Regularized Heuristic Method for Activation Monitor Neutron Spectrum Unfolding

Published: 1 June 2021| Version 1 | DOI: 10.17632/shf56c665r.1
Contributor:
Nicholas Quartemont

Description

Heuristic method to unfold a neutron spectrum from activation monitor dosimetry reactions. This repository contains the primary Python2 code and supplementary modules required to reproduce the results for regularized neutron spectrum unfolding results for two case studies. First, an energy tuning assembly producing a thermonuclear and prompt fission neutron spectrum is tested with 4 sub-cases. The sub-cases include a full model of the initial guess, a partial (neutron time-of-flight) model, a physics-based model, and no estimate. Second, a modified deuteron breakup source was tested to include artificial room return neutrons and modifications to the source region below a threshold energy. This unfold was conducted with a partial guess as well as with physics-based guess. Additionally, a resonance was added to test the capability of the model to be sensitive to resonance regions. Each case uses Unfold.py as a driver to call the Gnowee optimization algorithm with pre-defined values. The nuclear data utilized is the IRDFF v.1.05 library grouped based on PNNL STAYSL code structures.

Files

Steps to reproduce

Run Unfold.py in each respective case study. ResultsAggregator.py can be used along with the added Histograms.py and Plots.py included in the datapath.

Institutions

Air Force Institute of Technology

Categories

Heuristics, Derivative-Free Optimization, Nuclear Data

Licence