# RCAIDE/Methods/Aeroacoustics/Semi_Empirical/Turbofan/turbofan_engine_noise.py
#
#
# Created: Jul 2023, M. Clarke
# ----------------------------------------------------------------------------------------------------------------------
# IMPORT
# ----------------------------------------------------------------------------------------------------------------------
# RCAIDE imports
import RCAIDE
from RCAIDE.Framework.Core import Units , Data
from .angle_of_attack_effect import angle_of_attack_effect
from .external_plug_effect import external_plug_effect
from .ground_proximity_effect import ground_proximity_effect
from .jet_installation_effect import jet_installation_effect
from .mixed_noise_component import mixed_noise_component
from .primary_noise_component import primary_noise_component
from .secondary_noise_component import secondary_noise_component
from RCAIDE.Library.Methods.Aeroacoustics.Common import SPL_arithmetic
from RCAIDE.Library.Methods.Aeroacoustics.Metrics import A_weighting_metric
# Python package imports
import numpy as np
from copy import deepcopy
# ----------------------------------------------------------------------------------------------------------------------
# turbofan engine noise
# ----------------------------------------------------------------------------------------------------------------------
[docs]
def turbofan_engine_noise(microphone_locations, turbofan, aeroacoustic_data, segment, settings):
"""
This method predicts the free-field 1/3 Octave Band SPL of coaxial subsonic jets for turbofan engines under various conditions.
Parameters
----------
microphone_locations : array_like
Coordinates of the microphones used to capture noise data.
turbofan : RCAIDE type turbofan
Contains turbofan engine specifications.
- core_nozzle : object
Contains attributes like exit_velocity and diameter.
- fan_nozzle : object
Contains attributes like exit_velocity and diameter.
- height : float
Engine centerline height above the ground plane.
- length : float
Length of the turbofan.
- diameter : float
Diameter of the turbofan.
- plug_diameter : float
Diameter of the engine external plug.
- geometry_xe, geometry_ye, geometry_Ce : float
Geometric parameters for jet installation effects.
aeroacoustic_data : object
Contains aeroacoustic data for the turbofan.
- core_nozzle : object
Contains attributes like exit_stagnation_temperature and exit_stagnation_pressure.
- fan_nozzle : object
Contains attributes like exit_stagnation_temperature and exit_stagnation_pressure.
- low_pressure_spool : object
Contains angular_velocity.
segment : RCAIDE type segment
Contains flight path data and conditions.
- conditions : object
Contains freestream velocity, mach number, and speed of sound.
- frames : object
Contains inertial time data.
settings : object
Contains settings such as center frequencies for noise calculations.
Returns
-------
engine_noise : Data
Contains the computed noise data.
- SPL_1_3_spectrum : array_like
One Third Octave Band SPL spectrum.
- SPL : float
Sound Pressure Level.
- SPL_dBA : float
A-weighted Sound Pressure Level.
Notes
-----
The function uses semi-empirical methods for coaxial jet noise prediction. It accounts for various conditions such as flyover, static, and in-flight scenarios.
**Major Assumptions**
* Coaxial subsonic jets
* Free-field conditions
**Theory**
The noise prediction is based on the combination of primary, secondary, and mixed jet components, with adjustments for installation and environmental effects.
**Definitions**
'SPL'
Sound Pressure Level, a measure of the sound intensity.
