Simulating the dispersion of rotor-wash entrained dust

J.D. McAlpine

Atms 790 seminar

April 2, 2007

Collaborators:

Dr. D. Koracin

Dr. J. Gillies

Dr. D. Boyle

Introduction

Forecasting Desert Terrain Project

sponsored: Army Research Office

project coordinator: Dr. Eric McDonald

Our Aspect:- Exploring the flow field around a helicopter in ground effect

- What aspects of the flow field contribute the most to dust emission?

- Developing a method to simulate dust entrainment due to the helicopter flow field

- Coupled modeling of various scales mesoscale microscale

Developing a modeling method: outline

Why is helicopter dust emission a significant concern?

Modeling plan outline: - Computational Fluid Dynamics (CFD)- rotor wake simulation

- Dust entrainment simulation

- Particle modeling simulation

Upcoming Desert Terrain Rotorcraft Experiment- Measurement of helicopter flow features and dust dispersion

Why is dust entrainment a concern?

Regulation: PM emission inventories Clean air act: U.S. base operations Regional Haze Rule

Operation: Training simulation Visibility Equipment damage

Unknowns: flow field and dust source

1. Rotor jet distribution

and impingement

2. Turbulent burst

3. Surface jet

4. Vortex shedding

5. Re-entrainment

of dust

Modeling Scheme Elements

Proposed Modeling Scheme

Computational Fluid Dynamics (FLUENT)

Virtual Blade Model (VBM):

DRI Lagrangian Particle Model

Dust source term

CFD & VBM DRI LPM

Atmospheric simulation scheme

CAD ModelPost-processor:FiltererShear stress

Dust source term

Fluent CFD simulations:

Equations of motion solved over a discretized domain:• Continuity equation• Conservations of momentum• Energy equation• Equation of state• Turbulence parameterization scheme (K-eps, LES…)

initialization iteration solution

21Du pfv u

Dt x

Virtual Blade Model

vs.

Full blade modeling VBM: momentum source

• only time-averaged flow field needed• effects of flow on individual blades irrelevant• VBM: sophisticated technique- heli. specific

Virtual Blade Model: Blade Physics

21

2 LdL U cC dyForce= lift(L) – drag(D):

Blade Element Theory:

21

2 DdD U cC dy

•Lift & drag coefficients (CL and CD): f(angle)•U: function of blade orientation

Virtual Blade Model: in action

Model accounts for:

trimming, twist, chord var., flapping, coning Source evolves with solution: numerically stable Example: static pressure of validation case:

Untrimmed Trimmed

Atmospheric simulation

1st case: steady state neutral atmosphere

Desert Measurement Project Comparisons:- steady state profiles

- unsteady real-time

Final Product: - Coupled mesoscale-LES boundary layer model

Atmospheric simulation: 1st case

o

o

z

zzuzU ln)( *

C

uK

2*

- Neutral atmosphere, k-epsilon turbulence model

1st: validate: - TKE profile - epsilon profile - wind profile

2nd: rotor simulation-Blackhawk heli.

3rd: LPM input-Adapt CFD results-Ensure same atmos.conditions

INPUTS:

-surface roughness-wind profile:

-TKE profile and source term:

-epsilon profile:

)()(

3*

ozz

uz

Results: in progress

1st case:-Light winds-Blackhawk dimensions

Current work:-Simplified BlackhawkGeometry-Proper rotor variables -Validation of pressureDistribution-TKE, wind dist. validation

Dust Source Term

Physics of particle entrainment:

Shear Stress:u

Kz

Aerodynamic Lift: -determined from shear stress, velocity -overcome sliding friction 1st

-overcome gravity next

Dust Source Term “Lifting potential” of a shearing flow at the surface:

Factors: vegetation, surface consistency, supply, saltation

2 2* * *2

: airT

kgmassflux K u u u

m s g

*:Friction Velocity u

Dust Source Term

Helicopter case: more sophisticated methodneeded? Why? Highly turbulent: varying

friction velocity Significant local pressure

gradients Significant vertical

velocities Rapid saltation, source depletion

Lagrangian Particle Model

( ) ( ) ( ) ( )rx t t x t u t t u t t

( ) ( ) ( ) ( )r r u su t u t t R t u t Stochastic termDrift term

Gaussian Random Acceleration

Many Particles: Statistical Dispersion Modeling

Lagrangian Particle Model

Review of modeling scheme

1.CFD & VBM

2.Atmospheric simulation scheme

Post-processor:FiltererShear stress

4. LPM

3. Dust Source Term

Comparison to Measurement Study:#1: Correct Helicopter config.#1: Correct surface variables#2: Correct profiles#2: Real time simulation?#3: Shear stresses vs. mass#4: Downwind dispersion conc compared to measurements

Desert Rotor Entrainment Study

In planning: Summer 2007 • Military Helicopter in ground effect over desert terrain• Optical Remote Sensing- PM concentrations:

-LIDAR-FTIR

• Irwin sensors-Shear Stress

• Sonic Anemometer-Heli. flow and TKE

• Standard meteorological measurements for background

PM concentrations:

Optical Remote Sensing method:•FTIRs•(OP-LTs)•MPL

PM concentrations

Shear Stresses

P

Helicopter Flight over Irwin sensors

2

2( )u hph

f

Modeling validation

Variable Comparison method

Atmospheric

conditions

-Good stable atmospheric profiles in CFD domain

-Proper simulation in LPM

Heli. Flow

Field

-Sonic anem. data compared to CFD results

-Various runs with setting/ condition tweaks

Shear Stress -CFD output of shear stress compared to Irwin sensor data

PM conc. -LPM results compared to:

ORS: distribution

Tower data: point measurements

Model Validation

Significant variations? - source decay handling?- instrument error?- simulation errors?

- atmospheric setup- shear stress calculation

- landing/take-off cycle More sophisticated model runs

- non steady state vs. steady state solution?

Conclusion:

Scientific Value of this Project:

- Better understanding of perturbation dynamics through experimental observations and modeling

- Better understanding of the perturbation dynamics relationship to dust entrainment

- Computer Modeling: Simulation of the dust source and dispersion

- Coupling of models of various scales: Mesoscale CFD LPM

Future work

Reassessment of the LPM turbulence schemes Improvement of the LPM algorithm Validation of improved model Coupled WRF-LES microscale model for

atmospheric input Other sources: artillery, fixed-wing, tracked

vehicles, wheeled vehicles

Questions?

Thank you to:

•Army Research Office

•Sierra Pacific