k-Wave User Forum » Topic: Problem Simulation Transducer Beam Pattern

k-Wave User Forum » Topic: Problem Simulation Transducer Beam Pattern http://www.k-wave.org/forum/topic/problem-simulation-transducer-beam-pattern Support for the k-Wave MATLAB toolbox en-US Wed, 13 May 2026 16:24:26 +0000 http://bbpress.org/?v=1.0.2 <![CDATA[Search]]> q http://www.k-wave.org/forum/search.php Bradley Treeby on "Problem Simulation Transducer Beam Pattern" http://www.k-wave.org/forum/topic/problem-simulation-transducer-beam-pattern#post-6156 Thu, 19 Oct 2017 09:25:44 +0000 Bradley Treeby 6156@http://www.k-wave.org/forum/ Hi Mason, Your simulation is unstable (there should be a warning printed to the command line about this). You can fix this by reducing the size of the time step, e.g., <pre><code>% create the time array t_end = 7.5e-6; % [s] CFL = 0.1; kgrid.t_array = makeTime(kgrid, medium.sound_speed, CFL, t_end);</code></pre> Brad. Mason Schellenberg on "Problem Simulation Transducer Beam Pattern" http://www.k-wave.org/forum/topic/problem-simulation-transducer-beam-pattern#post-6149 Thu, 12 Oct 2017 19:16:18 +0000 Mason Schellenberg 6149@http://www.k-wave.org/forum/ Hey all, I am trying to simulate the beam pattern of a transducer but am getting some confusing results. The first time step results in the volume being saturated with acoustic pressure and then seems to go negative for the rest of the run. The resulting beam pattern looks like a checkerboard. Any help would be greatly appreciated. My code is based on the example provided when I downloaded it and is as follows: clear all; % simulation settings DATA_CAST = 'single'; % set to 'single' or 'gpuArray-single' to speed up computations MASK_PLANE = 'xy'; % set to 'xy' or 'xz' to generate the beam pattern in different planes USE_STATISTICS = true; % set to true to compute the rms or peak beam patterns, set to false to compute the harmonic beam patterns % ========================================================================= % DEFINE THE K-WAVE GRID % ========================================================================= % set the size of the perfectly matched layer (PML) PML_X_SIZE = 16; % [grid points] PML_Y_SIZE = 16; % [grid points] PML_Z_SIZE = 16; % [grid points] % set total number of grid points not including the PML Nx = 64 - 2*PML_X_SIZE; % [grid points] Ny = 256 - 2*PML_Y_SIZE; % [grid points] Nz = 256 - 2*PML_Z_SIZE; % [grid points] % calculate the spacing between the grid points dx = 50e-6; % [m] dy = dx; % [m] dz = dx; % [m] % create the k-space grid kgrid = makeGrid(Nx, dx, Ny, dy, Nz, dz); % ========================================================================= % DEFINE THE MEDIUM PARAMETERS % ========================================================================= % define the properties of the propagation medium medium.sound_speed = 1595; % [m/s] medium.density = 1000; % [kg/m^3] medium.alpha_coeff = 1.08; % [dB/(MHz^y cm)] medium.alpha_power = 1.001; % create the time array t_end = 7.5e-6; % [s] kgrid.t_array = makeTime(kgrid, medium.sound_speed, [], t_end); % ========================================================================= % DEFINE THE INPUT SIGNAL % ========================================================================= % define properties of the input signal source_strength = 1e6; % [Pa] tone_burst_freq = 12.5e6; % [Hz] tone_burst_cycles = 1; % 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./(medium.sound_speed*medium.density)).*input_signal; % ========================================================================= % DEFINE THE ULTRASOUND TRANSDUCER % ========================================================================= % physical properties of the transducer transducer.number_elements = 32; % total number of transducer elements transducer.element_width = 3; % width of each element [grid points] transducer.element_length = 120; % length of each element [grid points] transducer.element_spacing = 1; % spacing (kerf width) between the elements [grid points] % 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 = 1595; % sound speed [m/s] % apodization transducer.transmit_apodization = 'Rectangular'; transducer.receive_apodization = 'Rectangular'; % define the transducer elements that are currently active transducer.active_elements = ones(transducer.number_elements, 1); % append input signal used to drive the transducer transducer.input_signal = input_signal; % create the transducer using the defined settings transducer = makeTransducer(kgrid, transducer); % print out transducer properties transducer.properties; % ========================================================================= % DEFINE SENSOR MASK % ========================================================================= % define a sensor mask through the central plane sensor.mask = zeros(Nx, Ny, Nz); switch MASK_PLANE case 'xy' % define mask sensor.mask(:, :, Nz/2) = 1; % store y axis properties Nj = Ny; j_vec = kgrid.y_vec; j_label = 'y'; case 'xz' % define mask sensor.mask(:, Ny/2, :) = 1; % store z axis properties Nj = Nz; j_vec = kgrid.z_vec; j_label = 'z'; end % set the record mode such that only the rms and peak values are stored if USE_STATISTICS sensor.record = {'p_rms', 'p_max'}; end % ========================================================================= % RUN THE SIMULATION % ========================================================================= % set the input settings input_args = {'DisplayMask', transducer.all_elements_mask, ... 