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The spontaneous fission yields (SFY) sublibray aims to describe fission yields that happen spontaneous, without any incident particle. For ENDF/B-VIII.1, there were no new fission yields complete evaluations. However, many erroneously large uncertainties, present in both SFY from ENDF/B-VIII.0, were corrected.
The neutron standards sublibrary describes specific reaction cross sections, in a limited range, that are so well-known that they are used as ratios or references in other measurements. ENDF/B-VIII.1 remains unchanged from ENDF/B-VIII.0 for the neutron standards sublibrary
The thermal neutron scattering law (TSL) sublibrary aims to describe the interaction of incident neutrons at thermal or sub-thermal energies with different compound materials such fuels, moderators and special-purpose materials. In ENDF/B-VIII.1 there was a large number of new and updated TSL evaluations, including traditional moderators (light water, Beryllium metal, Beryllium Oxide, Calcium Hydride, plastics (Polystyrene and Lucite), graphite (reactor-grade and crystalline), anhydrous Hydrogen Fluoride, and heavy paraffinic oil); exotic moderators (Beryllium Carbide, Zirconium Hydride, Yttrium Hydride, Lithium-7 Hydride and Deuteride), FLiBe molten salt, structural materials and cladding (Silicon Carbide, Silicon Dioxide, Zirconium Carbide), fuels (Plutonium Dioxide, Uranium Carbide, Uranium metal, Uranium Nitride, Uranium Dioxide, Uranium Hydride), and special purpose materials. In ENDF/B-VIII.1 we also distribute alongside the evaluated files, a comma-separated file (CSV), named TSL_MAT_numbers.csv, which lists all evaluated files in the current release and their corresponding unique MAT number.
The tritons sublibrary aims to describe nuclear reactions between incident triton particles and different nuclei. For ENDF/B-VIII.1, compared to ENDF/B-VIII.0, there were only evaluation updates for 4 He.
Dry deposition to the surface is one of the main removal pathways of tropospheric ozone (O 3 ). We quantified for the first time the impact of O 3 deposition to the Arctic sea ice on the planetary boundary layer (PBL) O 3 concentration and budget using year-round flux and concentration observations from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign and simulations with a single-column atmospheric chemistry and meteorological model (SCM). Based on eddy-covariance O 3 surface flux observations, we find a median surface resistance on the order of 20,000 s m –1 , resulting in a dry deposition velocity of approximately 0.005 cm s –1 . This surface resistance is up to an order of magnitude larger than traditionally used values in many atmospheric chemistry and transport models. The SCM is able to accurately represent the yearly cycle, with maxima above 40 ppb in the winter and minima around 15 ppb at the end of summer. However, the observed springtime ozone depletion events are not captured by the SCM. In winter, the modelled PBL O 3 budget is governed by dry deposition at the surface mostly compensated by downward turbulent transport of O 3 towards the surface. Advection, which is accounted for implicitly by nudging to reanalysis data, poses a substantial, mostly negative, contribution to the simulated PBL O 3 budget in summer. During episodes with low wind speed (<5 m s –1 ) and shallow PBL (<50 m), the 7-day mean dry deposition removal rate can reach up to 1.0 ppb h –1 . Our study highlights the importance of an accurate description of dry deposition to Arctic sea ice in models to quantify the current and future O 3 sink in the Arctic, impacting the tropospheric O 3 budget, which has been modified in the last century largely due to anthropogenic activities.
In the Los Alamos National Laboratory’s Space Nuclear Detonation Detection (SNDD) program, several instruments detect hard radiation neutral particles. In this research, the transport of gamma rays were explored from both prompt emissions and delayed emissions. These are used by the SABRS instruments (ZDG, ZPG) to detect a nuclear detonation.
This milestone reports on the culmination of several years of effort by multiple PEM support software development teams to provide capabilities for use in LLNL-developed integrated codes on next-gen ASC platforms, including GPU support. We will provide a survey of relevant Application Program Interfaces (API) that are required to support LLNL IC code capability on relevant architectures, with a focus on Sierra and El Capitan. We will identify and summarize all dependencies between PEM supported libraries and IC supported physics codes. We will provide an assessment of algorithmic improvements that have been deployed, as well as future developments that are required to complete the GPU porting efforts. This assessment will include a description of programming models adopted by each of the PEM projects, distinct algorithmic challenges for each of the capabilities, and information about sharing GPU memory between the APIs and host codes. We will develop targeted test problems to assess computational performance. Finally, this milestone will result in identification of gaps in our effort to assist the LLNL ASC program in prioritization of effort for porting software to El Capitan.
The cross sections of neutron-induced reactions can be divided into three energy ranges: the resolved resonance region (RRR), the unresolved resonance region (URR), and the fast region. In general, the cross sections in the URR show significant fluctuations that cannot be predicted and cannot be experimentally resolved, thus, it is commonly assumed that the cross section at a specific energy is given by a probability distribution function (PDF) over a range of values that can span several orders of magnitude. The current methodology used to describe such behavior is to construct the PDF by stochastically generating resonance ladders and numerically measuring the PDF. The resonance ladders are sampled using known resonance statistical properties and average resonance widths and spacings extrapolated from the RRR. Although this is a standard and widely used technique, it is computationally very expensive, therefore, an alternative, analytical, approach would be preferable due to the considerable speed up of the computational time in real life applications. Moreover, the current methodology does not take into account existing experimental data, such for total and capture cross sections, that are available for many nuclei. Finally, this approach was developed to be used in reactor-scale applications and it is not suited for use in single-event applications. In this work we will rethink the entire approach to the PDF construction using a Bayesian mindset. This will allow us to provide a different definition of the PDF that allows a much faster calculation of the higher-temperature PDFs and a proper combination of theoretical and experimental PDFs following the probability theory. We will also show that our definition is well suited for single-event applications and we will make an explicit connection between our method and the standard approach. We do this by showing that the central limit theorem applies and our method leads to the same PDF obtained with the standard methodology, for a large number of events per history.
