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Results for “Nuclear Data Evaluation Methods”

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

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Redox chemistry of plutonium and plutonium surrogates in vitrified nuclear wastes

Lanthanide borosilicate glasses containing Pu and the analog element, Ce, were subjects of an X-ray absorption spectroscopy investigation to quantify the +3/+4 ratio of the redox-sensitive element. The data show that the dominant oxidation states are +4 for Pu and +3 for Ce. The data also indicate that the reductive potential of glasses can be quantified, although allowances must be made for glass composition, from a solution chemistry method adapted to glass chemistry. These data can therefore be used to formulate glass compositions and processing schedules that lead to knowledge of the oxidation state of Pu in melts. Furthermore, the data show that Ce is a poor analog for Pu behavior in melt and that the suitability of surrogates can be evaluated by this method. The methods demonstrated in this paper can be used to estimate the oxidation states of a range of multi-valent elements as functions of temperature and composition with data from only a single redox couple.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2016

Poster - 18: New features in EGSnrc for photon cross sections

Purpose: To implement two new features in the EGSnrc Monte Carlo system. The first is an option to account for photonuclear attenuation, which can contribute a few percent to the total cross section at the higher end of the energy range of interest to medical physics. The second is an option to use exact NIST XCOM photon cross sections. Methods: For the first feature, the photonuclear total cross sections are generated from the IAEA evaluated data. In the current, first-order implementation, after a photonuclear event, there is no energy deposition or secondary particle generation. The implementation is validated against deterministic calculations and experimental measurements of transmission signals. For the second feature, before this work, if the user explicitly requested XCOM photon cross sections, EGSnrc still used its own internal incoherent scattering cross sections. These differ by up to 2% from XCOM data between 30 keV and 40 MeV. After this work, exact XCOM incoherent scattering cross sections are an available option. Minor interpolation artifacts in pair and triplet XCOM cross sections are also addressed. The default for photon cross section in EGSnrc is XCOM except for the new incoherent scattering cross sections, which have to be explicitly requested. The photonuclear, incoherent, pair and triplet data from this work are available for elements and compounds for photon energies from 1 keV to 100 GeV. Results: Both features are implemented and validated in EGSnrc.Conclusions: The two features are part of the standard EGSnrc distribution as of version 4.2.3.2.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Constraining Hamiltonians from chiral effective field theory with neutron-star data

Multi-messenger observations of neutron stars (NSs) and their mergers have placed strong constraints on the dense-matter equation of state (EOS). The EOS, in turn, depends on microscopic nuclear interactions that are described by nuclear Hamiltonians. These Hamiltonians are commonly derived within chiral effective field theory (EFT). Ideally, multi-messenger observations of NSs could be used to directly inform our understanding of EFT interactions, but such a direct inference necessitates millions of model evaluations. This is computationally prohibitive because each evaluation requires us to calculate the EOS from a Hamiltonian by solving the quantum many-body problem with methods such as auxiliary-field diffusion Monte Carlo (AFDMC), which provides very accurate and precise solutions but at a significant computational cost. Additionally, we need to solve the stellar structure equations for each EOS which further slows down each model evaluation by a few seconds. In this work, we combine emulators for AFDMC calculations of neutron matter, built using parametric matrix models, and for the stellar structure equations, built using multilayer perceptron neural networks, with the PyCBC data-analysis framework to enable a direct inference of coupling constants in an EFT Hamiltonian using multi-messenger observations of NSs. We find that astrophysical data can provide informative constraints on two-nucleon couplings despite the high densities probed in NS interiors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

