Search NASA⌕ Search

SEARCH · Search NASA

Results for “Gas Reactor”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fuel Performance Modeling Plan to Support the Advance Gas Reactor Program

This report documents the current status of the fuel performance modeling initiative to support the Advanced Gas Reactor (AGR) program in the development of tristructural isotropic (TRISO) coated fuel particles. A brief summary of the modeling codes that have been developed to support TRISO modeling is included along with a summary of the behavior of fuel particles during irradiation and the modeling used to capture these effects. In addition, this report identifies further modeling and material property needs that have been identified for further development based on experience from previously performed AGR experiments. In general, the remaining activities to support fuel performance modeling for the AGR program include continued AGR experiment support for AGR-3/4 and AGR-5/6/7 as well as modeling improvements identified throughout the course of the program. These modeling improvements can be summarized as the following: Fission product transport Thermomechanical particle behavior Additional modeling needs may be identified during the processing the data collected during the AGR post-irradiation examination (PIE) campaign and may lead to further modeling improvements that are not included in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Transient Physical Modelling for the Coupling of a High Temperature Gas Reactor with Thermal Energy Storage

Improving the flexibility of nuclear reactors to meet fluctuating demand on grids with high renewable energy generation penetration is key to improving reactor economics. Economic optimization using the code HERON gives maximum profit of coupling high temperature gas reactors (HTGRs) to thermal energy storage (TES) systems in the configuration shown in Figure 1 when following the demand in Figure 3. We look to model the physics of operation for a HTGR-TES using the HYBRID library in the code Modelica.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Coupled Monte Carlo and thermal-hydraulics modeling of a prismatic gas reactor fuel assembly using Cardinal

Cardinal is a MOOSE application that couples OpenMC Monte Carlo transport and NekRS computational fluid dynamics to the MOOSE framework, closing the neutronics and thermal-fluid gaps in conducting tightly-coupled, high-resolution multiscale and multiphysics analyses. By leveraging MOOSE's interfaces for wrapping external codes, Cardinal overcomes many challenges encountered in earlier multiphysics coupling works, such as file-based I/O or overly-restrictive geometry mapping requirements. In this work, we leverage a subset of the multiphysics interfaces in Cardinal to perform coupling of OpenMC neutron transport, MOOSE heat conduction, and THM thermal-fluids for steady-state modeling of a prismatic gas reactor fuel assembly.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

UO 2 F 2 particulate formation in an impinging jet gas reactor

Computational fluid dynamics (CFD), chemical kinetics, and aerosol dynamics were combined to model the formation of uranyl fluoride particles from the hydrolysis of uranium hexafluoride gas. This chemical process has been studied for many decades, however, detailed measurements of aerosol formation have only become available in the past few years which provide a basis for model comparison. Here, CFD simulations predicted complicated flow patterns in the impinging jet gas reactor. Aerosol formation simulations also predicted higher mass concentrations than were observed experimentally. This suggested that experimental data provided a partial representation which was subsequently enhanced by modeling and simulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Summary of Thermocouple Performance in the Advanced Gas Reactor Experiment AGR-5/6/7 During Irradiation in the Advanced Test Reactor

This is a conference presentation ppt file. The following abstract is for the entire conference paper - which will later be the subject of a PRS artifact The Advanced Gas Reactor -5/6/7 (AGR-5/6/7) experiment was the fourth and final experiment in the AGR experiment series and completed irradiation in July 2020. It serves as the formal fuel qualification test for the TRISO fuels under development by the US Department of Energy. This experiment was designed to irradiate fuel particles at temperatures ranging from 800°C ? 1500°C. The high end of the range created unique challenges for thermocouple-based temperature measurements. Commercially available high-temperature platinum-rhodium thermocouples (Types S, R, and B) and tungsten-rhenium thermocouples (Type C) suffer rapid decalibration due to transmutation of the thermoelements from neutron absorption. A special low neutron cross-section thermocouple system based on molybdenum/niobium thermoelements called High Temperature Irradiation Resistant thermocouple (HTIR-TC) has been under development at INL since circa 2004. Several examples of this thermocouple type were incorporated into regions of the test operating above 1200°C. For regions in the test operating in the 1000°C ? 1200°C range, high-performance versions of Type N thermocouples recently developed at Cambridge University were installed. Standard Type N thermocouples were used in regions of the test operating below 1000°C. A total of 54 thermocouples were incorporated into the test. A report of the performance of this large heterogenous set of thermocouples over the first third of the irradiation was previously provided (ANIMMA 2019). This follow-on paper discusses results from the balance of the experiment (Feb 2019 - July 2020). Special attention is focused on potential drift of thermocouples operating in the higher temperature regions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Impact of Variable Gas Mixtures on Bubble Size Distribution and Mass Transfer in Gas Fermentation Reactors

