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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Coupled Reactor and Engine Nuclear Thermal Propulsion Modeling Methodology

The design and development process of a Nuclear Thermal Propulsion (NTP) system requires extensive multiphysics modeling to couple the neutron physics and thermal feedback effects to determine the reactor’s power shape. Propulsion system performance codes utilize this power shape to determine NTP key performance parameters. While the power shape is heavily dependent on the temperature profile and geometry of the reactor, many analyses either assume a constant power shape, or use neutronics analysis to determine a power shape for a specific reactor configuration. The development of a coupling interface for a propulsion system performance code and a Monte Carlo neutron transport code (OpenMC) allows for the reactor power shape to be calculated in an iteration loop. The interface utilizes a file share system to transfer geometry dimensions, temperatures, and material identifiers to OpenMC, which is used to perform a neutron transport simulation of a design like the government Testing Reference Design reactor. The interface is then able to post-process the results from OpenMC and use the same file share system to share a power shape and other important neutron transport parameters to the system performance code. Initial results show that neglecting the changes to power shape when comparing reactor configurations can yield inaccurate results. Furthermore, utilizing propellants other than hydrogen gas can cause significant changes to the power shape, and thus, the thermal performance of a specific reactor design. This methodology is being expanded to allow for multiple families of NTP reactors to be analyzed, including block moderator, particle bed, and NERVA-derived reactors.

multiphysics coupling↗

Coupled Reactor and Engine Nuclear Thermal Propulsion Modeling Methodology

The design and development process of a Nuclear Thermal Propulsion (NTP) system requires extensive multiphysics modeling to couple the neutron physics and thermal feedback effects to determine the reactor’s power shape. Propulsion system performance codes utilize this power shape to determine NTP key performance parameters. While the power shape is heavily dependent on the temperature profile and geometry of the reactor, many analyses either assume a constant power shape, or use neutronics analysis to determine a power shape for a specific reactor configuration. The development of a coupling interface for a propulsion system performance code and a Monte Carlo neutron transport code (OpenMC) allows for the reactor power shape to be calculated in an iteration loop. The interface utilizes a file share system to transfer geometry dimensions, temperatures, and material identifiers to OpenMC, which is used to perform a neutron transport simulation of a design like the government Testing Reference Design reactor. The interface is then able to post-process the results from OpenMC and use the same file share system to share a power shape and other important neutron transport parameters to the system performance code. Initial results show that neglecting the changes to power shape when comparing reactor configurations can yield inaccurate results. Furthermore, utilizing propellants other than hydrogen gas can cause significant changes to the power shape, and thus, the thermal performance of a specific reactor design. This methodology is being expanded to allow for multiple families of NTP reactors to be analyzed, including block moderator, particle bed, and NERVA-derived reactors.

multiphysics coupling↗

High-Fidelity Modeling Approach for Coupling Thermal, Fluid, and Neutronic Analysis in an NTP Engine

Nuclear thermal propulsion (NTP), with its increased efficiency compared to traditional rocket engines, is a potentially enabling technology for space missions of higher complexity, such as delivering heavy machinery or crew to the moon or other planets. Thus, exploring modeling approaches that can effectively couple the thermal, fluid, and neutronic behaviors of NTP reactors is essential to mitigate cost and schedule challenges with hardware development. This paper details one such approach which utilizes Cardinal to unify reactor physics analysis performed using OpenMC, heat transfer analysis performed using the MOOSE framework, and thermal hydraulic analysis performed using the MOOSE Thermal Hydraulic Module. This approach is demonstrated with a proof of concept that focuses on a legacy reactor geometry from the historic NERVA program. This preliminary model found an overprediction in, when compared to the reference data, axial power peaking and the temperatures of both solids and fluids by roughly 20%. It is clear, however, that the model conserved a number of broad trends, and a few model refinements should reduce the observed error. This approach has definite merit and should enable the production of informative results for more modern NTP systems. This work is a first step in creating a transient reactor model that can be updated across a sequence of time steps based on continually fluctuating, time-dependent boundary conditions.

Nuclear Thermal Propulsion↗

Coupled Reactor and Engine Nuclear Thermal Propulsion Modeling Methodology

The design and development process of a Nuclear Thermal Propulsion (NTP) system requires extensive multiphysics modeling to couple the neutron physics and thermal feedback effects to determine the reactor’s power shape. Propulsion system performance codes utilize this power shape to determine NTP key performance parameters. While the power shape is heavily dependent on the temperature profile and geometry of the reactor, many analyses either assume a constant power shape, or use neutronics analysis to determine a power shape for a specific reactor configuration. The development of a coupling interface for a propulsion system performance code and a Monte Carlo neutron transport code (OpenMC) allows for the reactor power shape to be calculated in a Picard iteration.

Jacob Stonehill↗