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Monte Carlo studies on Fully Bayesian Unfolding for a multi-layer silicon beta-ray spectrometer
Xingzhi Cheng1, Andrei R Hanu2, Benjamin Dyer1
1Department of Physics and Astronomy, McMaster University, Hamilton, Ontario, L8S 4K1, Canada.
Summary
This study introduces Fully Bayesian Unfolding (FBU) for silicon beta-ray spectrometers (SBS) used in nuclear plants. FBU accurately measures beta spectra in mixed radiation fields, improving safety and monitoring.
Area of Science:
- Nuclear Physics
- Radiation Detection and Measurement
Background:
- Accurate beta spectrometry is crucial for radiation monitoring in nuclear facilities.
- Silicon beta-ray spectrometers (SBS) face challenges in determining beta spectra due to partial energy deposition.
- Beta-gamma mixed fields require sophisticated methods for precise radiation analysis.
Purpose of the Study:
- To apply Fully Bayesian Unfolding (FBU) to a compact multi-layer silicon beta-ray spectrometer (SBS).
- To evaluate the performance of FBU for unfolding beta fluence spectra in beta-gamma mixed fields.
- To enhance beta-gamma discrimination and uncertainty quantification in radiation measurements.
Main Methods:
- Developed a simulation-based application of FBU using Monte Carlo response matrices.
- Implemented FBU in Python with PyMC for posterior distributions and credible intervals.
- Evaluated performance using Geant4 simulations across various beta-to-gamma ratios.
Main Results:
- FBU demonstrated promising beta fluence unfolding capabilities for SBS.
- Mean unfolded-to-truth ratio for beta fluence above 0.1 MeV was within 20% of unity for ratios ⩾ 0.1.
- The method provided valuable insights into the gamma component even at low count rates.
Conclusions:
- Fully Bayesian Unfolding is feasible and effective for silicon beta-ray spectrometers in mixed radiation fields.
- FBU enables reliable beta fluence spectrum measurements and improved uncertainty quantification.
- Future work will optimize the algorithm for real-time unfolding in practical applications.
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