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SINTEF ICT 1Adil RASHEEDResearch ScientistApplied MathematicsStrindveien 4, Trondheim, NORWAYwww.adilrasheed.comAdil.rashe...
SINTEF ICT• Background• Aviation• Wind Energy• Flow in complex terrain• Forecast• Computational efficiency and robustness•...
SINTEF ICTAMSTERDAM GENEVAPARIS FRANKFURTNON-NORWEGIAN AIRPORTS (Terrain)
SINTEF ICTNORWEGIAN AIRPORTS (Terrain)
SINTEF ICT 5Background: AviationWideroe DH8A on May 1st 2005The Aviation HeraldHammerfest AirportJust before landing the w...
SINTEF ICT 6Motivation: Wind Energy in complex terrainWind potential might change significantlyvary from one site to anoth...
SINTEF ICTWind shear in mountainous terrain
SINTEF ICTHORIZONTAL SHEAR
SINTEF ICTMountain waves: Qualilative Characteristics
SINTEF ICTMountain waves: Characteristics• Maximum amplitude on the leeward-side of the hill• Successive hills might enhan...
SINTEF ICTCan the flow characteristics be modelled ?11
SINTEF ICTGoverning Equations12
SINTEF ICTMountain WavesFr=1, stable stratificationFr=U/(NL)N2=(g/T)(dT/dz)Maximum amplitude on the leeward side of the hill
SINTEF ICTStokkaSANDNESSJØEN AIRPORT: STOKKATail wind on both directions of the runway
SINTEF ICTFr=0.2, Lateral movement of air more pronounced
SINTEF ICTFr=1, Ideal condition for the propagation of wavesWaves are diminished by destructive interference
SINTEF ICT
SINTEF ICT 18Confirm the Pilots experidence "Tail Wind from both sides of the runway"
SINTEF ICTCan we forecast flight conditions ?19The simulations seem to confirm pilots reports BUT…..
SINTEF ICTGlobal scales: seasonal changes,Sea currents etc. Meso scales: effects of largemountains, sea, forest, precipita...
SINTEF ICTNESTINGUM4UM1UM1UM1
SINTEF ICTSANDNESSJØEN AIRPORT
SINTEF ICT
SINTEF ICTHammerfest24
SINTEF ICTIs the model Computationally efficient and robust?25
SINTEF ICTNJORD: Hardware Configurations26• Technically192 nodes partitioned into 186 nodes, 4 input/ output nodes.186 nod...
SINTEF ICT 27
SINTEF ICTRobustness ?28
SINTEF ICTwww.ippc.no
SINTEF ICTValidation strategy ?30
SINTEF ICTALTA Normal Flight pathPILOTS REPORT:
SINTEF ICTRealistic Boundary condition to run offline simulations32
SINTEF ICTFree stream speed = 20m/s
SINTEF ICTVÆRNES AIRPORT
SINTEF ICT 35Photo : Pieter Morlion, The Nordic Page15 March 2012: Five people died when aHercules aircraft crashed in the...
SINTEF ICTKebnekaise case
SINTEF ICT 37
SINTEF ICT 38
SINTEF ICT 39Airport Siting: Farøe Island
SINTEF ICTApplication to Wind Energy: Bessaker Wind Farm40
SINTEF ICT
SINTEF ICT
SINTEF ICT
SINTEF ICTWind rose
SINTEF ICT
SINTEF ICT
SINTEF ICT
SINTEF ICTPower production in MW-h
SINTEF ICT
SINTEF ICTForecasting domainHARMONIE
SINTEF ICT
SINTEF ICT
SINTEF ICTConclusion53• A fully functional Multiscale Model for terrain induced turbulence prediction is in place• The pre...
SINTEF ICT 54NORWAY IS BEAUTIFULAdil.rasheed@sintef.no
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Appliecation of a Multiscale Turbulence Prediction System for Aviaiton Safety and Wind Turbine Siting

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Appliecation of a Multiscale Turbulence Prediction System for Aviaiton Safety and Wind Turbine Siting

