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NASA NTRS2004

Evaluation of the AMSR-E Data Calibration Over Land

Land observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), particularly of soil and vegetation moisture changes, have numerous applications in hydrology, ecology and climate. Quantitative retrieval of soil and vegetation parameters relies on accurate calibration of the brightness temperature measurements. Analyses of the spectral and polarization characteristics of early versions of the AMSR-E data revealed significant calibration biases over land at 6.9 GHz. The biases were estimated and removed in the current archived version of the data Radiofrequency interference (RFI) observed at 6.9 GHz is more difficult to quanti@ however. A calibration analysis of AMSR-E data over land is presented in this paper for a complete annual cycle from June 2002 through September 2003. The analysis indicates the general high quality of the data for land applications (except for RFI), and illustrates seasonal trends of the data for different land surface types and regions.

Njoku, E.↗

DOE OSTI2025

Measuring the muon content of inclined air showers using AERA and the water-Cherenkov detectors of the Pierre Auger Observatory

We present a novel approach for assessing the muon content of air showers with large zenith angles on a combined analysis of their radio emission and particle footprint. We use the radiation energy reconstructed by the Auger engineering radio array (AERA) as an energy estimator and determine the muon number independently with the water-Cherenkov detector array of the Pierre Auger Observatory, deployed on a 1500 m grid. We focus our analysis on air showers with primary energy above 4 EeV to ensure full detection efficiency. Over approximately ten years of accumulated data, we identify a set of 40 high-quality events that are used in the analysis. The estimated muon contents in data are compatible with those for iron primaries as predicted by current-generation hadronic interaction models. This result can be interpreted as a deficit of muons in simulations as a lighter mass composition has been established from X max measurements. This muon deficit was already observed in previous analyses of the Auger Collaboration and is confirmed using hybrid events that include radio measurements for the first time.

Abdul Halim, A. [Adelaide U.]↗

DOE OSTI2021

Saline: An API for Thermophysical Properties

An initial interface for thermophysical data was generalized for broader incorporation into modeling and simulation codes used for molten salt reactor analysis. A quality assurance review of the thermophysical properties data was conducted; errors were fixed, and improvements were made with consistency and accuracy to references. The Saline code application programming interface was created to facilitate access and integration of thermophysical properties. This report describes the thermophysical data, the quality assurance improvements, and the Saline interface.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1996

A Description of the Software Element of the NASA EME Flight Tests

In support of NASA's Fly-By-Light/Power-By-Wire (FBL/PBW) program, a series of flight tests were conducted by NASA Langley Research Center in February, 1995. The NASA Boeing 757 was flown past known RF transmitters to measure both external and internal radiated fields. The aircraft was instrumented with strategically located sensors for acquiring data on shielding effectiveness and internal coupling. The data are intended to support computational and statistical modeling codes used to predict internal field levels of an electromagnetic environment (EME) on aircraft. The software was an integral part of the flight tests, as well as the data reduction process. The software, which provided flight test instrument control, data acquisition, and a user interface, executes on a Hewlett Packard (HP) 300 series workstation and uses BP VEEtest development software and the C programming language. Software tools were developed for data processing and analysis, and to provide a database organized by frequency bands, test runs, and sensors. This paper describes the data acquisition system on board the aircraft and concentrates on the software portion. Hardware and software interfaces are illustrated and discussed. Particular attention is given to data acquisition and data format. The data reduction process is discussed in detail to provide insight into the characteristics, quality, and limitations of the data. An analysis of obstacles encountered during the data reduction process is presented.

Koppen, Sandra V.↗

NASA NTRSDate not supplied

The NASA Merra-2 Reanalysis Products: Data and Tools Used for Aerosol and Air Quality Studies

The NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is atmospheric reanalysis data spanning 1980 to present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data includes 100 collections of Earth system variables, mainly from the atmospheric model, such as aerosol fields and meteorological fields, radiation fields, and aerosol fields, guided by the assimilation of as many as six million observations every six hours. MERRA-2 has been one of the most popular datasets from NASA and is widely used in interdisciplinary research and applications, with increasing numbers of new users. For example, at least 7000 users accessed MERRA-2 data at GES DISC in the year 2021, ~1000 more users than in the year 2020. In this presentation, we will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use a wildfire case study to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and the level 3 and level 4 subsetter, and Jupyter Python notebook. We will also update the status of cloud migration of the MERRA-2 data to Amazon Web Services (AWS).

