Engineering topics

Hart, Shane W. D.

Publications and source records attributed to Hart, Shane W. D..

5 records

DOE OSTI2024

Comparison of Temperature-Dependent Cross Section Treatments Within the Shift Monte Carlo Radiation Transport Code

Multiple calculation methods have been developed to account for Doppler broadening of cross sections in Monte Carlo radiation transport simulations. This work compares the accuracy and performance of four different broadening methods, including an on-the-fly multipole treatment, applied to three different geometries of increasing complexity, including a nuclear reactor assembly with a realistic temperature profile. The comparisons reveal how the combination of physics implementations in the Shift Monte Carlo code result in slightly different temperature-dependent behavior, and different levels of performance, for a variety of materials and situations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Warthog: Coupling Nek5000 Thermal Hydraulics to BISON Fuel Performance through the Giraffe Interface

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program under the US Department of Energy (DOE) consists of three product lines. The Fuels Product Line (FPL), hosted at Idaho National Laboratory (INL), has produced a multiphysics framework with the name Multiphysics Object Oriented Simulation Environment (MOOSE) (Gaston et al. 2015). The FPL has also produced several high-fidelity physics codes including the fuel performance code Bison (Hales et al. 2016). The Reactors Product Line (RPL), hosted at Argonne National Laboratory (Argonne), has developed the high-order spectral-element Computational Fluid Dynamics (CFD) code Nek5000 (Fischer et al. 2015). The Integration Product Line (IPL), hosted at Oak Ridge National Laboratory (ORNL), is tasked with ensuring tools from the other product lines can be coupled together so that users may perform high-fidelity multiphysics simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Warthog Framework Update: Depletion Capabilities

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) program the US Department of Energy (DOE) Office of Nuclear Energy supports two simulation frameworks to provide advanced simulation techniques for analyzing nuclear reactors. Primarily at Idaho National Laboratory (INL), the fuels product line (FPL) is developing the fuel performance code BISON from Hales et al. [2016], which depends on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework developed by Gaston et al. [2009]. Likewise, at Argonne National Laboratory (ANL), in the reactor product line (RPL), PROTEUS is being developed by Lee et al. [2013] and Nek5000 by Fischer et al. [2015] based on the Simulation-based High-efficiency Advanced Reactor Prototyping (SHARP) framework from Tautges et al. [2013]. MOOSE employs a bottom-up approach to multiphysics coupling, where component codes are built upon a common framework. SHARP employs a top-down approach in which legacy component codes are connected after being separately developed. Each approach has benefits and disadvantages, but this work focuses on having the two approaches work in harmony.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2017

Warthog: Coupling Status Update

The Warthog code was developed to couple codes that are developed in both the Multi-Physics Object-Oriented Simulation Environment (MOOSE) from Idaho National Laboratory (INL) and SHARP from Argonne National Laboratory (ANL). The initial phase of this work, focused on coupling the neutronics code PROTEUS with the fuel performance code BISON. The main technical challenge involves mapping the power density solution determined by PROTEUS to the fuel in BISON. This presents a challenge since PROTEUS uses the MOAB mesh format, but BISON, like all other MOOSE codes, uses the libMesh format. When coupling the different codes, one must consider that Warthog is a light-weight MOOSE-based program that uses the Data Transfer Kit (DTK) to transfer data between the various mesh types. Users set up inputs for the codes they want to run, and then Warthog transfers the data between them. Currently Warthog supports XSProc from SCALE or the Sub-Group Application Programming Interface (SGAPI) in PROTEUS for generating cross sections. It supports arbitrary geometries using PROTEUS and BISON. DTK will transfer power densities and temperatures between the codes where the domains overlap. In the past fiscal year (FY), much work has gone into demonstrating two-way coupling for simple pin cells of various materials. XSProc was used to calculate the cross sections, which were then passed to PROTEUS in an external file. PROTEUS calculates the fission/power density, and Warthog uses DTK to pass this information to BISON, where it is used as the heat source. BISON then calculates the temperature profile of the pin cell and sends it back to XSProc to obtain the temperature corrected cross sections. This process is repeated until the convergence criteria (tolerance on BISON solve, or number of time steps) is reached. Models have been constructed and run for both uranium oxide and uranium silicide fuels. These models demonstrate a clear difference in power shape that is not accounted for in a stand-alone BISON run. Future work involves improving the user interface (UI), likely through integration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench. Furthermore, automating the input creation would ease the user experience. The next priority is to continue coupling the work with other codes in the SHARP package. Efforts on other projects include work to couple the Nek5000 thermo-hydraulics code to MOOSE, but this is in the preliminary stages.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

Implementation of the direct S ( α , β ) method in the KENO Monte Carlo code

The Monte Carlo code KENO contains thermal scattering data for a wide variety of thermal moderators. These data are processed from Evaluated Nuclear Data Files (ENDF) by AMPX and stored as double differential probability distribution functions. The method examined in this study uses S(α,β) probability distribution functions derived from the ENDF data files directly instead of being converted to double differential cross sections. This allows the size of the cross section data on the disk to be reduced substantially amount. KENO has also been updated to allow interpolation in temperature on these data so that problems can be run at any temperature. Results are shown for several simplified problems for a variety of moderators. In addition, benchmark models based on the KRITZ reactor in Sweden were run, and the results are compared with the previous versions of KENO without the direct S(α,β) method. Results from the direct S(α,β) method compare favorably with the original results obtained using the double differential cross sections. Finally, sampling the data increases the run-time of the Monte Carlo calculation, but memory usage is decreased substantially.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