Hello, I am a new K-wave user. I want to simulate a linear transducer array that will generate ARF at the interface of the two medium. I used the example code for defining the diagnostic transducer. I am not sure if the following code is correct or not. Anyone please help?
close all;
clear all;
clearvars;
% simulation settings
DATA_CAST = 'single';
% =========================================================================
% DEFINE THE K-WAVE GRID
% =========================================================================
% set the size of the perfectly matched layer (PML)
PML_X_SIZE = 20; % [grid points]
PML_Y_SIZE = 10; % [grid points]
PML_Z_SIZE = 10; % [grid points]
% set total number of grid points not including the PML
Nx = 128 - 2*PML_X_SIZE; % [grid points]
Ny = 128 - 2*PML_Y_SIZE; % [grid points]
Nz = 64 - 2*PML_Z_SIZE; % [grid points]
% set desired grid size in the x-direction not including the PML
x = 40e-3; % [m]
% calculate the spacing between the grid points
dx = x/Nx; % [m]
dy = dx; % [m]
dz = dx; % [m]
% create the k-space grid
kgrid = kWaveGrid(Nx, dx, Ny, dy, Nz, dz);
% =========================================================================
% DEFINE THE MEDIUM PARAMETERS
% =========================================================================
%define the properties of the propagation medium
medium.sound_speed = 2000.*ones(Nx,Ny,Nz) ; % [m/s] 2nd
medium.sound_speed(1:Nx/2,:,:) = 1000 ; % [m/s] 1st 101
medium.density = 2000*ones(Nx,Ny,Nz); % [kg/m^3] 2nd
medium.density(1:round(Nx/2),:,:) = 1134 ; % [kg/m^3] 1st
medium.alpha_coeff = 0.001*ones(Nx,Ny,Nz); % [dB/(MHz^y cm)] 2nd
medium.alpha_coeff(1:round(Nx/2),:,:)=0.01 ; % [dB/(MHz^y cm)] 1st
medium.alpha_power = 1.5;
medium.BonA = 6;
% create the time array
t_end = 40e-6; % [s]
kgrid.makeTime(medium.sound_speed, [], t_end);
% =========================================================================
% DEFINE THE INPUT SIGNAL
% =========================================================================
% define properties of the input signal
source_strength = 1e6; % [Pa]
tone_burst_freq = 0.5e6; % [Hz]
tone_burst_cycles = 5;
% create the input signal using toneBurst
input_signal = toneBurst(1/kgrid.dt, tone_burst_freq, tone_burst_cycles);
% scale the source magnitude by the source_strength divided by the
% impedance (the source is assigned to the particle velocity)
input_signal = (source_strength ./ (1000 .* 1134)) .* input_signal;
% =========================================================================
% DEFINE THE ULTRASOUND TRANSDUCER
% =========================================================================
% physical properties of the transducer
transducer.number_elements = 72; % total number of transducer elements
transducer.element_width = 1; % width of each element [grid points]
transducer.element_length = 12; % length of each element [grid points]
transducer.element_spacing = 0; % spacing (kerf width) between the elements [grid points]
transducer.radius = inf; % radius of curvature of the transducer [m]
% calculate the width of the transducer in grid points
transducer_width = transducer.number_elements * transducer.element_width ...
+ (transducer.number_elements - 1) * transducer.element_spacing;
% use this to position the transducer in the middle of the computational grid
transducer.position = round([1, Ny/2 - transducer_width/2, Nz/2 - transducer.element_length/2]);
% properties used to derive the beamforming delays
transducer.sound_speed = 1540; % sound speed [m/s]
transducer.focus_distance = 10e-3; % focus distance [m]
transducer.elevation_focus_distance = 19e-3; % focus distance in the elevation plane [m]
transducer.steering_angle = 0; % steering angle [degrees]
% apodization
transducer.transmit_apodization = 'Rectangular';
transducer.receive_apodization = 'Rectangular';
% define the transducer elements that are currently active
transducer.active_elements = zeros(transducer.number_elements, 1);
transducer.active_elements(21:52) = 1;
% append input signal used to drive the transducer
transducer.input_signal = input_signal;
% create the transducer using the defined settings
transducer = kWaveTransducer(kgrid, transducer);
% print out transducer properties
transducer.properties;
% =========================================================================
% DEFINE SENSOR MASK
% =========================================================================
% create a binary sensor mask with four detection positions
sensor.mask = zeros(Nx, Ny, Nz);
sensor.mask([Nx/4, Nx/2, 3*Nx/4], Ny/2, Nz/2) = 1;
% =========================================================================
% RUN THE SIMULATION
% =========================================================================
% set the input settings
input_args = {'DisplayMask', transducer.all_elements_mask | sensor.mask, ...
'PMLInside', false, 'PlotPML', false, 'PMLSize', [PML_X_SIZE, PML_Y_SIZE, PML_Z_SIZE], ...
'DataCast', DATA_CAST, 'PlotScale', [-1/2, 1/2] * source_strength};
% run the simulation
[sensor_data] = kspaceFirstOrder3D(kgrid, medium, transducer, sensor, input_args{:});
% calculate the amplitude spectrum of the input signal and the signal
% recorded each of the sensor positions
[f_input, as_input] = spect([input_signal, zeros(1, 2 * length(input_signal))], 1/kgrid.dt);
[~, as_1] = spect(sensor_data(1, :), 1/kgrid.dt);
[~, as_2] = spect(sensor_data(2, :), 1/kgrid.dt);
[f, as_3] = spect(sensor_data(3, :), 1/kgrid.dt);
% =========================================================================
% VISUALISATION
% =========================================================================
% plot the input signal and its frequency spectrum
figure;
subplot(2, 1, 1);
plot((0:kgrid.dt:(length(input_signal) - 1) * kgrid.dt) * 1e6, input_signal, 'k-');
xlabel('Time [\mus]');
ylabel('Particle Velocity [m/s]');