3-D Radiological Data Acquisition, Visualization and Modeling - 20211

The U.S. Army Corps of Engineers (USACE) was tasked to investigate and remediate low activity radiological contamination from research and production of the nation's first nuclear weapons at the former DuPont Chambers Works Formerly Utilized Sites Remedial Action Program (FUSRAP) site (DuPont). The DuPont site had several buildings used for the Manhattan project that were demolished in the 1940's and 1950's apparently using heavy earthmoving equipment. Some of the contaminated rubble from the demolition appears to have been spread out by this equipment resulting in somewhat random scattering of radiologically contaminated soil and debris along with aqueous spills. Traditional investigative methods such as soil borings, test pits and 2-dimensional gamma walkovers were only partially successful in delineating the radiological contamination at the site. It was feared that even 'chasing' the contamination during remediation would miss contamination if the demolition resulted in discontinuous trails of radiologically contaminated soils. In evaluating the data generated over the interceding decades, the USACE determined that a better method to collect and process the remedial action radiological data was needed to enable the project team to optimize predictive planning and meet documentation expectations. The purpose of this paper is to provide an overview of the effort and progress to combine and organize radiological survey methods into a highly flexible sampling, modeling, and decision analysis approach that emphasizes the quality of decision-making during remediation. This innovative system blends multiple tools to develop a methodology that can extend MARRSIM [1] into the subsurface and provide tools that can be applied to other sites. (authors)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Studies of NMR, molecular docking, and molecular dynamics simulation of new promising inhibitors of cruzaine from the parasite Trypanosoma cruzi

Cruzaine is the major cysteine protease of Trypanosoma cruzi. Cruzaine is involved throughout the parasite’s life cycle in host cells, and is a promising target in the search for new antichagasic agents. Quantum chemical calculations based on density functional theory (DFT B3LYP/cc-pVDZ) were performed to obtain nuclear magnetic resonance data and to optimize the geometry of four dihydrochalcones. The results showed good agreement with the experimental data and were used to suggest the relative stereochemistry of one of the four dihydrochalcones studied. In addition, we evaluated the interaction of cruzaine with these new inhibitors. We used molecular dynamics simulations, free energy calculations, and a per-residue energy decomposition method. It was observed that these molecules are capable of interacting with residues important for enzymatic activity, like Cys25, His161, and Asp160. The ranking of the inhibitors obtained from the binding free energy calculations is in agreement with that experimentally reported. The evaluation of the energy components involved in these calculations demonstrated that the van der Waals term is the major contributor to the drug–receptor stabilizing interactions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Uncertainties in secondary angular distributions and their impact on shielding, criticality and kinetics analysis - 25556

The availability of the covariance data improved over the last decades. Use of covariance matrices of different origin (such as JEFF, JENDL, ENDF, TENDL, SCALE, etc.) and types (files MF31, MF33, MF34, MF35) in sensitivity and uncertainty analysis of vast list of cases ranging from fission to fusion and from criticality, kinetics and shielding to adjustment applications was already studied in the past. The present work focuses on the status and the availability of the covariance of the angular distributions of scattered neutrons (secondary angular distributions - SAD covariances). SAD uncertainties are usually neglected in classical uncertainty propagation codes, even though the methods and codes for calculating the sensitivities are available for decades and excellent agreement was demonstrated between different deterministic and Monte Carlo codes. Of particular concern is still the availability, quality and completeness of covariance matrices. Indeed, in most evaluations the SAD covariances are limited to P1 term, if available at all. Furthermore, some differences were observed between different evaluations, e.g. in the case of iron. (author)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

MPACT Verification and Validation Manual (rev 1)

