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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerating transients with NekRS: GPU overlapping domain implementation and multi-rate timestepping

The simulation of nuclear transients using Computational Fluid Dynamics (CFD) presents significant computational challenges due to the inherent complexity and the wide separation in temporal scales between various flow physical phenomena. These disparities lead to high computational costs, often making the simulation of transients impractical without advanced techniques. Consequently, multiple research initiatives are being pursued by the NEAMS thermal-hydraulic area, some driven by academic institutions and some by national laboratories. Overall, they are exploring novel methods to make transient simulations more feasible and efficient. This report delves into recent advancements within the CFD code NekRS, specifically those achieved in Fiscal Year 2024 under the CONNECT effort, aimed at improving the performance and feasibility of transient simulations. The first major advancement involves the porting of NekRS to Aurora, one of the Department of Energy’s (DOE) most powerful supercomputers. Additionally, the report discusses the implementation of an overlapping domain capability within NekRS. This novel GPU-accelerated capability allows different spatial regions of the domain to be solved independently, enhancing the code’s efficiency, particularly when running large-scale simulations in complex domains. The scalability of this approach is demonstrated, highlighting its potential to transform how transients are approached in CFD simulations. Lastly, the report focuses on how this overlapping domain capability specifically accelerates transient simulations through multi-rate timestepping. By decoupling different regions and facilitating faster computations, this method offers a promising pathway to making nuclear transient simulations more computationally feasible, addressing one of the critical bottlenecks in the field. Together, these advancements represent a significant leap forward in transient simulation technology, bringing closer the possibility of handling highly complex nuclear scenarios with greater efficiency and accuracy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Nuclear–Electronic Orbital Quantum Mechanical/Molecular Mechanical Real-Time Dynamics

Simulating the nuclear–electronic quantum dynamics of large-scale molecular systems in the condensed phase is key for studying biologically and chemically important processes such as proton transfer and proton-coupled electron transfer reactions. Herein, the real-time nuclear–electronic orbital time-dependent density functional theory (RT-NEO-TDDFT) approach is combined with a hybrid quantum mechanical/molecular mechanical (QM/MM) strategy to enable the accurate description of coupled nuclear–electronic quantum dynamics in the presence of heterogeneous environments such as solvent or proteins. The densities of the electrons and quantum protons are propagated in real time, while the other nuclei are propagated classically on the instantaneous electron–proton vibronic surface. This approach is applied to phenol bound to lysozyme, intramolecular proton transfer in malonaldehyde, and nonequilibrium excited-state intramolecular proton transfer in o-hydroxybenzaldehyde. Furthermore, these examples illustrate that the RT-NEO-TDDFT framework, coupled with an atomistic representation of the environment, allows the simulation of condensed-phase systems that exhibit significant nuclear quantum effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗
DOE OSTI2023

Effect of feed composition on the production of off-gases during vitrification of simulated low-activity nuclear waste

During the vitrification of nuclear waste, hazardous and radioactive emissions are generated from the feed-to-glass conversion reactions, in addition to discharges from forced air bubbling and air inleakage. Although the major gaseous emissions are water vapor, nitrogen, and carbon dioxide, various monitored environmental pollutants are also released, such as nitrogen oxides or sulfur dioxide. In addition, reactions between organics and nitrates in the feed may also form products of incomplete combustion such as carbon monoxide and acetonitrile. Although off-gas emissions are commonly measured during both laboratory- and pilot-scale melter testing, no predictive tool is currently available to a priori estimate the composition of gaseous emissions during nuclear waste vitrification. This work forms a basis for the development of such predictive tool by measuring gas evolution from a broad range of simulated low-activity waste melter feeds using evolved gas analysis data and developing correlations between the feed and off-gas compositions. Using reaction stoichiometry and regression analysis, we demonstrate that next to the content of nitrogen and organic carbon in the feed, the gaseous emissions are affected by the feed reduction-oxidation conditions – the more the feed is reduced, the less nitrogen monoxide, and more carbon monoxide and acetonitrile evolves. In conclusion, the results presented in this work provide a first step towards reducing the amount of expensive physical melter testing and the regression analysis provides a simple tool for rapid optimization of feed composition with respect to off-gas composition.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Extension of SCALE/Sampler’s sensitivity index for the assessment of cross section, fission yield, and decay data uncertainties

