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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Status of the CERBERUS Evaluation for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook

Modeling & Simulation (M&S) tools are used to analyze advanced reactor designs and the safety of current nuclear operations. As computers continue to improve, we are able to enhance resolution in our calculations. Therefore, the limitations of simulation capability are in the quality of data that is being used, including our ability to quantify the uncertainty and sensitivity of that data. In order to model systems of interest with increasing accuracy, the industry must improve key nuclear data measurements. The International Criticality Safety Benchmark Evaluation Project (ICSBEP) compiles and evaluates experiment data in a handbook that can be used by criticality safety engineers and others to validate computer codes and cross section libraries at nuclear facilities. Both critical and subcritical experiments are included in the handbook. These experiments, along with differential measurements, can help improve the quality of nuclear data. Concerns regarding the accuracy of Cu nuclear data have been published. The large values and trend of C-E for the Zeus intermediate energy benchmark, being one of the primary examples. Furthermore, very few experiments have been designed to be sensitive to Cu (as shown in Figure 1), so an integral, critical experiment is needed to help resolve these differences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Nuclear Criticality Safety Margin and Handbook Data: Concepts and Applications [Slides]

At the end of this briefing, personnel should be able to: • Define concepts associated with criticality safety margin • Provide and understand practical applications that illustrate safety margin concepts • Describe how safety margin is addressed in criticality safety evaluations • Improve documentation and communication of safety margin • Connect these concepts to related statements in the ANS-8 Standards • Find numerous applications for handbook data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2006

Description of Light Ion Production Cross Sections and Fluxes on the Mars Surface using the QMSFRG Model

The atmosphere of Mars significantly attenuates the heavy ion component of the primary galactic cosmic rays (GCR), however increases the fluence of secondary light ions (neutrons, and hydrogen and helium isotopes) because of particle production processes. We describe results of the quantum multiple scattering fragmentation (QMSFRG) model for the production of light nuclei through the distinct mechanisms of nuclear abrasion and ablation, coalescence, and cluster knockout. The QMSFRG model is shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections. We use the QMSFRG model and the space radiation transport code, HZETRN to make predictions of the light particle environment on the Martian surface at solar minimum and maximum. The radiation assessment detector (RAD) experiment will be launched in 2009 as part of the Mars Science Laboratory (MSL). We make predictions of the expected results for time dependent count-rates to be observed by RAD experiment. Finally, we consider sensitivity assessments of the impact of the Martian atmospheric composition on particle fluxes at the surface.

Cucinotta, Francis A.↗
DOE OSTI2025

Investigation of the Performance and Explainability Tradeoffs for Machine-Learning Models for Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Predictive maintenance (PdM) has shown great potential for achieving substantial cost savings and enhancing the economic competitiveness of nuclear power plants (NPPs) in today's energy market. Among the different modeling approaches that exist, machine learning (ML) tools in particular have a demonstrated ability to handle high dimensional and multivariate data and to extract hidden relationships within data in industrial environments. While ML methods show great potential, their lack of explainability---especially for black-box models---is a major hurdle to their adoption. Moreover, considering the supposed trade-off between explainability and performance challenges, careful consideration must be made as to which of these quality aspects takes precedence in light of multiple modeling options, resource availability, and domain characteristics. The present work evaluates the performance of six ML models, each with a different degree of explainability, in classifying the conditions of circulating water pumps (CWPs) by utilizing sensor data from nuclear power plants. To determine the drivers behind the trade-offs presented by this array of models, this work also tests different combinations of CWP units as the training and testing data, degrees of data imbalance, and objective functions for hyperparameter tuning. It was found that black-box models tend to afford superior performance in cases where there are far more instances of one type of labeled data than of any other type. It is recommended that a guided procedure be followed for designing and delivering an ML system that is sufficiently explainable to all involved stakeholders.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Development and validation of a software for simulating γ-γ coincidence emission and detection probabilities