The MPACT code provides the capability to calculate the steady-state and transient reactor core neutron distribution for operating nuclear power plant (PWR) conditions across multiple fuel cycles. As required in the CASL SQA plan, it is the responsibility of UM and ORNL as joint owners of MPACT to ensure that verification and validation activities are performed and documented in a V&V manual with supporting publications and CASL technical reports which can be distributed for reference and distribution within VERA. This document provides the first revision of the MPACT verification and validation (V&V) manual and describes the current state of MPACT V&V and updates the framework for future MPACT V&V activities. During FY16, MPACT V&V activities in the areas of code verification have continued to mature and work has progressed on code error evaluation using the Method of Manufactured Solutions (MMS). Several specific tasks have also been completed to improve MPACT code verification to include tasks to improve the unit and regression test coverage. A joint UM/ORNL task was completed to develop standardize coding standards and workflow for the continued collaborative development of MPACT. During the past year, MPACT validation work has continued in both the areas of measured data from critical experiments as well as measured data from operating nuclear power plants. Preliminary work was also performed in FY16 on the use of post-irradiation examinations for evaluation and validation of the isotopic depletion capability in MPACT. Based on the results of V&V efforts this past year, the confidence level has increased in the ability of MPACT to model an operational Pressurized Water Reactor. Areas were identified which require increased emphasis during FY17 to include updating all the V&V problems with the new 51-group library, the completion of cycle 2 of the BEAVRS benchmark, initial validation for BWR applications, the addition of Uncertainty Quantification results into the benchmark results, and the completion of specific validation tasks for the CASL Challenge problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Sensitivity-based Experiment Design Optimization for a Molybdenum Critical Experiment

A lack of intermediate molybdenum benchmarks in the ICSBEP has been identified by LANL, Y-12, and IRSN. This lacking adversely effects criticality safety operations and leaves new differential molybdenum data unvalidated. NCERC is proposing a series of intermediate integral experiments to better the understanding of molybdenum systems. Using MCNP6.2 with the ENDF/B-VIII.0 nuclear data library a single unmoderated and four moderated system designs were identified using a sensitivity optimization method. Each proposed system was found to be at least twice as sensitive to the 95 Mo capture cross section in the URR as the sole existing intermediate molybdenum benchmark in the ISCBEP handbook. The addition of a new molybdenum sensitive intermediate system would improve future nuclear data evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Quantitative resilience evaluation on recovery from emergency situations in nuclear power plants

Here, this paper mainly introduces how to develop a resilience evaluation model by quantifying the relationship between resilience and resilience components in regard to recovering from emergency situations in nuclear power plants (NPPs). It is an extension of the author’s previous researches. To develop the model, the first step was to analyze event reports published in Republic of Korea in terms of resilience factors from different safety perspectives. Second, statistical methods such as factor analysis, principal component analysis, and multivariate regression analysis were applied to the dataset to identify relations among resilience factors and develop a quantitative resilience evaluation model for recovery from emergency situations in NPPs. Third, the model was validated using the recent event report data released in Korea. Lastly, we present a discussion on how to apply the quantitative resilience evaluation model to results from stress tests performed in Korea.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

NCSP Analytical Methods Subtask 3, AMPX Development and Maintenance, and NCSP Nuclear Data Subtask 6, SAMMY Modernization

SAMMY 1 is a production code that still contains a lot of old-style FORTRAN (F77) code. While the code is widely used and performs well, the legacy code base makes it difficult to maintain and to add new features. However, because it is a production code, it cannot lose any functionality while being modernized. In addition, new features need to be added to support the changing needs of the evaluators to analyze data obtained with new equipment and at higher resolution. In addition, as the data are analyzed with higher fidelity and new models within SAMMY, the processing codes and formats must keep pace. This will ensure that any new SAMMY evaluation can be processed by AMPX and can be tested and used in transport codes like SCALE 2 for maximum benefit of the Nuclear Criticality Safety Program (NCSP) mission.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Improving Spectral Image Classification through a Custom Data Sparsing and Pixel Clustering Algorithm

The Underground Nuclear Explosion Signatures Experiment (UNESE) seeks to characterize non-prompt observables from underground nuclear explosions (UNE). As part of this effort, we evaluated the ability of Digital Globe’s World View-3 (WV3) to detect and map UNE signatures. WV3 has proven capabilities in the detection of large-scale, anomalous, man-made features; however, it has relatively limited spectral and spatial resolution as compared to airborne hyperspectral imaging. These limitations impede standard image classifiers from identifying UNE signatures that are spatially small and lack distinct spectral features. In order to improve image classification results, we developed a custom algorithm that increases the true positive rate, while decreasing the false positive rate. Our algorithm’s flexible front-end allows the user to choose the method used to sparse the data. These methods include band-ratio optimization, correlation coefficient threshold, or Adaptive Coherence Estimator (ACE) threshold. The resulting sparsed pixels are clustered into like-objects. A novel weighted-sum of ACE and correlation coefficient scores is used to classify each object based on the average spectrum of its constituent pixels. WV3 and AVIRIS data of Cuprite, Nevada were used as a verification data set. This algorithm improves overall pixel classification accuracy over standard classifiers by up to 14%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Aided Active Learning (AAL) for Enhanced Critical Heat Flux Prediction

