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DOE OSTI2021

Determining the range of validity of quasar X-ray and UV flux measurements for constraining cosmological model parameters

ABSTRACT We use six different cosmological models to study the recently released compilation of X-ray and UV flux measurements of 2038 quasars (QSOs) which span the redshift range 0.009 ≤ z ≤ 7.5413. We find, for the full QSO data set, that the parameters of the X-ray and UV luminosities LX−LUV relation used to standardize these QSOs depend on the cosmological model used to determine these parameters, i.e. it appears that the full QSO data set includes QSOs that are not standardized and so cannot be used for the purpose of constraining cosmological parameters. Subsets of the QSO data, restricted to redshifts z ≲ 1.5–1.7 obey the LX−LUV relation in a cosmological-model-independent manner, and so can be used to constrain cosmological parameters. The cosmological constraints from these lower z, smaller QSO data subsets are mostly consistent with, but significantly weaker than, those that follow from baryon acoustic oscillation and Hubble parameter measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

A Similarity-Based Analysis Tool for Porting OpenMP Applications. In: Facing the Multicore-Challenge III. Lecture Notes in Computer Science, vol 7686.

Exascale computers are expected to exhibit an unprecedented level of complexity, thereby posing significant challenges for porting applications to these new systems. One of the ways to support this transition is to create tools that allow their users to benefit from prior successful porting experiences. The key to such an approach is the manner in which we define source code similarity, and whether similar codes can be ported in the same way to a given system. In this paper, we propose a novel approach based on the notion of similarity that uses static and dynamic code features to check if two serial subroutines can be ported with the same OpenMP strategy. Our approach creates an annotated family distance tree based on the syntactic structure of subroutines, where subroutines that belong to the same syntactic family and share the similar code features have a greater potential to be optimized in the same way. We describe the design and implementation of a tool, based upon a compiler and performance tool, that is used to gather the data to build this porting planning tree. We then validate our approach by analyzing the similarity in subroutines of the serial version of the NAS benchmarks and comparing how they were ported in the OpenMP version of the suite.

Ding, Wei↗

DOE OSTI2021

Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models

This study aims to implement a hybrid ensemble surrogate machine learning technique in predicting the compressive strength (CS) of concrete, an important parameter used for durability design and service life prediction of concrete structures in civil engineering projects. For this purpose, an experimental database consisting of 1030 records has been compiled from the machine learning repository of the University of California, Irvine. The database was used to train and validate four conventional machine learning (CML) models, namely Artificial Neural Network (ANN), Linear and Non-Linear Multivariate Adaptive Regression Splines (MARS-L and MARS-C), Gaussian Process Regression (GPR), and Minimax Probability Machine Regression (MPMR). Subsequently, the predicted outputs of CML models were combined and trained using ANN to construct the Hybrid Ensemble Model (HENSM). It is observed that the proposed HENSM produces higher predictive accuracy compared to the CML models used in the present study. The predictive performance of all models for CS prediction was compared using the testing dataset and it is found that the HENSM model attained the highest predictive accuracy in both phases. Based on the experimental results, the newly constructed HENSM model is very potential to be a new alternative in handling the overfitting issues of CML models and hence, can be used to predict the concrete CS, including the design of less polluting and more sustainable concrete constructions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R 2 =0.70, P<0.001) and BBC (R 2 =0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Location Identifiers, Metadata, and Map for Field Measurements at the East-Taylor Watershed Community Observatory, Colorado, USA (Version 3.3)

