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IPPW-10

Royal Observatory of Belgium. von Karman Institute for Fluid Dynamics. Mars atmosphere reconstruction using FADS on ExoMars EDM. Bart Van Hove Ö zgür Karatekin Royal Observatory of Belgium Ringlaan 3, Brussel 1180 bartvh@observatory.be 10 th International Planetary Probe Workshop

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IPPW-10

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  1. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Mars atmosphere reconstructionusing FADS on ExoMars EDM Bart Van HoveÖzgürKaratekin Royal Observatory of BelgiumRinglaan 3, Brussel1180bartvh@observatory.be 10th International PlanetaryProbe Workshop San Jose, CA, US18 June 2013 IPPW-10 18 June 2013

  2. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Why is reconstruction important? • Mars is the ultimate test facility: learn from one mission to design the next • Trajectory reconstruction • Vehicle response:deceleration, velocity, attitude • Atmosphere reconstruction • What environmentproduces the vehicle response? • Constrain environment to validate ground predictions • Constrain Mars climate models • ExoMars EDL Demonstrator Module (EDM) will land during the 2016 Mars dust season Viking Pathfinder MSL IPPW-10 18 June 2013

  3. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Reconstructing from conventional instrumentation • Inertial Measurement Unit = IMU • Positional measurements by accelerometers and gyroscopes • Estimate atmosphere from trajectory reconstruction: • Densityfrom acceleration and drag coefficient • Pressure from hydrostatic equilibrium • Temperature from ideal gas law • Atmospheric reconstruction starts from density from drag equation: • acceleration aerodynamic drag coefficienttrue air speed IPPW-10 18 June 2013

  4. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Reconstructing from heat shield instrumentation • Flush Air Data System = FADS • Installed on MSL and ExoMars EDM 2016:heat shield surface pressure sensors • Flow field measurements include atmospheric motion FADSsolver IMU trajectory True air speed Atmospheric densityAtmospheric winds FADS pressure signals Surface pressure model Relation to free stream • Does not require aerodynamic drag model: could instead be validated IPPW-10 18 June 2013

  5. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Presentation overview • Toolkit development: EDL simulation and reconstruction tools • ExoMars EDM 2016: preliminary study reconstruction uncertainty Atmospheric reconstruction at high velocities, before parachute opening IPPW-10 18 June 2013

  6. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Toolkit development Match reconstruction at parachute deployment • Reconstruction tool + Monte Carlo • Validated in Mars Phoenix case study(public IMU flight data set) • Matches independent reconstructions • Monte Carlo with time varying bias and noise errors • 6-DOF entry simulator • To produce flight data (IMU and FADS) • No parachute phase, no guidance • Validated in collaboration NASA Langley IPPW-10 18 June 2013

  7. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM 2016: preliminary reconstruction study • Solar longitude: 244.8 ° in dust season • Unguided ballistic entry • Mars entry interface • Altitude: 120 km Longitude: 344.6 ° Latitude: 4.5°Speed: 5.9 km/s Flight path: -12.7 ° Azimuth: 124 ° • IMU & FADS instrumentation • Sampling frequencies: • IMU 100 Hz • FADS 10 Hz • Preliminary uncertainty estimates ExoMars EDM 2016 entry vehicle IPPW-10 18 June 2013

  8. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: 6-DOF simulation • Simulated up to parachute opening at Mach 2 • MCD (Mars Climate Database) dust storm scenario predicted by LMD GCM [Forget et al.] • Reproduces expected flight behavior • → Let’s reconstruct from the synthetic flight data Δt= 2 ms ESA aero v5.12 MCD 5.0 dust IPPW-10 18 June 2013

  9. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: impact of assumptions in IMU atmosphere reconstruction • Typical error sources in IMU reconstruction • Start from “true” MCD density profile provided to 500 Hz simulation (dust storm scenario) • Reconstruct at 100 Hz like the ExoMars IMU • Assume pure CO2 instead of actual gas mixture • Neglect winds since IMU can’t resolve those • Incorrectly model the drag coefficient (+ 3-σ) • Conclusion • Neglecting wind can be as detrimentalas mispredicting the drag coefficient! IPPW-10 18 June 2013

  10. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Strong winds along EDM trajectory: especially during dust storms • EDM will fly along the equator • Seen from the Mars surface:stronghigh altitude retrograde wind • Seen from space: atmosphere lags behind rigid planet rotation • Caused by migrating thermal tides due to solar heating Relative velocity and atmospheric density from IMU data are uncorrected for winds Could we improve density reconstruction by estimating winds from FADS? MCD 5.0 (Mars Climate Database) wind profiles IPPW-10 18 June 2013

