Gaussian Energy Broadening tally

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SUMMARY

The discussion centers on applying Gaussian energy broadening in the MCBEND simulation program for analyzing spectra from radioactive sources, specifically 137Cs, 60Co, and 133Barium. The user seeks guidance on determining the necessary parameters for Gaussian broadening, emphasizing the importance of measuring the Full Width at Half Maximum (FWHM) for known peaks. By collecting FWHM data, the user can derive parameters a, b, and c to minimize the mean square difference in their analysis. This method is essential for accurate spectral comparison and interpretation.

PREREQUISITES
  • Understanding of Gaussian energy broadening principles
  • Familiarity with the MCBEND simulation program
  • Knowledge of Full Width at Half Maximum (FWHM) measurement techniques
  • Proficiency in data analysis using Excel
NEXT STEPS
  • Research Gaussian energy broadening techniques in nuclear spectroscopy
  • Learn how to implement FWHM calculations in MCBEND
  • Explore optimization methods for parameter fitting in data analysis
  • Investigate case studies involving spectral analysis of radioactive sources
USEFUL FOR

Researchers in nuclear physics, radiation safety professionals, and anyone involved in spectral analysis of radioactive materials will benefit from this discussion.

gxa
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TL;DR
FWHM-Gauss Energy Broadening
I took measurements by placing 137Cs, 60Co, and 133Barium 5 cm away from the detector and simulated this with the MCBEND program. First, I compared the dose rates. Now I want to compare the spectra. I examined similar studies. They explain the way to go, but I am not exactly sure how to do it. I have this on Excel. There are graphics. I would be happy if you could help me on what path to follow.I want to apply Gaussian energy brodening in the MCBEND code. What do I need to do to find the parameters here?
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I'll give this my best shot. I think you need to have measured the real source for all those cases. I think you would measure the FWHM - that is the width of the peak half way up - for every known peak. That would give you the data you need.

From that it probably wouldn't be too difficult to solve for a, b and c such that the mean square difference is minimised.
 

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