Gas fermentation has emerged as a promising new technology for the generation of fuels and chemicals from mixtures of greenhouse and energy rich gas streams (CO2/CH4/H2/CO) via microbial bioreaction. Example pathways include biomethanation (CO2/H2 to CH4), biogas upgrading, CO fermentation and wet-waste conversion. Effective Gas-liquid mass-transfer is an important physical phenomenon that determines the design and scale-up of these systems. There is currently a knowledge-gap regarding bubble-size distributions when using a mixture of gases with vastly different properties, which can have a significant impact on overall mass-transfer. For example, hydrogen bubbles are more buoyant compared to other relatively heavier gases (CO2/CH4/CO), resulting in a large distribution of residence times and bubble sizes. This work therefore develops a deeper understanding of bubble dynamics and interphase mass transfer in such heterogenous gas mixtures through well-resolved computational models. We use a detailed multiphase computational-fluid-dynamics (CFD) model to study the impact of gas-mixtures on overall mass-transfer in bubble column and air-lift reactors. The CFD tool previously developed by the authors (1) for simulating aerobic fermentation reactors at scale is used in this study. The Reynolds-averaged mass, momentum, energy, and species transport equations are solved for interpenetrating gas and liquid phase in this model. We use a population balance-based bubble-size-distribution model that is validated against small-scale experiments in our solver. Results pertaining to multiple simulations of gas-fermentation reactors are presented where gas mixtures with varying compositions of CO2/CH4/CO/H2 are imposed at the sparger boundaries. The spatio-temporal variations in bubble-size distribution and mass transfer coefficient is analyzed for varying superficial velocities and gas-compositions for varying sizes of bubble-column and airlift reactors.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Economic solution for low carbon process heat: A horizontal, compact high temperature gas reactor

In 2018, nuclear energy generated 55% of United States’ and one third of the world’s carbon free electricity, making nuclear energy a key tool in efforts to mitigate climate change before 2050. However, the current nuclear technology, light water reactors (LWRs), is limited to 300°C, so it cannot be used to decarbonize industrial process heat which accounts for 12% of US greenhouse gas emissions. High temperature gas reactors (HTGRs) can meet the high temperature demand with carbon free nuclear heat. The estimated cost of HTGRs, such as the Next Generation Nuclear Plant (NGNP), are even higher than state-of-the-art LWRs. In this paper, we expanded our nuclear cost estimating tool to include HTGRs and find that the NGNP overnight capital costs were 32% higher than an advanced LWR per unit capacity. The higher cost will naturally result in larger risk to cost overrun as recently experienced by larger LWRs in western nations. With a design-to-build mindset to minimize cost and construction risk, we introduce the horizontal, compact HTGR (HC-HTGR). The reactor core and steam generator are mounted horizontally on rails and in-line with one another, decreasing the size of the reactor building relative to the power capacity four times when compared to traditional HTGRs. The HC-HTGR reduced overnight civil structure costs by 42%, indirect costs by 38%, and total capital costs by 20% from NGNP. We discussed the required engineering of new systems for the HC-HTGR including vessel supports, the reactor cavity cooling system, and steam generator design. Finally, we estimated the fuel and operations costs of the HC-HTGR, and a survey of low-carbon industrial process heat technology showed the HC-HTGR can deliver a highly competitive levelized cost of heat in the range of $6.13–12.48/GJ.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Application of a Physics-Informed Convolutional Neural Network for Monitoring the Temperature Fields in High-Temperature Gas Reactors

