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Evaluated spectroscopic data and level schemes from radioactive decay and nuclear reaction studies are presented for 23 N, 23 O, 23 F, 23 Ne, 23 Na, 23 Mg, 23 Al, and 23 Si. Here, this evaluation for A=23 supersedes the earlier one by R. B. Firestone (2007Fi02).
In December 2011, the National Nuclear Data Center (NNDC) released ENDF/BVII.1, the “latest recommended evaluated nuclear data file for use in nuclear science and technology applications”. The data was released in the standard Evaluated Nuclear Data Format (ENDF). This release represents the advances made in nuclear data during the five years since the release of ENDF/B-VII.0. The Nuclear Data Team at Los Alamos National Laboratory has processed the ENDF/B-VII.1 library and has made available a library of ACE data tables at several temperatures for each of the ENDF/B files. The ACE data library is called ENDF71x.
The 9 B neutron capture cross section has significant implications for Be materials in the nuclear industry as well as the α process in stellar nucleosynthesis. While the cross section is well constrained at thermal neutron energies, there is a lack of experimental data at higher neutron energies, and the evaluated nuclear data libraries can differ by up to two orders of magnitude. We calculate the 9 Be(n, γ) 10 Be integral cross section at fission neutron energies in an effort to resolve disagreements amongst the nuclear data libraries. Foil irradiation experiments were performed using the Flattop critical assembly at the National Criticality Experiments Research Center with either the highly enriched U or Pu cores, with target foil stacks placed at multiple locations to exploit different neutron energy profiles. Accelerator mass spectrometry was used to measure the 10 Be/ 9 Be ratio in irradiated Be foils, while all other activation products were quantified through gamma spectrometry. The experiments were simulated using the Monte Carlo N-Particle radiation transport code and combined with experimental results to determine the total neutron fluence, while the staysl-pnnl suite and fispact-ii code were used to validate the model and assess the systematic uncertainty. The new 9 Be(n, γ) 10 Be integral cross sections calculated in this work are 26.5 ± 2.2µb at 0.59 ± 0.07 MeV, 24 ± 3 µb at 0.98 ± 0.14 MeV, 21.7 ± 1.3 µb at 1.26 ± 0.11 MeV, 21.8 ± 1.4 µb at 1.32 ± 0.11 MeV, and 18.6 ± 1.1 µb at 1.46 ± 0.13 MeV. These results do not agree with integral cross sections from any of the nuclear data library evaluations. Discrepancies between the new integral cross sections reported here and the nuclear data libraries suggest a more complex cross-section structure in the MeV range which allows for more resonance contributions, and more work is needed to further constrain the evaluated cross sections.
Evaluated experimental data are presented for 13 known mass 189 nuclides (Hf, Ta, W, Re, Os, Ir, Pt, Au, Hg, Tl, Pb, Bi, Po). Since the 2003Wu02 publication, structure and decay data from 25 new and primary publications have been incorporated in the current work, while adding a new 189 Hf nuclide. New data have been added for all nuclides except 189 Au and 189 Hg. Moreover, several previous datasets were modified for β-decay Q values and conversion coefficients even when no new publications appeared since 2003Wu02. In spite of large amounts of data available for A=189 nuclides, several deficiencies remain, which are pointed out below in the hope that further experimental work may improve our knowledge of structure of these nuclides. For 189 Hf and 189 Ta, ground-state half-lives, and their decay schemes are unknown. An isomer in 189 Ta has recently been established but its decay characteristics are unknown, even though several gamma rays were connected with its decay. No excited states are known in 189 W and only one in 189 Po. The decay scheme of 189 W is known poorly with most gamma rays left as unassigned. The decay schemes of 189 Au and 189 Pb g.s. suffer from incompleteness, while those for the g.s. and isomer of 189 Tl are almost absent. The decay schemes of g.s. and isomer of 189 Hg are very complex as apparent from the study by 1996Wo04. Evaluators feel that these two decay schemes could be improved with modern gamma-ray detector arrays. While several isomers are known in many of the A=189 nuclides, there is in general lack of information of level half-lives, thus limiting the knowledge of transition probabilities. High-spin structures, including SD bands in 189 Hg and 189 Tl, are known in 189 Re, 189 Ir, 189 Pt, 189 Au, 189 Hg, 189 Tl, 189 Pb and 189 Bi. Single-particle transfer data are available for 189 Re, 189 Os, and 189 Pt; and two-neutron transfer data for 189 Ir.
