Hi Ben and Bradely,
I was trying to stimulate the example Heterogeneous Propagation medium with a few layers of different sound speed and density. And there is actually an extra stream of signal that follows the actual signal. I dont really get the reason for this. Could you please help me explain??
The pic of the result is uploaded in this link:
http://tinypic.com/r/o86r5s/5
Thanks,
Eldhose
Hi Eldhose,
Is it a PML issue? Try turning off the PML on the two sides to see if it goes away.
Ben
Hi Ben,
sensor_data = kspaceFirstOrder2D(kgrid, medium, source, sensor, 'PlotLayout', true, 'PlotPML', false);
This is how i have defined the sensor_data in the program. And i believe that the PML layer is turned off.
Thanks,
Eldhose
Hi Eldhose
Try this line instead.
sensor_data = kspaceFirstOrder2D(kgrid, medium, source, sensor, 'PlotLayout', true, 'PMLAlpha', [0 2]);
I think you were just asking the program not to plot the absorbing boundary layer region, but you weren't actually turning it off. If you want to use a plane wave exactly aligned to the grid then by turning off the PML where it reaches the edges you can simulate a true (infinite) plane wave, as the spectral gradient calculations in the code will implicitly make the function periodic.
Does this solve the problem, or was it another effect you were seeing?
Ben
Hi Ben,
I have tried to set the input parameter PMLAlpha [0,2] as per your previous comment. Now i am seeing a totally different effect as you have suspected.
http://tinypic.com/r/210ivj4/5
Thanks,
Eldhose
Hi Eldhose,
Mmm. I'm afraid I can't tell what's going on without more details of the simulation you're running. Can you post your code and I'll run it and see if I spot anything obvious.
Thanks,
Ben
Hi Ben
The source code of the program is given below:
clear all;
close all;
clc;
% =========================================================================
% SIMULATION
% =========================================================================
% create the computational grid
Nx = 600; % number of grid points in the x (row) direction
Ny = 600; % number of grid points in the y (column) direction
dx = 6.52e-5; % grid point spacing in the x direction [m]
dy = 6.52e-5; % grid point spacing in the y direction [m]
kgrid = makeGrid(Nx, dx, Ny, dy);
% define the properties of the propagation medium (Mucosa and Submucosa)
medium.sound_speed = 1500*ones(Nx, Ny); % [m/s]
medium.sound_speed(300:315,:) = 1500; % [m/s]
medium.density = 1000*ones(Nx, Ny); % [kg/m^3]
medium.density(300:315,:) = 1200; % [kg/m^3]
%medium.alpha_power = 1.5;
%medium.alpha_coeff = 1.8; % [dB/(MHz^y cm)]
% define the properties of the propagation medium (Muscle)
medium.sound_speed(316:329,:) = 1580; % [m/s]
medium.density(316:329,:) = 1000; % [kg/m^3]
% define the properties of the propagation medium (Fat)
medium.sound_speed(330:335,:) = 1450; % [m/s]
medium.density(330:335,:) = 910; % [kg/m^3]
% define the properties of the propagation medium (Water)
medium.sound_speed(336:end,:) = 1482; % [m/s]
medium.density(336:end,:) = 1000; % [kg/m^3]
% create the time array
[kgrid.t_array, dt] = makeTime(kgrid, medium.sound_speed);
Nt = length(kgrid.t_array);
% define a single source element
source.p_mask = zeros(Nx, Ny);
source.p_mask( Nx/2, Ny/2) = 1;
% define a time varying sinusoidal source
source_freq = 10e6; % [Hz]
source_mag = 15; % [au]
source.p = source_mag*sin(2*pi*source_freq*kgrid.t_array);
% smooth the source
source.p = filterTimeSeries(kgrid, medium, source.p);
% define a centered circular sensor
sensor_x_pos = Nx/2; % [grid points]
sensor_y_pos = Ny/2; % [grid points]
sensor_radius = 290; % [m]
sensor_arc_angle = pi;
sensor.mask = makeCircle(Nx, Ny, sensor_x_pos, sensor_y_pos, sensor_radius, sensor_arc_angle);
% run the simulation
sensor_data = kspaceFirstOrder2D(kgrid, medium, source, sensor, 'PlotLayout', true, 'PMLAlpha', [0 2]);
% =========================================================================
% VISUALISATION
% =========================================================================
% plot the simulated sensor data
figure;
imagesc(sensor_data, [-1, 1]);
colormap(getColorMap);
ylabel('Sensor Position');
xlabel('Time Step');
colorbar;
Thanks,
Eldhose
Hi Eldhose,
A few points:
1. Your 10 MHz input signal is almost completely removed by the call to filterTimeSeries. If you look at the command line outputs you can see the maximum frequency supported by the grid is 11.1 MHz while the filter cutoff frequency is 7.4 MHz.
2. For this type of simulation, you would most likely want to use the default PML settings unless you are trying to simulate a plane wave (see Ben's comments above).
3. Part of your detector is within the PML. Either use a smaller detector, or set 'PMLInside' to false.
4. It seems most of the lower section of your computational domain is not used (homogeneous sound speed and no source or detector points). You could speed up your simulations by using a smaller domain.
I hope that helps,
Brad.
Hi Brad,
Thanks for the options given out to try.
I have tried setting the PML layer outside the domain as you have advised together with a smaller input frequency of 7MHz since the filter cut off frequency is 7.4MHz. But its still looks the same.
May be you can help me explain why these tailoring signals occur in the results of the example "Heterogeneous Propagation Medium Example" of Initial Value Problems inside the toolbox.
I have pasted a link of the result after running the example exactly as it is in the toolbox.
http://tinypic.com/r/122c00m/5
Thanks,
Eldhose
Hi Eldhose,
This looks correct. The 'tails' are just the reflections from where the impedance changes due to the change in sound speed.
(There will be a slight tail even in the homogeneous case due to the fact that the example is in 2D and acoustic waves in 2D have tails - they never quite return to zero.)
Ben
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