# RCAIDE/Methods/Noise/Common/compute_relative_noise_evaluation_locations.py
#
#
# 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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# Relative Noise Evaluatation Locations
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[docs]
def compute_relative_noise_evaluation_locations(settings,microphone_locations, segment):
"""This computes the relative locations on the surface in the computational domain where the
propogated sound is computed. Vectors point from observer/microphone to aircraft/source
Assumptions:
Acoustic scattering is not modeled
Source:
N/A
Inputs:
settings.microphone_locations - array of microphone locations on the ground [meters]
segment.conditions.frames.inertial.position_vector - position of aircraft [boolean]
Outputs:
GM_THETA - angle measured from ground microphone in the x-z plane from microphone to aircraft
GM_PHI - angle measured from ground microphone in the y-z plane from microphone to aircraft
RML - relative microphone locations
num_gm_mic - number of ground microphones
Properties Used:
N/A
"""
MSL_altitude = settings.mean_sea_level_altitude
N = settings.noise_times_steps
pos = segment.state.conditions.frames.inertial.position_vector
# rediscretize time and aircraft position to get finer resolution
time = segment.state.conditions.frames.inertial.time[:,0]
noise_time = np.linspace(time[0], time[-1], N)
noise_pos = np.zeros((N,3))
noise_pos[:,0] = np.interp(noise_time,time,pos[:,0])
noise_pos[:,1] = np.interp(noise_time,time,pos[:,1])
noise_pos[:,2] = np.interp(noise_time,time,pos[:,2])
num_gm_mic = len(microphone_locations)
RML = np.zeros((N,num_gm_mic,3))
PHI = np.zeros((N,num_gm_mic))
THETA = np.zeros((N,num_gm_mic))
for cpt in range(N):
relative_locations = np.zeros((num_gm_mic,3))
relative_locations[:,0] = microphone_locations[:,0] - (settings.aircraft_origin_location[0] + noise_pos[cpt,0])
relative_locations[:,1] = microphone_locations[:,1] - (settings.aircraft_origin_location[1] + noise_pos[cpt,1])
if MSL_altitude:
relative_locations[:,2] = -(noise_pos[cpt,2]) - microphone_locations[:,2]
else:
relative_locations[:,2] = -(noise_pos[cpt,2])
RML[cpt,:,:] = relative_locations
PHI[cpt,:] = np.arctan2(np.sqrt(np.square(relative_locations[:, 0]) + np.square(relative_locations[:, 1])), relative_locations[:, 2])
THETA[cpt,:] = np.arctan2(relative_locations[:, 1], relative_locations[:, 0])
return noise_time,noise_pos,RML,PHI,THETA,num_gm_mic