This conference paper summarizes an initial assessment of the evaluated atomic data libraries released in ENDF/BVIII. 0 and in EPICS2017 in early 2018. The new versions supersede the data libraries currently used by Monte Carlo particle transport codes to handle electron and photon interactions with matter, which date back to the 1990's. Several features of the data are evaluated: their consistency, the content available in the different formats of the data libraries and from different distribution sources, and the computational performance associated with their use. Additionally, an overview of the validation status of the data is given, including some preliminary results concerning new cross section data released in 2018. These evaluations contribute to estimate the impact of the new data libraries in Monte Carlo simulations and highlight areas where future versions would benefit from improvements. (authors)
Knowledge of when critical crop stages occur and how the environment affects them should provide useful information for crop management decisions and crop production models. Two sources of data were evaluated for predicting dates of silking and physiological maturity of corn (Zea mays L.). Initial evaluations were conducted using data of an adapted corn hybrid grown on a Typic Agriaquoll at the Purdue University Agronomy Farm. The second phase extended the analyses to large areas using data acquired by the Statistical Reporting Service of USDA for crop reporting districts (CRD) in Indiana and Iowa. Several thermal models were compared to calendar days for predicting dates of silking and physiological maturity. Mixed models which used a combination of thermal units to predict silking and days after silking to predict physiological maturity were also evaluated. At the Agronomy Farm the models were calibrated and tested on the same data. The thermal models were significantly less biased and more accurate than calendar days for predicting dates of silking. Differences among the thermal models were small. Significant improvements in both bias and accuracy were observed when the mixed models were used to predict dates of physiological maturity. The results indicate that statistical data for CRD can be used to evaluate models developed at agricultural experiment stations.
The accidents at the Three Mile Island Unit 2 (TMI-2) Pressurized Water Reactor (PWR) and the Daiichi Units 1, 2, and 3 Boiling Water Reactors (BWRs) provide unique opportunities to evaluate instrumentation exposed to severe accident conditions. Conditions associated with the release of coolant and the hydrogen burn that occurred during the TMI-2 accident exposed instrumentation to harsh conditions, including direct radiation, radioactive contamination, and high humidity with elevated temperatures and pressures. As part of a program initiated in 2012 by the Department of Energy Office of Nuclear Energy (DOE-NE), a review was completed to gain insights from prior TMI-2 sensor survivability and data qualification efforts. This initial review focused on the set of sensors deemed most important by post-TMI-2 instrumentation evaluation programs. Instrumentation evaluation programs focused on data required by TMI-2 operators to assess the condition of the reactor and containment and the effect of mitigating actions taken by these operators. In addition, prior efforts focused on sensors providing data required for subsequent forensic evaluations and accident simulations. To encourage the potential for similar activities to be completed for qualifying data from Daiichi Units 1, 2, and 3, this report provides additional details related to the formal process used to develop a qualified TMI-2 data base and presents data qualification details for three parameters: primary system pressure; containment building temperature; and containment pressure. As described within this report, sensor evaluations and data qualification required implementation of various processes, including comparisons with data from other sensors, analytical calculations, laboratory testing, and comparisons with sensors subjected to similar conditions in large-scale integral tests and with sensors that were similar in design to instruments easily removed from the TMI-2 plant for evaluations. As documented in this report, results from qualifying data for these parameters led to key insights related to TMI-2 accident progression. Hence, these selected examples illustrate the types of activities completed in the TMI-2 data qualification process and the importance of such a qualification effort. These details are documented in this report to facilitate implementation of similar process using data and examinations at the Daiichi Units 1, 2, and 3 reactors so that BWR-specific benefits can be obtained.
The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program User Facility produces ground-based long-term continuous unique measurements for atmospheric state, precipitation, turbulent fluxes, radiation, aerosol, cloud and the land surface, which are collected at multiple sites. These comprehensive datasets have been widely used to calibrate climate models and are proven to be invaluable for climate model development and improvement. This article introduces an evaluation package to facilitate the use of ground-based ARM measurements in climate model evaluation. The ARM data-oriented metrics and diagnostics package (ARM-DIAGS) includes both ARM observational datasets and a Python-based analysis toolkit for computation and visualization. The observational datasets are compiled from multiple ARM data products and specifically tailored for use in climate model evaluation. In addition, ARM-DIAGS also includes simulation data from models participating the Coupled Model Inter-comparison Project (CMIP), which will allow climate-modeling groups to compare a new, candidate version of their model to existing CMIP models. The analysis toolkit is designed to make the metrics and diagnostics quickly available to the model developers.
