Modeling of Radar Signatures of Wake Vortices in Rainy weather

Size: px

Start display at page:

Download "Modeling of Radar Signatures of Wake Vortices in Rainy weather"

Morgan Barton
6 years ago
Views:

1 Modeling of Radar Signatures of Wake Vortices in Rainy weather Directeur de thèse: VINCENT François (ISAE, France), JEANNIN Nicolas (ONERA, France) LIU Zhongxun 27 th May, 213 1

2 Outline 1. Introduction 2. Raindrop s motion and distribution 3. Radar signatures simulation 4. Radar signatures interpretation 5. Conclusions and perspectives 2

3 Institut Supé rieur de l Aé ronautique et de l Espace 1. Introduction 1.1 Wake vortex hazards 1.2 Airport capacity 1.3 Candidate sensors for monitoring wake vortex 3

1.1 Wake vortex hazards What is wake vortex A disturbance in the air that occurs when a wing is generating lift the high-pressure air moves around the wingtip to the low pressure Two

4 1.1 Wake vortex hazards What is wake vortex A disturbance in the air that occurs when a wing is generating lift the high-pressure air moves around the wingtip to the low pressure Two counter-rotating vortices Wake vortex strength: initial circulation Especially hazardous during take-off and landing Illustration of two counterrotating vortices (Gilson, 1992; Myers, 1997) 4

Bowen) Wake vortices at high altitude as contrail Wake vortices made visible in a NASA test by using

5 1.1 Wake vortex hazards Wake vortex evolution (Four Phases) Ginevsky and Zhelannikov 29 Wake vortex can be made visible Wake vortices of Learjet 6 in cloud (Photo by P. Bowen) Wake vortices at high altitude as contrail Wake vortices made visible in a NASA test by using colored smoke rising from the ground Large extension: up to 3 kilometers behind the aircraft Long lifetime: several minutes Large strength: potential hazards 5

6 Wake vortex encounters (Breitsamter, 21) depending upon how the aircraft penetrates the wake vortex three main hazards caused by vortex encounters an increased structural dynamic load a loss of lift the induced roll 1.1 Wake vortex hazards 6

7 Current ICAO wake separation standards 1.2 Airport capacity classification based on aircraft weight (implemented over 4 years ago ) too conservative but not always safe ( when wake vortex under cross wind or ground effect) 7

8 1.2 Airport capacity EU project: SESAR (24-22) by 22 Long term CAPACITY +73% 3 SAFETY 3 1 Single European Sky ATM Research SESAR Project : Runway Wake Vortex Detection, Prediction and decision support tools Aviation Safety Airport Capacity Requirements on sensors for monitoring wake vortex in real time 8

$RADAR--- the refractive$ index fluctuations ---

9 1.3 Candidate sensors for monitoring wake vortex LIDAR SODAR RADAR Lockheed Martin OptiNav ASC THALES USDOT NUDT LIDAR---- the atmospheric aerosols in clear air (Mie scattering) SODAR-- the temperature (or density) fluctuations RADAR--- the refractive index fluctuations --- rain/fog droplets (Rayleigh or Mie scattering) 9

10 1.3 Candidate sensors for monitoring wake vortex Radar monitoring of wake vortex In clear air, radar reflectivity from wake vortex is extremely low Experiment results: Nespor et al : C band Shephard. 199 : S and X band In rainy weather, raindrops are strong scatterers Experiment results: F. Barbaresco, 212: X band Radar T. A. Seliga, 29: W band Radar 1

Meter-scale observations of aircraft wake vortices in precipitation using a high

11 W band radar trials in rain: 1.3 Candidate sensors for monitoring wake vortex T. A. Seliga and J. B. Mead. Meter-scale observations of aircraft wake vortices in precipitation using a high resolution solid-state W-band radar. In The 34 th conference on Radar Meteorology, 29. Location of the W-Band Radar at Boston s Logan Int. Airport W-Band Radar parameters 11

power level of the signal within each range bin, and peak

12 W band radar trials in rain (29): 1.3 Candidate sensors for monitoring wake vortex Peak spectral power level of the signal within each range bin, and peak Doppler velocity Time history of the wake vortices detected by the W-Band Radar on March 26, 29 12

2.2 XP trials campaign at Paris CDG Airport.

13 X band radar trials in rain (212): 1.3 Candidate sensors for monitoring wake vortex F. Barbaresco. Radar/Lidar Sensors for Wind & Wake-Vortex Monitoring on Airport: First results of SESAR P XP trials campaign at Paris CDG Airport. In WakeNet3-Europe 4th Major Workshop "Wake Turbulence in Current Operations and Beyond", 212. Wake-Vortex Sensors Deployment Close to Runways under the glide slope WINDCUBE-2S BOR-A radar 13