  1. 1. SINTEF ICT 1Adil RASHEEDResearch ScientistApplied MathematicsStrindveien 4, Trondheim, NORWAYwww.adilrasheed.comAdil.rasheed@sintef.noApplication of a Multiscale TurbulencePrediction System for Aviation Safety andWind Turbine Siting
  2. 2. SINTEF ICT• Background• Aviation• Wind Energy• Flow in complex terrain• Forecast• Computational efficiency and robustness• Validation strategy• Application to Wind Energy• Conclusion2OVERVIEW
  3. 3. SINTEF ICTAMSTERDAM GENEVAPARIS FRANKFURTNON-NORWEGIAN AIRPORTS (Terrain)
  4. 4. SINTEF ICTNORWEGIAN AIRPORTS (Terrain)
  5. 5. SINTEF ICT 5Background: AviationWideroe DH8A on May 1st 2005The Aviation HeraldHammerfest AirportJust before landing the wind speed veered andincreased, creating a tail wind.The increase in the descent rate wascompensated, but was insufficient, and theplane had a touch-down on the right mainlanding gear, with the leg failing and theaircraft sliding on its belly.The aircraft was written off and Widerøe wascriticized for permitting landings under toohigh winds and gustsNorwegian Civil Aviation Authority imposedstricter wind regulations upon the airport.
  6. 6. SINTEF ICT 6Motivation: Wind Energy in complex terrainWind potential might change significantlyvary from one site to anotherExperimental and measurement techniquesAre not good enoughFarm Operators need wind forecast
  7. 7. SINTEF ICTWind shear in mountainous terrain
  8. 8. SINTEF ICTHORIZONTAL SHEAR
  9. 9. SINTEF ICTMountain waves: Qualilative Characteristics
  10. 10. SINTEF ICTMountain waves: Characteristics• Maximum amplitude on the leeward-side of the hill• Successive hills might enhance or diminish the strength of the waves• The waves are more pronounced when the buoyant andinertial forces are comparable. The ratio is defined by Froude no.
  11. 11. SINTEF ICTCan the flow characteristics be modelled ?11
  12. 12. SINTEF ICTGoverning Equations12
  13. 13. SINTEF ICTMountain WavesFr=1, stable stratificationFr=U/(NL)N2=(g/T)(dT/dz)Maximum amplitude on the leeward side of the hill
  14. 14. SINTEF ICTStokkaSANDNESSJØEN AIRPORT: STOKKATail wind on both directions of the runway
  15. 15. SINTEF ICTFr=0.2, Lateral movement of air more pronounced
  16. 16. SINTEF ICTFr=1, Ideal condition for the propagation of wavesWaves are diminished by destructive interference
  17. 17. SINTEF ICT
  18. 18. SINTEF ICT 18Confirm the Pilots experidence "Tail Wind from both sides of the runway"
  19. 19. SINTEF ICTCan we forecast flight conditions ?19The simulations seem to confirm pilots reports BUT…..
  20. 20. SINTEF ICTGlobal scales: seasonal changes,Sea currents etc. Meso scales: effects of largemountains, sea, forest, precipitationMicro scales:terrain effects,mountain wavesEach model is capable of resolving only a particularrange of spatio-temporal scalesThe problem can be handled through nesting ofdifferent models
  21. 21. SINTEF ICTNESTINGUM4UM1UM1UM1
  22. 22. SINTEF ICTSANDNESSJØEN AIRPORT
  23. 23. SINTEF ICT
  24. 24. SINTEF ICTHammerfest24
  25. 25. SINTEF ICTIs the model Computationally efficient and robust?25
  26. 26. SINTEF ICTNJORD: Hardware Configurations26• Technically192 nodes partitioned into 186 nodes, 4 input/ output nodes.186 nodes are shared memory nodes with 8 dual core power 5+ 1.9GHz processors each180 of the computational noes have 32 GB memory eachThe code is parallelized using MPI• MythologicallyNJORD is the God of the wind and fertility as well as the sea and merchantsat sea and therefore was invoked before setting out to sea on hunting andfishing expeditions. He is also known to have the ability to calm the watersas well as fire.
  27. 27. SINTEF ICT 27
  28. 28. SINTEF ICTRobustness ?28
  29. 29. SINTEF ICTwww.ippc.no
  30. 30. SINTEF ICTValidation strategy ?30
  31. 31. SINTEF ICTALTA Normal Flight pathPILOTS REPORT:
  32. 32. SINTEF ICTRealistic Boundary condition to run offline simulations32
  33. 33. SINTEF ICTFree stream speed = 20m/s
  34. 34. SINTEF ICTVÆRNES AIRPORT
  35. 35. SINTEF ICT 35Photo : Pieter Morlion, The Nordic Page15 March 2012: Five people died when aHercules aircraft crashed in the peak ofKebnekaise in northern SwedenREASON: INCONCLUSIVE
  36. 36. SINTEF ICTKebnekaise case
  37. 37. SINTEF ICT 37
  38. 38. SINTEF ICT 38
  39. 39. SINTEF ICT 39Airport Siting: Farøe Island
  40. 40. SINTEF ICTApplication to Wind Energy: Bessaker Wind Farm40
  41. 41. SINTEF ICT
  42. 42. SINTEF ICT
  43. 43. SINTEF ICT
  44. 44. SINTEF ICTWind rose
  45. 45. SINTEF ICT
  46. 46. SINTEF ICT
  47. 47. SINTEF ICT
  48. 48. SINTEF ICTPower production in MW-h
  49. 49. SINTEF ICT
  50. 50. SINTEF ICTForecasting domainHARMONIE
  51. 51. SINTEF ICT
  52. 52. SINTEF ICT
  53. 53. SINTEF ICTConclusion53• A fully functional Multiscale Model for terrain induced turbulence prediction is in place• The prediction system confirms the experiences recorded in the pilots reports and givespossible explanations• The code has been validated extensively against wind tunnel data for cubes, hills, cylinders• There is a scarcity of data for the validation of numerical codes but flight data, wind farmdata, weather station data can be used together to get better insight into the flow atmicroscales.• The data from the different sources can be used for fine tuning the models
  54. 54. SINTEF ICT 54NORWAY IS BEAUTIFULAdil.rasheed@sintef.no

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