Xiaohua Pan↗

DOE OSTI2024

Automated Algorithms for Screening Electronic Parts for Aging using Power Spectra Analysis (PSA) Data

Understanding the age of semiconductor parts being built into devices and systems is of interest for manufacturing quality control. Power spectrum analysis (PSA) is a fast, non-destructive, sensitive method for examining semiconductor parts. This talk will cover the use of multivariate analysis on both PSA data and conventional current-voltage data generated prior to PSA analysis to create algorithms that can be automated to screen semiconductor parts for aging.

Multari, Rosalie A↗

DOE OSTI2025

Integrated Methane Monitoring Platform Extension, Volume I: Final Technical Report

The IMMPE project, DE-FE0032284, was to enhance methane monitoring technologies and their applications across various natural gas asset classes. The scope included deploying advanced methane detection and monitoring technologies to identify and mitigate fugitive methane emissions, measuring emission rates, and assessing impacts. The findings included the successful mitigation of identified emissions and quantification of emission rates. A key outcome was the development of a comprehensive template and summary of recommendations for methane emissions monitoring, which is replicable for both upstream and downstream applications. Furthermore, the project emphasized the importance of education by providing training opportunities for technicians and regulators, thereby fostering awareness and promoting the adoption of cost-effective methane emissions monitoring and management techniques.

02 PETROLEUM↗

NASA NTRS1991

Geography of cretaceous extinctions: Data base development

Data bases built from the source literature are plagued by problems of data quality. Unless the data acquisition is done by experts, working slowly, the data base may contain so much garbage that true signals and patterns cannot be detected. On the other hand, high quality data bases develop so slowly that satisfactory statistical analysis may never be possible due to the small sample sizes. Results of a test are presented of the opposite strategy: rapid data acquisition by non-experts with minimal control on data quality. A published list of 186 species and genera of fossil invertibrates of the latest Cretaceous Age (Maestrichtian) were located through a random search of the paleobiological and geological literature. The geographic location for each faunal list was then transformed electronically to Maestrichtian latitude and longitude and the lists were further digested to identify the genera occurring in each ten-degree, latitude-longitude block. The geographical lists were clustered using the Otsuka similarity coefficient and a standard unweight-pair-group method. The resulting clusters are remarkably consistent geographically, indicating that a strong biogeographic signal is visible despite low-quality data. A further test evaluated the geographic pattern of end-Cretaceaous extinctions. All genera in the data base were compared with Sepkoski's compendium of time ranges of genera to determine which of the reported genera survived the Cretaceous mass extinction. In turn, extinction rates for the ten-degree, latitude-longitude blocks were mapped. The resulting distribution is readily interpretable as a robust pattern of the geography of the mass extinction. The study demonstrates that a low-quality data base, built rapidly, can provide a basis for meaningful analysis of past biotic events.

Raup, D. M.↗

DOE OSTI2022

Investigation of the 176 Yb Interference Correction during Determination of the 176 Hf/ 177 Hf Ratio by Laser Ablation and Solution Analysis on the Neoma MC-ICP-MS

We utilized the Neoma™, a recently released MC-ICP-MS platform offered by ThermoFisher Scientific, to assess the behavior of the Lu-Yb-Hf system during laser ablation analyses of various zircon standards as well as solution-based analyses of the JMC-475 Hf standard doped with varying quantities of Yb and Lu. The primary goal of this work was to characterize the behavior of the Yb interference correction on the Neoma™ platform since this is one of the biggest issues in the Hf isotope analysis community and because the Neoma™ platform will supplant the Neptune™ series instrument. During laser ablation analysis, we found that the overall data quality scales proportionally with the total Hf signal intensity, with higher signal analyses producing extremely accurate (within 1 ε Hf unit) and precise (sub ε Hf unit within-run standard errors) data. At low Yb signals (<0.1 V 173 Yb), we were not able to produce an accurate internal Yb mass bias factor. However, utilizing an empirical approach allows for the application of session-specific relationships between the Yb and Hf mass bias factors, determined by analysis of standards of varying Yb content, to produce accurate ε Hf values from zircons with higher Yb/Hf ratios even where the total Hf signal intensity is relatively low. Similar behavior was observed in the solution analyses. Lastly, while the behavior of the Yb interference correction on the Neoma™ platform appears comparable to the Neptune™ series MC-ICP-MS, further work will help refine the understanding of the controls on mass bias behavior, oxide formation, session-to-session stability, etc.

