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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluating Safeguards Statistical Assumptions via Stochastic Simulation

Herein, the authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 SQ, using typical IAEA inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Assessing the Impact of Effective Thermal Conductivity on Gas-cooled Reactor Transients in RELAP5-3D

In block-type high-temperature gas-cooled reactors (HTGRs), coolant holes in blocks lead to a reduction in heat transfer through conduction. In systems codes like RELAP5-3D, we must account for this degradation by using an effective thermal conductivity (ETC). This presentation discusses a few ETC relationships and demonstrates the impact of ETC for the modular High-Temperature Gas-Cooled Reactor 350 MW -- a computational benchmark for HTGR modeling -- and for the High Temperature Test Facility (HTTF) -- an HTGR thermal hydraulics test facility. We demonstrate that the use of ETC leads to temperatures that are higher than the bulk thermal conductivity of the block material would yield, but these differences have no meaningful impact on the transient performance of the reactors. The ETC also reduces the cooldown rate, leading to more time at elevated temperatures. Overall, while accounting for ETC is important in capturing the physics of the reactor, it is not expected to have a meaningful impact on transient performance.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

The authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 significant quantities (SQ), using typical International Atomic Energy Agency (IAEA) inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5 gamma spectrometer. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NASA NTRS2017

Benchmarking the Collocation Stand-Alone Library and Toolkit (CSALT)

This paper describes the processes and results of Verification and Validation (VV) efforts for the Collocation Stand Alone Library and Toolkit (CSALT). We describe the test program and environments, the tools used for independent test data, and comparison results. The VV effort employs classical problems with known analytic solutions, solutions from other available software tools, and comparisons to benchmarking data available in the public literature. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results for a broad range of problems, and detailed comparisons for selected problems.

trajectory optimization↗
NASA NTRSDate not supplied

Verification Test Suite for Spalart-Allmaras QCR2000 Turbulence Model

The paper presents three benchmark cases for verification of Reynolds-averaged Navier-Stokes solvers. The verification studies focus on a one-equation Spalart-Allmaras model, SA-[neg]-QCR2000, that uses a version of quadratic constitutive relations.The benchmark cases are a two-dimensional subsonic flow around a Joukowski airfoil, a three-dimensional supersonic flow through a square duct, and a three-dimensional flow over a wing-fuselage configuration. The turbulence-model formulation, geometry, flow conditions, grids, and the expected output are described in detail. Reference solutions computed by several established codes are shown

Computational Aerodynamics↗
DOE OSTI2025

AGR 1 and 2 Isotopic Depletion Validation

This presentation includes work performed developing a computational benchmark for the AGR 1 and 2 experiments. These experiments involve irradiation of TRISO particle compact in the Advanced Test Reactor (ATR). Many post-irradiation measurements were made from these experiments, including isotopic concentrations of fission products. The benchmark involves a MCNP-ORIGEN coupled model of the ATR and AGR experiment capsules to calculate a comprehensive inventory of fission product and actinide concentrations in the compacts. This presentation describes the experiments, the measurements obtained, the benchmark model, and results of the model evaluation.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS1998

Improved Modeling of Finite-Rate Turbulent Combustion Processes in Research Combustors