'PMLInside', false, 'PlotPML', false, 'PMLSize', [PML_X_SIZE, PML_Y_SIZE, PML_Z_SIZE], ... 'DataCast', DATA_CAST, 'DataRecast', true, 'PlotScale', [-source_strength/2, source_strength/2]}; % stream the data to disk in blocks of 100 if storing the complete time % history if ~USE_STATISTICS input_args = [input_args {'StreamToDisk', 100}]; end % run the simulation sensor_data = kspaceFirstOrder3D(kgrid, medium, transducer, sensor, input_args{:}); % ========================================================================= % COMPUTE THE BEAM PATTERN USING SIMULATION STATISTICS % ========================================================================= if USE_STATISTICS % reshape the returned rms and max fields to their original position sensor_data.p_rms = reshape(sensor_data.p_rms, [Nx, Nj]); sensor_data.p_max = reshape(sensor_data.p_max, [Nx, Nj]); % plot the beam pattern using the pressure maximum figure; imagesc(j_vec*1e3, (kgrid.x_vec - min(kgrid.x_vec(:)))*1e3, sensor_data.p_max/1e6); xlabel([j_label '-position [mm]']); ylabel('x-position [mm]'); title('Total Beam Pattern Using Maximum Of Recorded Pressure'); colormap(jet(256)); c = colorbar; ylabel(c, 'Pressure [MPa]'); axis image; % plot the beam pattern using the pressure rms figure; imagesc(j_vec*1e3, (kgrid.x_vec - min(kgrid.x_vec(:)))*1e3, sensor_data.p_rms/1e6); xlabel([j_label '-position [mm]']); ylabel('x-position [mm]'); title('Total Beam Pattern Using RMS Of Recorded Pressure'); colormap(jet(256)); c = colorbar; ylabel(c, 'Pressure [MPa]'); axis image; % end the example return end % ========================================================================= % COMPUTE THE BEAM PATTERN FROM THE AMPLITUDE SPECTRUM % ========================================================================= % reshape the sensor data to its original position so that it can be % indexed as sensor_data(x, j, t) sensor_data = reshape(sensor_data, [Nx, Nj, kgrid.Nt]); % compute the amplitude spectrum [freq, amp_spect] = spect(sensor_data, 1/kgrid.dt, 'Dim', 3); % compute the index at which the source frequency and its harmonics occur [f1_value, f1_index] = findClosest(freq, tone_burst_freq); [f2_value, f2_index] = findClosest(freq, tone_burst_freq*2); % extract the amplitude at the source frequency and store beam_pattern_f1 = amp_spect(:, :, f1_index); % extract the amplitude at the second harmonic and store beam_pattern_f2 = amp_spect(:, :, f2_index); % extract the integral of the total amplitude spectrum beam_pattern_total = sum(amp_spect, 3); % plot the beam patterns figure; imagesc(j_vec*1e3, (kgrid.x_vec - min(kgrid.x_vec(:)))*1e3, beam_pattern_f1/1e6); xlabel([j_label '-position [mm]']); ylabel('x-position [mm]'); title('Beam Pattern At Source Fundamental'); colormap(jet(256)); c = colorbar; ylabel(c, 'Pressure [MPa]'); axis image; figure; imagesc(j_vec*1e3, (kgrid.x_vec - min(kgrid.x_vec(:)))*1e3, beam_pattern_f2/1e3); xlabel([j_label '-position [mm]']); ylabel('x-position [mm]'); title('Beam Pattern At Second Harmonic'); colormap(jet(256)); c = colorbar; ylabel(c, 'Pressure [kPa]'); axis image; figure; imagesc(j_vec*1e3, (kgrid.x_vec - min(kgrid.x_vec(:)))*1e3, beam_pattern_total/1e6); xlabel([j_label '-position [mm]']); ylabel('x-position [mm]'); title('Total Beam Pattern Using Integral Of Recorded Pressure'); colormap(jet(256)); c = colorbar; ylabel(c, 'Pressure [MPa]'); axis image; % ========================================================================= % PLOT DIRECTIVITY PATTERN AT FOCUS % ========================================================================= % compute the directivity at each of the harmonics directivity_f1 = squeeze(beam_pattern_f1(round(transducer.focus_distance/dx), :)); directivity_f2 = squeeze(beam_pattern_f2(round(transducer.focus_distance/dx), :)); % normalise directivity_f1 = directivity_f1./max(directivity_f1(:)); directivity_f2 = directivity_f2./max(directivity_f2(:)); % compute relative angles from transducer if strcmp(MASK_PLANE, 'xy') horz_axis = ((1:Ny) - Ny/2)*dy; else horz_axis = ((1:Nz) - Nz/2)*dz; end angles = 180*atan2(horz_axis, transducer.focus_distance)/pi; % plot the directivity figure; plot(angles, directivity_f1, 'k-', angles, directivity_f2, 'k--'); axis tight; set(gca, 'FontSize', 12); xlabel('Angle [deg]'); ylabel('Normalised Amplitude'); legend('Fundamental', 'Second Harmonic', 'Location', 'NorthWest');