Radar antenna array (14 ft by 2.5 ft)
6,000 km (3,200 nm) round trip
1 km (3,300 ft) AGL for survey
126 knots for survey (155 knots cruise)
Jet or Diesel fuel preferred
Mission Profile (Greenland)
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Taxi / takeoff / climb
Cruise 200 nm to glacier
Conduct survey
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Local survey
or
Regional survey
Return cruise to base
Land / taxi
Mission 1 Profile (Antarctica)
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Taxi / takeoff / climb
Cruise 1,350 nm
Conduct survey
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Local survey
or
Regional survey
Return cruise
Land / taxi
Redesign – Full Scale Concept
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Low wing
Larger center wing
More details
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Antennas, etc.
artist’s concept
Full Scale Sizing
80.0
(W/P)TO 72.0
Take-off Distance
T = -30 deg F
Maximum Cruise Speed
Sustained g / Turn Rate
Landing Distance
T = -30 deg F
OEI-RC: FAR 23.67.a
lb
hp
CL
64.0
max
= 3.80
L
56.0
CL
= 3.80
max
L
CL
48.0
= 2.80
max
(W/S)TO = 22.43 lb
L
2
Design Point
CL
max
= 2.80
ft
40.0
(W/P)TO = 19.9 lb
hp
CL
32.0
= 1.80
max
L
L
24.0
16.0
CL
max
= 1.80
L
8.0
CL
max
0.0
10.00
41.67
= 0.93
TO
73.33
CL
= 1.93
max
CL
max
TO
105.00
136.67
= 2.93
TO
168.33
(W/S)TO
200.00
lb
2
ft
Revised Design
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Take-off gross weight
Empty weight
Fuel weight
2,806 lbs
1,552 lbs
1,064 lbs
Regression Study of 18 UAVs
Design
Engine Power Estimation
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Wing loading = 22 lb/ft2
Power loading = 19 lb/hp
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Total Power Required = 2806/19  150 hp
Power Required per engine = 75 hp
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½ Scale to use two 3W-75 engines
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Graduate Design-Build-Fly Team
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Four students:
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David Borys
Satish Chilakala
Edmond Leong
Nelson Brown
Advisors:
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Dr. Richard Colgren
Jewon Lee (TA)
Collaboration
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Undergrad manufacturing class (AE510)
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Pittsburg State University
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Water-jet cutting
Templates
Kansas State University
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Center wing
Autopilot
You?
Goals
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Stability and control demonstrator for
CReSIS
Experience for KUAE
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Manufacturing larger aircraft
Operating sizable UAVs
Asset for ongoing
UAV research
Schedule
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October 11th PDR and Scaled Design
October 25th Begin Engine Testing
November 3rd CDR (Full Size and Scaled)
November 21st Start Construction
December 1st Final Presentation
December 5th Initial Flight Test Plan
December 15th Final Report Submission
January 20th All Scaled UAV Parts
May 15th First Flight
Current Scaled Design
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90 lb (empty)
18 ft span, 9 ft long
Main spar 1.75” dia., 1/8” thick, 6061-T6
aluminum tube
Wings
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Fiberglass skin
Balsa & Foam ribs
Fuselage
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Fiberglass skin
Wooden structure
Building the Cryohawk
Participation
Budget
Challenges
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Time
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Partnerships with:
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Undergraduate class
PSU
KSU
Embry-Riddle
Others?
Money
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Seeking support from:
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University of Kansas ($2,000)
CReSIS ($8,000)
Others?
Questions / Discussion
artist’s concept
artist’s concept