This dataset contains identifiers, metadata, and a map of the locations where field measurements have been conducted at the East-Taylor Watershed Community Observatory located in the Upper Colorado River Basin, United States. This is version 3.3 of the dataset and replaces the prior version 3.2 (see below for details on changes between the versions). Dataset description: The East River-Taylor Watershed is the primary field site of the Watershed Function Scientific Focus Area (WFSFA) and the Rocky Mountain Biological Laboratory. Researchers from several institutions generate highly diverse hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data at the East-Taylor Watershed in collaboration with the WFSFA. Thus, the purpose of this dataset is to maintain an inventory of the field locations and instrumentation to provide information on the field activities in the East-Taylor Watershed and coordinate data collected across different locations, researchers, and institutions. The dataset contains (1) a README file with information on the various files, (2) three csv files describing the metadata collected for each surface point location, plot and region registered with the WFSFA, (3) csv files with metadata and contact information for each surface point location registered with the WFSFA, (4) a csv file with with metadata and contact information for plots, (5) a csv file with metadata for geographic regions and sub-regions within the watershed, (6) a compiled xlsx file with all the data and metadata which can be opened in Microsoft Excel, (7) a kml map of the locations plotted in the watershed which can be opened in Google Earth, (8) a jpg image of the kml map which can be viewed in any photo viewer, and (9) a zipped file with the registration templates used by the SFA team to collect location metadata. The zipped template file contains two csv files with the blank templates (point and plot), two csv files with instructions for filling out the location templates, and one compiled xlsx file with the instructions and blank templates together. Additionally, the templates in the xlsx include drop down validation for any controlled metadata fields. Persistent location identifiers (Location_ID) are determined by the WFSFA data management team and are used to track data and samples across locations. Dataset uses: This location metadata is used to update the Watershed SFA’s publicly accessible Field Information Portal (an interactive field sampling metadata exploration tool; https://wfsfa-data.lbl.gov/watershed/), the kml map file included in this dataset, and other data management tools internal to the Watershed SFA team. Version Information: The latest version of this dataset publication is version 3.3. This version contains 167 new point locations, 1 new plot, and 2 new geographic regions. Overall, there are a total of 1439 point locations, 75 plots, and 54 geographic regions. Additionally, the kml map of locations and image now includes two boundaries (Upper Ohio Creek (UO) and Carbon Creek (CA)) outside of the East River watershed (USGS HUC-10) and accompanying stream network that represents areas of focus. Refer to methods for further details on the version history. This dataset will be updated on a periodic basis with new measurement location information. Researchers interested in having their East-Taylor Watershed measurement locations added to this list should reach out to the WFSFA data management team at wfsfa-data@googlegroups.com. Acknowledgments: Please cite this dataset if using any of the location metadata in other publications or derived products. If using the location metadata for the 2018 NEON hyperspectral campaign, additionally cite Chadwick et al. (2020). doi:10.15485/1618130. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

2018 NEON and 2025 CHESS Campaigns↗

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 OSTI2026

Design of Controller Hardware-In-the-Loop Model of Microgrid with Modular Building Blocks and Automated Design Script

The scalability of controller hardware-in-the-loop (CHIL) simulation is critical for validating control coordination and energy management in microgrids with distributed energy resources, especially as these modern systems become more complex and decentralized. This paper presents a CHIL modeling methodology that combines modular building blocks with an automated design script to streamline the development of high-fidelity microgrid models. Standardized subsystem templates for resources, converters, and buses are integrated with a Python-based script that compiles structured JSON configuration files into simulation-ready initialization code. The proposed approach reduces development time, improves model consistency, and enhances simulation fidelity. The methodology is validated on a Typhoon HIL604 platform and is broadly applicable to real-time simulation of complex, networked microgrid systems. This framework establishes a foundation for automated, scalable CHIL validation and accelerates the design of next-generation distributed energy systems.

Kim, Namwon [ORNL] (ORCID:0000000200438489)↗

DOE OSTI2016

Plan to Verify and Validate Multi-Hazard Risk-Informed Margin Management Methods and Tools

This report describes the development plan for verification and validation (V&V) of multihazard risk informed margin management (RIMM) methods and tools. The plan will include using new INL developed tool sets coupled with the new multi-partner External Hazards Experimental Group (EHEG) coordinated by the Idaho National Laboratory (INL) within the Risk-Informed Safety Margin Characterization (RISMC) technical pathway of the Light Water Reactor Sustainability Program. The RISMC pathway is developing a suite of new tools and methods for advanced evaluation of facility risk. The RISMC toolkit, includes tools and methods focused on evaluation of risk from external hazards (e.g, seismic and flooding events), which have been shown to be dominant risk contributors in probabilistic risk assessments performed for operating nuclear power plants (NPPs). The external events activity (EEA) within the RISMC pathway is tasked with developing tools and methods focused on evaluation of multi-hazard external risk (e.g, seismic and flooding events). The EHEG will provide technical expertise and experimental large-scale testing data needed for development and validation of tools and methods in the RISMC toolkit for external hazard safety evaluations. The EEA within RISMC has two key elements: (1) an organizational and research framework provided by INL and (2) a coordinated group of university and national laboratory partners with the complementary expertise and experimental capabilities needed to conduct large-scale external hazard-focused experiments. This cooperative group will allow INL to leverage a range of existing capabilities to meet the unique needs of RISMC tool and method development. In addition, the capabilities of the EHEG could be used to address needs of other national laboratories. Currently, there is limited data available for development and validation of the tools and methods being developed in the RISMC Toolkit. The EHEG is being developed to obtain high quality, large-scale experimental data validation of RISMC tools and methods in a timely and cost-effective way. The group of universities and national laboratories that will eventually form the EHEG (which is ultimately expected to include both the initial participants and other universities and national laboratories that have been identified) have the expertise and experimental capabilities needed to both obtain and compile existing data archives and perform additional seismic and flooding experiments. The data developed by EHEG will be stored in databases within RISMC. These databases will be used to validate the advanced external hazard tools and methods. The numerical tools under development in RISMC are used to evaluate the impacts that external hazards have on nuclear power plants. These analysis tools will be used to advanced current risk calculation processes and reduce uncertainty in these calculations. To have confidence in the predictive capability of these numerical tools it is important to verify and validate them. To verify and validate numerical tools the user must understand what physics is being used to represent the problem (i.e. constitutive models used to represent the soil and structure), the numerical solver approach used (i.e. finite element), what data already exists that could be used to validate the tools, and what data is needed for validation.

