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Using SeeYou for Soaring Flight Analysis
GPS-trace based flight analysis
Real Question: How I do become a better cross-country glider pilot
Agenda
• Overview SeeYou capabilities
• Quick review of theoretical underpinnings of X-country flight optimization
• Example of competitive analysis of G-Cup flights on May 19th, 2003
Overview SeeYou Capabilities
• Turnpoint Database Management– Importing/creating new turnpoints– Modifying/deleting turnpoints
• Task Database Management– Importing tasks/creating new tasks– Modifying/deleting tasks
• GPS Trace Analysis– Importing GPS traces (connection wizzard)– Analyzing flights
• 2-D flight analysis– Single flight– Multiple flights– Synchronization– Customizing screen
• 3-D flight analysis– Single flight– Multiple flight– How to move about
• Barograph-type analysis of flight parameters– Cross-matching of parameters
• Statistical Analysis– Info Available– Selections
• Quick review of theoretical underpinnings of X-country flight optimization– MacCready (deterministic)– Mathar (stochastic)– Cochrane (stochastic)
MacCready Theory• Q: How fast should I fly based on known lift conditions ahead of me in order to minimize
time from A to B when my altitude is unlimited?• Answer: Classic speed-to-fly (MacCready) theory – provides explicit interthermal cruise
speed and implicit rule, in which thermals to climb
A BDistance s
Net lift l
lv
vpss
v
st
target
sink/liftairmass alintertherm/)(
targetB to A
target
vcruise
polarsink
vtarget
polarsink ps at
vtarget
Net lift l in next thermal +/-inthermal
airmass sink/lift
Cruise time to next thermal
Time spent regaining altitude in thermal
Two key constraints of MacCready theory:• Deterministic model, based on known net lift l – which in reality is unknown• Doesn’t account for limited altitude
Constraint 1: Uncertain lift – R. Mathar, Technical Soaring Oct 1996
• Q: How fast should I fly based on unknown lift conditions ahead of me in order to minimize time from A to B?
• Answer: If there is a distribution of expected lift set the MacCready ring (or equivalent device) to the harmonic mean rather than the arithmetic mean (=straight average)
Mathematics:
Practice:
l
1E
v
vpss
v
s
lv
vpss
v
sEE[t
target
sink/liftairmass alintertherm/)(
target
target
sink/liftairmass alintertherm/)(
targetB to A
target
target]
Key insight• Provides theoretical underpinning for common sense strategy to fly a little
more on the cautious side based on uncertainty
Lift distributionLift
(knots) ProbabilityMacCready
SettingCruise Speed
(LS-8 dry)
Cruise Time for 10 nm
(min)
Time to climb (min)
Total Time
Outcome A: 1 1/3 4 76 7.9 16.5 24.3Outcome B: 4 1/3 4 76 7.9 4.1 12.0Outcome C: 7 1/3 4 76 7.9 2.4 10.2
Average 15.5
Outcome A: 1 1/3 2.15 69 8.6 14.1 22.7Outcome B: 4 1/3 2.15 69 8.6 3.5 12.2Outcome C: 7 1/3 2.15 69 8.6 2.0 10.7
Average 15.2
Calculation of average speed flying according to MacCready theory using the arithmetic mean
Calculation of average speed flying according to MacCready theory using the harmonic mean
Constraint 2: Limited Altitude – R. Mathar, 1996
• Q: What is the best strategy in order to minimize time from A to B given variable known lift conditions and limited altitude?
• Answer: Depends on glider performance and the altitude available. With limited glider performance and/or limited altitude the weakest lift needed to get around the task is dominant in determining optimum speed-to-fly
Example:
Key insight• Provides theoretical underpinning for common sense strategy to fly a little
more on the cautious side with limited altitude
A B
Ground
2 knots 6 knots 2 knots
Combining the Constraints – J. Cochrane, 1999
• Q: What is the best strategy in order to minimize time from A to B given uncertain lift conditions and limited altitude?
• Answer: No closed form solution. Numerical investigation yields insights:Confirmation of standard McCready theory:• Set McCready ring (Speed-to-fly computer)• Fly best speed when lift below setting• Circle, if above settingAdditional insights relative to McCready theory:• Lower the setting as you get lower• Increase setting with altitude• Use setting well below best climb of day• Start final glides low & aggressive, end conservativeDeficiencies:• Thermals assumed static (daytime & height variability)• Information driven discrete strategies (clouds, topography) • Competitive dynamics (game theory, scoring asymmetries)• Wind, ballast options etc.
