Rotorcraft Noise Prediction with Multi-disciplinary Coupling Methods Yi Liu NIA CFD Seminar, April 10, 2012
Outline Introduction and Background Multi-disciplinary Analysis Approaches Computational Fluid Dynamics Rotor Wake Modeling Methods Computational Structural Dynamics CFD/CSD Coupling Procedure Acoustic Analysis Results for High speed impulsive noise prediction Results for Blade vortex interaction noise prediction Concluding remarks
Introduction and Background Complex interactional aerodynamics Dynamic Loads and Structure Dynamics Aeroelastic Response Acoustic Noise Flight Controlling System Engine/Drive Train Dynamics Leishman, Principles of Helicopter Aerodynamics
Rotor Source Noise
Lighthill s Formulation
Ffowcs Williams-Hawkings Formulation Numerical Solution to FW-H equation = + " # $ # + $ # $ % (' #,% ) ) Three source terms: = +, - + +. -, - thickness source (monopole) Requires rotor blade geometry and kinematics " # =/ #,% - % + +. #. -, - loading source (dipole) Requires rotor blade geometry, kinematics and surface loading ' #,% =+. #. % +/ #,% + + 0 #,% quadrupole source Requires flow field around the rotor blade (volume integration)
Noise prediction method The noise standard became ever more stringent, and the cost of flight testing and wind tunnel experiments was increasing Computational aero-acoustics gets more attention Direct Numerical Method Hybrid Numerical Method High-speed impulsive (HSI) noise represents one of the most intense and annoying forms of noise generated by helicopter rotors in high-speed forward flight. Blade Vortex Interaction (BVI) noise represents another type of intensive noise generated by helicopter rotor in low-speed decent flight close to ground.
Approaches CAMRAD II, DYMORE Multi-body, Nonlinear Computational Structure Dynamics (CSD) Noise Propagation (WopWop, RNM) High-order Computational Fluid Dynamics (CFD) High-fidelity Wake Modeling (Particle-VTM) Shock Wave Boundary Layer Blade-Vortex Interaction FUN3D, OVERFLOW NASA RANS Flow Solver A systematic coupling approach among multiple disciplines to predict rotor noise
Computational Fluid Dynamics TURNS (Transonic Unsteady Rotor Navier-Stokes by Prof. Baeder) Compressible unsteady Reynolds Averaging Navier-Stokes (RANS) solver Inviscid terms are computed using 3 rd MUSCL, and 5 th order WENO scheme Viscous terms are computed using 2 nd central differencing Second order time accuracy with Newton-type sub-iteration Baldwin-Lomax and Spalart-Allmaras turbulence models The low dispersion and dissipation Total Variation Diminishing (STVD) scheme developed by Helen Yee is implemented
Rotorcraft Wake Modeling Methods Free-wake module Wake geometry is decided by potential flow based method CFD calculates the wake effects with the inputted wake geometry Heavily depend on empirical input Overset grid methodology to capture wake directly Physics based, high resolution wake capturing method Grid dependency Numerical dissipation diffuses the tip vortex too rapidly Particle Vortex Transport Method (PVTM) (Dr. Phuriwat Anusonti-Inthra) Solves the incompressible vortex transport equation using a Lagrangian (vortex particle) approach Fully coupled with CFD Uses CFD in near body to capture vortex generation Uses PVTM in other domains for calculating vortex evolution
Computational Structural Dynamics CAMRAD II (Dr. Wayne Johnson) Comprehensive Finite Element Analysis with Multi-body Dynamics Forced periodic solutions for steady and level flight to get trim solutions The structural dynamics response is very important for the rotor blade simulations in forward flight conditions
CFD/CSD Coupling Procedure CAMRAD II Aero-loading Aero-loading Difference F/M n+1 = (F/M cfd F/M CII ) + F/M n Check convergence CAMRAD II Lifting line aero with uniform inflow + delta force CAMRAD II trim solutions Forces and motions at quarter chord Blade Motions TURNS / CFD Aero CFD Surface Aeroloading A loose coupling strategy based on a trimmed periodic rotor solution The comprehensive airloadsare replaced with CFD airloadswith a delta force method Use the lifting line aerodynamics to trim and CSD to account for blade deformation in the comprehensive analysis
Acoustic Analysis PSU-WOPWOP (Prof. Brentner) Solves Farassat s retarded-time formulation 1A of the Ffowcs Williams-Hawkings (FW-H) equation Propagate and compute the tone noises at any given observer locations Impermeable surface method Noise source based on the blade loadings or surface pressure predicted by CFD or comprehensive analysis Thickness noise and loading noise Permeable surface method Noise source based on the flow field solutions provided by CFD on a specified surface around the rotor blade Thickness noise, loading noise, high-speed impulsive noise
High-order STVD scheme for Permeable Surface method Physical Blade Surface Permeable Surface surrounding the blade or Acoustic Data Surface High-order CFD scheme provides sufficient spatial and temporal accuracy to propagate acoustic characteristic waves to the acoustic data surface Implemented the low dispersion and low dissipation Symmetric Total Variation Diminishing (STVD) scheme introduced by Helen Yee into our current CFD solver, which replaces the original 2 nd order ROE scheme inside the code
High Speed Impulsive Noise Prediction with CFD+overset grid method The DNW acoustic wind tunnel test is conducted in the large low-speed facility (LLF) at the Duits Nederlands Windtunnel (DNW) for a scaled model of the UH-60a helicopter main rotor High speed forward flight case with advance ratio 0.3010 and the rotor tip Mach number of 0.8737 CFD + overset background grid method coupled with CSD, with 10 million total grid points.