References
----------
[1] SAE ARP876D: Gas Turbine Jet Exhaust Noise Prediction (original)
[2] de Almeida, Odenir. "Semi-empirical methods for coaxial jet noise prediction." (2008). (adapted)
See Also
--------
RCAIDE.Library.Methods.Aeroacoustics.Metrics.A_weighting_metric
RCAIDE.Library.Methods.Aeroacoustics.Common.SPL_arithmetic
"""
# unpack
N1 = aeroacoustic_data.fan.angular_velocity / Units.rpm
Velocity_secondary = aeroacoustic_data.fan_nozzle.exit_velocity
Temperature_secondary = aeroacoustic_data.fan_nozzle.exit_stagnation_temperature
Pressure_secondary = aeroacoustic_data.fan_nozzle.exit_stagnation_pressure
Velocity_primary = aeroacoustic_data.core_nozzle.exit_velocity
Temperature_primary = aeroacoustic_data.core_nozzle.exit_stagnation_temperature
Pressure_primary = aeroacoustic_data.core_nozzle.exit_stagnation_pressure
Velocity_aircraft = segment.conditions.freestream.velocity
Mach_aircraft = segment.conditions.freestream.mach_number
AOA = segment.conditions.aerodynamics.angles.alpha / Units.deg
noise_time = segment.conditions.frames.inertial.time
distance_microphone = np.linalg.norm(microphone_locations,axis = 1)
Diameter_primary = turbofan.core_nozzle.diameter
Diameter_secondary = turbofan.fan_nozzle.diameter
engine_height = turbofan.origin[0][2] # This needs to be updated in a future PR
EXA = turbofan.length / turbofan.diameter
Plug_diameter = turbofan.plug_diameter
Xe = turbofan.geometry_xe
Ye = turbofan.geometry_ye
Ce = turbofan.geometry_Ce
frequency = settings.center_frequencies[5:]
n_cpts = len(noise_time)
n_freq = len(frequency)
n_mic = len(microphone_locations)
# =============================================================================
# Step 1: Computing atmospheric conditions
# =============================================================================
sound_ambient = segment.conditions.freestream.speed_of_sound
density_ambient = segment.conditions.freestream.density
pressure_amb = segment.conditions.freestream.pressure
pressure_isa = 101325 # [Pa]
R_gas = 287.1 # [J/kg K]
gamma_primary = 1.37 # Corretion for the primary jet
gamma = 1.4
# =============================================================================
# Step 2: Compute operating conditions and properties of jet
# =============================================================================
# Calculation of nozzle areas
Area_primary = np.pi*(Diameter_primary/2)**2
Area_secondary = np.pi*(Diameter_secondary/2)**2
# Defining each array before the main loop
theta = np.zeros(n_mic)
bool_1 = (microphone_locations[:,1] > 0) & (microphone_locations[:,0] > 0)
bool_2 = (microphone_locations[:,1] > 0) & (microphone_locations[:,0] < 0)
bool_3 = (microphone_locations[:,1] < 0) & (microphone_locations[:,0] < 0)
bool_4 = (microphone_locations[:,1] < 0) & (microphone_locations[:,0] > 0)
theta[bool_1] = np.pi - np.arctan(microphone_locations[:,1]/microphone_locations[:,0])[bool_1]
theta[bool_2] = np.arctan(microphone_locations[:,1]/ abs(microphone_locations[:,0]))[bool_2]
theta[bool_3] = np.arctan(abs(microphone_locations[:,1])/ abs(microphone_locations[:,0]))[bool_3]
theta[bool_4] = np.pi - np.arctan(abs(microphone_locations[:,1])/ microphone_locations[:,0])[bool_4]
theta_P = np.tile(theta[None,:],(n_cpts,1))
theta_S = deepcopy(theta_P)
theta_M = deepcopy(theta_P)
EX_p = np.zeros((n_cpts,n_mic,n_freq))
EX_s = np.zeros((n_cpts,n_mic,n_freq))
EX_m = np.zeros((n_cpts,n_mic,n_freq))
SPL_p = np.zeros((n_cpts,n_mic,n_freq))
SPL_s = np.zeros((n_cpts,n_mic,n_freq))
