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NASA NTRS1994

Regional rainfall climatologies derived from Special Sensor Microwave Imager (SSM/I) data

Climatologies of convective precipitation were derived from passive microwave observations from the Special Sensor Microwave Imager using a scattering-based algorithm of Adler et al. Data were aggregated over periods of 3-5 months using data from 4 to 5 years. Data were also stratified by satellite overpass times (primarily 06 00 and 18 00 local time). Four regions (Mexico, Amazonia, western Africa, and the western equatorial Pacific Ocean (TOGA COARE area) were chosen for their meteorological interest and relative paucity of conventional observations. The strong diurnal variation over Mexico and the southern United States was the most striking aspect of the climatologies. Pronounced morning maxima occured offshore, often in concativities in the coastline, the result of the increased convergence caused by the coastline shape. The major feature of the evening rain field was a linear-shaped maximum along the western slope of the Sierra Madre Occidental. Topography exerted a strong control on the rainfall in other areas, particularly near the Nicaragua/Honduras border and in Guatemala, where maxima in excess of 700 mm/month were located adjacent to local maxima in terrain. The correlation between the estimates and monthly gage data over the southern United States was low (0.45), due mainly to poor temporal sampling in any month and an inadequate sampling of the diurnal cycle. Over the Amazon Basin the differences in morning versus evening rainfall were complex, with an alternating series of morning/evening maxima aligned southwest to northeast from the Andes to the northeast Brazilian coast. A real extent of rainfall in Amazonia was slightly higher in the evening, but a maximum in morning precipitation was found on the Amazon River just east of Manaus. Precipitation over the water in the intertropical convergence zone (ITCZ) north of Brazil was more pronounced in the morning, and a pronounced land-/sea-breeze circulation was found along the northeast coast of Brazil. Inter-comparison of four years revealed 1992 to be the driest over Amazonia, with about a 23% decrease in mean rate compared to the 4-year mean estimated rain rate.

Negri, Andrew J.↗

DOE OSTI2024

Availability and Performance Loss Factors for U.S. PV Fleet Systems

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data and publish aggregated, anonymized results. This report is an update of our previous publications, specifically a FY 2021 performance index publication and a FY 2022 fleet degradation analysis. In this analysis, we have increased our data participants and system totals by around 10% to 8.5 GW and 24,000 separate inverter data channels. Four major analysis topics are considered in this report: Performance Index (PI) trends, PV system availability, soiling losses, and PV system degradation. Performance Index and inverter availability are assessed on a larger set of data from our FY 2021 report: 1,128 systems compared with 200 systems from before. The increased number of systems is due to an improved data quality methodology, as well as introducing new systems to the analysis. Overall results are similar to previously published values - overall inverter availability is low in the first six months of system performance before reaching steady-state by the end of the first year. Excluding this six-month startup period, system-level aggregated data shows a median (P50) system availability of 0.99 and a lower 10th percentile (P90) value of 0.95 (Figure ES-1). A dependence on system size is also demonstrated, with worse inverter availability results for larger PV systems. Causes of this effect are under investigation, but may be impacted by inverter size, which also show lower availability for larger inverter sizes. This report also investigates PI, correcting for degradation, soiling, snow, and availability. Following these corrections, the median system PI over its entire lifetime is 0.95. PI values reported here are approximately 3% lower than what we presented in our previous FY 2021 report. Soiling loss is assessed in a comprehensive way for the first time in this report. Results are presented using the COmbined Degradation and Soiling (CODS) method, as implemented in RdTools (v3.0.0a4). Soiling values are presented for 255 systems, which indicated irradiance-weighted soiling loss greater than 1%. The values have been published in an updated NREL soiling map at nrel.gov/pv/soiling.html. Finally, we investigated system degradation using three different data analysis techniques: conventional RdTools (year-on-year (YOY)), CODS, and Performance Loss Rate (PLR) analysis. Overall degradation results are consistent with our previous publications. Rerunning conventional RdTools on our updated fleet shows that some data partners have systematically fallen below the median system degradation rate (change over time) of -0.75 %/year. A comparison with PLR analysis, which looks at change in annual PI over time, shows that median system degradation is consistent with -0.5% to -0.75% per year change. However, at the P90 value, system degradation is substantially faster. These two results are consistent and indicate that resulting degradation statistics depend to a great degree on the population of PV systems making up the analysis cohort and whether soiling impacts the systems. The use of CODS for degradation analysis provides a different method for degradation assessment, which explicitly excludes the impact of recoverable soiling on degradation analysis. Excluding soiling effects yields an annual system degradation around -0.5% per year on average. This indicates that a portion of system performance loss may be attributed to periodic soiling that is not fully recovered. This report provides PV system owners/operators with background and methods to analyze PV system performance, give guidance for expected cohort performance, and performance loss values for use in pro-forma financial models, which guide new-build system design and bankability reports.