Gamma-gamma coincidence spectrometers have the potential to significantly enhance detection sensitivity for ultra-trace radionuclide measurements. The implementation of these spectrometers, however, is limited by the complexity of acquisition hardware, data processing and quantification. This work reports development of a novel radionuclide quantification software for γ-γ coincidence measurements. For any radionuclide, the software parses the Evaluated Nuclear Structure Data File (ENSDF) database, recursively simulating all possible γ-γ coincidence signatures and their respective emission and detection probabilities. Implemented using Python programming language, the software employs several strategies to boost overall computational performance. Since coincidence-based spectrometers are of notable interest in monitoring compliance for the Comprehensive Nuclear-Test-Ban Treaty (CTBT), the software’s execution was tested for 84 CTBT-relevant radionuclides. To date, the software has been experimentally validated for 15 radionuclides using the Advanced Radionuclide Gamma spectrOmeter (ARGO) at Pacific Northwest National Laboratory, USA (PNNL). Notably, the software can be operated in convergence mode, whereby coincidence detection efficiency’s convergence behavior can help avoid unreliable radionuclide activity estimates. With growing number of coincidence spectrometers worldwide, this paper aims to assist the radiation metrology community in developing similar software for their system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2010

Overview of the Graphical User Interface for the GERMcode (GCR Event-Based Risk Model)

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERMcode calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERMcode also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERMcode for application to thick target experiments. The GERMcode provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERMcode GUI, as well as providing training applications.

Kim, Myung-Hee Y.↗
DOE OSTI2025

WRS Capabilities Booklet [Slides]

WRS is the digital backbone of the Weapons Program—delivering trusted data assets, cyber-assured software and systems, and AI-enabling software—that transform insights into decisive action. We empower physicists, engineers, researchers, and scientists to think faster, act strategically, and stay ahead in an ever-evolving threat landscape. Our efforts ensure critical nuclear weapons data remains secure, accessible, and usable—supporting mission-critical work, informed decision making, and scientific advancement at LANL and across the Nuclear Security Enterprise (NSE).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2010

Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERM code GUI, as well as providing training applications.

Kim, Myung-Hee↗
DOE OSTI2024

Powering Data Centers with Clean Energy: A Techno-Economic Case Study of Nuclear and Renewable Energy Dependability

Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1972

Generation of NEP heliocentric trajectory data

A study, designed to generate representative nuclear electric propulsion data for rendezvous missions to the comet Encke using the variational calculus program HILTOP, is presented. Other purposes of the study include a comparison of the HILTOP data with equivalent data generated with QUICKTOP program and to propose approaches for storing and subsequently accessing the optimum trajectory and performance data in the QUICKLY program.

Horsewood, J. L.↗
DOE OSTI2025

NDMAS

Overview of Current ART-GCR Data: Fuel Fabrication, Irradiation Monitoring (Fuel & Graphite – near real-time for HDG-1), Post-Irradiation Examination (Fuel & Graphite), Graphite Characterization (Baseline and Irradiated), High Temperature Metals Mechanical Tests, Design, Methods, and Validation Data, Japan Atomic Energy Agency’s High Temperature Test Reactor (HTTR), Argonne National Laboratory’s Natural convection Shutdown heat removal Test Facility (NSTF), Oregon State University’s High Temperature Test Facility (HTTF), Generation IV International VHTR Materials Handbook, Additional related data, and Advanced Test Reactor operations (near real-time).

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2012

GERMcode: A Stochastic Model for Space Radiation Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and high charge and energy (HZE) particles that have been studied at the NASA Space Radiation Laboratory (NSRL) for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of HZE particles in tissue and shielding materials is made with a stochastic approach that includes both particle track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections. For NSRL applications, the GERMcode evaluates a set of biophysical properties, such as the Poisson distribution of particles or delta-ray hits for a given cellular area and particle dose, the radial dose on tissue, and the frequency distribution of energy deposition in a DNA volume. By utilizing the ProE/Fishbowl ray-tracing analysis, the GERMcode will be used as a bi-directional radiation transport model for future spacecraft shielding analysis in support of Mars mission risk assessments. Recent radiobiological experiments suggest the need for new approaches to risk assessment that include time-dependent biological events due to the signaling times for activation and relaxation of biological processes in cells and tissue. Thus, the tracking of the temporal and spatial distribution of events in tissue is a major goal of the GERMcode in support of the simulation of biological processes important in GCR risk assessments. In order to validate our approach, basic radiobiological responses such as cell survival curves, mutation, chromosomal aberrations, and representative mouse tumor induction curves are implemented into the GERMcode. Extension of these descriptions to other endpoints related to non-targeted effects and biochemical pathway responses will be discussed.