Accurate prediction of critical heat flux (CHF) is crucial for the safe and efficient operation of nuclear reactors. Traditional CHF modeling methods often require extensive experimental data, which are hard to obtain. This study introduces the Aided Active Learning (AAL) framework, which strategically minimizes data requirements without sacrificing model accuracy. Unlike conventional Active Learning (AL), AAL introduces an additional step of randomly selecting a subset from the sample pool before applying the query strategy. To evaluate the performance of AAL, two query strategies—uncertainty-based sampling and error-reduction sampling—were evaluated across the following models: random forest (RF), feedforward neural network (FNN), and variational feedforward neural network (vFNN). The proposed framework demonstrated that AAL effectively reduces the number of training samples needed to achieve comparable predictive accuracy. For the RF model, AL required only 710 samples to achieve an R2 score of 0.98, as compared to the 4,785 samples needed by random sampling. Similarly, the FNN model achieved the same R2 score with just 355 samples when using AL, a significant improvement over the 825 samples required by random sampling. In case of uncertainty-based sampling strategy, vFNN attained an R2 of 0.98 with 3,420 samples, reducing the sample requirement by 47% relative to the 6,440 samples needed for random sampling. Its performance suggests that larger training data are required to fully leverage its uncertainty quantification capabilities.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Improving nuclear data evaluations with predictive reaction theory and indirect measurements

Nuclear reaction data required for astrophysics and applications is incomplete, as not all nuclear reactions can be measured or reliably predicted. Neutron-induced reactions involving unstable targets are particularly challenging, but often critical for simulations. In response to this need, indirect approaches, such as the surrogate reaction method, have been developed. Nuclear theory is key to extract reliable cross sections from such indirect measurements. We describe ongoing efforts to expand the theoretical capabilities that enable surrogate reaction measurements. We focus on microscopic predictions for charged-particle inelastic scattering, uncertainty-quantified optical nucleon-nucleus models, and neural-network enhanced parameter inference.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Applying Waveform Correlation to Mining Blasts Using a Global Sparse Network

Agencies that monitor for underground nuclear tests are interested in techniques that automatically characterize mining blasts to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is effective in finding similar waveforms from repeating seismic events, including mining blasts. We report the results of an experiment that uses waveform templates recorded by multiple International Monitoring System stations of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization for up to 10 years prior to the time period of interest to detect and identify mining blasts that occur during single weeks of study. We discuss approaches for template selection, threshold setting, and event detection that are specialized for mining blasts and a sparse, global network. We apply the approaches to two different weeks of study for each of two geographic regions, Wyoming and Scandinavia, to evaluate the potential for establishing a set of standards for waveform correlation processing of mining blasts that can be effective for operational monitoring systems with a sparse network. We compare candidate events detected with our processing methods to the Reviewed Event Bulletin of the International Data Centre to develop an intuition about potential reduction in analyst workload.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Weighted active space protocol for multireference machine-learned potentials