Accurate prediction of nuclide compositions and neutron and gamma sources and spectra for fresh and spent nuclear fuel through computational modeling and simulations is the basis for safeguards instruments design, optimization, and calibration, and for validation of the measured responses. The accuracy of these simulations can be significantly impacted by uncertainties in input parameters to the applied computer code. Input parameters are, for example, dimensions, material compositions, and temperatures of the model. Additionally, important but sometimes neglected input parameters for simulations of nuclear systems are the nuclear data that include nuclear reaction cross sections, fission product yields, and decay data. It has been shown that uncertainties of calculated results are dominated by uncertainties of these nuclear data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2013

Nuclear Thermal Rocket Element Environmental Simulator (NTREES) Upgrade Activities

A key technology element in Nuclear Thermal Propulsion is the development of fuel materials and components which can withstand extremely high temperatures while being exposed to flowing hydrogen. NTREES provides a cost effective method for rapidly screening of candidate fuel components with regard to their viability for use in NTR systems. The NTREES is designed to mimic the conditions (minus the radiation) to which nuclear rocket fuel elements and other components would be subjected to during reactor operation. The NTREES consists of a water cooled ASME code stamped pressure vessel and its associated control hardware and instrumentation coupled with inductive heaters to simulate the heat provided by the fission process. The NTREES has been designed to safely allow hydrogen gas to be injected into internal flow passages of an inductively heated test article mounted in the chamber.

Emrich, William↗
DOE OSTI2022

Nuclear Theory from First Principles to Forefront Experiments (Final Report for DE-SC0018638)

The Lee research group is a part of the Nuclear Lattice Effective Field Theory Collaboration, which has developed and performed ab initio lattice simulations of nuclear structure, scattering, reactions, and many-body systems. The other senior members of the collaboration include Ulf-G. Meißner at Bonn/Julich, Evgeny Epelbaum and Hermann Krebs at Bochum, Timo Lahde and Thomas Luu at Julich, and Gautam Rupak at Mississippi State. Our letter “Ab initio alpha-alpha scattering” was featured in a Nature News and Views article. Another letter “Nuclear binding near a quantum phase transition” was highlighted in a Viewpoint article in the online APS journal Physics as well as a news article in the IOP publication Physics World (September 21, 2016). Our letter “Eigenvector continuation with subspace learning” was also highlighted a Synopsis article in Physics. There are many promising ab initio approaches being used to calculate the properties of few-and many-nucleon systems. This includes the no-core shell model, symmetry-adapted no-core shell model quantum Monte Carlo, auxiliary-field diffusion Monte Carlo, self-consistent Green’s functions, many-body perturbation theory, in-medium similarity renormalization group, and coupled cluster methods. Lattice effective field theory is another ab initio approach which combines the framework of effective field theory with lattice Monte Carlo methods to allow favorable scaling from few- to many-body systems. Perhaps the most important aspect of lattice effective field theory is that its strengths and weaknesses are orthogonal to that of other ab initio methods. For example, lattice effective field theory has little difficulty in probing cluster structures and collectivity, while such features are much more difficult using other methods. Furthermore it can be used to compute superfluid condensate fractions as well as the phase diagram of strongly matter and the density and temperature dependence of clustering. Lattice effective field theory was first used in simulations of infinite nuclear matter and infinite neutron matter with pions and without pions. In addition to the efforts by our collaboration, there have been recent efforts by other groups as well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1972

Flowing gas, non-nuclear experiments on the gas core reactor

Flow tests were conducted on models of the gas core (cavity) reactor. Variations in cavity wall and injection configurations were aimed at establishing flow patterns that give a maximum of the nuclear criticality eigenvalue. Correlation with the nuclear effect was made using multigroup diffusion theory normalized by previous benchmark critical experiments. Air was used to simulate the hydrogen propellant in the flow tests, and smoked air, argon, or freon to simulate the central nuclear fuel gas. All tests were run in the down-firing direction so that gravitational effects simulated the acceleration effect of a rocket. Results show that acceptable flow patterns with high volume fraction for the simulated nuclear fuel gas and high flow rate ratios of propellant to fuel can be obtained. Using a point injector for the fuel, good flow patterns are obtained by directing the outer gas at high velocity along the cavity wall, using louvered or oblique-angle-honeycomb injection schemes.