Here, this work presents current advances in applying a physics-informed convolutional neural network (CNN) to evaluate temperature distributions in advanced reactors. Our goal is to demonstrate that the CNN can reconstruct temperature fields within the solid region of a prismatic fuel assembly in a high-temperature gas reactor (HTGR) with sensor data available in only a few cooling channels. Before that, we showcase the superior performance of the physics-informed CNN in comparison to a purely data-driven multilayer perceptron (MLP), considering a canonical heated channel setup. This analysis shows the advantages of our approach and justifies its choice. The datasets employed here are obtained upon numerical simulations performed with codes under the Nuclear Energy Advanced Modeling and Simulation program. This work is important, as industry experience indicates that the assembly material in HTGR concepts is prone to large thermal-mechanical loads nearing operational limits. This makes it crucial to characterize peak temperatures and their distributions near hot spots. Modern thermocouples are unreliable in these types of harsh environments because of the high neutron fluxes and elevated temperatures involved. The CNN-based field reconstruction represents an attractive solution, enabling sensor arrays in less aggressive locations and augmenting indirect predictions for less accessible regions. The results show that the CNN reduces prediction errors by orders of magnitude in comparison to the MLP, considering the simple yet well-representative heated channel case. In the case of the HTGR fuel assembly, the CNN can successfully reconstruct temperature fields over various cooling regimes. Furthermore, we also explore the algorithm’s ability to detect abnormalities. Interestingly, the CNN proves it has the capacity to detect blockage in one of the noninstrumented cooling channels.

Machine learning↗
DOE OSTI2022

Coupled Monte Carlo and thermal-fluid modeling of high temperature gas reactors using Cardinal

Cardinal is an open-source application that couples OpenMC Monte Carlo transport and NekRS computa-tional fluid dynamics to the Multiphysics Object-Oriented Simulation Environment (MOOSE), closing neutronics and thermal-fluid gaps in conducting high-resolution multiscale and multiphysics analyses of nuclear systems. Here, we provide an introduction to Cardinal's software design, data mapping, and multi -physics coupling strategy to highlight our approach to overcoming common challenges in multiphysics simulation. We then describe an application of Cardinal to prismatic High Temperature Gas Reactors (HTGRs) with various combinations of NekRS, OpenMC, BISON, and THM. A high-resolution coupling of NekRS, OpenMC, and BISON provides a reference solution at the unit cell level and shows excellent agree-ment with a lower-resolution coupling of THM, OpenMC, and BISON. A full core coupling of THM, OpenMC, and BISON resolving the three-dimensional conjugate heat transfer and sub-pin power distri-bution then provides detailed predictions of HTGR temperatures and the fission distribution.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2010

Test Results from a Direct Drive Gas Reactor Simulator Coupled to a Brayton Power Conversion Unit

Component level testing of power conversion units proposed for use in fission surface power systems has typically been done using relatively simple electric heaters for thermal input. These heaters do not adequately represent the geometry or response of proposed reactors. As testing of fission surface power systems transitions from the component level to the system level it becomes necessary to more accurately replicate these reactors using reactor simulators. The Direct Drive Gas-Brayton Power Conversion Unit test activity at the NASA Glenn Research Center integrates a reactor simulator with an existing Brayton test rig. The response of the reactor simulator to a change in Brayton shaft speed is shown as well as the response of the Brayton to an insertion of reactivity, corresponding to a drum reconfiguration. The lessons learned from these tests can be used to improve the design of future reactor simulators which can be used in system level fission surface power tests.

Hervol, David S.↗
DOE OSTI2022

DOE Advanced Gas Reactor Fuel Development and Qualification Program Overview

AGR-3/4 post-irradiation examination and data analysis AGR-5/6/7 PIE and safety testing Supplemental fuel microanalysis and method development Fuel oxidation testing Air/moisture Ingress Experiment (AMIX) system development (deployed in FY23) Single particle testing in FITT Data management and analysis Fuel performance modeling

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1991

Atmospheric pressure flow reactor: Gas phase chemical kinetics under tropospheric conditions without wall effects

A flow reactor for simulating the interaction in the troposphere is set forth. A first reactant mixed with a carrier gas is delivered from a pump and flows through a duct having louvers therein. The louvers straighten out the flow, reduce turbulence and provide laminar flow discharge from the duct. A second reactant delivered from a source through a pump is input into the flowing stream, the second reactant being diffused through a plurality of small diffusion tubes to avoid disturbing the laminar flow. The commingled first and second reactants in the carrier gas are then directed along an elongated duct where the walls are spaced away from the flow of reactants to avoid wall interference, disturbance or turbulence arising from the walls. A probe connected with a measuring device can be inserted through various sampling ports in the second duct to complete measurements of the first and second reactants and the product of their reaction at selected XYZ locations relative to the flowing system.