Multireference methods such as multiconfiguration pair-density functional theory accurately capture electronic correlation in systems with strong multiconfigurational character, but their cost precludes direct use in molecular dynamics. Combining these methods with machine-learned interatomic potentials (MLPs) can extend their reach. However, the sensitivity of multireference calculations to the choice of the active space complicates the consistent evaluation of energies and gradients across structurally diverse nuclear configurations. To overcome this limitation, we introduce the weighted active space protocol (WASP), a systematic approach to assign a consistent active space for a given system across uncorrelated configurations. By integrating WASP with MLPs and enhanced sampling techniques, we propose a data-efficient active learning cycle that enables the training of an MLP on multireference data. We demonstrated the approach on the TiC + -catalyzed C–H activation of methane, a reaction that poses challenges for Kohn–Sham density functional theory due to its significant multireference character. This framework enables accurate and efficient modeling of catalytic dynamics, establishing a paradigm for simulating complex reactive processes beyond the limits of conventional electronic-structure methods.

enhanced sampling↗
DOE OSTI2017

Software Quality Assurance for LeachXS/ORCHESTRA as a Tool for Assessment of Waste Management Systems Performance - 17486

Qualified modeling and simulation tools and experimental data are needed to provide a reasonable basis for the incorporation of realistic wasteform retention assumptions (i.e., those without orders-of-magnitude conservatism) into performance assessments and regulatory decisions. Use of highly conservative assumptions in performance assessments has historically led to the overprediction of release and near-field transport by as much as 4- to 6-orders of magnitude thereby limiting the nature and quantities of certain contaminants of concern in near surface disposal facilities. This project provides peer-reviewed models and characterization methods to provide more reasonable assumptions for use in performance assessments and regulatory decisions. Simulations tools have been developed to predict hydraulic and chemical performance of waste-forms and barriers used in nuclear applications under several important aging and degradation scenarios, including sulfate attack, carbonation, oxidation, cracking, and leaching; these tools are complaint with DOE Order 414.1D and ASME NQA-1. Wasteform characterization methods have been developed that are consistent with US EPA's Leaching Environmental Assessment Framework (LEAF) currently part of EPA's Hazardous Waste Test Methods (SW-846); the resulting experimental data are evaluated using LeachXS. ORCHESTRA models, that can be called seamlessly from LeachXS, have been developed representing both laboratory and field conditions; these models have undergone an extensive Software Quality Assurance process where they have been calibrated (where necessary), verified, and validated to be compliant with relevant guidelines. The models used for field predictions have also been incorporated into the Cementitious Barriers Partnership (CBP) Software Toolbox that allows probabilistic evaluation of field scenarios. The foci over the next year will be on providing 1) a mechanistic basis for projecting the retention of Tc-99, I-129, and other important radionuclides in near-surface disposal facilities at the Savannah River and Hanford Sites and 2) a technical basis for assessing the efficacy of macro-encapsulation of mercury-contaminated debris at the Oak Ridge Reservation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Uncertainty quantification in (α,n) neutron source calculations for an oxide matrix

Here we present a methodology to propagate nuclear data covariance information in neutron source calculations from (α,n) reactions. The approach is applied to estimate the uncertainty in the neutron generation rates for uranium oxide fuel types due to uncertainties on 1) 17,18 O( α,n) reaction cross sections and 2) uranium and oxygen stopping power cross sections. The procedure to generate reaction cross section covariance information is based on the Bayesian fitting method implemented in the R-matrix SAMMY code. The evaluation methodology uses the Reich-Moore approximation to fit the 17,18 O(α,n) reaction cross-sections in order to derive a set of resonance parameters and a related covariance matrix that is then used to calculate the energydependent cross section covariance matrix. The stopping power cross sections and related covariance information for uranium and oxygen were obtained by the fit of stopping power data in the -energy range of 1 keV up to 12 MeV. Cross section perturbation factors based on the covariance information relative to the evaluated 17,18 O( α,n) reaction cross sections, as well as uranium and oxygen stopping power cross sections, were used to generate a varied set of nuclear data libraries used in SOURCES4C and ORIGEN for inventory and source term calculations. The set of randomly perturbed output (α,n) source responses, provide the mean values and standard deviations of the calculated responses reflecting the uncertainties in nuclear data used in the calculations. Lastly, the results and related uncertainties are compared with experiment thick target (α,n) yields for uranium oxide.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