SPL_m = np.zeros((n_cpts,n_mic,n_freq))
SPL = np.zeros((n_cpts,n_mic))
SPL_dBA = np.zeros((n_cpts,n_mic))
SPL_1_3_spectrum = np.zeros((n_cpts,n_mic,n_freq))
SPL_1_3_spectrum_dBA = np.zeros((n_cpts,n_mic,n_freq))
# Primary and Secondary jets
Cpp = R_gas/(1-1/gamma_primary)
Cp = R_gas/(1-1/gamma)
# densitys
density_primary = Pressure_primary/(R_gas*Temperature_primary-(0.5*R_gas*Velocity_primary**2/Cpp))
density_secondary = Pressure_secondary/(R_gas*Temperature_secondary-(0.5*R_gas*Velocity_secondary**2/Cp))
# mas sflow
mass_flow_primary = Area_primary*Velocity_primary*density_primary
mass_flow_secondary = Area_secondary*Velocity_secondary*density_secondary
# Mach number of the external flow - based on the aircraft velocity
Mach_aircraft = Velocity_aircraft/sound_ambient
# Calculation Procedure for the Mixed Jet Flow Parameters
Velocity_mixed = (mass_flow_primary*Velocity_primary+mass_flow_secondary*Velocity_secondary)/ (mass_flow_primary+mass_flow_secondary)
Temperature_mixed = (mass_flow_primary*Temperature_primary+mass_flow_secondary*Temperature_secondary)/ (mass_flow_primary+mass_flow_secondary)
density_mixed = pressure_amb/(R_gas*Temperature_mixed-(0.5*R_gas*Velocity_mixed**2/Cp))
Area_mixed = Area_primary*density_primary*Velocity_primary*(1+(mass_flow_secondary/mass_flow_primary))/ (density_mixed*Velocity_mixed)
Diameter_mixed = (4*Area_mixed/np.pi)**0.5
XBPR = mass_flow_secondary/mass_flow_primary - 5.5
XBPR[XBPR<0] = 0
XBPR[XBPR>4] = 4
# Auxiliary parameter defined as DVPS
DVPS = np.abs((Velocity_primary - (Velocity_secondary*Area_secondary+Velocity_aircraft*Area_primary)/(Area_secondary+Area_primary)))
DVPS[DVPS<0.3] =0.3
# =============================================================================
# Step 3: Update dimension of jet for spectral calculations
# =============================================================================
frequency = np.tile(np.atleast_2d(frequency),(n_cpts,1))
Diameter_primary = np.tile(np.array([[Diameter_primary]]),(n_cpts,n_freq))
DVPS = np.tile(DVPS,(1,n_freq))
Diameter_secondary = np.tile(np.array([[Diameter_secondary]]),(n_cpts,n_freq))
Velocity_secondary = np.tile(Velocity_secondary,(1,n_freq))
Velocity_primary = np.tile(Velocity_primary,(1,n_freq))
Velocity_aircraft = np.tile(Velocity_aircraft,(1,n_freq))
Diameter_mixed = np.tile(Diameter_mixed,(1,n_freq))
Velocity_mixed = np.tile(Velocity_mixed,(1,n_freq))
sound_ambient = np.tile(sound_ambient,(1,n_freq))
# =============================================================================
# Step 4: Comptue noise at each microphone
# =============================================================================
for j in range(n_mic):
theta_p = np.tile(np.atleast_2d(abs(theta_P[:,j])).T,(1,n_freq))
theta_s = np.tile(np.atleast_2d(abs(theta_S[:,j])).T,(1,n_freq))
theta_m = np.tile(np.atleast_2d(abs(theta_M[:,j])).T,(1,n_freq))
# Calculation of the Strouhal number for each jet component (p-primary, s-secondary, m-mixed)
Str_p = frequency*Diameter_primary/(DVPS) # Primary jet
Str_s = frequency*Diameter_secondary/(Velocity_secondary-Velocity_aircraft) # Secondary jet
Str_m = frequency*Diameter_mixed/(Velocity_mixed-Velocity_aircraft) # Mixed jet
# Calculation of the Excitation adjustment parameter
excitation_Strouhal = (N1/60)*(Diameter_mixed/Velocity_mixed)
SX = 50*(excitation_Strouhal-0.25)*(excitation_Strouhal-0.5)
SX[excitation_Strouhal > 0.25] = 0.0
SX[excitation_Strouhal < 0.5] = 0.0
# Effectiveness
exps = np.exp(-SX)
#Spectral Shape Factor