The objective of this thesis is to further develop and test a stochastic model of turbulent combustion in recirculating flows. There is a requirement to increase the accuracy of multi-dimensional combustion predictions. As turbulence affects reaction rates, this interaction must be more accurately evaluated. In this work a more physically correct way of handling the interaction of turbulence on combustion is further developed and tested. As turbulence involves randomness, stochastic modeling is used. Averaged values such as temperature and species concentration are found by integrating the probability density function (pdf) over the range of the scalar. The model in this work does not assume the pdf type, but solves for the evolution of the pdf using the Monte Carlo solution technique. The model is further developed by including a more robust reaction solver, by using accurate thermodynamics and by more accurate transport elements. The stochastic method is used with Semi-Implicit Method for Pressure-Linked Equations. The SIMPLE method is used to solve for velocity, pressure, turbulent kinetic energy and dissipation. The pdf solver solves for temperature and species concentration. Thus, the method is partially familiar to combustor engineers. The method is compared to benchmark experimental data and baseline calculations. The baseline method was tested on isothermal flows, evaporating sprays and combusting sprays. Pdf and baseline predictions were performed for three diffusion flames and one premixed flame. The pdf method predicted lower combustion rates than the baseline method in agreement with the data, except for the premixed flame. The baseline and stochastic predictions bounded the experimental data for the premixed flame. The use of a continuous mixing model or relax to mean mixing model had little effect on the prediction of average temperature. Two grids were used in a hydrogen diffusion flame simulation. Grid density did not effect the predictions except for peak temperature and tangential velocity. The hybrid pdf method did take longer and required more memory, but has a theoretical basis to extend to many reaction steps which cannot be said of current turbulent combustion models.

VanOverbeke, Thomas J.↗
NASA NTRS2017

Benchmarking the Collocation Stand-Alone Library and Toolkit (CSALT)

This paper describes the processes and results of Verification and Validation (V&V) efforts for the Collocation Stand Alone Library and Toolkit (CSALT). We describe the test program and environments, the tools used for independent test data, and comparison results. The V&V effort employs classical problems with known analytic solutions, solutions from other available software tools, and comparisons to benchmarking data available in the public literature. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results for a broad range of problems, and detailed comparisons for selected problems.

optimal control↗
DOE OSTI2021

Sensitivity and Uncertainty of the IFR-1 BISON Benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This report summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment. For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. The resulting variations in benchmark predictions were normalized to calculate sensitivities. The strongest sensitivities were identified and used to inform input selections for the UQ. The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because of the wide confidence intervals associated with the benchmark predictions. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark development and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

An uncertainty quantification method relevant to material test reactors

Within material test reactor calculations, energy dependent flux and reaction rate uncertainties are typically not quantified when performing as-run analyses to determine the neutron field experienced by the experiment. When high fidelity Monte-Carlo codes are used in such analyses, straight forward methods to calculate output uncertainties are not available, instead expert opinion is used to postulate computational uncertainties. New methods to propagate uncertainties through these high fidelity simulations are available when sufficient computational power is available. A tool is developed here for sampling any part of an MCNP input from random distributions to determine output uncertainties based on those inputs. Another tool is developed to sample nuclear data cross-section in ACE format using multi-group nuclear data covariances. The Total Monte-Carlo Method and Gesellschaft für Anlagen-und Reaktorsicherheit method (GRS) are implemented and compared to one another as well as MCNP sensitivity and uncertainty calculations. The methods were applied to the Godiva critical sphere k-eigenvalue, the UAM pin-cell benchmark energy dependent flux and reaction rates, and the Advanced Test Reactor energy dependent flux within an experimental location. Furthermore, the two methods agree well, with GRS allowing for an order of magnitude speedup for reaction rate uncertainty calculations and several orders of magnitude for eigenvalue uncertainty calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1993

Creep-Rupture Strength of a Ni-Base Superalloy at 1400 K

While NASAIR 100 is not the strongest of elevated-temperature single-crystal alloys, its higher-temperature properties are indicative of this technology's behavior. Attention is presently given to test results for this alloy which illuminate its 1400 K creep failure properties in air, and furnish a benchmark for the comparison of advanced materials to existing technology. The creep rupture behavior resembles that found after 1273 K testing, and is indicative of gamma-prime strengthening.