31274↗

DOE OSTI2024

HTGR Validation: NEUP Survey and Database - Data Reporting Standard for HTGR Thermal-Fluid Experiments

Since 2009, the U.S. Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (NEUP) has been at the forefront of nuclear research, specifically concentrating on advancing high-temperature gas-cooled reactor (HTGR) technologies. By Fiscal Year 2024, NEUP has authorized 36 projects dedicated to HTGR research, each contributing significantly to the enhancement of our understanding of this technology. The outcomes of these diverse projects have been disseminated through final NEUP reports, peer-reviewed journal articles, and presentations at academic conferences, forming a comprehensive tapestry of knowledge. Despite the substantial value of these findings, their dissemination has been fragmented, posing challenges for accessibility to researchers and policymakers and leading to underutilization of DOE investments. Recognizing this critical gap and its potential consequences for the future of nuclear research, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program conducted an extensive survey of completed and ongoing HTGR NEUP projects. This survey enabled the compilation of crucial data, resulting in the development of a specialized public-access database tailored for computational fluid dynamics and system code validation, specifically designed for HTGR applications. However, the data collection process revealed a significant challenge in central data organization due to individual researchers from different institutes employing varying logics and preferences for recording and documenting experimental data. Consequently, an urgent need has been identified to establish a standardized reporting format for HTGR experimental projects. Addressing this issue is essential for enhancing collaboration, maximizing the impact of DOE investments, and ensuring the seamless advancement of HTGR technologies in nuclear research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

A Bayesian approach to evaluation of soil biogeochemical models

Abstract. To make predictions about the carbon cycling consequences of rising global surface temperatures, Earth system scientists rely on mathematical soil biogeochemical models (SBMs). However, it is not clear which models have better predictive accuracy, and a rigorous quantitative approach for comparing and validating the predictions has yet to be established. In this study, we present a Bayesian approach to SBM comparison that can be incorporated into a statistical model selection framework. We compared the fits of linear and nonlinear SBMs to soil respiration data compiled in a recent meta-analysis of soil warming field experiments. Fit quality was quantified using Bayesian goodness-of-fit metrics, including the widely applicable information criterion (WAIC) and leave-one-out cross validation (LOO). We found that the linear model generally outperformed the nonlinear model at fitting the meta-analysis data set. Both WAIC and LOO computed higher overfitting risk and effective numbers of parameters for the nonlinear model compared to the linear model, conditional on the data set. Goodness of fit for both models generally improved when they were initialized with lower and more realistic steady-state soil organic carbon densities. Still, testing whether linear models offer definitively superior predictive performance over nonlinear models on a global scale will require comparisons with additional site-specific data sets of suitable size and dimensionality. Such comparisons can build upon the approach defined in this study to make more rigorous statistical determinations about model accuracy while leveraging emerging data sets, such as those from long-term ecological research experiments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Examples of Use of SINBAD Database for Nuclear Data and Code Validation