Various numerical analysis schemes for the classification of remotely sensed data are evaluated with respect to their capabilities for crop identification. A per point Gaussian maximum likelihood classifier, per point sum-of-normal-densities classifier, per point linear classifier, per point Gaussian maximum likelihood decision tree classifier and a texture-sensitive per field Gaussian maximum likelihood classifier were applied to seven sets of Landsat MSS data on several crop types and regions. The results of the implementation of the classifiers indicate that, given a representative set of training statistics, the choice of classification algorithm of the differentiation of corn and soybeans from one another and from other crop types made relatively little difference in accuracy, whereas the use of a different training method affected the accuracy significantly. In addition, the linear classifier is found to be the easiest for the analyst to use and to cost least in computer time per classification.
This is the eighth in a series of evaluated sets of rate constants and photochemical cross sections compiled by the NASA Panel for Data Evaluation. The primary application of the data is in the modeling of stratospheric processes, with particular emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena. Copies of this evaluation are available from the Jet Propulsion Laboratory, Documentation Section, 111-116B, California Institute of Technology, Pasadena, California, 91109.
Representative data spans covering a little more than a year since the LANDSAT-4 launch were analyzed to evaluate the flight performance of the satellite's horizon scanner. High frequency noise was filtered out by 128-point averaging. The effects of Earth oblateness and spacecraft altitude variations are modeled, and residual systematic errors are analyzed. A model for the predicted radiance effects is compared with the flight data and deficiencies in the radiance effects modeling are noted. Correction coefficients are provided for a finite Fourier series representation of the systematic errors in the data. Analysis of the seasonal dependence of the coefficients indicates the effects of some early mission problems with the reference attitudes which were computed by the onboard computer using star trackers and gyro data. The effects of sun and moon interference, unexplained anomalies in the data, and sensor noise characteristics and their power spectrum are described. The variability of full orbit data averages is shown. Plots of the sensor data for all the available data spans are included.
NASA's traditional science data processing systems have focused on specific missions, and providing data access, processing and services to the funded science teams of those specific missions. Recently NASA has been modifying this stance, changing the focus from Missions to Measurements. Where a specific Mission has a discrete beginning and end, the Measurement considers long term data continuity across multiple missions. Total Column Ozone, a critical measurement of atmospheric composition, has been monitored for'decades on a series of Total Ozone Mapping Spectrometer (TOMS) instruments. Some important European missions also monitor ozone, including the Global Ozone Monitoring Experiment (GOME) and SCIAMACHY. With the U.S.IEuropean cooperative launch of the Dutch Ozone Monitoring Instrument (OMI) on NASA Aura satellite, and the GOME-2 instrumental on MetOp, the ozone monitoring record has been further extended. In conjunction with the U.S. Department of Defense (DoD) and the National Oceanic and Atmospheric Administration (NOAA), NASA is now preparing to evaluate data and algorithms for the next generation Ozone Mapping and Profiler Suite (OMPS) which will launch on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in 2010. NASA is constructing the Science Data Segment (SDS) which is comprised of several elements to evaluate the various NPP data products and algorithms. The NPP SDS Ozone Product Evaluation and Test Element (PEATE) will build on the heritage of the TOMS and OM1 mission based processing systems. The overall measurement based system that will encompass these efforts is the Atmospheric Composition Processing System (ACPS). We have extended the system to include access to publically available data sets from other instruments where feasible, including non-NASA missions as appropriate. The heritage system was largely monolithic providing a very controlled processing flow from data.ingest of satellite data to the ultimate archive of specific operational data products. The ACPS allows more open access with standard protocols including HTTP, SOAPIXML, RSS and various REST incarnations. External entities can be granted access to various modules within the system, including an extended data archive, metadata searching, production planning and processing. Data access is provided with very fine grained access control. It is possible to easily designate certain datasets as being available to the public, or restricted to groups of researchers, or limited strictly to the originator. This can be used, for example, to release one's best validated data to the public, but restrict the "new version" of data processed with a new, unproven algorithm until it is ready. Similarly, the system can provide access to algorithms, both as modifiable source code (where possible) and fully integrated executable Algorithm Plugin Packages (APPs). This enables researchers to download publically released versions of the processing algorithms and easily reproduce the processing remotely, while interacting with the ACPS. The algorithms can be modified allowing better experimentation and rapid improvement. The modified algorithms can be easily integrated back into the production system for large scale bulk processing to evaluate improvements. The system includes complete provenance tracking of algorithms, data and the entire processing environment. The origin of any data or algorithms is recorded and the entire history of the processing chains are stored such that a researcher can understand the entire data flow. Provenance is captured in a form suitable for the system to guarantee scientific reproducability of any data product it distributes even in cases where the physical data products themselves have been deleted due to space constraints. We are currently working on Semantic Web ontologies for representing the various provenance information. A new web site focusing on consolidating informaon about the measurement, processing system, and data access has been established to encourage interaction with the overall scientific community. We will describe the system, its data processing capabilities, and the methods the community can use to interact with the standard interfaces of the system.
