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Using SeeYou for Soaring Flight Analysis

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

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Using SeeYou for Soaring Flight Analysis

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  1. Using SeeYou for Soaring Flight Analysis GPS-trace based flight analysis

  2. Real Question: How I do become a better cross-country glider pilot

  3. 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

  4. 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

  5. Quick review of theoretical underpinnings of X-country flight optimization • MacCready (deterministic) • Mathar (stochastic) • Cochrane (stochastic)

  6. Distance s A B Net lift l Net lift l in next thermal +/-inthermal airmass sink/lift vtarget vcruise polar sink ps at vtarget polar sink Cruise time to next thermal Time spent regaining altitude in thermal 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 • 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

  7. 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: • Key insight • Provides theoretical underpinning for common sense strategy to fly a little more on the cautious side based on uncertainty

  8. 2knots 6knots 2knots A B Ground 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

  9. 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 setting Additional 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 conservative Deficiencies: • 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

  10. Example of competitive analysis of G-Cup flights on May 19th, 2003

  11. A beautiful day…the weather on May 19th, 20029 completions to analyze1K2, B21 (2 flights), DRT, FD2, PX, SM, TB, TUP

  12. The Pros leave at ~1:30 pm… …with a few newcomers painting thermals on course for them Early bird, doesn’t catch the worm……but potentially gets to complete the G-Cup twice in a day!

  13. …but beginners might take heart and lower that nose… High Interthermal speed is not sufficient for success… Rush, ΔΣ (=Delta Echo)!

  14. MacCready alright… Too much of a good thing…is a bad thing… …especially when easy does it!

  15. ...but in modesty lies wisdom indeed!

  16. Circling for lift is so 20th century… Time well spent…?

  17. Low energy consumption is the name of the game, even when energy is free Scaling new heights

  18. Summary of Relevant statistics

  19. Summary of Relevant statistics 2

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