14 X band radar trials in rain (212): 1.3 Candidate sensors for monitoring wake vortex X band radar parameters Time Doppler spectrum of raindrops in three successive radar cells 14

15 1.4 Objective of the Dissertation Radar is a potential sensor for monitoring wake vortex in rain, very few research has been reported until now to model and evaluate the radar signatures of wake vortex in rainy weather. Thus, some critical problems arising from this requirement need to be studied: Raindrops motion and distribution in wake vortices; Radar signatures of raindrops in wake vortex; Interpretation of wake vortex radar signatures. 15

16 1.4 Objective of the Dissertation 16

17 Institut Supé rieur de l Aé ronautique et de l Espace 2. Raindrops motion and distribution 2.1 Parametrization of raindrops 2.2 Wake vortex velocity field 2.3 The equation of motion 2.4 Raindrop s trajectory in wake vortices 2.5 Raindrop s distribution in wake vortices 17

2.1 Parametrization of raindrops Raindrop size distribution Raindrop s terminal falling velocity Asumptions for Raindrops: spherical and not deformable no collision or coalescence (Atlas and

18 2.1 Parametrization of raindrops Raindrop size distribution Raindrop s terminal falling velocity Asumptions for Raindrops: spherical and not deformable no collision or coalescence (Atlas and Ulbrich 1974; Owolawi 21) no significant evaporation or condensation D. Atlas, R. C. Srivastava, and R. S. Sekhon 1973; V. N. Bringi and V. Chandrasekar 24.5mm - 4. mm A. B. Kostinski and R. A. Shaw, 29 18

19 y(m) 2.2 Wake vortex velocity field Hallock-Burnham model Biot-Savart Law Assumptions for wake vortex: the background atmosphere is still air the wake vortex is in stable phase 2D velocity field of A34 wake vortices Descent velocity x(m) Aircraft landing weight: 259 kg; Landing speed: 29 km/h; Wingspan: 6.3 m 2 m/s 19

20 2.2 Wake vortex velocity field Vertical velocity profile on a line passing through the wake vortex centroids of three types of aircrafts: an A32, an A34 and an A38 Illustration of the descent of wake vortex pairs behind three types of aircrafts: A32, A34 and A38 2

21 2.3 The equation of motion Stokes number St ts t flow t V g s T t 2 r V flow1 max max The Stokes number of raindrops in wake vortex Diameter.5 mm mm mm mm Stokes number 21

22 2.3 The equation of motion Under the assumption of one-way coupling, the motion of a raindrop is governed by its gravity the fluid drag force Equation of motion of raindrops Four variables differential equations 4 th order four variables Runge- Kutta algorithm 22

23 Vertical: m Vertical: m Vertical: m 2.4 Raindrop s trajectory in wake vortices Diameter=.5mm Diameter=1.mm Diameter=4.mm t Ss t Horizontal: m Horizontal: m Horizontal: m S t =.286 S t =.567 S t = The trajectories of raindrops with smaller diameters seem to be more largely changed by the vortex flow; In some part of the region under the vortex flow, there are no raindrops falling down; In the region between the two vortex cores, some of raindrops are preferentially concentrated, the velocities of the raindrops here are also considerably increased

24 Y: m Raindrops' trajectories in wake vortices with different circulation 25 D = 1. mm (b) 2.4 Raindrop s trajectory in wake vortices 2 Wake vortex circulation: X: m m 2 /s m 2 /s m 2 /s.. 3 m 2 /s The motion characteristic of raindrops (d) in wake vortices is representative of the vortex strength. 24

25 2.5 Raindrop s distribution in wake vortices The methodology to approximately compute raindrops' distribution in wake vortices by box counting method: Number concentration Horizontal velocity distribution Vertical velocity distribution 25

columns, there are two narrow regions where the number concentration of raindrops

26 2.5 Raindrop s distribution in wake vortices In the wake vortex region, there are two columns where the raindrops' concentration is zero and between these two columns, there are two narrow regions where the number concentration of raindrops is enhanced. Number concentration Horizontal velocity (m/s) Vertical velocity (m/s) 26

and velocity distribution (.5mm, 2 mm) 15 1 Raindrop concentration (D=.