Benchmark experiments can serve several purposes and the availability of suitable experimental data is fundamental to ensure that modelling tools meet the requirements of nuclear industry and licensing needs. Essentially, they are used for: - validation of nuclear cross-section data, - validation of nuclear codes and models used, - qualification and training of users through benchmarking and code comparison exercises. The Shielding Integral Benchmark Archive and Database (SINBAD) project was started in the early 1990's at the OECD Nuclear Energy Agency Data Bank (NEA DB) and the Radiation Safety Information Computational Center (RSICC) as a collection of quality experiments for validating and benchmarking computer codes and data for radiation transport and shielding applications. Currently, the SINBAD database comprises over 100 benchmark compilations and evaluations of relevance to: - reactor shielding, pressure vessel dosimetry (48); - fusion blanket neutronics (31); - accelerator shielding (23). In order to facilitate their use, the data are organized in the standardized format structure. The index and the master document (called abstract) use the Hyper Text Markup Language (HTML) format with links to text files, figures, Portable Document Format (pdf) documents and computer code inputs. The format allows easy access and forward/backward navigation among the data and has proved to be suitable, general enough and above all easy (and low-cost) to maintain. In addition to the characterization of the radiation source, description of the shielding set-up, the instrumentation and the relevant detector measurements, most sets in SINBAD contain also the deterministic or Monte Carlo radiation transport computer model used for the interpretation of the experiment and, where available, results from uncertainty analysis. The set of primary documents used for the benchmark compilation and evaluation are provided in computer readable form. The database is intended for different types of users, including nuclear data evaluators, computer code developers, experiment designers and university students. SINBAD is available from the NEA Data Bank and RSICC (see https://www.oecdnea.org/science/wprs/shielding/sinbad/). Up to now several hundreds of SINBAD packages were distributed from the NEA DB and RSICC. Since 2011 the maintenance and further development of the database is coordinated in the scope of the OECD NEA Nuclear Science Committee (NSC) Working Party on Scientific Issues of Reactor Systems (WPRS) Expert Group on Radiation Transport and Shielding (EGRTS). A key objective of the group is to identify, evaluate and preserve experimental data on shielding benchmarks. The Expert Group maintains close links with the International Reactor Physics Experiment Evaluation (IRPhE) and International Criticality Safety Benchmark Evaluation (ICSBEP) projects, as well as in co-ordination with the JEFF and EFF NEA Data Bank projects and with the SATIF community of accelerator shielding specialists. In the last years, much effort was devoted to the quality review of the available benchmark information.

42 ENGINEERING↗

DOE OSTI2019

Analytical Modeling of Cache Behavior for Affine Programs

Modern optimizing compiler design integrates program transformation strategies aimed at reducing data movement to/from main memory by exploiting the data cache hierarchy. But in reality, the effect of these transformations on the actual cache miss count is ignored in compilers due to the lack of precise compile-time models of misses for hierarchical caches. The current state of practice for cache miss analysis is based on accurate simulation. However, simulation requires time proportional to the dataset/problem size as well as the number of distinct cache configurations of interest to be evaluated. This paper takes a fundamentally different approach, made possible by focusing on polyhedral programs with static control flow: instead of relying on costly simulation, this paper develops the first closed-form solution for exact modeling of misses in a set-associative cache hierarchy. It enabling simulation-less selection of program transformations at compile-time to optimize cache misses. A push-button tool implementing the approach is developed and used for extensive validation of the complete framework.

affine programs, cache modeling, set associativity↗

DOE OSTI2012

Critical configuration and physics measurements for graphite reflected assemblies of U(93.15)O 2 fuel rods (1.506-CM pitch)

A series of critical experiments were completed in 1962-1965 at Oak Ridge National Laboratory’s Critical Experiments Facility in support of the Medium-Power Reactor Experiments (MPRE) program. In the late 1950’s efforts were made to study “power plants for the production of electrical power in space vehicles”. The MPRE program was a part of those efforts and studied the feasibility of a stainless steel system, boiling potassium 1 MW(t), or about 140 kW(e), reactor. The program was carried out in [fiscal years] 1964, 1965, and 1966. A summary of the program’s effort was compiled in 1967. The delayed critical experiments were a mockup of a small, potassium-cooled space power reactor for validation of reactor calculations and reactor physics methods.

1.506-cm pitch UO2 Assembly↗

DOE OSTI2012

Critical Configuration for Beryllium Reflected Assemblies of U(93.15)O 2 Fuel Rods (1.506-CM Pitch and 7-Tube Clusters)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2013

Critical Configuration and Physics Measurements for Assemblies of U(93.15)O 2 Fuel Rods