14 SOLAR ENERGY↗

DOE OSTI2025

Uranium particle age dating, aggregation, and model age best estimators

We present important aspects of uranium particle age dating by Large-Geometry Secondary Ion Mass Spectrometry (LG-SIMS) that can introduce bias and increase model age uncertainties, especially for small, young, and/or low-enriched particles. This metrology is important for applications related to International Nuclear Safeguards. We explore influential factors related to model age estimation, including the effects of evolving surface chemistry on inter-element measurements of particles (e.g., Th and U), detector background, and aggregation methods using simulated and actual particle samples. We introduce a new model age estimator, called “mid68”, that supplements 95% confidence intervals, providing a “best estimate” and uncertainty about the most likely age. The mid68 estimator can be calculated using the Feldman and Cousins method or Bayesian methods and provides a value with a symmetric uncertainty that can be used for calculations and approximate aggregation of processed model age values when the raw data and correction factors are not available. For particles yielding low 230 Th counts amidst nonzero detector background, their underlying model age probability distributions are asymmetric, so the mid68 estimator provides additional robust information regarding the underlying model age likelihood. This study provides a comprehensive and timely examination of critical aspects of uranium particle age dating as more laboratories establish particle chronometry capabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

BASIN-3D Data Integration for Selected ARM Data Field Campaign Report

The purpose of this data services request was to demonstrate integration of the Atmospheric Radiation Measurement (ARM) User Facility’s “met” datastreams with time series data from other earth science data sources using the BASIN-3D data synthesis software tool. BASIN-3D is an open-source Python library that enables researchers to integrate data across configured public and private data sources. It provides a common query language for researchers to request measurement locations and time series data based on specified locations, variables, time period, statistics, aggregation, and data quality. BASIN-3D acquires the data that match the query from each configured data source and translates the results into harmonized vocabularies, thus reducing researchers' data-wrangling effort. In addition, because the queries are executed on demand, researchers can easily regenerate their synthesized data sets as new data and/or data updates become available, eliminating one-off data products. BASIN-3D can output data using a variety of different data structures for end-user applications including Python pandas data frames and hdf5 output formats.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗

DOE OSTI2024

Offshore Geologic Carbon Storage Data Collection and International Project Inventory

We present an interactive data collection to aggregate, understand, and disseminate the data that are publicly available to support offshore GCS which can be leveraged by stakeholders to understand where GCS may be viable offshore, create GCS project analogs, and address challenges to GCS in offshore environments. The Offshore Geologic Carbon Storage Data Collection is an Experience Builder web application of multiple web mapping applications, aggregated into a single tool for each data type for access, visualization, and exploration. We also present a spatial inventory of global offshore GCS efforts to visualize the scale and locations of actualized and potential offshore GCS. It includes project location, project type and stage, CO2 storage resource potential, injection rate, reservoir and seal geology, and key literature references. Quantitative and qualitative comparisons of the distribution and magnitude of projects by their attributes lends spatial insight into the status of global GCS operations and storage resource potential, thereby enabling comparative assessments and cross-cutting knowledge transfer for projects in development. These datasets illuminate trends in ongoing offshore projects and can be leveraged by stakeholders to estimate storage resources, identify subsurface analogs, review regulations, and address challenges to offshore GCS. Additionally, opportunities for concurrent decarbonization strategies can be identified.

