Actually the temperature rise is very lower than what is measured in the lab and I'm wondering what is the reason.

I extract the max temperature at a point using a line passing through the point (I find lines of the intersection of the 3 slices xy-xz-yz at max). But the value is much smaller than the value which a point sensor gives and also the max value which the color scale bar shows. What is the reason?

The 10 g PsSAR can not be calculated as well. The density of Gel in the simulation is 1000 kg/m^3, the length of a cube with 10 g should be about 20 mm. what the max step value should be based on the cube length? I did the simulation with the max step 0.1 mm and it seems it should be able to calculate 10 g PsSSAR. But it still can not calculate it and gives the error.

Thanks for your reply.

Yeay. It worked. Great. Thank you so much for your patience 🙂

Can't you do the same procedure directly for the E_tan along the baseline, instead of doing it for the random splines?

Hello Sylvain,
Thanks for your reply.

Do you know which of the four steps is slowing down the pipeline?
Because you could always choose to go for a more dedicated programming language rather than python to do part of the processing.

The Field_Combiner will allow you to sum two E fields, provided that they are at the same frequency.
However, I think this combiner requires that the two fields are on the same grid. This means you may first have to use the Interpolator algorithm first (Select both fields, choose the Interpolator in the ribbon, and it will interpolate the first field on the grid of the second).

One needs to be careful with the naming of the quantities. Notice that B1(x,y,z,f0) refers to a field with two components, namely (B1+, B1-) !!!! I personally find the name a bit unfortunate but it was directly taken from MRI jargon where they denote B1 to the RF B-field to distinguish it from the static magnetic field, denoted as B0.

Do NOT confuse with B(x,y,z,f0) that is a C^3 quantity with (Bx, By, Bz) components!!

Check in the manual B1(x,y,z,f0) for more details.

Hi,

Yes, this is possible, as shown in the example below.
Note that this sort of scripts can in principle be automatically generated using the "To Python" function from the GUI (in this case by right-clicking on the Streamline Viewer). Here, however, the autogenerated script did not fully work, as it forgets a crucial Update() call before setting up the Plane Center and Normal.

I hope this helps!

# Creating the analysis pipeline # Adding a new SimulationExtractor simulation = document.AllSimulations["EM"] simulation_extractor = simulation.Results() # Adding a new EmSensorExtractor em_sensor_extractor = simulation_extractor["Overall Field"] document.AllAlgorithms.Add(em_sensor_extractor) # Adding a new StreamLineViewer inputs = [em_sensor_extractor.Outputs["EM E(x,y,z,f0)"]] stream_line_viewer = analysis.viewers.StreamLineViewer(inputs=inputs) stream_line_viewer.Streamline.SeedSource = stream_line_viewer.Streamline.SeedSource.enum.PlaneSource stream_line_viewer.Update() # this line is needed, otherwise the next lines have no effect stream_line_viewer.Streamline.Plane.PlaneCenter = numpy.array([0.2, 0.05, 0.002]) stream_line_viewer.Streamline.Plane.PlaneNormal = numpy.array([0.2, 0.5, 1.2]) stream_line_viewer.Update() document.AllAlgorithms.Add(stream_line_viewer)

The Power Balance works for both harmonic and Gaussian simulations. The computation is done for the "extracted frequencies" of a given field sensor (usually the "overall field" sensor). Harmonic simulations have just one extracted frequency whereas Gaussian ones can have several. That's the only difference, as far as the Power Balance is concerned.