A series of critical experiments were completed in 1962-1965 at Oak Ridge National Laboratory’s (ORNL’s) Critical Experiments Facility (CEF) in support of the Medium-Power Reactor Experiments (MPRE) program. In the late 1950s, efforts were made to study “power plants for the production of electrical power in space vehicles.”(a) The MPRE program was a part of those efforts and studied the feasibility of a stainless-steel system, boiling potassium 1 MW(t), or about 140 kW(e), reactor. The program was carried out in [fiscal years] 1964, 1965, and 1966. A summary of the program’s effort was compiled in 1967. The delayed critical experiments were a mockup of a small, potassium-cooled space power reactor for validation of reactor calculations and reactor physics methods. Initial experiments, performed in November and December of 1962, consisted of a core of unmoderated stainless-steel tubes, each containing 26 UO 2 fuel pellets, surrounded by a graphite reflector. Measurements were made to determine critical reflector arrangements, fission-rate distributions, and cadmium ratio distributions. Subsequent experiments used beryllium reflectors and also measured the reactivity for various materials placed in the core. “The [assemblies were built] on [a] vertical assembly machine so that the movable part was the core and bottom reflector.”(Reference 1) The experiment studied in this evaluation was the first of the series and had the fuel tubes packed tightly into a 22.87 cm outside diameter (OD) core tank. Two critical configurations were found by varying the amount of graphite reflector (References 1 and 2). Once the critical configurations had been achieved, various measurements of reactivity, relative axial and radial activation rates of 235 U rates, and cadmium ratios were performed. The cadmium ratio, reactivity, and activation rate measurements performed on the critical configurations are described in Sections 1.3, 1.4 and 1.7, respectively.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Middle Kittanning Coal Waste and Underclay as an Alternative Rare Earth Elements Feedstock

In order to secure domestic sources of rare earth elements (REE) from coal related materials, there must be validation of representative feedstocks. Actively producing coal mines that target the Middle Kittanning coal seam in the Appalachian Basin were compiled. These mines were cross-referenced with publicly available geochemical data such as the U.S. Geological Survey (USGS) Earth Mapping Resources Initiative geochemical data along with samples evaluated and characterized by the National Energy Technology Laboratory (NETL). This work evaluated the extent of elevated Middle Kittanning underclay concentrations of REE in comparison to other underclay formations. Therefore, further up-scaling of research associated with the separation and extraction of REE and other critical minerals can be beneficial to utilizing domestic REE supplies for various technology sectors, to include energy, biomedical, and defense. Numerous current active mines targeting the Middle Kittanning coal seam represent a geographically significant opportunity for shared feedstocks and collaborations to further understand the role of Middle Kittanning underclay as a critical mineral feedstock.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2016

Development plan for the External Hazards Experimental Group. Light Water Reactor Sustainability Program

This report describes the development plan for a new multi-partner External Hazards Experimental Group (EHEG) coordinated by Idaho National Laboratory (INL) within the Risk-Informed Safety Margin Characterization (RISMC) technical pathway of the Light Water Reactor Sustainability Program. Currently, there is limited data available for development and validation of the tools and methods being developed in the RISMC Toolkit. The EHEG is being developed to obtain high-quality, small- and large-scale experimental data validation of RISMC tools and methods in a timely and cost-effective way. The group of universities and national laboratories that will eventually form the EHEG (which is ultimately expected to include both the initial participants and other universities and national laboratories that have been identified) have the expertise and experimental capabilities needed to both obtain and compile existing data archives and perform additional seismic and flooding experiments. The data developed by EHEG will be stored in databases for use within RISMC. These databases will be used to validate the advanced external hazard tools and methods.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

The NUBASE2016 evaluation of nuclear properties

This paper presents the NUBASE2016 evaluation that contains the recommended values for nuclear and decay properties of 3437 nuclides in their ground and excited isomeric (T1/2≥100 ns) states. All nuclides for which any experimental information is known were considered. NUBASE2016 covers all data published by October 2016 in primary (journal articles) and secondary (mainly laboratory reports and conference proceedings) references, together with the corresponding bibliographical information. During the development of NUBASE2016, the data available in the “Evaluated Nuclear Structure Data File” (ENSDF) database were consulted and critically assessed for their validity and completeness. Furthermore, a large amount of new data and some older experimental results that were missing from ENSDF were compiled, evaluated and included in NUBASE2016. The atomic mass values were taken from the “Atomic Mass Evaluation” (AME2016, second and third parts of the present issue). In cases where no experimental data were available for a particular nuclide, trends in the behavior of specific properties in neighboring nuclides (TNN) were examined. This approach allowed to estimate values for a range of properties that are labeled in NUBASE2016 as “non-experimental” (flagged “#”). Evaluation procedures and policies used during the development of this database are presented, together with a detailed table of recommended values and their uncertainties. AMDC: http://amdc.impcas.ac.cn/

Atomic Mass Evaluation (AME)↗