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HEND science after 9 years in space    

HEND science after 9 years in space    .

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HEND science after 9 years in space    

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  1. HEND science after 9 years in space    

  2. HEND (High Energy Neutron Detector)was developed in Space Research Institute in 1996-2001 specially for NASA Mars Odyssey mission to provide global orbital mapping of Martian neutron albedo in different energy bands. It includes three proportional counters surrounded with different thickness polyethylene and organic scintillator to detect neutrons starting from 0.4 eV up to 10 MeV.

  3. HEND Instrument Status

  4. HEND health: HEND operates nominally in science operation mode, none of anomalies are observed, all detectors (5 for measuring neutrons, 2 for gammas) are on and in a good shape. No spectra degradation is visible in HEND detectors, spectra shape is very stable. Current examples of spectra (accumulated for Apr 2010) in proportional counters (epithermal neutrons) and in organic scintillator (fast neutrons) are presented below in comparison with spectra measured at the beginning mapping in April 2002

  5. HEND/Mars Odyssey SCIENCE • Global Mapping of Mars neutron flux in different energy ranges • Global Mapping of water distribution in Martian subsurface down to depth 1m • Observation of Mars seasons • Observation of Galactic cosmic rays flux variations (solar cycle) • Observation of Solar Particle Events • Participation in Gamma Ray Burst Interplanetary Network

  6. Global Mapping of Mars neutron flux in different energy ranges & Global Mapping of water distribution in Martian subsurface down to depth 1 m

  7. North South Summer Epithermal neutron flux map averaged over 8 years of orbit observations Ten times drop off of neutron flux showed presence of water ice Ten times drop off of neutron flux showed presence of water ice

  8. SD sensor LD sensor Stilben Neutron Energy

  9. Model Testing Machine =  (Cik – Mik)2 2 ik2 Different detectors (Cik ,ik2) (Mik) Testing model & MCNPX code Where k - index of given pixel on map, Cik – normalized (to Solis Planum, where we suggested presence of 2% of water by weight) counting rates in different i detectors (SD, MD, LD, Stilben), ik – statistical erorrs of counting rates, Mik – normalized (to 2% of water) modeled counting rates corresponded to the water distribution with given parameters (thickens of upper layer and water content in bottom one)

  10. Depth (cm) Results: North high latitudes Ice depth and water content distributions Water (%) 40N 40N

  11. Depth (cm) Results: South high latitudes Ice depth and water content distributions Water (%) 40S 40S

  12. Observation of Mars seasonal caps

  13. Condensation of atmospheric CO2 on Mars polar and near polar regions North South Summer Winter

  14. North Hemisphere Spring Summer Fall Winter 80N-90N

  15. North Hemisphere Spring Summer Fall Winter 80N-90N 70N-80N

  16. North Hemisphere Spring Summer Fall Winter 80N-90N 70N-80N 60N-70N

  17. North Hemisphere Spring Summer Fall Winter 80N-90N 70N-80N 60N-70N 50N-60N

  18. Southern Hemisphere Fall Winter Spring Summer 80S-90S

  19. Southern Hemisphere Fall Winter Spring Summer 80S-90S 50S-60S 70S-80S

  20. Southern Hemisphere Fall Winter Spring Summer 80S-90S 50S-60S 70S-80S 60S-70S

  21. Southern Hemisphere Fall Winter Spring Summer 80S-90S 50S-60S 70S-80S 60S-70S 50S-60S

  22. Polar regions of Mars. Production of neutrons in the subsurface (<1-2 m depths) Summer Subsurface depth [ < 1-2 m below the surface ] Water ice rich layer Neutron signal vs Martian seasons Observable subsurface layer consists of water ice only Martian seasons, Ls

  23. Polar regions of Mars. Production of neutrons in the subsurface (<1-2 m depths) Fall,Winter&Spring Dry CO2 deposit Subsurface depth [ < 1-2 m below the surface ] Water ice rich layer Neutron signal vs Martian seasons Observable subsurface layer consists of water ice only Martian seasons, Ls

  24. Inter annual variations Many years on the orbit give us possibility to measure inter annual variations of Martian seasonal cycle: how it is changes on the base of four successive Martian years.

  25. Inter-annual variations of Northern seasonal cap (60N-90N)

  26. Inter-annual variations of Southern seasonal cap (60S-90S)

  27. 80N-90N Northern polar cap 70N-80N 60N-70N Different colors dots corresponds to the different Martian years. Black solid curves corresponds to the column density averaged through the several Martian years

  28. Southern polar cap 80S-90S 60S-70S 70S-80S Different colors dots corresponds to the different Martian years. Black solid curves corresponds to the column density averaged through the several Martian years

  29. Estimation of volume density (g/cm3) of northern seasonal cap HEND ρ 0.33 g/cm3 MOLA HEND: Max column density ~40 g/cm3 MOLA: Max thickness ~1.2 m

  30. Masses of seasonal caps Knowing column density of CO2 deposit it is possible to go to the estimation of total masses of Martian seasonal caps. Because Mass of CO2 at given region is equal to multiplication of average column density by area of this region. Summing by latitude belts we may estimate the total mass of northern and southern seasonal cap and make comparison with predictions of General Circulation Model (NASA Ames Research Center) and other measurements taken for example from GRS/Mars Odyssey & NS/Mars Odyssey or with gravity models.

  31. Mass of northern seasonal cap (60N-90N)

  32. Mass of southern seasonal cap (60S-90S)

  33. CONCLUSIONS • Continuous mapping of Mars neutron albedo for ~ 9 years. • Detection of significant regional variations as a signature of water/water ice • Observation of seasonal variations • Coverage of several Martian years. Monitoring of year to year difference • Water/Water ice distribution. • Detection of water ice at high latitude north and south provinces. • Model depended deconvolution of data to test double layered model of regolith • Mapping of water ice content and ice depth • Estimation of CO2 deposit’s column density (g/cm2) • Estimation of CO2 column density at different latitude belts. • Estimation of mass of seasonal caps • Estimation of CO2 deposit’s volume density (g/cm3) from comparison with MOLA • Comparison with other data sets • Comparison with GCM • Comparison with GRS data • Comparison with MOLA data

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