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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Knowledge management: Role of the the Radiation Safety Information Computational Center (RSICC)

The Radiation Safety Information Computational Center (RSICC) at Oak Ridge National Laboratory (ORNL) is an information analysis center that collects, archives, evaluates, synthesizes and distributes information, data and codes that are used in various nuclear technology applications. RSICC retains more than 2,000 software packages that have been provided by code developers from various federal and international agencies. RSICC’s customers (scientists, engineers, and students from around the world) obtain access to such computing codes (source and/or executable versions) and processed nuclear data files to promote on-going research, to ensure nuclear and radiological safety, and to advance nuclear technology. The role of such information analysis centers is critical for supporting and sustaining nuclear education and training programs both domestically and internationally, as the majority of RSICC’s customers are students attending U.S. universities. Additionally, RSICC operates a secure CLOUD computing system to provide access to sensitive export-controlled modeling and simulation (M&S) tools that support both domestic and international activities. This presentation will provide a general review of RSICC’s activities, services, and systems that support knowledge management and education and training in the nuclear field.

Valentine, Timothy↗
DOE OSTI2013

EUROPIUM s-PROCESS SIGNATURE AT CLOSE-TO-SOLAR METALLICITY IN STARDUST SiC GRAINS FROM ASYMPTOTIC GIANT BRANCH STARS

Individual mainstream stardust silicon carbide (SiC) grains and a SiC-enriched bulk sample from the Murchison carbonaceous meteorite have been analyzed by the Sensitive High Resolution Ion Microprobe-Reverse Geometry for Eu isotopes. The mainstream grains are believed to have condensed in the outflows of {approx}1.5-3 M{sub Sun} carbon-rich asymptotic giant branch (AGB) stars with close-to-solar metallicity. The {sup 151}Eu fractions [fr({sup 151}Eu) = {sup 151}Eu/({sup 151}Eu+{sup 153}Eu)] derived from our measurements are compared with previous astronomical observations of carbon-enhanced metal-poor stars enriched in elements made by slow neutron captures (the s-process). Despite the difference in metallicity between the parent stars of the grains and the metal-poor stars, the fr({sup 151}Eu) values derived from our measurements agree well with fr({sup 151}Eu) values derived from astronomical observations. We have also compared the SiC data with theoretical predictions of the evolution of Eu isotopic ratios in the envelope of AGB stars. Because of the low Eu abundances in the SiC grains, the fr({sup 151}Eu) values derived from our measurements show large uncertainties, in most cases being larger than the difference between solar and predicted fr({sup 151}Eu) values. The SiC aggregate yields a fr({sup 151}Eu) value within the range observed in the single grains and provides a more precise result (fr({sup 151}Eu) = 0.54 {+-} 0.03, 95% conf.), but is approximately 12% higher than current s-process predictions. The AGB models can match the SiC data if we use an improved formalism to evaluate the contribution of excited nuclear states in the calculation of the {sup 151}Sm(n, {gamma}) stellar reaction rate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Enhanced Component Performance Study: Motor-Driven Pumps 1998–2013

This report presents an enhanced performance evaluation of motor-driven pumps at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from fiscal year 1998 through 2013 for the component reliability as reported in the Institute of Nuclear Power Operations (INPO) Consolidated Events Database (ICES). The motor-driven pump failure modes considered for standby systems are failure to start, failure to run less than or equal to 1 hour, and failure to run more than 1 hour; for normally running systems, the failure modes considered are failure to start and failure to run. An 8 hr unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire active period. One statistically significant increasing trend was identified in the standby pump run hours per reactor year. Statistically significant decreasing trends were identified for standby systems industry-wide frequency of start demands, run hours per reactor year for runs of less than or equal to 1 hour, and frequency of fail to start events per reactor year.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Review of SCALE Validations Applicable to Spent Nuclear Fuel Shielding Calculations

This report presents a review of publicly available documents providing validations of SCALE code system capabilities for depletion and shielding calculations. The validation studies primarily used information available in the Spent Fuel Isotopic Composition Database, the Shielding Integral Benchmark Archive and Database, and the International Criticality Safety Benchmark Evaluation Project Handbook. Validation results based on radiochemical assay data and shielding benchmark experiments relevant to spent nuclear fuel shielding applications are summarized in this report. The information summarized in this report supports pressurized water reactor and boiling water reactor spent fuel storage and transportation safety analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Enhanced Component Performance Study: Turbine Driven Pumps 1998–2022

This report presents an enhanced performance evaluation of turbine driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2022 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The TDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR=1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10 year period while yearly estimates for reliability are provided for the entire study period. No increasing trends were identified for TDPs for the most recent 10 year period: The following decreasing trends were identified for TDPs for the most recent 10 year period: • Standby TDP FTR>1H failure rate • Normally running TDP FTR failure rate • Standby TDP unavailability • Standby MDP total unreliability (8-hour mission) • Standby TDP frequency of start demands (demands per reactor year) • Standby TDP frequency of FTR=1H hours (hours per reactor year) • Standby TDP frequency of FTR>1H events (failures per reactor year) • Normally running TDP frequency of start demands • Normally running TDP frequency of run hours • Normally running TDP frequency of FTR events.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Enhanced Component Performance Study: Air Operated Valves 1998–2022

