RE: FLAIR projections and statistical error

From: Roger Hälg <>
Date: Thu, 17 Feb 2011 23:45:13 +0100

Dear Mario

Thanks for the quick reply and your practical tips. It is really helpful
to think about these points when preparing a new simulation and doing
some test runs.

I'm not sure if I understand your question about the planes correctly.
But I do agree that a cylindrical binning would give some advantages
concerning the symmetry.


Roger Hälg

On Thu, 2011-02-17 at 09:42 -0800, Santana, Mario wrote:
> Roger,
> By increasing the size of your voxel (either achieved by augmenting the transverse dimensions or be longitudinal, or both) the PRECISION of your results will usually increase (more 'hits'), but it may happen at the expense of the ACCURACY. For example, if you want to obtain a sharp peak value accurately, you should try to keep your bin size as small as possible. In your case I'd advise you to make a plot on the beam direction, so that you know if the profile is roughly constant in that range or if it has a strong Z dependence.
> If the first is true (~constant) then you are OK
> If the latter was true (~strong Z function), then going for thicker bins is probably not a good idea, and since your statistics is not so good, I'd try the following:
> 1) run more histories, or send more parallel jobs
> 2) make a more efficient CPU usage, i.e. use biasing (for regions, reactions, etc. set blackhole outside the zone of interest,...)
> 3) Combine all the techniques above, plus adjust bin dimensions in all directions, making some compromise among accuracy, precision and CPU time.
> By the way, you mention that you used the symmetry of the irradiation. Was it through planes?
> Remember that you can also define usrbin in cylindrical coordinates (r,Z), there you'd still gain a big factor with respect of a rectangular usrbin with symmetry planes.
> Good luck
> Mario
> -----Original Message-----
> From: Roger Hälg []
> Sent: Thursday, February 17, 2011 6:26 AM
> To: Santana, Mario
> Cc:
> Subject: RE: FLAIR projections and statistical error
> Dear Mario
> Thank you for your detailed explanation. The part of the projections is
> now clear to me, but I still have questions concerning the statistical
> error.
> To be more specific, let me describe an example. I simulated a proton
> beam impinging a water phantom to score neutron dose. I used a pretty
> small bin size. To improve the statistical error, I used the symmetry of
> the irradiation field and of the phantom to average bins perpendicular
> to the beam but keeping the full resolution in beam direction. The
> statistical error for my binning with the original bin size is,
> depending on the location inside the phantom, quite high. According to
> the table in the FLUKA course material with a statistical error of about
> 50%, the result can be within a "factor of a few" to "garbage".
> After averaging over multiple bins perpendicular to the beam as
> described above, the statistical error drops far below 10% and should be
> reliable according to the table.
> My question is now, is this spatial averaging acceptable to reduce the
> statistical error and can the result be stated as reliable? Or is the
> error on the original bin size still dominant?
> If yes, is this also true in case of low energy neutrons, where the
> group algorithm is used and the calculation is no more microscopic
> analogue?
> Thanks again very much for your help!
> Regards,
> Roger Hälg
> On Tue, 2011-02-15 at 14:34 -0800, Santana, Mario wrote:
> > Roger,
> >
> > Let's take as an example a 2D plot. Usually you will want to plot a
> > 3D matrix generated by USRBIN.
> > But the plot can only be made in 2D, so you need to choose what kind of
> > view you want (e.g. elevation, plain, cross section ~ X, Y, Z depending on
> > your reference frame). If you project the matrix on the y-z plane (X axis),
> > you will be plotting a {y, z} mesh in which each point {y_j, z_k} is the
> > average value of all the layers with the same {y_j, z_k} but different x_i
> > (x_1, x_2...). If you specify limits for your x axis, then FLAIR will only take
> > into account all the layers between your specified x range. The associated
> > error, for any {y_j, z_k} bin is obtained in FLAIR by calculating the
> > relative error of the sum of bins and dividing by the square root of the
> > numberof terms. In FLAIR you can actually select the 'error' box to plot the
> > associated relative errors. If you do so, remember to set the normalization
> > factor to 1 and to use a scale ranging from 0 (or close) to 100.
> >
> > Anyway, in most practical cases, if your plot looks smooth (isolines are
> > well defined, no big traces, nor 'random' fluctuations in neighboring values)
> > most likely your statistical error will be acceptable. Of course, this
> > depends on the scale range that you use, so use good judgment.
> >
> > Mario
> >
> >
> > -----Original Message-----
> > From: [] On Behalf Of Roger Haelg
> > Sent: Tuesday, February 15, 2011 6:01 AM
> > To:
> > Subject: FLAIR projections and statistical error
> >
> > Dear FLUKA and FLAIR experts
> >
> > Could anyone explain to me what the "projection& limits" for data plots
> > (1d and 2d) in FLAIR exactly do with the data for plotting? The manual
> > does not explain this.
> >
> > And what happens to the statistical error in this case? The manual says:
> > "WARNING errors will be underestimated, since it treats all bin values
> > as uncorrelated."
> > How can I estimate the error when using this projections and limits for
> > several bins? Are there different cases to be differentiated?
> >
> > In the FLUKA course materials there is a table listing the statistical
> > errors and the usefulness of the results. Is this always related to the
> > statistical errors of the individual bin or is there a way to estimate
> > the error using projections and averaging?
> >
> > Thank you very much for your help!
> >
> > Regards,
> >
> > Roger Haelg
> >
Received on Fri Feb 18 2011 - 10:44:03 CET

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