exs = 5*exps*np.exp(-(np.log10(Str_m/(2*excitation_Strouhal+0.00001)))**2)
#Fan Duct Lenght Factor
exd = np.exp(0.6-(EXA)**0.5)
#Excitation source location factor (zk)
zk = 1-0.4*(exd)*(exps)
# Loop for the frequency array range
exc = sound_ambient/Velocity_mixed
exc[theta_m>1.4] = (sound_ambient[theta_m>1.4]/Velocity_mixed[theta_m>1.4])*(1-(1.8/np.pi)*(theta_m[theta_m>1.4]-1.4))
#Acoustic excitation adjustment (EX)
EX_m = exd*exs*exc # mixed component - dependant of the frequency
EX_p = +5*exd*exps #primary component - no frequency dependance
EX_s = 2*sound_ambient/(Velocity_secondary*(zk)) #secondary component - no frequency dependance
distance_primary = np.tile(np.array([[distance_microphone[j]]]),(n_cpts,n_freq))
distance_secondary = np.tile(np.array([[distance_microphone[j]]]),(n_cpts,n_freq))
distance_mixed = np.tile(np.array([[distance_microphone[j]]]),(n_cpts,n_freq))
# Noise attenuation due to Ambient Pressure
dspl_ambient_pressure = 20*np.log10(pressure_amb/pressure_isa)
# Noise attenuation due to Density Gradientes
dspl_density_p = 20*np.log10((density_primary+density_secondary)/(2*density_ambient))
dspl_density_s = 20*np.log10((density_secondary+density_ambient)/(2*density_ambient))
dspl_density_m = 20*np.log10((density_mixed+density_ambient)/(2*density_ambient))
# Noise attenuation due to Spherical divergence
dspl_spherical_p = 20*np.log10(Diameter_primary/distance_primary)
dspl_spherical_s = 20*np.log10(Diameter_mixed/distance_secondary)
dspl_spherical_m = 20*np.log10(Diameter_mixed/distance_mixed)
# Calculation of the total noise attenuation (p-primary, s-secondary, m-mixed components)
DSPL_p = dspl_ambient_pressure+dspl_density_p+dspl_spherical_p
DSPL_s = dspl_ambient_pressure+dspl_density_s+dspl_spherical_s
DSPL_m = dspl_ambient_pressure+dspl_density_m+dspl_spherical_m
# Calculation of interference effects on jet noise
ATK_m = angle_of_attack_effect(AOA,Mach_aircraft,theta_m)
INST_s = jet_installation_effect(Xe,Ye,Ce,theta_s,Diameter_mixed)
Plug = external_plug_effect(Velocity_primary,Velocity_secondary, Velocity_mixed, Diameter_primary,Diameter_secondary,
Diameter_mixed, Plug_diameter, sound_ambient, theta_p,theta_s,theta_m)
GPROX_m = ground_proximity_effect(Velocity_mixed,sound_ambient,theta_m,engine_height,Diameter_mixed,frequency)
# Calculation of the sound pressure level for each jet component
SPL_p = primary_noise_component(Velocity_primary,Temperature_primary,R_gas,theta_p,DVPS,sound_ambient, Velocity_secondary,Velocity_aircraft,Area_primary,Area_secondary,DSPL_p,EX_p,Str_p) + Plug.PG_p
SPL_p[np.isnan(SPL_p)] = 1E-6
SPL_s = secondary_noise_component(Velocity_primary,theta_s,sound_ambient,Velocity_secondary, Velocity_aircraft,Area_primary,Area_secondary,DSPL_s,EX_s,Str_s) + Plug.PG_s + INST_s
SPL_s[np.isnan(SPL_s)] = 1E-6
SPL_m = mixed_noise_component(Velocity_primary,theta_m,sound_ambient,Velocity_secondary, Velocity_aircraft,Area_primary,Area_secondary,DSPL_m,EX_m,Str_m,Velocity_mixed,XBPR) + Plug.PG_m + ATK_m + GPROX_m
SPL_m[np.isnan(SPL_m)] = 1E-6
# Sum of the Total Noise
SPL_total = 10 * np.log10(10**(0.1*SPL_p)+10**(0.1*SPL_s)+10**(0.1*SPL_m))
# Store SPL history
SPL_1_3_spectrum[:,j,:] = SPL_total
SPL[:,j] = SPL_arithmetic(SPL_total,sum_axis=1 )
SPL_1_3_spectrum_dBA[:,j,:] = A_weighting_metric(SPL_total,frequency)
SPL_dBA[:,j] = SPL_arithmetic(np.atleast_2d(A_weighting_metric(SPL_total,frequency)),sum_axis=1)
engine_noise = Data()
engine_noise.SPL_1_3_spectrum = SPL_1_3_spectrum_dBA
engine_noise.SPL = SPL
engine_noise.SPL_dBA = SPL_dBA
return engine_noise
