Event Detail

Event Type: 
Applied Mathematics and Computation Seminar
Friday, December 6, 2019 - 12:00 to 12:50
STAG 160

Speaker Info

School of Nuclear Science and Engineering

Modeling the time-dependent multiphysics behavior of nuclear reactor cores pose unique challenges to
researchers and oftentimes require the use of high-performance computing resources. In this work, we
attempt to overcome the 'curse of dimensionality' inherent to neutron diffusion kinetics problems by
employing a novel, a-priori 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 models (ROMs) of two standard benchmark calculations when
compared to a reference high-fidelity solution.

For problems that exhibit sufficient spatial regularity, we show that our proposed PGD algorithm
computes accurate ROMs in less time using significantly fewer degrees of freedom than the reference
calculations. However, when introducing the stronger spatial heterogeneities of the reference
benchmarks, the accuracy and timing of the proposed PGD algorithm diminish. In this presentation, we
motivate the use of PGD in neutron diffusion kinetics, discuss the adopted mathematical framework, and
using our results, discuss the challenges and unique aspects of our implementation moving forward.