Dr. Michael Hackemack
Principal Engineer
Navel Nuclear Laboratory

Abstract

Successful analysis of nuclear reactor systems requires the calculation of many different design products throughout reactor life. This necessitates the accurate, efficient, and robust modelling of reactor systems through many states and configurations. There is an associative tradeoff and balance between the modeling fidelity and the required computational resources. For this reason, there have been myriad transport methodologies developed, including nodal methods, diffusion theory, discrete ordinates, Method of Characteristics, Monte Carlo, and others. Part of the artwork in performing reactor analyses, is determining the appropriate transport methodology to utilize (i.e., “the right tool for the right job”). This seminar presents the work performed at the Naval Nuclear Laboratory in developing high-fidelity, state-of-the-art physics solvers based on discrete ordinates and Monte Carlo transport methodologies. We will discuss some of the code developments that have been made to make the systems’ as robustly flexible as possible for user applications, while maintaining excellent performance on HPC architectures.

Biography

Dr. Michael Hackemack obtained his B.S. in nuclear engineering from Texas A&M University in 2011. As an undergraduate, he interned at the Comanche Peak Nuclear Power Plant and performed research under Professor Fred Best in space nuclear power systems. Under the Rickover fellowship sponsored by the Naval Nuclear Laboratory (NNL), Michael pursued a M.S. and then Ph.D. in nuclear engineering at Texas A&M University. He studied under the guidance of Professors Akabani and Ragusa in reactor physics and computational transport methods. Upon completion of his PhD, Michael began work for NNL as a computational transport methods developer. He has focused his efforts on development of deterministic transport methods for reactor analysis applications and is currently the team lead of NNL’s Sn transport code, Jaguar.

Thursday, November 10. 2022
4:00 pm seminar

Hybrid Option  (Speaker is in person)
Zoom link upon request
or
Room 1202 Burlington Labs