Kunze, J. F.↗
NASA NTRS1973

Flowing gas, non-nuclear experiments on the gas core reactor

Variations in cavity wall and injection configurations of the gas core reactor were aimed at establishing flow patterns that give a maximum of the nuclear criticality eigenvalue. Correlation with the nuclear effect was made using multigroup diffusion theory normalized by previous benchmark critical experiments. Air was used to simulate the hydrogen propellant in the flow tests, and smoked air, argon, or Freon to simulate the central nuclear fuel gas. Tests were run both in the down-firing and upfiring directions. Results showed that acceptable flow patterns with volume fraction for the simulated nuclear fuel gas and high flow rate ratios of propellant to fuel can be obtained. Using a point injector for the fuel, good flow patterns are obtained by directing the outer gas at high velocity long the cavity wall, using louvered injection schemes. Recirculation patterns were needed to stabilize the heavy central gas when different gases are used.

Kunze, J. F.↗
NASA NTRS2011

Fission Surface Power Technology Development Update

Power is a critical consideration in planning exploration of the surfaces of the Moon, Mars, and places beyond. Nuclear power is an important option, especially for locations in the solar system where sunlight is limited or environmental conditions are challenging (e.g., extreme cold, dust storms). NASA and the Department of Energy are maintaining the option for fission surface power for the Moon and Mars by developing and demonstrating technology for a fission surface power system. The Fission Surface Power Systems project has focused on subscale component and subsystem demonstrations to address the feasibility of a low-risk, low-cost approach to space nuclear power for surface missions. Laboratory demonstrations of the liquid metal pump, reactor control drum drive, power conversion, heat rejection, and power management and distribution technologies have validated that the fundamental characteristics and performance of these components and subsystems are consistent with a Fission Surface Power preliminary reference concept. In addition, subscale versions of a non-nuclear reactor simulator, using electric resistance heating in place of the reactor fuel, have been built and operated with liquid metal sodium-potassium and helium/xenon gas heat transfer loops, demonstrating the viability of establishing system-level performance and characteristics of fission surface power technologies without requiring a nuclear reactor. While some component and subsystem testing will continue through 2011 and beyond, the results to date provide sufficient confidence to proceed with system level technology readiness demonstration. To demonstrate the system level readiness of fission surface power in an operationally relevant environment (the primary goal of the Fission Surface Power Systems project), a full scale, 1/4 power Technology Demonstration Unit (TDU) is under development. The TDU will consist of a non-nuclear reactor simulator, a sodium-potassium heat transfer loop, a power conversion unit with electrical controls, and a heat rejection system with a multi-panel radiator assembly. Testing is planned at the Glenn Research Center Vacuum Facility 6 starting in 2012, with vacuum and liquid-nitrogen cold walls to provide simulation of operationally relevant environments. A nominal two-year test campaign is planned including a Phase 1 reactor simulator and power conversion test followed by a Phase 2 integrated system test with radiator panel heat rejection. The testing is expected to demonstrate the readiness and availability of fission surface power as a viable power system option for NASA's exploration needs. In addition to surface power, technology development work within this project is also directly applicable to in-space fission power and propulsion systems.

Palac, Donald T.↗
DOE OSTI2023

New Covariant Density Functionals of Nuclear Matter for Compact Star Simulations

We generate three families of extended covariant density functionals of nuclear matter that have varying slope of symmetry energy and skewness at nuclear saturation density, but otherwise share the same basic parameters (symmetry energy, compressibility, saturation parameters, etc.) with the standard DDME2, DD2, and MPE functionals. Tables of the parameters of these new density functionals are given, which can be straightforwardly used in DDME2, DD2, and MPE parameterization-based codes. Furthermore, we provide tables of a large number of equations of state (81 for each family) that can be used in astrophysical simulations to assess the impact of variations of the not-well-known slope of symmetry energy and skewness of nuclear systems on the astrophysics of compact objects. We also provide tables of computed integral parameters (mass, radius, and tidal deformability) that can be used, e.g., for modeling gravitational waveforms. Finally, for the extended DDME2-based parameterization, we implement a first-order phase transition to quark matter to obtain a family of equations of state that accommodates a phase transition to quark matter. Analogous tables of the equations of state and integral parameters are provided for this case as well.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Nuclear light bulb propellant heating simulation using a tungsten/argon aerosol and radiation from a dc arc surrounded by a segmented mirror cavity

