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At least 793 records · Page 44

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Design and validation of a gamma-ray scanning system for measuring irradiated nuclear fuel

We report a prototype gamma-ray scanning system was designed to perform post-irradiation measurements of nuclear fuel at Idaho National Laboratory (INL). The system is composed of a coaxial high-purity germanium (HPGe) detector, a collimator, and mechanical positioning stages that translate the fuel sample across the front of the collimator. This paper documents the design process, modeling and the laboratory characterization performed to validate the system. The modeling of the system was done using the Monte Carlo N-Particle code with vendor-supplied design specifications, dimensional measurements, and x-ray radiographs of the HPGe detector. The characterization included measurements of calibrated radiation sources in different geometries, and calculations for absolute efficiency and dead time. Benchmark measurements were performed scanning an irradiated fuel rodlet containing ten pellets of 4.9% enriched UO2 in zirconium alloy. These results were compared to simulated spectra to further help characterize the detector model. One goal of the system is to determine the number of fissions per gram of UO2 in the fuel; comparison of the results from this prototype system's assay of the irradiated fuel rodlet are in agreement with previously estimated results.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2021

Condensed Phase Water Molecular Multipole Moments from Deep Neural Network Models Trained on Ab Initio Simulation Data

Ionic solvation phenomena in liquids involve intense interactions in the inner solvation shell. For interactions beyond the first shell, the ion–solvent interaction energies result from the sum of many smaller-magnitude contributions that can still include polarization effects. Deep neural network (DNN) methods have recently found wide application in developing efficient molecular models that maintain near-quantum accuracy. In this work, we extend the DeePMD-kit code to produce accurate molecular multipole moments in the bulk and near interfaces. The new method is validated by comparing the DNN moments with those generated by ab initio simulations. The moments are used to compute the electrostatic potential at the center of a molecular-sized hydrophobic cavity in water. The results show that the fields produced by the DNN models are in quantitative agreement with the AIMD-derived values. These efficient methods will open the door to more accurate solvation models for large solutes such as proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data

Nationwide population-based cohort provides a new opportunity to build an automated risk prediction model based on individuals’ history of health and healthcare beyond existing risk prediction models. We tested the possibility of machine learning models to predict future incidence of Alzheimer’s disease (AD) using large-scale administrative health data. From the Korean National Health Insurance Service database between 2002 and 2010, we obtained de-identified health data in elders above 65 years (N = 40,736) containing 4,894 unique clinical features including ICD-10 codes, medication codes, laboratory values, history of personal and family illness and socio-demographics. To define incident AD we considered two operational definitions: “definite AD” with diagnostic codes and dementia medication (n = 614) and “probable AD” with only diagnosis (n = 2026). We trained and validated random forest, support vector machine and logistic regression to predict incident AD in 1, 2, 3, and 4 subsequent years. For predicting future incidence of AD in balanced samples (bootstrapping), the machine learning models showed reasonable performance in 1-year prediction with AUC of 0.775 and 0.759, based on “definite AD” and “probable AD” outcomes, respectively; in 2-year, 0.730 and 0.693; in 3-year, 0.677 and 0.644; in 4-year, 0.725 and 0.683. The results were similar when the entire (unbalanced) samples were used. Important clinical features selected in logistic regression included hemoglobin level, age and urine protein level. This study may shed a light on the utility of the data-driven machine learning model based on large-scale administrative health data in AD risk prediction, which may enable better selection of individuals at risk for AD in clinical trials or early detection in clinical settings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Modeling the contributions to acoustic nonlinearity from complex dislocation networks using 3D dislocation dynamics

Nonlinear ultrasonic parameters are highly sensitive to microstructural features that affect macroscale material behavior, providing a nondestructive means to characterize their evolution. Although dislocations are known to be a strong source of acoustic nonlinearity, establishing quantitative links between the acoustic nonlinearity parameter (β), measured via Second Harmonic Generation, and dislocation morphology—such as dislocation length and density—remains an open challenge. This work advances the numerical modeling of dislocation–β relationships using 3D dislocation dynamics (DD) simulations in two approaches: a “static” method computing strain and stress fields from dislocation configurations in the absence of external loading, and a “quasi-static” method to estimate β from the curvature of dislocation lines under applied load. First, the static method is combined with finite element analysis to investigate a recent assertion that heterogeneous initial strain fields can induce higher harmonic generation in a linear elastic medium; the present results do not corroborate this outcome. Then, the quasi-static method is applied to multiple-dislocation scenarios through parametric studies, revealing behaviors not predicted by analytical models, such as the competing interactions of edge and screw dislocations and the significant influence of applied stress on β. Finally, the simulations are used to model SHG experimental results and validate the hypothesis that β can decrease during plastic deformation, despite increasing dislocation density. As the DD code used here is open-source, it provides a practical platform for future investigation into microstructure–β relationships important to the interpretation of SHG results.