Whittenberger, J. D.↗
DOE OSTI2022

Sensitivity and uncertainty of the IFR-1 BISON benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered for adoption by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This paper summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment.For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. Here, the resulting variations in benchmark predictions were normalized to calculate sensitivities. These sensitivities were then used to inform input selections for the UQ.The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of the benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because the confidence intervals associated with benchmark predictions were wide. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

ATF Cladding Mechanical Properties Report: Capability Demonstration

This report documents mechanical testing capability demonstration activities performed in fiscal year (FY)2025 at Oak Ridge National Laboratory(ORNL)on chromium-coated (Cr-coated) and uncoated advanced zirconium alloy claddings irradiated in the High Flux Isotope Reactor (HFIR) to approximately 4 displacements per atom (dpa), corresponding to ~13GWd/t burnup. Specimens were prepared in axial tension (ATT) and ring tension (RTT) geometries, and passive silicon carbide(SiC)thermometry (TM) was employed to determine irradiation temperatures, which averaged 38–43 °C below the 330 °C design target. Mechanical testing at ambient temperature demonstrated the expected irradiation-induced hardening, with yield strength(YS)and ultimate tensile strength(UTS)values increasing substantially relative to unirradiated counterparts. However, this strengthening was accompanied by a reduction in ductility, as indicated by lower uniform and total elongations(UE and TE). Both coated and uncoated claddings exhibited similar mechanical response, though Cr-coated specimens showed surface cracking perpendicular to the loading direction, attributable to the hardness mismatch between the coating and substrate. Fracture in all cases remained ductile, and no coating spallation was observed following HFIR irradiation. Complementary efforts were directed toward the fabrication of test specimens from commercially irradiated cladding (rod 47I, ~31.1 GWd/t average burnup). Axial sectioning and computer numerical control(CNC)machining successfully produced ATT geometries suitable for benchmarking against HFIR-irradiated specimens. This capability enables direct comparison of cladding behavior between test reactor and commercial reactor environments, thereby supporting the validation of HFIR as a surrogate irradiation platform for accident tolerant fuel (ATF) development. Once HFIR irradiations are completed in FY26,the relevant comparison tests will be completed. Collectively, the FY 2025 PIE campaign has provided mechanical performance data for irradiated advanced claddings The demonstrated capabilities support the framework for mechanical testing and further evaluations in subsequent years. These efforts will represent an important contribution toward the licensing and deployment of Cr-coated zirconium alloy cladding as a near-term ATF solution.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗
NASA NTRS2006

Local Neutral Density and Plasma Parameter Measurements in a Hollow Cathode Plume

In order to understand the cathode and keeper wear observed during the Extended Life Test (ELT) of the DS1 flight spare NSTAR thruster and provide benchmarking data for a 2D cathode/cathode-plume model, a basic understanding of the plasma and neutral gas parameters in the cathode orifice and keeper region of the cathode plume must be obtained. The JPL cathode facility is instrumented with an array of Langmuir probe diagnostics along with an optical diagnostic to measure line intensity of xenon neutrals. In order to make direct comparisons with the present model, a flat plate anode arrangement was installed for these tests. Neutral density is deduced from the scanning probe data of the plasma parameters and the measured xenon line intensity in the optical regime. The Langmuir probes are scanned both axially, out to 7.0 cm downstream of the keeper, and radially to obtain 2D profile of the plasma parameters. The optical fiber is housed in a collimating stainless steel tube, and is scanned to view across the cathode plume along cuts in front of the keeper with a resolution of 1.5 mm. The radial intensities are unfolded using the Abel inversion technique that produces radial profiles of local neutral density. In this paper, detailed measurements of the plasma parameters and the local neutral densities will be presented in the cathode/keeper plume region for a 1.5 cm diameter NEXIS cathode at 25A of discharge current at several different strengths of applied magnetic field.

Plasma density↗
DOE OSTI2025

Detection of Isotopes in Urban Source Search Low-Count Gamma Spectra Using Hopfield Neural Networks

