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 Model Post-processor: Filterer Shear 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…) initializationiterationsolution

Virtual Blade Model vs. Full blade modelingVBM: 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 Force= lift(L) – drag(D): Blade Element Theory: Lift & drag coefficients (C L and C D ): 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 1 st 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: 1 st case - Neutral atmosphere, k-epsilon turbulence model 1 st : validate: - TKE profile - epsilon profile - wind profile 2 nd : rotor simulation -Blackhawk heli. 3 rd : LPM input -Adapt CFD results -Ensure same atmos. conditions INPUTS: -surface roughness -wind profile: -TKE profile and source term: -epsilon profile:

Results: in progress 1 st case: -Light winds -Blackhawk dimensions Current work: -Simplified Blackhawk Geometry -Proper rotor variables -Validation of pressure Distribution -TKE, wind dist. validation

Dust Source Term Physics of particle entrainment: Shear Stress: Aerodynamic Lift: -determined from shear stress, velocity -overcome sliding friction 1 st -overcome gravity next

Dust Source Term “Lifting potential” of a shearing flow at the surface: Factors: vegetation, surface consistency, supply, saltation

Dust Source Term Helicopter case: more sophisticated method needed? Why? Highly turbulent: varying friction velocity Significant local pressure gradients Significant vertical velocities Rapid saltation, source depletion

Lagrangian Particle Model 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: Filterer Shear 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 Helicopter Flight over Irwin sensors

Modeling validation VariableComparison 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