Materials science↗

DOE OSTI2024

Radial drift of plasma blobs in a toroidal magnetic field with fully kinetic and reduced fluid models

Abstract In curved magnetic geometries, field-aligned regions of enhanced plasma pressure and density, termed ‘blobs,’ move as coherent filaments across the magnetic field lines. Coherent blobs account for a significant fraction of transport at the edges of magnetic fusion experiments and arise in naturally-occurring space plasmas. This work examines the dynamics of blobs with a fully kinetic electromagnetic particle-in-cell code and with a drift-reduced fluid code. In low-beta regimes with moderate blob speeds, good agreement is found in the maximum blob velocity between the two simulation schemes and simple analytical estimates. The fully kinetic code demonstrates that blob speeds saturate near the initial sound speed, which is a regime outside the validity of the reduced fluid model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Verification and Validation of Two Hydrodynamic Methods for Simulations of High Energy Density Physics Problems

A 3D verification and validation suite of test problems is presented and used to evaluate hydrodynamic methods within a radiation hydrodynamics code, xRAGE. These test problems exercise different levels of complexity, building towards ICF problems which in addition to hydrodynamics also include three temperature plasma physics, thermal conduction, and radiation diffusion. Among the problems in the test suite are the Kidder ball problem, the Verney shell problem, and a 5-material compression problem, which exercise different purely hydrodynamic methods implemented within xRAGE. There is excellent agreement between 2D and 3D XRAGE simulation results and between the xRAGE results and the benchmark solutions. Two 3D ICF test problems are also presented, based on an OMEGA direct drive capsule experiment and on a NIF indirect drive capsule experiment. It is demonstrated that the newer unsplit hydrodynamic method in xRAGE produces more vorticity relative to the older default method. For the indirect drive capsule, the 3D simulations are in reasonable agreement with the experimental values of ion temperature and neutron production.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Definition of the Stiesdal Offshore TetraSpar Floating Wind System for OC6 Phase IV

The Offshore Code Comparison Collaboration, Continued, with Correlation, and unCertainty (OC6) is an international project focused on verifying and validating modeling tools used in the analysis of floating offshore wind systems. The fourth phase of the project aims to assess the ability of the tools to model a novel floating wind design. The TetraSpar was designed by Stiesdal Offshore Technologies and was selected as the subject platform for the project. The platform is a unique design that features spar-like stability with a very low center of gravity, but does not require rare deep-water ports. This combination is achieved with a system made of two separate steel structures, a hull at the water's surface that supports the wind turbine tower, and a keel that is suspended below the main body. This lower keel has a very high density and drives the total platform's low center of gravity. The TetraSpar, with hull and keel, spar-type stability, and relatively slender components, is unique compared to platforms studied in earlier phases of OC3-OC6 projects, and it offers an opportunity to evaluate the applicability of modeling tools to a novel design, especially unique hydrodynamics and compliant cables. Scaled model tests of the TetraSpar design were performed in 2018-2019 by the University of Maine. The data collected in the model tests provides a detailed description of the response of the platform in various controlled and relatively well understood conditions. Comparison with this data provides a good opportunity for validation of numerical models. The OC6 Phase IV work focuses on the specific parameters used in these scaled model tests. Descriptions of the platform and the test campaign in this document are based on the report written by Allen and Fowler of the University of Maine in 2019.

17 WIND ENERGY↗

DOE OSTI2024

PHASM: A Toolkit for Creating AI Surrogate Models within Legacy Codebases

PHASM (“Parallel Hardware viA Surrogate Models”) is a software toolkit for creating AI-based surrogate models of scientific code. AI-based surrogate models are widely used for creating fast and inverse simulations. PHASM anticipates an additional future use case: adapting legacy code to modern hardware. While data centers are investing in heterogeneous hardware such as GPUs and FPGAs, many established scientific codebases remain unable to take advantage of the hardware’s higher parallelism without undergoing a costly rewrite. An alternative is to train a AI-based surrogate model to mimic computationally intensive functions in the code, and run the surrogate instead. PHASM formalizes a development lifecycle for such surrogate models, including discovering functions amenable to replacement with a surrogate model, predicting the resulting performance, identifying the function’s space of inputs and outputs, binding the model to the code, and managing model versions. A suite of software tools for facilitating these steps was written and validated against a set of model problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