Experiments were conducted to simulate radiant heating of the propellant stream of a nuclear light bulb engine to obtain high bulk exit temperatures in the flowing simulated propellant stream by absorption of large fractions of the incident thermal radiation. A high-power, vortex-stabilized dc arc within an uncooled fused silica tube was used as the radiant energy source. It was surrounded by a mirror system to increase the radiation incident on the simulated propellant. The 12.7-cm-long by 2.3-cm-wide, diverging-duct test section had a transparent front wall and a reflecting rear wall. The central stream of seeded gas, a tungsten-particle/argon aerosol, had unseeded argon buffer layers on both sides to prevent coating of the duct walls. Arc operating times were approximately 0.5 sec with power levels up to 780 kW. Bulk exit temperatures were measured using a calorimeter downstream of the duct. The maximum simulated propellant bulk exit temperature obtained was 4515 K, compared with 3860 K in previous tests, 3300 to 3700 K expected in in-reactor tests in the Nuclear Furnace, and 6660 K in the reference nuclear light bulb engine. The maximum temperature in these tests was limited primarily by the amount of radiation incident on the test section (determined by the arc operating characteristics and the effectiveness of the mirror cavity).

Klein, J. F.↗
DOE OSTI2023

Real-time infrared spectroscopy coupled with blind source separation for nuclear waste process monitoring

On-line infrared absorbance spectroscopy enables rapid measurement of solution-phase molecular species. Many spectra-to-concentration models exist for spectral data, with some models able to handle overlapping spectral bands and nonlinearities. However, model accuracy is limited by the quality of training data used in model fitting. The process spectra of nuclear waste simulants at the Savannah River Site display incongruity between training and process spectra; the glycolate spectral signature in the training data does not match the glycolate signature in Savannah River National Laboratory process data. A novel blind source separation algorithm is proposed that preprocesses spectral data so that process spectra more closely resemble training spectra, thereby improving model quantification accuracy when unexpected sources of variation appear in process spectra. The novel blind source separation preprocessing algorithm is shown to improve nitrate quantification from an R 2 of 0.934 to 0.988 and from 0.267 to 0.978 in two instances analyzing nuclear waste simulants from the Slurry Receipt Adjustment Tank and Slurry Mix Evaporator cycle at the Savannah River Site.

Crouse, Steven H.↗
DOE OSTI2023

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Tabulated Fluid Properties Research Report

The Multiphysics Object-Oriented Simulation Environment (MOOSE) enables a wide range of advanced nuclear reactor simulations.[6] Under the guidance of MOOSE’s Thermal Hydraulics Team,I worked to expand the capabilities of Tabulated Fluid Properties (TFP) in the fluid properties module. The fluid properties module allows the user to determine a variety of fluid properties by interpolating points between tabulated data. I implemented the ability to use bilinear interpolation instead of bicubic interpolation for interpolating tabulated data. I also changed the method of variable set inversions to use a 2-dimensional Newton’s Method utility that I created. Variable set inversions are often done from (v,e) to (p,T), where v is specific volume, e is specific internal energy, p is pressure and T is temperature. New routines have also been added into TFP such that it can be used with more applications, such as the Navier Stokes and Thermal Hydraulics modules in MOOSE for Pronghorn[5] and RELAP-7[1] respectively. This work was spurred by interest from NASA in testing a Nuclear Thermal Propulsion (NTP) engine system. NTP engines have drastically different fluid properties throughout the engine and Tabulated Fluid Properties provides the flexibility needed to properly simulate and test these engines.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Overview of Nuclear Data Measurement and Analysis at RPI [Slides]

This presentation discusses the experimental, simulation, and nuclear data methods that were validated for the RPI γ-Multiplicity Detector. When the neutron capture γ-cascade data is well-known, the γ-emission spectra can be accurately calculated using the modified simulation tools. The RPI γ-Multiplicity Detector system is now ready for analysis and recommendations for isotopes with deficiencies in γ-ray data. The presentation also discusses future work which includes developing a method for analyzing and adjusting nuclear data for 59 Co, 55 Mn and other measured isotopes including 181 Ta. Additionally, future work includes comparing experimental γ-emission spectra with MCNP-6.2/DICEBOX simulations for 238 U and 235 U. In summation, new capture and transmission measurements for 54 Fe will help improve resonance parameter evaluation. Neutron capture gamma cascade spectra and yields were measured in the resolved resonance region and compared to evaluations. In addition, the pulsed neutron die-away method was developed as a tool to provide data for validation of TSLs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