LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Impact of Nuclear Data Uncertainty in the Modeling of Neutron-Induced Recoil Atom Energy Distributions in Silicon

Photo from wikipedia

Recoil ion distributions in silicon and the resulting distribution of the linear energy transfer (LET) are important metrics in microdosimetric studies and in the investigation of neutron-induced single-event effects. A… Click to show full abstract

Recoil ion distributions in silicon and the resulting distribution of the linear energy transfer (LET) are important metrics in microdosimetric studies and in the investigation of neutron-induced single-event effects. A rigorous methodology is presented for quantifying the uncertainty in these metrics due to the underlying uncertainty contributors, including that due to the nuclear data, recoil ion electronic stopping power, and incident neutron spectrum. The methodology uses a Monte Carlo-based approach so that the nonlinear uncertainty propagation is rigorously treated as the response function folded with the full incident neutron spectrum. The uncertainty is captured in the form of both recoil energy and LET-dependent covariance matrices. The uncertainty contributions from the nuclear data are shown to have strong energy-dependent correlations which are comparable in magnitude to that from the uncertainty found in the spectrum characterization for high fidelity reference neutron fields. The uncertainty from the stopping power has the largest magnitude of the largest contributors, but it shows a very strong energy-dependent correlation that translates into a systematic uncertainty that may cancel out in many applications.

Keywords: methodology; nuclear data; distributions silicon; uncertainty; recoil; energy

Journal Title: IEEE Transactions on Nuclear Science
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.