Source code for RCAIDE.Library.Methods.Aeroacoustics.Semi_Empirical.Turbofan.mixed_noise_component

# RCAIDE/Methods/Aeroacoustics/Semi_Empirical/Engine/mixed_noise_component.py
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# Created:  Jul 2023, M. Clarke  

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#  IMPORT
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# Python package imports   
import numpy as np   

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#  Mixed Noise Component
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[docs] def 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): """ This function calculates the noise contribution of the mixed jet component. Parameters ---------- Velocity_primary : float Velocity of the primary jet [m/s]. theta_m : float Angle for the mixed jet [rad]. sound_ambient : float Ambient sound level [SPL]. Velocity_secondary : float Velocity of the secondary jet [m/s]. Velocity_aircraft : float Velocity of the aircraft [m/s]. Area_primary : float Area of the primary jet [m^2]. Area_secondary : float Area of the secondary jet [m^2]. DSPL_m : float Decibel Sound Pressure Level for the mixed jet [SPL]. EX_m : float Excess noise level for the mixed jet. Str_m : float Strouhal number for the mixed jet. Velocity_mixed : float Velocity of the mixed jet [m/s]. XBPR : float Bypass ratio adjustment factor. Returns ------- SPL_m : float Sound Pressure Level for the mixed jet component [dB]. Notes ----- The function uses semi-empirical methods to calculate the noise contribution of the mixed jet component. **Definitions** 'SPL_m' Sound Pressure Level for the mixed jet component. 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) """ #Calculation of the velocity exponent velocity_exponent = (Velocity_mixed/sound_ambient)**0.5*(0.6+(0.2/(0.2+Str_m) * \ np.exp(-0.3*(theta_m+(Str_m/(1+Str_m))-2.7)**2))) #Calculation of the Source Strengh Function (FV) FV = ((Velocity_mixed-Velocity_aircraft)/sound_ambient)**velocity_exponent * \ ((Velocity_mixed+Velocity_aircraft)/sound_ambient)**(1-velocity_exponent) #Determination of the noise model coefficients Z1 = -30*((1.8*theta_m/np.pi)-0.6)**2 Z2 = -9 -4*((Velocity_primary-Velocity_secondary)/sound_ambient)-38*((1.8*theta_m/np.pi)-0.6)**3 + \ 30*(0.6-np.log10(1+Area_secondary/Area_primary))*(1.8*theta_m/np.pi - 0.6) Z3 = 1-0.4*((1.8*theta_m/np.pi)-0.6)**2 Z4 = 0.44-0.5/np.exp(((4.5*theta_m/np.pi)-4)**2) + 0.2*Velocity_primary/sound_ambient - \ 0.7*Velocity_mixed/sound_ambient - 0.2*np.log10((1+Area_secondary)/Area_primary) + \ 0.05*(XBPR)*np.exp(-5*(theta_m-2.4)**2) Z5 = 34 + 81*theta_m/np.pi - 20*((1.8*theta_m/np.pi)-0.6)**3 Z6 = 108 + 37.8*theta_m/np.pi + 5*Velocity_mixed*(Velocity_primary-Velocity_secondary)/(sound_ambient**2) - \ np.exp(-5*(theta_m-1.8)**2) + 7*Velocity_mixed/sound_ambient*(1-0.4*(Velocity_primary/sound_ambient) * \ np.exp(-0.7*np.abs(Str_m-0.8))) / np.exp(8*(theta_m-2.4)**2) + 0.8*(XBPR)*np.exp(theta_m-2.3-Velocity_mixed/sound_ambient) + \ DSPL_m + EX_m #Determination of Sound Pressure Level for the mixed jet component SPL_m = (Z1*np.log10(FV)+Z2)*(np.log10(Str_m)-Z3*np.log10(FV)-Z4)**2 + Z5*np.log10(FV) + Z6 return SPL_m