ORNL Contributions to the ENDF/B-VIII.1 Library [Slides]

For uranium and plutonium isotopes, evaluation work is converging to a stable configuration with an overall satisfactory benchmark performance (more information on the validation tests after CSEWG). Strontium evaluation was included in the repository library and successfully tested by processing codes relative to an alternative quantification of the external function. Cerium covariance matrices were updated to address review comments on the magnitude of the uncertainty. For future uncertainty quantification, theoretical observables should be properly decoupled from current measured guidelines. Tests to correctly include LP (from resonance parameters) fitted to measured energy-averaged data are in progress. Current ENDF files contains experimental LP data.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Radial drift of plasma blobs in a toroidal magnetic field with fully kinetic and reduced fluid models

In curved magnetic geometries, field-aligned regions of enhanced plasma pressure and density, termed ‘blobs,’ move as coherent filaments across the magnetic field lines. Coherent blobs account for a significant fraction of transport at the edges of magnetic fusion experiments and arise in naturally-occurring space plasmas. This work examines the dynamics of blobs with a fully kinetic electromagnetic particle-in-cell code and with a drift-reduced fluid code. In low-beta regimes with moderate blob speeds, good agreement is found in the maximum blob velocity between the two simulation schemes and simple analytical estimates. The fully kinetic code demonstrates that blob speeds saturate near the initial sound speed, which is a regime outside the validity of the reduced fluid model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Sensitivity Analysis of Irradiated Fueled Experiments using the MOOSE Framework [Slides]

Modeling and simulation (M&S) methods are able to predict uncertainties in experimental parameters (e.g., power and fission density) during irradiation. A shortfall exists in predicting how sensitive some of the parameters will behave during the experimental process. Sensitivity and Uncertainty Quantification (SUQ) is critical in support of qualification and licensing reactor fuels. The application of a method to quantify the uncertainty in these experiments is critical to the prediction of their performance. In this work, we propose the use of a polynomial chaos expansion (PCE) method to quantify the sensitive parameters in these simulations and, in an extension, their experimental surrogates. We propose to perform M&S using PCE uncertainty quantification on a previously irradiated fueled experiment in order to provide a validation case for Griffin and expand its use as a verification and validation (V&V) tool for experiments with a neutronics component. Griffin is an advanced, deterministic neutronics analysis code built using the MOOSE (multiphysics object-oriented simulation environment) framework which can provide state-of-the-art neutronic analysis on M&S of experiments. We will use the stochastic tools module (STM) in MOOSE to provide PCE uncertainty quantification on the proposed experimental setup. Idaho National Laboratory (INL) does not yet have an in-house developed code with V&V approval for experiments performed on-site; this work would provide a necessary addition of support for experiments performed at INL. The Nuclear Regulatory Commission (NRC) has explicitly requested uncertainties in calculated values such as fuel power and burnup, and the development of this capability would benefit the relationship between INL and the NRC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Design and Validation of a Gammaray Scanning System for Measuring Irradiated Nuclear Fuel

A prototype gamma-ray scanning system was designed to perform post-irradiation measurements of nuclear fuel at Idaho National Laboratory (INL). The system is composed of a coaxial high-purity germanium (HPGe) detector, a collimator, and mechanical positioning stages that translate the fuel sample across the front of the collimator. This paper documents the design process, modeling and the laboratory characterization performed to validate the system. The modeling of the system was done using the Monte Carlo N-Particle code with vendor-supplied design specifications, dimensional measurements, and x-ray radiographs of the HPGe detector. The characterization included measurements of calibrated radiation sources in different geometries, and calculations for absolute efficiency and dead time. Benchmark measurements were performed by scanning an irradiated fuel rodlet containing ten pellets of 4.9% enriched UO2 in zirconium alloy. These results were compared to simulated spectra to further help characterize the detector model. One goal of the system is to determine the number of fissions per gram of UO2 in the fuel; comparison of the results from this prototype system's assay of the irradiated fuel rodlet are in agreement with previously estimated results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

DESIGN AND VALIDATION OF A GAMMA-RAY SCANNING SYSTEM FOR MEASURING IRRADIATED NUCLEAR FUEL (ABSTRACT)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Benchmarking MELCOR's NAC Package to ABCOVE Test AB7

