Open Access. Powered by Scholars. Published by Universities.®

Nuclear Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Nuclear Engineering ETDs

Monte Carlo

Articles 1 - 2 of 2

Full-Text Articles in Nuclear Engineering

Doppler Temperature Coefficient Calculations Using Adjoint-Weighted Tallies And Continuous-Energy Cross Sections In Mcnp6, Matthew A. Gonzales Dec 2016

Doppler Temperature Coefficient Calculations Using Adjoint-Weighted Tallies And Continuous-Energy Cross Sections In Mcnp6, Matthew A. Gonzales

Nuclear Engineering ETDs

The calculation of the thermal neutron Doppler temperature reactivity feedback co- efficient, a key parameter in the design and safe operation of advanced reactors, using first order perturbation theory in continuous energy Monte Carlo codes is challenging as the continuous energy adjoint flux is not readily available. Traditional approaches of obtaining the adjoint flux attempt to invert the random walk process as well as require data corresponding to all temperatures and their respective tem- perature derivatives within the system in order to accurately calculate the Doppler temperature feedback.

A new method has been developed using adjoint-weighted tallies and On-The-Fly (OTF ...


Reduced-Order Monte Carlo Modeling Of Radiation Transport In Random Media, Aaron J. Olson Nov 2016

Reduced-Order Monte Carlo Modeling Of Radiation Transport In Random Media, Aaron J. Olson

Nuclear Engineering ETDs

The ability to perform radiation transport computations in stochastic media is essential for predictive capabilities in applications such as weather modeling, radiation shielding involving non-homogeneous materials, atmospheric radiation transport computations, and transport in plasma-air structures. Due to the random nature of such media, it is often not clear how to model or otherwise compute on many forms of stochastic media. Several approaches to evaluation of transport quantities for some stochastic media exist, though such approaches often either yield considerable error or are quite computationally expensive. We model stochastic media using the Karhunen-Loève (KL) expansion, seek to improve efficiency through use ...