-15-15 -1-5 5 1 15 X: m -12 15 1 Raindrop concentration (D=2.

27 Y: m Y: m Y: m Y: m Y: m Y: m 2.5 Raindrop s distribution in wake vortices Raindrops number concentration and velocity distribution (.5mm, 2 mm) 15 1 Raindrop concentration (D=.5mm) Horizontal velocity (D=.5mm) Vertical velocity (D=.5mm) X: m X: m X: m Raindrop concentration (D=2.mm) Horizontal velocity (D=2.mm) Vertical velocity (D=2.mm) X: m X: m X: m

28 Institut Supé rieur de l Aé ronautique et de l Espace 3. Radar signatures simulation 3.1 Wake vortex Radar simulators 3.2 X band Radar in staring mode 3.3 X band Radar in scanning mode 3.4 W band Radar in scanning mode 28

29 3.1 Wake vortex Radar simulators Microwave properties of raindrops Rayleigh Approximation S, C, X bands Raindrops RCS as function of diameter Mie Formulas Ka, W bands 29

30 Simulator A: Simulator B: 3.1 Wake vortex Radar simulators # Rain rate # DSD Radar Parameters Radar Parameters # Rain rate # DSD Update of position and velocity of each raindrop Radar Equation Radar signal time series Computation of Radar Signatures Radar reflectivity and velocity spectrum 3

31 Simulator A : A time series wake vortex radar simulator 3.1 Wake vortex Radar simulators v h R 31

32 Simulator B : Raindrop's distribution based radar simulator The radar reflectivity of raindrops in the kth radar cell is given by 3.1 Wake vortex Radar simulators where i, j are indices of the grid boxes which are located in the kth radar cell. where i, j are the indices of the grid boxes where the raindrop's radial velocity is < 32

33 3.1 Wake vortex Radar simulators Simulator A: Radar signatures simulation based on superimposing the radar signals from all the raindrops in the radar cell Simulator B: Radar signatures simulation based on the raindrops statistical distribution Firstly, the database of the raindrop's distribution is independent of the rain rate and DSD model, the radar signatures of raindrops in wake vortices under different rain rates or DSD models can be simulated very easily and efficiently. Secondly, the computation load is much lower compared to the simulation based on the generation a large population of raindrops in the radar resolution volume. Thirdly, the in-phase (I) and quadrature (Q) components of the radar signal time series can also be obtained by taking an inverse discrete Fourier transform of the spectrum and noise model. 33

34 Vertical: m Generation of the initial raindrops 3.2 X band Radar in staring mode (Simulator A) Rainrate: 1.19 mm/h :.5 mm : 1. mm : 2. mm : 3. mm : 4. mm Horizontal: m 34

35 db db db Doppler spectrum for 4m radial resolution 3.2 X band Radar in staring mode (Simulator A) Radar cell: 2 Radar cell: 3 Radar cell: Doppler velocity: m/s Doppler velocity: m/s Doppler velocity: m/s 35

36 db db db Doppler spectrum for 1m radial resolution 3.2 X band Radar in staring mode (Simulator A) Radar cell: 1 Radar cell: 2 Radar cell: Doppler velocity: m/s Doppler velocity: m/s Doppler velocity: m/s 36

37 Y: m 3.3 X band Radar in scanning mode (Simulator B) Radar-Wake vortex geometry configuration (close to runway) : left vortex core x : right vortex core Simulation region C 25 D A X: m B 37

V r : m/s V r : m/s V r : m/s V r : m/s V r : m/s 3.

reflectivity (rain rate: 1 mm/h ) Time-Doppler velocity

m 2 /m 3 (a) (b) (c) (d) (e) -25-3 -35 s 1 s 2 s 3 s 4 s 5 s

3 s 4 s 5 s 3 s 4 s 5 s 6 s (a) 2-2 1 2 3 4 5 6 (b) 2-2 1 2

3 4 5 6-4 -5-6 -7-8 -9-4 -5-6 -7-8 -9-4 -5-6 -7-8 -9-4 -5-6

38 V r : m/s V r : m/s V r : m/s V r : m/s V r : m/s 3.3 X band Radar in scanning mode (Simulator B) Radar reflectivity (rain rate: 1 mm/h ) Time-Doppler velocity spectrum db m 2 /m 3 db m 2 /m 3 db m 2 /m 3 db m 2 /m 3 db m 2 /m 3 (a) (b) (c) (d) (e) s 1 s 2 s 3 s 4 s 5 s 6 s s 1 s 2 s 3 s 4 s 5 s 6 s s 1 s 2 s 3 s 4 s 5 s 6 s s 1 s 2 s 3 s 4 s 5 s 6 s s 1 s 2 s 3 s 4 s 5 s 6 s (a) (b) (c) (d) (e)