Source search campaigns involve measurements of background gamma-ray spectra with a mobile detector-spectrometer traveling along arbitrarily chosen trajectories over a wide screening area. Radiation counts are typically measured with a tellurium-doped sodium iodide [NaI(Tl)] scintillator detector-spectrometer in short acquisition intervals, usually 1 s. The objective is to detect orphan isotopes with half-lives shorter than those of the isotopes in the natural background. In principle, radioisotopes can be identified by their unique gamma emission spectrum. However, detecting orphan isotopes in search data is challenging because low counts measured in short acquisition intervals result in incomplete spectral lines. In this study, we investigate the performance of a Hopfield neural network (HNN) that implements an auto-associative memory for the detection of isotopes of interest in an urban search campaign. The HNN is trained on one example of gamma spectra with well-resolved spectral lines of each isotope of interest. During testing, the auto-associative memory implementation of the HNN processes low-count gamma spectra with partially complete isotopic lines by matching incoming measurements to the closest one of its memory-stored patterns. The testing database consisted of almost 10 000 1-s gamma spectra, including measurements of orphan isotopes 137 Cs, 241 Am, and 131 I, obtained during two urban search surveys with a NaI(Tl) detector. The performance of the HNN detection algorithm was evaluated using precision, recall, and F1 scores, and benchmarked with a multiple linear regression (MLR) identification algorithm. In conclusion, the test results demonstrate that HNN outperforms MLR in the detection of all the isotopes of interest.

Auto associative memory↗
NASA NTRS2013

Hybrid Wing Body Aircraft Acoustic Test Preparations and Facility Upgrades

NASA is investigating the potential of acoustic shielding as a means to reduce the noise footprint at airport communities. A subsonic transport aircraft and Langley's 14- by 22-foot Subsonic Wind Tunnel were chosen to test the proposed "low noise" technology. The present experiment studies the basic components of propulsion-airframe shielding in a representative flow regime. To this end, a 5.8-percent scale hybrid wing body model was built with dual state-of-the-art engine noise simulators. The results will provide benchmark shielding data and key hybrid wing body aircraft noise data. The test matrix for the experiment contains both aerodynamic and acoustic test configurations, broadband turbomachinery and hot jet engine noise simulators, and various airframe configurations which include landing gear, cruise and drooped wing leading edges, trailing edge elevons and vertical tail options. To aid in this study, two major facility upgrades have occurred. First, a propane delivery system has been installed to provide the acoustic characteristics with realistic temperature conditions for a hot gas engine; and second, a traversing microphone array and side towers have been added to gain full spectral and directivity noise characteristics.

Heath, Stephanie L.↗
DOE OSTI2022

A Strong-QCD Regime Measurement of the Proton’s Spin Structure

The theory of the strong force, Quantum Chromodynamics (QCD) remains one of the most important ways to understand the fundamental properties of ordinary matter. However, at low momentum transfer Q 2 , in the regime where the strong force becomes extremely strong, our understanding of QCD for ordinary nucleons becomes hazy. Several cutting edge theories such as Chiral Perturbation Theory (χPT) and Lattice QCD have provided valuable predictions in this regime, but Lattice QCD has not yet extended predictions of many important quantities to this kinematic region, and Chiral Perturbation Theory has faced several important disagreements with experimental data for the neutron over the last several decades. It is therefore of extreme importance to have a benchmark of experimental data in the low energy regime for the proton’s behavior, as a test of leading theories for the behavior of QCD in this regime. The E08-027 (g2p) experiment ran at Jefferson Lab in 2012 with the goal of collecting this valuable data, and though I was still completing my undergraduate studies at the time, I became involved in the analysis in 2015 and built on the previous work to complete it and analyze the exciting results. This experiment achieved a high precision measurement of the spin structure functions g1 and g2 for the proton, quantities which describe the internal spin structure of the proton. These measurements were taken in the valuable low Q 2 region described above, and used to extract several moments of these spin structure functions which can be directly compared to the cutting-edge predictions of Chiral Perturbation Theory. Though the experiment’s timeline was such that I didn’t have a chance to work directly on the experimental setup, I had the opportunity to acquire hands-on experience working on a polarized target at UNH which is very similar to the crucial polarized target used in the g2p experiment. Full details of the g2p experiment and my experimental work at the University of New Hampshire are presented in this thesis, as well as a detailed description of the analysis process and the exciting benchmark results, which serve as a direct test of all current and future theories of QCD in the low-Q 2 regime.

Ruth, David↗