36 MATERIALS SCIENCE↗

NASA NTRS2014

Robust Informatics Infrastructure Required For ICME: Combining Virtual and Experimental Data

With the increased emphasis on reducing the cost and time to market of new materials, the need for robust automated materials information management system(s) enabling sophisticated data mining tools is increasing, as evidenced by the emphasis on Integrated Computational Materials Engineering (ICME) and the recent establishment of the Materials Genome Initiative (MGI). This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Further, the use of increasingly sophisticated nonlinear, anisotropic and or multi-scale models requires both the processing of large volumes of test data and complex materials data necessary to establish processing-microstructure-property-performance relationships. Fortunately, material information management systems have kept pace with the growing user demands and evolved to enable: (i) the capture of both point wise data and full spectra of raw data curves, (ii) data management functions such as access, version, and quality controls;(iii) a wide range of data import, export and analysis capabilities; (iv) data pedigree traceability mechanisms; (v) data searching, reporting and viewing tools; and (vi) access to the information via a wide range of interfaces. This paper discusses key principles for the development of a robust materials information management system to enable the connections at various length scales to be made between experimental data and corresponding multiscale modeling toolsets to enable ICME. In particular, NASA Glenn's efforts towards establishing such a database for capturing constitutive modeling behavior for both monolithic and composites materials

Mutli-scale models↗

DOE OSTI2021

Evaluation of Differential Peptide Loading on Tandem Mass Tag-Based Proteomic and Phosphoproteomic Data Quality

Global and phosphoproteome profiling has demonstrated great utility for the analysis of clinical specimens. One major barrier to the broad clinical application of proteomic profiling is the large amount of biological material required, particularly for phosphoproteomics—currently on the order of 25 mg wet tissue weight, depending on tissue type. For hematopoietic cancers such as acute myeloid leukemia (AML), the sample requirement is in excess of 10 million (1E7) peripheral blood mononuclear cells (PBMCs). Throughout the course of a prospective study, this requirement will certainly exceed what is obtainable from many of the individual patients/timepoints. For this reason, we were interested in examining the impact of differential peptide loading across multiplex channels on proteomic data quality. Methods: To achieve this, we tested a range of channel loading amounts (20, 40, 100, 200, and 400 µg of tryptic peptides, or approximately the material obtainable from 5E5, 1E6, 2.5E6, 5E6, and 1E7 AML patient cells) to assess proteome coverage, quantification reproducibility and accuracy in experiments utilizing isobaric tandem mass tag (TMT) labeling. As expected, we found that fewer missing values are observed in TMT channels with higher peptide loading amounts compared to those with lower loading. Moreover, channels with lower loading amounts have greater quantitative variability than channels with higher loading amounts. Statistical analysis of the differences in means among the five loading groups showed that the 20 µg loading group was significantly different from the 400 µg loading group. However, no significant differences were detected among the 40, 100, 200 and 400 µg loading groups. Conclusions: These assessment data demonstrate the practical limits of loading differential quantities of peptides across channels in TMT multiplexes, and provide a basis for designing the optimal clinical proteomics study when specimen quantities are limited.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1999

Preliminary Results from a New Analysis Method for EGRET Data

In order to extend the life of EGRET, the gas in the spark chamber was allowed to deteriorate more than was originally planned for the nominal two year Compton Observatory mission. Gamma ray events are lost because the pattern recognition analysis rules are not optimized for the poorer quality data. By changing the rules used by the data analysts, we can recover a significant fraction of the lost events, allowing improved statistics for detection and study of sources. Preliminary results from the Crab, Geminga, and BL Lacertae indicate the feasibility of this analysis.

Thompson, D. J.↗

NASA NTRS1986

The March 1985 demonstration of the fiducial network concept for GPS geodesy: A preliminary report

The first field tests in preparation for the NASA Global Positioning System (GPS) Caribbean Initiative were conducted in late March and Early April of 1985. The GPS receivers were located at the POLARIS Very Long Base Interferometry (VLBI) stations at Westford, Massachusetts; Richmond, Florida; and Ft. Davis, Texas; and at the Mojave, Owens Valley, and Hat Creek VLBI stations in California. Other mobile receivers were placed near Mammoth Lakes, California; Pt. Mugu, California; Austin, Texas; and Dahlgren, Virginia. These sites were equipped with a combination of GPS receiver types, including SERIES-X, TI-4100 and AFGL dual frequency receivers. The principal objectives of these tests were the demonstration of the fiducial network concept for precise GPS geodesy, the performance assessment of the participating GPS receiver types, and to conduct the first in a series of experiments to monitor ground deformation in the Mammoth Lakes-Long Valley caldera region in California. Other objectives included the testing of the water vapor radiometers for the calibration of GPS data, the development of efficient procedures for planning and coordinating GPS field exercise, the establishment of institutional interfaces for future cooperating ventures, the testing of the GPS Data Analysis Software (GIPSY, for GPS Inferred Positioning SYstem), and the establishment of a set of calibration baselines in California. Preliminary reports of the success of the field tests, including receiver performance and data quality, and on the status of the data analysis software are given.