Koontz, Steven L.↗
DOE OSTI2025

Microwave-Assisted Dehydroaromatization of Flare Gas: Reactor Modeling, Plant-Wide Simulation and Economic Feasibility Analysis

Flaring is widely practiced in the oil, gas, and petrochemical sectors to ensure safety during upsets and maintenance but emits large amounts of GHGs, causing energy and economic losses. In the U.S., about one-third of Bakken gas (~250 MMSCFD) and ~100 MMSCFD from Eagle Ford are flared. Recovering this gas is essential for sustainability. Existing recovery methods—compression and reinjection (EOR), conversion to NGL, LNG/CNG, GTL, and GTW—are often limited by flowrate, composition, and variability, especially in unconventional wells. This study develops a microwave-assisted dehydroaromatization (DHA) process to convert flare gas into benzene, toluene, ethylene, and naphthalene. A laboratory reactor model is scaled up into a modular plant-wide system. Techno-economic (TEA) and life-cycle (LCA) analyses evaluate performance and sustainability, with sensitivity studies on plant capacity, electricity cost, and catalyst price confirming strong economic potential.

dehydroaromatization↗
NASA NTRS2009

Test Results From a Direct Drive Gas Reactor Simulator Coupled to a Brayton Power Conversion Unit

The Brayton Power Conversion Unit (BPCU) located at NASA Glenn Research Center (GRC) in Cleveland, OH is a closed cycle system incorporating a turboaltemator, recuperator, and gas cooler connected by gas ducts to an external gas heater. For this series of tests, the BPCU was modified by replacing the gas heater with the Direct Drive Gas heater or DOG. The DOG uses electric resistance heaters to simulate a fast spectrum nuclear reactor similar to those proposed for space power applications. The combined system thermal transient behavior was the focus of these tests. The BPCU was operated at various steady state points. At each point it was subjected to transient changes involving shaft rotational speed or DOG electrical input. This paper outlines the changes made to the test unit and describes the testing that took place along with the test results.

Hervol, David S.↗
DOE OSTI2025

Reduced-order modeling for efficient cross section library development in high-temperature gas reactor pebble-bed depletion analysis

Accurate modeling of running-in and equilibrium conditions in pebble-bed reactors (PBRs) requires precise microscopic multigroup neutron cross sections. In Griffin, deterministic neutronics calculations rely on multivariate interpolation over large cross section libraries, resulting in significant memory usage and performance bottlenecks. This work, together with a companion paper on Griffin integration, explores reduced-order models (ROMs) to replace interpolation with lightweight surrogates. Several ROM techniques are benchmarked, with deep neural networks (DNNs) demonstrating superior memory efficiency, scalability, and predictive accuracy. A total of 295 DNNs were trained to build a comprehensive isotope library, integrated into Griffin through a custom LibTorch interface for depletion analysis. Initial results demonstrate that DNN-based ROMs drastically reduce memory demands while preserving accuracy, enabling finer tabulations and additional state variables without overhead. In conclusion, the framework also supports online cross section generation and real-time DNN updates through transfer learning, improving fidelity by capturing self-shielding and evolving nuclide compositions during burnup.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Improving Gas Reactor Design with Complex Non-Standard Reaction Mechanisms in a Reactive Flow Model

Fluorinated gases are critical to a number of high-technology industries including semiconductor manufacturing and related processes such as flat panel display, LED, and photovoltaic manufacturing. These fluorinated gases have very high global warming potentials (GWPs) and, unfortunately are chemically very stable, in some cases lasting for thousands of years in the atmosphere. For environmental reasons, it is imperative that the release of these gases be minimized, but existing methods to destroy them requires a significant amount of energy. The goal of this project was to develop a more energy efficient method of destroying these high GWP gases using computational fluid dynamics, but the computational requirements are significant. In this project, we bring together resources available at the national labs, including high-performance computing hardware and modern computational methods, in order to explore an industrially important problem with key environmental and economic impact. In this project, we examined the state-of-the-art models for the physical processes involved, and made subtle changes to arrive at alternative formulations considerably better suited for computation and study. We examined several representative scenarios and developed a set of analyses techniques and tools that could be used to explore the systems in much greater detail. This exploratory project has demonstrated to ALZETA that HPC can indeed provide a unique view into their complex engineering problem - one that is simply inaccessible by any other means. The tools allow us to explore the details of the chemical process, and allow one to construct "what-if" scenarios to address shortcomings of the physical device in its current operating modes. However, as with many sources of completely new information, many new questions are illuminated with this capability. It will take considerable time, effort and experience before we learn to probe the solutions, pose operating scenarios and confirm modifications to the device that lead to real engineering advances.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