This report presents an enhanced performance evaluation of air operated valves (AOVs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2022 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The AOV failure modes considered are fail to open or close (FTOC), fail to operate or control (FTOP), and spurious operation (SO). The component reliability estimates and the reliability data are trended for the most recent 10 year period while yearly estimates for reliability are provided for the entire study period. The following increasing trends were identified for AOVs for the most recent 10 year period: • Low demand AOV frequency of FTOC demands (demands per reactor year) • High demand AOV frequency of FTOC demands. The following decreasing trends were identified for AOVs for the most recent 10 year period: • Low demand AOV FTOC failure probability • Low demand AOV FTOP failure rate • Low demand AOV frequency of FTOC events (failures per reactor year) • Low demand AOV frequency of FTOP events.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Enhanced Component Performance Study: Turbine-Driven Pumps 1998-2024

This report presents an enhanced performance evaluation of turbine driven pumps (TDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2024 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The TDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR=1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10 year period while yearly estimates for reliability are provided for the entire study period. No increasing trends were identified for TDPs for the most recent 10 year period.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Update on Radiochemical Assessment of High Burnup Commercially Irradiated Fuel

This work documents an effort to collect burnup measurements on a high burnup rod, designated 6XV, and first cycle accident tolerant fuel (ATF) rod, designated 47I, to enable benchmarking of fuel performance codes and neutronics codes. In addition to measurements, Virtual Environment for Reactor Applications (VERA) full-core-depletion analysis was also performed for the rods that were experimentally analyzed to provide an opportunity for code validation. This effort focuses on collecting data from rods irradiated at Byron Generating Station and shipped to the Oak Ridge National Laboratory (ORNL) hot-cells. This data will also anchor non-destructive examination evaluations of burnup of the various fuel rods undergoing postirradiation examination (PIE) at ORNL. Previous PIE of these fuel rods provides some guidance on the burnup trend across the fuel. Axial gamma spectroscopy scans provide a measure of relative changes in burnup across a fuel pin. Mass spectrometry based burnup measurements performed for this work at specific axial locations in the fuel are fully quantitative. By combining the mass spectrometry data with the gamma scans it is possible to more quantitatively evaluate axial variations in burnup across the entire fuel pin [1]. The combined set of burnup evaluations will be made available to other organizations that have an interest in high burnup radiochemistry data for validation of neutronic simulations and source term evaluation such as the Nuclear Regulatory Commission (NRC).

Harp, Jason [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2020

Hierarchical Bayesian Thermonuclear Rate for the 7 Be(n,p) 7 Li Big Bang Nucleosynthesis Reaction

Big Bang nucleosynthesis provides the earliest probe of standard model physics, at a time when the universe was less than 1000 seconds old. It determines the abundances of the lightest nuclides, which give rise to the subsequent history of the visible matter in the universe. This work derives new 7 Be(n,p) 7 Li thermonuclear reaction rates based on all available experimental information. This reaction sensitively impacts the primordial abundances of 7 Be and 7 Li during big bang nucleosynthesis. We critically evaluate all available data and disregard experimental results that are questionable. For the nuclear model, we adopt an incoherent sum of single-level, two-channel, R -matrix approximation expressions, which are implemented into a hierarchical Bayesian model, to analyze the remaining six data sets we deem most reliable. In the fitting of the data, we consistently model all known sources of uncertainty, including discrepant absolute normalizations of different data sets, and also take the variation of the neutron and proton channel radii into account, hence providing less biased estimates of the 7 Be(n,p) 7 Li thermonuclear rates. From the resulting posteriors, we extract R -matrix parameters ($E_r, γ^2_n, γ^2_p$) and derive excitation energies and partial and total widths. Our fit is sensitive to the contributions of the first three levels above the neutron threshold. Reaction rates were computed by integrating 10,000 samples of the reduced cross section. Our 7 Be(n,p) 7 Li thermonuclear rates have uncertainties between 1.5% and 2.0% at temperatures of ≤1 GK. Finally, we compare our rates to previous results and find that the 7 Be(n,p) 7 Li rates most commonly used in big bang simulations have uncertainties that are too optimistic.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

Yankee Rowe isotopics benchmark using MCNP-XT

The Yankee Rowe spent fuel isotopic data provides a valuable source to benchmark the burnup calculations as part of verification and validation (V and V) efforts for the TerraPower's Monte Carlo depletion code, MCNP-XT. A total of 71 fuel rods were selected in the Yankee Rowe isotopic measurements covering a burnup range up to 44 MWd/kg ({approx}4.4%) under both the asymptotic spectrum and the non-asymptotic spectrum. The MCNP-XT pin cell depletion provides a comparison against the asymptotic spectrum measurement; and full assembly depletion with 322 depletion materials provides comparisons against various non-asymptotic depletion conditions. All calculations are performed based on the recent ENDF/B-VII.O data. Furthermore, the Monte Carlo depletion uncertainties and biases were examined showing their effect as insignificant. The set of burnup calculations cover the scattered experimental measurements demonstrating excellent agreement with the measured values. This benchmark exercise demonstrates the depletion analysis capability of the MCNP-XT code and validates the low burnup range. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