39 3.3 X band Radar in scanning mode (Simulator B) Radar-Wake vortex geometry configuration (Thales radar trials) Scanning rate: 8 /s Scanning area: 5-8 Location of the right vortex core: 7 m, 6 (élévation) M range cells, N elevation angles Output: Radar signatures M N For each radar cell, compute the time- Doppler signature in scanning mode 39

V r : m/s V r : m/s V r : m/s Range: 72 m 3.

2 1-1 -2-6 -7-8 -9 1 2 3 4 5 6 7 8 Time: s Range: 64 m 2 1-1 -2-6 -7-8

40 V r : m/s V r : m/s V r : m/s Range: 72 m 3.3 X band Radar in scanning mode (Simulator B) Comparison with X band radar trials (F. Barbaresco 212) Time: s Range: 68 m Time: s Range: 64 m Time: s (a) Simulated time-doppler spectrum of raindrops in wake vortices (b) Time-Doppler spectrum observed by Thales radar trials in 211 4

41 Elevation (m) Elevation (m) Elevation (m) Elevation (m) Elevation (m) Elevation (m) 3.4 W band Radar in scanning mode (Simulator B) W band radar signatures of raindrops at different times (rain rate: 2 mm/h) Average received power Peak Doppler velocity profile 3 t = 1 s 15 3 t = 5 s Range (m) Range (m) t = 1 s 15 3 t = 2 s Range (m) Range (m) t = 4 s 15 3 t = 6 s Range (m) Range (m)

95 1 15 11 115 Range (m) 3 25 2 15 Doppler Velocity 1 85 9

42 Elevation (m) Elevation (m) 3.4 W band Radar in scanning mode (Simulator B) Comparison with W band radar trials (T. A. Seliga 29) 3 Average Power Range (m) Doppler Velocity Range (m) Rain rate 2.mm/h, Range Resolution: 2 m W-Band Radar Measurements (T. A. Seliga 29) 42

43 Institut Supé rieur de l Aé ronautique et de l Espace 4. Radar signatures interpretation 4.1 Dependence of radar signatures on vortex circulation 4.2 Wake vortex detection 4.3 Wake vortex parameter estimation 43

44 V r : m/s db 4.1 Dependence of radar signatures on vortex circulation X band Radar Doppler signatures in one scanning period between vortices between vortices In still air Left vortex Between vortices Right vortex right vortex left vortex in still air left vortex right vortex Time: s Time-Doppler spectrum of raindrops in one scanning period V r : m/s Comparison of the Doppler velocity spectrums of raindrops in still air and in wake vortices The Doppler spectrums widths of raindrops around the left vortex and right vortex are obviously extended The Doppler spectrum of raindrops between the two vortices are shifted and the spectrum widths are also extended 44

45 4.1 Dependence of radar signatures on vortex circulation Three moments of radar Doppler spectrum are utilized to interpret the radar signatures: radar average received power (zeroth moment), mean Doppler velocity (first moment ) Doppler spectrum width (second moment ) Obviously, the mean Doppler velocity is related to the power weighted mean radial motion of the particles and the Doppler spectrum width is related to the relative particle motions. 45

46 4.1 Dependence of radar signatures on vortex circulation Relationship between Doppler spectrum width of raindrops and vortex circulation The Doppler spectrum width of raindrops is representative of wake vortex circulation, as vortex circulation decays, the Doppler spectrum width of raindrops is decreasing. 46

47 4.2 Wake vortex detection Radar geometry congurations for different radar range resolutions +' and 'x' indicate the location of the left and right vortex respectively 47

48 Range cell Range cell Range cell Range cell Range cell Range cell Range cell Range cell Range cell Range cell Interpretation of radar Doppler signatures of raindrops 4.2 Wake vortex detection Radar reflectivity Mean Doppler Vel Spectrum width Radar reflectivity Mean Doppler Vel Spectrum width th scan 5th scan 5th scan 15th scan 15th scan 15th scan 3th scan 3th scan 3th scan 45th scan 45th scan 45th scan 5th scan th scan 5th scan 15th scan 5 15th scan 15th scan th scan 5 3th scan 3th scan th scan 5 45th scan 45th scan th scan 6th scan 6th scan 6th scan 5 6th scan 6th scan Elevation angle: o Elevation angle: o Elevation angle: o Elevation angle: o Elevation angle: o Elevation angle: o (a) Radar reflectivity: db (b) Mean Doppler velocity: m/s (c) Doppler spectrum width: m/s (a) Radar reflectivity: db (b) Mean Doppler velocity: m/s (c) Doppler spectrum width: m/s 48

