The impact of MCNP6 depletion resolution on core lifetime is examined in the context of the Snowflake microreactor with explicit TRISO fuel. The change in core lifetime and iso- tope mass as a result of different tracked isotopes, timesteps, and spatial regions is discussed. Calculation speed of a prototype MCNP...
Nuclear fuel management is an optimization problem on many levels. Finding “viable” solutions for the core reload design problem is difficult without expert knowledge and software automation. Small modular reactors with a shared used fuel pool demonstrate a novel opportunity for fuel cycle optimization.
A Python package was developed and...
The primary goal of this dissertation is to improve the quality of nuclear data available to the nuclear science community. We propose to accomplish this by applying machine learning algorithms to the large number of available benchmark experiments and simulations, with the goal of determining which nuclear data have strong...
We present a method for deterministically solving the consistent temperature and frequency dependent phonon radiative transport problem. We use the single relaxation time (SRT) approximation in the Self-Adjoint Angular Flux (SAAF) form with discrete ordinates (S_N) angular discretization method and continuous finite element method (CFEM) for spatial discretization. Included are...
In this dissertation, we derive and implement a new transport-diffusion hybrid algorithm for solving thermal radiative transfer (TRT) problems. Using the method of nonlinear elimination (NLEM), the TRT system of equations can be written in terms of a transport equation with the absence of scattering and a diffusion equation. The...
We present a novel multi-objective optimization methodology built upon a multi-agent blackboard framework. This multi-agent blackboard system (MABS) synthesizes blackboard architectures, multi-agent environments, and optimization theory. The blackboard architecture creates the framework for initializing, storing, and solving a multi-objective optimization problem. Multiple agents allow for an optimization problem to be...
Circulating fuel reactor (CFR) kinetics are characterized by delayed neutron precursor (DNP) drift in addition to the neutronic and thermal hydraulic phenomena typical of other reactor types. This environment can be computationally challenging to model, given that the multiphysics phenomena generally have non-linear interdependencies requiring the use of iterative solution...
Material testing experiments are needed to enable the next generation of nuclear fission reactors. Concluding in 2009, the Boosted Fast Flux Loop (BFFL) project was devised as a way to test fast reactor materials and fuels in the Advanced Test Reactor (ATR), however the experiment location it used is now...
Radiation therapy is a sophisticated complex process. Systematic methods are needed to quantitatively evaluate the quality of a complex process and hence radiation therapy treatments. An ideal result for a complex process must be established to determine if the complex process is completed acceptably. For radiation therapy, this can be...
In this dissertation, we attempt to overcome the "curse of dimensionality" inherent to radiation diffusion kinetics problems by employing a novel reduced order modeling technique known as proper generalized decomposition (PGD). After verifying a proposed PGD algorithm and associated solvers through various tests, we explore its performance for computing reduced-order...