UMo Benchmark Experiment Data Needed to Support Computational and Nuclear Data Validation

Currently there are almost no benchmark experiment data available directly supporting neutronics modeling and simulation of ~20 wt.% 235U, UMo fuel contained within the Organisation for Co-operation and Development Nuclear Energy Agency (OECD NEA) international benchmark handbooks from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and International Reactor Physics Experiment Evaluation Project (IRPhEP). The benchmarks within these two handbooks represent the international standards used to support computational and nuclear data validation. Recent activities in nuclear data development supporting new neutronics thermal scattering cross sections for UMo fuel indicate the necessity to provide quality benchmark experiment data that can be utilized to support their validation and development. Preparation of high-integrity neutronics benchmarks from UMo experimental data will ensure proper integral testing of these cross sections, as well as serve to support computational validation of contemporary modeling and simulation software.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Nevada National Security Site (NNSS) Environmental Remediation Using EPA's Model Evaluation Guidance to Move to Closure - 15588

The National Nuclear Security Administration Nevada Field Office (NNSA/NFO) has adapted the Environmental Protection Agency's guidance on environmental model evaluation as a framework for evaluating corrective action investigation models. Model evaluation is an important confidence building activity, which is needed to support closure of the Nevada National Security Site (NNSS) Corrective Action Units (CAUs) associated with underground nuclear testing. Through this process, site-investigation models of groundwater flow and contaminant transport are reviewed and compared to new site-specific data to determine if the results can be used to support regulatory decisions required for closure and to achieve NNSA/NFO site management objectives. The regulatory decisions include identifying and establishing CAU regulatory boundaries; identifying institutional controls, including use-restriction boundaries; and developing a long-term closure monitoring program. A successful case study from Frenchman Flat, Nevada is used to illustrate the model evaluation process. Groundwater flow and transport from two of the 10 underground nuclear tests in Frenchman Flat had the largest potential for contaminating groundwater, and were selected for evaluation. Wells were drilled, logged, hydraulically tested, sampled, and analyzed for radionuclides and the data was evaluated with respect to previous site conceptualization and numerical model results. The approach and results of this process as applied to the PIN STRIPE test and how it helped build confidence to close the Frenchman Flat CAU is described in this case study. (authors)

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

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Industry Level Feasibility of LiDAR Data into Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial information this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but support groups such as security. LIDAR mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add, or there is no way to extract specific spatial data needed for other tools. This report presents Idaho National Lab's work with Environmental Intellect (Ei) covering two main efforts. First, to reduce the effort of "tagging" data in large 3D models. By using both existing plant database information, and artificial intelligence (AI) to find and read equipment labels. This research explores the ability of to provide a simple way for the user to tag items and verify plant data, capturing both the speed of AI and human verification. The second part of the work is the development of an interface for importing pieces needed for Modeling & Simulation. Analysis work such as that for fire, flood, or physical security all require spatial or 3D models in various levels of detail. This interface will allow for the retrieval of item location or boundaries, enabling the auto generation of models for varying tools. The application program interface (API) of the fire risk investigation in 3D (FRI3D) was used to test feasibility of exporting the LiDAR tagged spatial information. Outcomes from this work provide preliminary data to determine if the tools and methods could provide substantial industry benefit if fully matured.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

The heavy particle hazard, what physical data are needed?

The physical data required to evaluate the radiation hazard from heavy galactic cosmic rays to astronauts on extended missions are discussed. The spectral characteristics, nuclear interaction parameters, and track structure of particles are emphasized. The data on the lower energy portion of the differential spectrum of the iron group and nuclear fragmentation in tissue and aluminum are tested, and results are shown.

Curtis, S. B.↗
DOE OSTI2016

5.0. Depletion, activation, and spent fuel source terms

SCALE’s general depletion, activation, and spent fuel source terms analysis capabilities are enabled through a family of modules related to the main ORIGEN depletion/irradiation/decay solver. The nuclide tracking in ORIGEN is based on the principle of explicitly modeling all available nuclides and transitions in the current fundamental nuclear data for decay and neutron-induced transmutation and relies on fundamental cross section and decay data in ENDF/B VII. Cross section data for materials and reaction processes not available in ENDF/B-VII are obtained from the JEFF-3.0/A special purpose European activation library containing 774 materials and 23 reaction channels with 12,617 neutron-induced reactions below 20 MeV. Resonance cross section corrections in the resolved and unresolved range are performed using a continuous-energy treatment by data modules in SCALE. All nuclear decay data, fission product yields, and gamma-ray emission data are developed from ENDF/B-VII.1 evaluations. Decay data include all ground and metastable state nuclides with half-lives greater than 1 millisecond. Using these data sources, ORIGEN currently tracks 174 actinides, 1149 fission products, and 974 activation products. The purpose of this chapter is to describe the stand-alone capabilities and underlying methodology of ORIGEN—as opposed to the integrated depletion capability it provides in all coupled neutron transport/depletion sequences in SCALE, as described in other chapters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