This archive provides scripts, input files, and datasets used for the implementation and evaluation of a fully coupled surface–subsurface hydrologic model in the Neches River Basin, southeast Texas. The study uses the Advanced Terrestrial Simulator (ATS) to simulate coupled surface–subsurface hydrologic processes over a mixed urban–rural watershed and evaluates model performance using a dense network of 136 in situ water-level sensors, nine U.S. Geological Survey (USGS) stream gauges, and SSEBop-derived evapotranspiration estimates during the period October 2014–June 2024. The workflow is implemented primarily in Python 3 using the Watershed Workflow package. The Jupyter notebooks can be executed using open-source software such as Anaconda JupyterLab or Visual Studio Code. Other data files include TXT, CSV, XML, SHP, TIF, NetCDF, HDF5, and ExodusII files, which can be processed using the provided Python scripts. ATS input files are provided in XML format and can be edited using any commonly used text editor. This archive contains: *Scripts and input files used to generate the ATS model setup, including watershed discretization, mesh generation, parameter mapping, and model configuration. *Jupyter notebooks used for preprocessing observational data, evaluating streamflow, water levels, and evapotranspiration, computing performance metrics, and generating the figures presented in the manuscript. *ATS simulation outputs and processed observational datasets, including OneRain and DD6 water-level sensors, USGS streamflow observations, GIS data, and supporting spatial datasets used throughout the study.
This is the eleventh in a series of evaluated sets of rate constants and photochemical cross sections compiled by the NASA Panel for Data Evaluation. The primary application of the data is in the modeling of stratospheric processes, with special emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena.
The feasibility of GEANT4 and PHITS with ENDF/B-VIII.0, JEFF-3.3 and JENDL-4.0 evaluated nuclear data libraries in 14.8-MeV neutron transport simulation are verified by comparing with the MCNP calculations and the experimental data. Here the measured data are from neutron integral experiments including graphite and polyethylene samples. For 6 cm-thick polyethylene and 20 cm-thick graphite samples, the results from GEANT4 and PHITS with three evaluated nuclear data libraries agree well with the MCNP calculations. For a 2 cm-thick graphite sample, the simulated results from GEANT4 and PHITS agree with the MCNP calculations, and they all underestimate the experiment data in below 3 MeV and overestimate them in the energy range of 5–7 MeV. The difference between the simulation results and the experimental data depends on the evaluated nuclear data libraries. In overall, GEANT4 and PHITS are performing reasonable jobs for 14.8-MeV neutron transport simulations.
The evaluated spectroscopic data are presented for known nuclides of mass 228 (Ac, At, Fr, Np, Pa, Pu, Ra, Rn, Th, and U). Excited states in {sup 228}At, {sup 228}Rn, {sup 228}Fr, {sup 228}Np, and {sup 228}Pu have not been identified as yet. Significant amounts of new data have been added since the last evaluation of A=228 nuclides. This work supersedes earlier full evaluations of A=228 published by 1997Ar08.
Handbook for performance evaluation and cost effectiveness of extravehicular functions in manned space flight
Detailed level schemes, decay schemes, and the experimental data on which they are based are presented for all nuclei with mass number A=248. The experimental reaction and decay data are evaluated; inconsistencies and discrepancies are noted; and adopted values are given for various level properties (including spin and parity, halflife, and configuration), γ properties (including energy, intensity, and multipole character) and α properties (including energy, intensity, and hindrance factor). This evaluation replaces the A=248 evaluation published by A. Akovali in Nuclear Data Sheets 87, 249 (1999)