This report presents analyses of the AB7 ABCOVE sodium spray fire experiment with the MELCOR code. This code simulates the progression of accident events for analysis and auditing purposes of nuclear facilities during accident conditions. Historically, the ABCOVE experiments have contributed to the validation of aerosol physics and related phenomena. Given advancements in sodium-cooled reactor designs, characterization of the sodium spray combustion may further the review and validation of newly incorporated sodium properties and physics packages, namely, the sodium equations of state (EOS) and the sodium combustion (NAC) package within MELCOR. Previously, the AB5 and AB6 experiments were analyzed with and without the NAC package. This work builds on the previous analyses with a demonstration of the current code capabilities of MELCOR with a more mild Na spray and pool fire scenario.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Comparison of spatial dynamics and point kinetics approaches in multiphysics modeling of the molten salt reactor experiment

In this work, we present validation test results of fully coupled neutronics and thermal-hydraulics models of the Molten Salt Reactor Experiment (MSRE) against experimental data of the zero power pump transients and the natural circulation tests at low power. To capture the strong coupling between neutronics and thermal-hydraulics due to fuel circulation, and to account for the delayed neutron precursor (DNP) distribution, the porous media thermal-hydraulics solver Pronghorn was fully coupled to the spatial neutron dynamics code Griffin, which solves the neutron diffusion equation, and to the 0-D point kinetics solver Squirrel, using a 2-D homogenized representation of the MSRE. The validation test results show very good agreement with experimental data for both point kinetics and spatial dynamics simulations, capturing the strong feedback effect and DNP losses in the MSRE. The 0-D code Squirrel accurately predicted the time-dependent behavior in the MSRE given the steady-state spatial dynamics solution of Griffin.

42 - ENGINEERING↗

DOE OSTI2022

Development of a high fidelity model of the CROCUS experimental reactor

Measurements of scalar flux distributions with fine spatial and energy resolutions are needed to remedy one of the validation shortcomings of the novel neutronics full core solvers, such as MPACT and nTRACER. While a very detailed resolution of the flux can be calculated with such codes, only a limited experimental data set is available to check their accuracy. Such type of measurements are on-going at the zero power reactor CROCUS, operated at the Laboratory for Reactor Physics and System Behaviours of the EPFL, thanks to the development of advanced miniature neutron detection systems. This kind of experimental data would provide the community with a suitable benchmark for the validation of high fidelity neutronics solvers. In parallel, a multi-physics solver for steady-state and transient analysis of nuclear reactors, named GeN-Foam, has been developed. Based on the finite-volume OpenFOAM library, GeN-Foam provides us with enough flexibility to analyze non-conventional reactor geometries such as that of CROCUS. While CROCUS heterogeneities cannot be modeled by MPACT and nTRACER for the moment, GeN-Foam offers a unique opportunity to build a high fidelity model which mimics these codes' method to reach sub-pin simulation resolution. This document aims at describing the work achieved to get from the existing GeN-Foam model of the CROCUS reactor based on a structured mesh and using the neutron diffusion, the first high-fidelity model using discrete ordinates method as an approximation to neutron transport and an unstructured mesh for inter lattice water gap description and sub-pin heterogeneous modeling. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

MARVEL 90% Final Design Report

This document provides documentation of the Microreactor Applications Research Validation and Evaluation Project’s (MARVEL) 90% Final Design, as required by U.S. Department of Energy (DOE) Standard-1189, “Integration of Safety into the Design Process." Per DOE-STD-1189-2016, the 90% Final Design documentation focuses on design completion, at a level capable of supporting procurement, construction, testing, and operation. At this phase, the design organization finalizes the hazards and accident analyses, Fire Hazard Analysis (FHA), security vulnerability assessments, and other supporting analyses for design completion. The objective of this report is to provide a high-level summary of the design thus far and provide references including, but not limited to, the following design deliverables: • Complete final drawings, specifications and commercial grade dedications that may be released for bid and/or construction. • Clearly defined testing plans for the safety and functionality of all subsystems. • Quality Assurance Program for Design, Testing and Procurement. • Software Quality Assurance Plan. • Code of Record (COR), applicable design requirements including codes and standards. • Final design that meets all the requirements stipulated in the COR. • Final design review, consisting of final validation of comment resolution from previous reviews, and a review of any additional developments since the last review. • Updated Safety Design Strategy. • Hazard Analysis. • Fire Hazard Analysis. • Accident analysis. • Security vulnerability assessment. • Current and detailed cost estimate. • Current construction schedule, and • Risk & Opportunities Assessment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