  11. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: FADS reconstruction methodology • Rebuild oncoming flow from heat shield instrumentation angle of attack α side slip angle β • Surface pressure distribution modelstagnation pressure and flow angles • Shock wave pressure ratio • Derive density from dynamic pressureair speed from IMU (neglecting winds)or FADS (corrected with wind estimate) ? stagnationpressurept2 corrected for winds? surface pressure IPPW-10 18 June 2013

  12. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: FADS reconstruction methodology • Rebuild oncoming flow from heat shield instrumentation • Surface pressure distribution model • Modified Newtonian flow model: • Non-linearleast-squares solver • Solve for and flow angles from • Fix atmospheric pressure from IMU • (errors on have small impact since ) • True flow angles: sensitive to wind velocity angle of attack α side slip angle β stagnationpressurept2 with IPPW-10 18 June 2013

  13. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: FADS reconstruction methodology • Rebuild oncoming flow from heat shield instrumentation • Shock wave pressure ratio • Normal shock wave conservation equations • VKI Mutation library: high temperature gas properties for 5-species CO2[Magin et al. 2009] • 1-D flow solver to build a database of • High temperature effects are main approximation inanalytical cold gas relations – up to 5% difference! angle of attack α side slip angle β stagnationpressurept2 IPPW-10 18 June 2013

  14. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: FADS reconstruction methodology • Rebuild oncoming flow from heat shield instrumentation • Derive density from dynamic pressure • Air speed from IMU (no winds) or corrected using FADS wind velocity estimates • Wind estimate from true FADS flow angles • Non-linear LSQ solver neglecting vertical wind IPPW-10 18 June 2013

  15. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Monte Carlo: FADS reconstruction vs. IMU MCD 5.0 dust • IMU density estimate: large bias error (neglects winds) • FADS with IMU air speed: similar to IMU < 80 km • FADS with corrected air speed: wind estimate too noisy • Limited benefit from additional sensors Conclusion Poor wind estimate increases uncertainty Both FADS and IMU over 5% uncertainty on IPPW-10 18 June 2013

  16. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: horizontal wind estimate from FADS Along the entire entry trajectory the wind estimation error ≥ wind amplitude IPPW-10 18 June 2013

  17. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: uncertainties for different weather scenarios Dust storms strongly affect atmospheric profiles: detectable below 80 km IPPW-10 18 June 2013

  18. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Hypothetical FADS pressure sensors to resolve winds • Imagine very accurate pressure sensors over the entire (high velocity) trajectory • Density bias error reduced: especially at high altitudes where winds are strongest IPPW-10 18 June 2013

  19. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Hypothetical FADS pressure sensors to resolve winds IPPW-10 18 June 2013

  20. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Summary & Conclusions • Approximate general FADS solver: modified Newtonian 1-D flow • Winds can affect air speed and density estimate • Currently difficult to resolve from FADS pressure measurements • Additional low range pressure sensors • Atmospheric reconstruction sufficiently accurate to detect dust storms IPPW-10 18 June 2013

  21. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Future work • Coupled FADS-IMU reconstruction using Kalman filtering • FADS reconstruction based on CFD • Consider other Mars missions • Consider Doppler analysis of radio communications • Simulate parachute phase (multi-body model under development) IPPW-10 18 June 2013

  22. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Acknowledgements François Forget – Université Paris Jeffrey Herath/ Juan Cruz / Daniel Litton– NASA Langley Research Center Paul Withers– Boston University ESA Education IPPW student support project support IPPW-10 18 June 2013

  23. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics References IPPW-10 18 June 2013

  24. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics ExoMars EDM: is a dust storm detectable? Dust storm impact density profile very strongly: should be detectable above 20 km IPPW-10 18 June 2013

  25. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Impact of approximations on IMU temperature reconstruction IPPW-10 18 June 2013

  26. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Aerodynamic drag uncertainty IPPW-10 18 June 2013

  27. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics FADS normal shock wave pressure ratio • Discrepancy up to 7% with ideal (cold) gas approximation IPPW-10 18 June 2013

  28. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Toolkit development – 6-DOF entry simulator • Simulate entry to synthesize IMU and FADS flight data • Impact of atmospheric conditions, wind velocities… • Planet, aerodynamics, gravity, vehicle models • No parachute phase or real-time flight control systems • Validated in collaboration with NASA Langley IPPW-10 18 June 2013

  29. Royal Observatory of Belgium von Karman Institute for Fluid Dynamics Toolkit development – Reconstruction and Monte Carlo • Integrate IMU data to reconstruct entry profiles • Validated in our Mars Phoenix case study(only IMU available) • Good match with independent reconstructions • Monte Carlo with time varying bias and noise errors of various types and distributions Match reconstruction at parachute deployment IPPW-10 18 June 2013

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