This training is designed to refresh knowledge of basic radiological principles and terms, the risks from exposure to ionizing radiation, LANL’s radiological hazards and postings, ALARA methods, your responsibilities during emergencies, and how to obtain your personal radiological dose records.
LLNL implemented infrastructure to include treatment of URR in GNDS. There are two options to store URR probabilities: cross-sections pdf and ACE-like probability tables. Issues were found with both options during verification with criticality benchmarks. Projected future steps include resolving issues in the next year and adding criticality benchmarks sensitive to URR.
The level density distribution of near closed-shell nuclei is much lower than the typical nucleus, therefore, the cross sections show significant fluctuations, and these fluctuations are not predictable. The current methodology used to describe such behavior and construct the probability table of the cross section is based on the extrapolation of the average resonance widths and average resonance spacings from the resonance region and use these parameters to construct the probability table. Although this is a standard and widely used technique, it does not take into account the existing experimental data, such for total and the elastic cross section. Our goal is to extend the current theory and provide a more general approach to compute the probability distribution function of the cross section combining the existing probability tables and the available experimental data. Results will be presented for 90 Zr.
This report provides the status of discrete nuclear levels and inelastic gamma-ray production for neutron induced reactions in current ENDF-VIII.0 evaluations for the isotopes in the GRIN project. Different categories of issues are identified after a comparison with information from “adopted” ENSDF files. Improvement strategies are given and recommendations are described. We have included a similar, but more limited, analysis for thermal capture data where EGAF and ENSDF thermal libraries are considered. In addition, we provide a validation plan to employ different transport code simulations.
LLNL’s Nuclear Data and Theory Group has created the 2011.5 revised release of the Evaluated Nuclear Data Library (ENDL2011.5). ENDL2011.5 is designed to support LLNL’s current and future nuclear data needs and will be employed in nuclear reactor, nuclear security and stockpile stewardship simulations with ASC codes. This database is currently the most complete nuclear database for Monte Carlo and deterministic transport of neutrons and charged particles. This library was assembled with strong support from the ASC PEM and Attribution programs, leveraged with support from Campaign 4 and the DOE/Office of Science’s US Nuclear Data Program. This document lists the revisions made in ENDL2011.5 compared with the data existing in the original ENDL2011.2 and ENDL2011.3 releases. These changes are made in parallel with some similar revisions for ENDL2009.5. We also describe ENDL2011.5-direct that directly uses ENDF sources wherever possible.
LLNL’s Nuclear Data and Theory Group have created a 2009.5 revised release of the Evaluated Nuclear Data Library (ENDL2009.5). This library is designed to support LLNL’s current and future nuclear data needs and will be employed in nuclear reactor, nuclear security and stockpile stewardship simulations with ASC codes. The ENDL2009 database was the most complete nuclear database for Monte Carlo and deterministic transport of neutrons and charged particles. It was assembled with strong support from the ASC PEM and Attribution programs, leveraged with support from Campaign 4 and the DOE/Office of Science’s US Nuclear Data Program. This document lists the revisions and fixes made in a new release called ENDL2009.5, by comparing with the existing data in the previous releases ENDL2009.3 and ENDL2009.4. In addition to the legacy library ENDL2009.5 from ENDL-format files generated by Fete, an ENDL2009.5-direct library is also released, in which ENDF6-formatted sources are used wherever possible to avoid possible translation errors from Fete.
The ENDL2009.5 Evaluated Nuclear Data Library is now available three different processed forms for users: (1) the Legacy form using NDF and MCF processing of the ENDL files, (2) the GNDS form which uses FUDGE and Merced to process the translations in to GNDS of the ENDL files, and (3) the Direct form which uses FUDGE and Merced to process where available the original ENDF6- format source files used to make the ENDL files. If original files are not available for various protares in the Direct form, then the ENDL forms are used.
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Background: The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation. Health-related misinformation threatens adherence to public health messaging, and monitoring its spread on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts. Objective: The aim of this study is to use Twitter data to explore methods to characterize and classify four COVID-19 conspiracy theories and to provide context for each of these conspiracy theories through the first 5 months of the pandemic. Methods: We began with a corpus of COVID-19 tweets (approximately 120 million) spanning late January to early May 2020. We first filtered tweets using regular expressions (n=1.8 million) and used random forest classification models to identify tweets related to four conspiracy theories. Our classified data sets were then used in downstream sentiment analysis and dynamic topic modeling to characterize the linguistic features of COVID-19 conspiracy theories as they evolve over time. Results: Analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. Random forest classifier metrics varied across the four conspiracy theories considered (F1 scores between 0.347 and 0.857); this performance increased as the given conspiracy theory was more narrowly defined. We showed that misinformation tweets demonstrate more negative sentiment when compared to non-misinformation tweets and that theories evolve over time, incorporating details from unrelated conspiracy theories as well as real-world events. Conclusions: Although we focus here on health-related misinformation, this combination of approaches is not specific to public health and is valuable for characterizing misinformation in general, which is an important first step in creating targeted messaging to counteract its spread. Initial messaging should aim to preempt generalized misinformation before it becomes widespread, while later messaging will