Kim, Myung-Hee Y.↗
NASA NTRS2011

A Stochastic Model of Space Radiation Transport as a Tool in the Development of Time-Dependent Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and heavy ions that have been studied at the NASA Space Radiation Laboratory (NSRL) [1] for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of heavy ions in tissue and shielding materials is made with a stochastic approach that includes both ion track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model [2]. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections

Kim, Myung-Hee Y.↗
DOE OSTI2024

NDMAS Portal Updates

Overview of current ART-GCR Data, including fuel fabrication, irradiation monitoring, fuel and graphite, post-irradiation examination, graphite characterization, high temperature metals mechanical tests, methods validation data (including: HTTR, NSTF, and HTTF), addition of AGR fuel data, other GCR and related data, updated high temperature metals, ongoing and upcoming work, users guide, and the link to those interested in access to NDMAS.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2001

Integration of the QMSFRG Database into the HZETRN Code

Accurate nuclear interaction data bases are needed for describing the transport of space radiation in matter including space craft structures, atmospheres, and tissues. Transport models support the identification and development of new material concepts for human and electronic part protection. Quantum effects are manifested in nuclear reactions in several ways including interference effects between terms in the multiple scattering series, the many-body nuclear wave functions (for e.g. the roles of shell structure and Fermi momentum) and nuclear clustering. The quantum multiple scattering fragmentation model (QMSFRG) is a comprehensive model for generating nuclear interaction databases for galactic cosmic ray (GCR) transport. Other nuclear databases including the NUCFRG model and Monte-Carlo simulation codes such as FLUKA, LAHET, HETC, and GEANT ignore quantum effects. These codes fail to describe many important features of nuclear reactions and are thus inaccurate for the evaluation of materials for radiation protection. Previously we have shown that quantum effects are manifested through constructive interference in forward production spectra, the effects of Fermi momentum on production spectra, cluster nuclei knockout, and the nuclear response function. Quantum effects are especially important for heavy ions with mass numbers less than 20 that dominate radiation transport in human tissues and for the materials that are expected to be superior in space radiation protection. We describe the integration of the QMSFRG model into the HZETRN transport code. Integration milestones include proper treatment of odd-even charge-mass effects in nuclear fragmentation and the momentum distribution of nucleon production from GCR primary heavy ions. We have also modified the two-body amplitudes in the model to include nuclear medium effects. In order to include a comprehensive description of the GCR isotopic composition in materials, we have described the isotopic composition of the GCR by extending the 59-isotope version of HZETRN to an 120-isotope version. The isotopic composition of most primary GCR elements (including H, He, C, N, O, Ne, Mg, Si, Ar, Ca, Cr, and Fe) are included in the extended model. We discuss results for the high-energy neutron composition inside materials, and the charge and mass distribution for benchmark GCR problems.

Cucinotta, F. A.↗
DOE OSTI2025

Impact of Newly Measured 𝛽-Delayed Neutron Emitters around 78 Ni on Light Element Nucleosynthesis in the Neutrino Wind Following a Neutron Star Merger

Neutron emission probabilities and half-lives of 37 𝛽-delayed neutron emitters from 75 Ni to 92 Br were measured at the RIKEN Nishina Center in Japan, including 11 one-neutron and 13 two-neutron emission probabilities and six half-lives for the first time that supersede theoretical estimates. These nuclei lie in the path of the weak 𝑟 process occurring in neutrino-driven winds from the accretion disk formed after the merger of two neutron stars synthesizing elements in the 𝐴∼80 abundance peak. The presence of such elements dominates the accompanying kilonova emission over the first few days and have been identified in the AT2017gfo event, associated to the gravitational wave detection GW170817. Abundance calculations based on over 17,000 simulated trajectories describing the evolution of matter properties in the merger outflows show that the new data lead to an increase of 50%–70% in the abundance of Y, Zr, Nb, and Mo. This enhancement is large compared to the scatter of relative abundances observed in old very metal poor stars and thus is significant in the comparison with other possible astrophysical processes contributing to the light-element production. These results underline the importance of including experimental decay data for very neutron-rich 𝛽 -delayed neutron emitters into 𝑟 -process models.

59 ≤ A ≤ 89↗
DOE OSTI2024

Energy Levels of Light Nuclei A=13

Experimental nuclear spectroscopic data are evaluated for the 7 known nuclides of mass 13 (Li, Be, B, C, N, O, F). Detailed information is compiled and presented for each reaction and decay experiment. The results are combined and used to provide a set of recommended values that include level energies, spins and parities, half-lives of levels, decay branching ratios, and other nuclear properties. Furthermore, this work supersedes the earlier work by Fay Ajzenberg-Selove (1990Aj01) published in Nuclear Physics A 523 (1991) 1. Earlier reviews were published in (1986Aj01, 1981Aj01, 1976Aj04, 1970Aj04, 1959Aj76).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