Acoustic Experiments Set-up 3R Mic. 1 Mic. 7 30 o 3R The acoustic predictions and measured sound pressure at microphone 1 and microphone 7 are compared Wind Top View Mic. 1 Mic. 7 3R Side View R
Acoustic Experimental Measurements (Microphone 1) 100 EXP-Microphone 1 Sound Pressure (Pa) 50 0-50 Noise due to vortex HSI Noise -100 0 0.25 0.5 0.75 1 Normalized Time
Acoustic Experimental Measurements (Microphone 7) 100 Noise due to vortex EXP-Microphone 7 Sound Pressure (Pa) 50 0-50 HSI Noise -100 0 0.25 0.5 0.75 1 Normalized Time
Impermeable Surface Method (Microphone 1) 30 20 10 0 Sound Pressure-Total -10-20 -30-40 -50-60 -70 Impermeable Surface Method EXP - Microphone 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 No-dimension Time
Impermeable Surface Method (Microphone 7) 40 20 0 Sound Pressure-Total -20-40 -60-80 -100 Impermeable Surface Method EXP - Microphone 7 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 No-dimension Time
Permeable Surface Method: Acoustic Data Surface Red Blade; Blue Baseline Grid; Orange New Grid
Acoustic Predictions for Different Acoustic Data Surfaces 30 20 10 0 Sound Pressure-Total -10-20 -30-40 Baseline Grid Grid No. 1 Grid No. 2 Grid No. 3 EXP -50-60 -70 0 0.01 0.02 0.03 0.04 Time
Permeable Surface Method (Microphone 1) 30 20 10 0 Sound Pressure-Total -10-20 -30-40 -50-60 -70 Impermeable Surface Method Permeable Surface Method EXP - Microphone 1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 No-dimension Time
Permeable Surface Method (Microphone 7) 40 20 0 Sound Pressure-Total -20-40 -60-80 -100 Impermeable Surface Method Permeable Surface Method EXP - Microphone 7 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 No-dimension Time
Blade Vortex Interaction Noise Prediction with CFD+PVTM method Particle Vortex Transport Method: ω 2 d = ω u + v ω + S L dt Coupled with CFD, where vortex source term come from RAN solution First-principle method Conserve vorticity Gridless wake (No grid adaptation) Paper: Anusonti-Inthra, P. Validations of Coupled CSD/CFD and Particle Vortex Transport Method for Rotorcraft Applications: Hover, Transition, and High Speed Flights Proc. 66 th AHS Forum, Phoenix, AZ, 2010
HART II Baseline PVTM Set up (a) HART II CFD grid Higher Harmonic Control Aeroacoustic Rotor Test (HARTII) performed in October 2001 in the Large Low-Speed Facility (LLF) of the DNW Wind Tunnel Flight Conditions: Low speed decent flight Advance ratio, µ = 0.15 CAMRAD II 5 beam elements CFD grid 1.5M cells 4 blades Boundaries 0.5c: downstream 1.0c: other directions PVTM resolution Fine: 0.5c (5R 1.25R) Medium: 1c(10R 3.75R) Coarse: 2c (15R 6.25R)
HART II Baseline Loading Predictions 0.18 r/r = 0.8700 0.16 0.14 0.12 M2CN 0.1 0.08 0.06 0.04 0.02 0 0 90 180 270 360 Azimuth Exp 0 Iteration 1st Iteration 2nd Iteration 3rd Iteration 4th Iteration 5th Iteration 6th Iteration CFD with Overset Grid 4.82 million near-body grid points 5.69 million back-ground grid points PVTM
HART II Baseline Experimental Noise Map Tunnel Wind 4 m Rotor Disk Plane (Radius = 2m) 4 m Microphone Plane 2.215 m below the rotor disk 2.7 m 2.7 m
HART II Predicted BVI Noise Contour CFD + overset grid Method CFD + PVTM Method
Concluding Remarks A multi-disciplinary analysis method with coupled algorithms among CFD/Wake/CSD/Acoustics to predict the rotor source noise The rotor blade loadings and acoustic signatures predictions are compared with DNW high-speed forward flight case, and HART II low-speed decent case For High-speed forward flight case with transonic impulsive noise, the acoustic signature predictions are more dependent on the acoustic and CFD coupling procedure, where the permeable surface method is giving much better results than the impermeable surface method
Concluding Remarks (cond.) For Low-speed decent flight case with blade vortex interaction noise, the predictions are more dependent on the rotor tip wake modeling/capturing, where the PVTM method gives better results than the CFD overset grid method with relative coarse grid. Overall, for this kind of hybrid CAA method for rotorcraft, the accuracy of the noise prediction is greatly dependent on the accuracy of the blade loading and rotor wake simulation results from CFD. Thus, any improvement of the accuracy of CFD simulations for rotorcraft complex flow phenomena will also great improve the noise prediction