Davidson, J. M.↗

NASA NTRS1977

Analysis of transmission error effects on the transfer of real-time simulation data

An analysis was made to determine the effect of transmission errors on the quality of data transferred from the Terminal Area Air Traffic Model to a remote site. Data formating schemes feasible within the operational constraints of the data link were proposed and their susceptibility to both random bit error and to noise burst were investigated. It was shown that satisfactory reliability is achieved by a scheme formating the simulation output into three data blocks which has the priority data triply redundant in the first block in addition to having a retransmission priority on that first block when it is received in error.

Credeur, L.↗

NASA NTRS1984

Solar Seismology from Space. a Conference at Snowmass, Colorado

The quality of the ground based observing environment suffers from several degrading factors: diurnal interruptions and thermal variations, atmospheric seeing and transparency fluctuations and adverse weather interruptions are among the chief difficulties. The limited fraction of the solar surface observable from only one vantage point is also a potential limitation to the quality of the data available without going to space. Primary conference goals were to discuss in depth the scientific return from current observations and analyses of solar oscillations, to discuss the instrumental and site requirements for realizing the full potential of the seismic analysis method, and to help bring new workers into the field by collecting and summarizing the key background theory. At the conclusion of the conference there was a clear consensus that ground based observation would not be able to provide data of the quality required to permit a substantial analysis of the solar convection zone dynamics or to permit a full deduction of the solar interior structure.

Ulrich, R. K.↗

DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

Resistance Spot Welding (RSW) is a critical process in the automotive industry, valued for its cost-effectiveness, short cycle time, and robustness. However, achieving consistent high-quality joints remains challenging due to the complex interplay of various factors, like materials, processes, and manufacturing uncertainties, etc. Under the collaborative project between Oak Ridge National Laboratory (ORNL) and General Motors (GM), we have developed a robust and expansible machine learning (ML) framework aimed at enhancing quality control in RSW. By harnessing the power of machine learning, we have developed the ability to ensure every aspect of the welding process, from the initial process design stage to the final weld joint quality. The framework operates by analyzing a variety of data streams, including in-line process signals, process parameters, materials, and postprocessed weld joint data. Through this analysis, the models have been trained to detect deviations from optimal quality standards, leveraging their ability to identify signature data patterns and anomalies within in-line signals and construct complex correlations between these signals and weld quality parameters. Meanwhile, the machine learning framework is designed to adapt to a variety of materials, including high strength steels and aluminum alloys, etc. Its flexible architecture facilitates the incorporation of diverse data sources and features, enabling precise modeling and prediction across a broad range of material properties and weld quality variables. The expansible ML frameworks represent a promising transformation in weld quality monitoring and control, empowering industry to achieve high levels of efficiency, consistency, and reliability in manufacturing.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Machine Learning for Automated Weld Quality Monitoring and Control

42 ENGINEERING↗

DOE OSTI2025

A Markov chain Monte Carlo (MCMC) Bayesian inference approach to analyze apparent activation barriers and reaction orders from microreactor data

Statistical analysis of steady-state catalytic kinetic data is often limited by data sparsity due to the slow pace at which the data is collected. Data sparsity and limitations in statistical analysis make it difficult to differentiate between mechanistic models and catalytic sites. A Bayesian inference tool is reported for catalysis researchers to estimate error in the determination of reaction orders from steady state microreactor data. The benefits of a Bayesian inference approach are discussed, as an alternative to the more common frequentist approach. The approach incorporates prior knowledge of the system and the data collected to form an error estimate on reaction orders. We investigated the effects of three distinct data treatments—individual fitting of trials, pooled analysis, and constrained regression methods—on the precision and uncertainty of reaction order determinations. To assess the robustness of our findings, we conducted sensitivity analyses to evaluate the influence of Bayesian parameters on uncertainty estimation. Additionally, we utilized synthetic data to illustrate how data quality impacts the precision of uncertainty assessments. We show Bayesian analysis can obtain a more precise estimation of error with a sparse data set than a frequentist analysis. Finally, this work provides strong evidence that the adoption of Bayesian analysis of kinetic data may help researchers make more precise arguments as to the strength of their evidence for a particular mechanistic hypothesis, or in comparing across different catalysts.

42 ENGINEERING↗