Key insight:Common sense is confirmed; implementation requires a statistical mindset when flying; real life too complicated for theory
• Example of competitive analysis of G-Cup flights on May 19th, 2003
A beautiful day…the weather on May 19th, 2002 9 completions to analyze1K2, B21 (2 flights), DRT, FD2, PX, SM, TB, TUP
Lift as a function of local time
-
1
2
3
4
5
6
7
8
9
10:00:00 11:00:00 12:00:00 13:00:00 14:00:00 15:00:00 16:00:00 17:00:00
Daytime (local)
Ave
rag
e L
ift
Rec
ord
ed (
kts)
Early bird, doesn’t catch the worm……but potentially gets to complete the G-Cup twice in a day!
Dependence of Speed achieved on Start Time
40
45
50
55
60
65
70
10:00 11:00 12:00 13:00 14:00 15:00 16:00
Task Start Time (local)
Avg
Sp
eed
(m
ph
)
The Pros leave at ~1:30 pm…
…with a few newcomers
painting thermals on coursefor them
Rush, ΔΣ (=Delta Echo)!
Dependence of Speed Achieved on Interthermal Cruise
40
50
60
70
55 60 65 70 75 80 85
Average Interthermal Cruise Speed (local)
Tas
k S
pe
ed
(m
ph
)
High Interthermal speed is not sufficient
for success…
…but beginners might take heart and lower
that nose…
Dependence of Speed Achieved on Interthermal Cruise Speed Variability
45
50
55
60
65
70
0 5 10 15 20
Interthermal Speed Variability (mph)
Ach
ieve
d T
ask
Sp
eed
(m
ph
)MacCready alright…
Too much of a good thing…is a
bad thing…
…especially when easy does it!
Dependence of L/D Achieved on Interthermal Cruise Speed Variability
30
35
40
45
50
0 5 10 15 20
Interthermal Speed Variability (mph)
Ach
ieve
d L
/D...but in modesty lies wisdom indeed!
Time well spent…?Composition of Task Time
0:00
1:00
2:00
3:00
4:00
0
10
20
30
40
50
60
70
80Time Circled (min)
Time in Straight & Level
Avg Spd (mph)
Circling for lift is so 20th century…
Scaling new heights
Composition and Amount of Altitude Gains Needed
-
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
11,000
12,000
13,000
Alt
itu
de
(m)
0
10
20
30
40
50
60
70
80
Task
Sp
eed
(m
ph
)
Height gain in straight f light (m)Height gain circling (m)Avg Spd (mph)
Low energy consumption is the name of
the game, even when
energy is free
Summary of Relevant statistics
Comp ID GliderAvg Spd
(mph)Start Time
LocalRelative Detours
Height Gain Circled (m)
Avg Climb (knots)
B21 -2 ASW 24 68.4 13:29 1.02 3,630 5.2
TB ASW 28 66.1 13:24 1.03 4,620 5.1
PX - normalized Scimitar 64.4 13:09 1.06 5,291 5.2
TUP LS-3 60.9 15:10 1.06 6,076 4.8
DRT LS-3 52.1 12:25 1.08 6,290 3.9
B21 ASW 24 51.5 10:37 1.09 5,620 3.8
1K2 LS-3 50.5 12:58 1.04 6,043 2.9
SM - normalized Kestrel 49.3 13:09 1.06 7,050 3.1
FD2 LS-3 46.7 13:18 1.06 5,519 3.1
40
45
50
55
60
65
70
10:00 11:00 12:00 13:00 14:00 15:00 16:00
Summary of Relevant statistics 2
Comp ID
Time Circling
(min)
Time in Straight &
LevelTotal Time
Height gain in straight flight
(m) Avg L/D
Avg Cruise Speed (knots)
StdDev Speed
Average Height
B21 -2 0:22 1:45 2:08 4,450 48 74 10 1,201
TB 0:29 1:43 2:12 3,521 40 76 11 1,317
PX - normalized 0:32 1:43 2:16 5,510 38 79 13 1,437
TUP 0:41 1:42 2:23 3,996 34 79 16 1,535
DRT 0:52 1:56 2:48 3,552 36 71 10 1,473
B21 0:48 2:02 2:50 4,260 47 68 7 1,127
1K2 1:07 1:45 2:53 3,118 35 75 7 1,264
SM - normalized 1:14 1:43 2:57 4,578 35 76 13 1,326
FD2 0:57 2:10 3:07 3,202 39 59 3 1,226
40
45
50
55
60
65
70
10:00 11:00 12:00 13:00 14:00 15:00 16:00
Av
g S
pe
ed
(m
ph
)