49 Range cell index Range cell index 4.2 Wake vortex detection Wake vortex detection Given the I & Q radar signal time series from a sequence of radar scans, the procedures for wake vortex detection can be summarized as the following: (1) Computation of the Doppler velocity spectrum for raindrops; (2) Estimation of the Doppler spectrum width; (3) For the Range-Elevation map of Doppler spectrum width of raindrops at each scan, determination of the two radar cells with peak values of Doppler spectrum width by local peak detection algorithms Doppler spectrum width (m/s): 11th scan Detection results: 11th scan Elevation angle index Elevation angle index.1 49

50 Wake vortex parameter estimation Wake vortex position 4.3 Wake vortex parameter estimation Vortex separation Vortex circulation and descent velocity 5

51 X : m Vortex separation: m Y : m Y : m 4.3 Wake vortex parameter estimation Estimation of Wake vortex position and vortex separation 7 65 Left vortex: True value Left vortex: Estimation 7 65 Right vortex: True value Right vortex: Estimation Time: s Vertical location of left vortex Time: s Vertical location of right vortex Left vortex: True value Left vortex: Estimation Right vortex: True value Right vortex: Estimation True value Estimation Time: s Horizontal location Scan number Vortex separation computed from a sequence of scans 51

52 Wake vortex circulation: m 2 /s Descent velocity: m/s Estimation of descent velocity and vortex circulation 4.3 Wake vortex parameter estimation True value -2.5 Left vortex estimation Right vortex estimation Time: s Estimated descent velocity of wake vortex pair (Radar under flight path observation) True value Left vortex estimation Right vortex estimation Scanning time: s Wake vortex circulation estimation 52

53 Institut Supé rieur de l Aé ronautique et de l Espace 5. Conclusions and perspectives 5.1Conclusions 5.2 Perspectives 53

54 5.1 Conclusions The radar signatures of wake vortices in rainy weather have been modeled and analyzed in three successive steps: Computation of the raindrops motion and distribution Simulation of the radar signatures of raindrops Interpretation of the simulated radar signatures A series of valuable models and methodologies, which can be further exploited for designing new wake vortex radar systems, have been developed, including: A methodology to compute the raindrops' trajectory in wake vortices A methodology to compute the raindrops' distribution in wake vortices A wake vortex radar simulator based on radar signal time series A wake vortex radar simulator based on the raindrops' number concentration and velocity distribution in wake vortices 54

55 5.1 Conclusions A methodology based on the computation of three spectral moments to interpret the radar signatures of raindrops in wake vortices A wake vortex detection method based on the analysis of Doppler spectrum width of raindrops A methodology to estimate the wake vortex characteristics, including the position, vortex separation, descent velocity and vortex circulation The simulation results are consistent with the results of radar trials and the capability of X/W band radar to detect wake vortex in rainy weather have been demonstrated. The raindrops appear to be the wake vortex tracer, hence, wake vortex is visible: by eyes due to cloud droplets motion or contrail by Lidar due to the aerosols motion within it by Radar due to the raindrops motion within it 55

56 5.2 Perspectives Conclusions The analysis of raindrops' motion and distribution can be improved by integrating non-idealized atmospheric characteristics Interaction between raindrops (collision or coalescence) and the effects of raindrops on wake vortex should be further studied The developed radar simulators can be extended to the study of radar signatures of other hydrometeors like fog, cloud or snow Exploitation and upgrade of the radar simulators: optimal radar parameters, on-board detection, polarimetric measurements, GPU parallel computation Wake vortex detection and characterization: detection and false alarm probability, circulation estimation based on the retrieval of wake vortex velocity field from the radar signatures of raindrops in wake vortices 56

57 Thank you for your attention! 57

Zhongxun LIU (ISAE/NUDT), Nicolas JEANNIN(ONERA), François VINCENT (ISAE), Xuesong WANG(NUDT)

Institut Supérieur de l Aéronautique et de l Espace Radar Monitoring of Wake Turbulence in Rainy Weather: Modelling and Simulation Zhongxun LIU (ISAE/NUDT), Nicolas JEANNIN(ONERA), François VINCENT (ISAE),