Mulhern, Julia↗

DOE OSTI2024

International Offshore Geologic Carbon Storage Project Inventory and Data Collection

Mulhern, Julia↗

DOE OSTI2024

International Offshore Geologic Carbon Storage Inventory and Data Collection

Mulhern, Julia↗

NASA NTRS2014

Data Albums: An Event Driven Search, Aggregation and Curation Tool for Earth Science

Approaches used in Earth science research such as case study analysis and climatology studies involve discovering and gathering diverse data sets and information to support the research goals. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. In cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. This paper presents a specialized search, aggregation and curation tool for Earth science to address these challenges. The search rool automatically creates curated 'Data Albums', aggregated collections of information related to a specific event, containing links to relevant data files [granules] from different instruments, tools and services for visualization and analysis, and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non relevant information and data.

Ramachandran, Rahul↗

NASA NTRS1999

Psychological changes in hundred-day remote Antarctic field groups

Psychological adaptation to extreme environments has been examined from several perspectives. In this study, two Australian teams, each consisting of six male crew members, completed computer-administered questionnaires twice weekly during 100-day traverses around the Lambert Glacier Basin, Antarctica. Only small trends were noted when data were aggregated at the group level, which is consistent with the findings of others. Data were then analyzed using pooled time-series regression. These analyses incorporated personality characteristics, environmental factors, and interpersonal factors as predictors of Group Tensions, Personal Morale, Emotional State, Cognitive Readiness, and the Team's Work Life. Most of the psychological discomfort and problems that occurred appeared to be within the individual or between individuals. They did not affect all members of the group equally.

NASA Discipline Space Human Factors↗

DOE OSTI2021

Evaluation of a Surface Spill Operation to Return Adult Steelhead Overshoots Downstream of McNary Dam

This study, funded by the U.S. Army Corps of Engineers (USACE), was conducted by the Pacific Northwest National Laboratory to evaluate the efficacy of operating one Top Spill Weir (TSW) at McNary Dam outside the normal TSW operation dates for juvenile salmon passage. Of interest is whether the TSW is an effective downstream passage route for adult steelhead overshoots. Overshoots are fish which, having passed upstream at McNary Dam, must pass downstream to return to their natal stream to spawn. This report covers Fall (2019) and Spring (2020) study periods. The study design arranged the available 24 hours of TSW spill per week into weekly blocks with sub-blocks differentiated into day and night operations with TSW discharge periods of 4- and 8-hours duration. Hydroacoustic techniques were used to sample adult fish passage at the TSW and at turbine units 1 and 10. The experimental design contrasted TSW spill periods of differing duration and at different times of the day. The small number of fish detected passing the TSW, and the smaller number of fish detected passing the turbine units, were best suited to an ad hoc, exploratory approach to evaluating the effect of TSW spill. It is worthwhile to note that the operations data obtained for the fall study period had a greater than expected number of gaps and apparent anomalies that we believe were a result of how the data were aggregated. These problems are not particularly problematic for the present study, because the available data still provide a good indication of whether the TSW was operating at each point in time. TSW flows in both fall and spring data sets were able to be cleaned up using the established relationship between forebay elevation and TSW discharge rate. Additional cleanup of operations data would be needed, however, if more quantitative evaluation of dam-wide flow and passage relationships were needed. This study contrasted TSW spill periods of differing duration and at different times of the day. The small number of fish detected passing the TSW, and the smaller number of fish detected passing the turbine units were best suited to an ad hoc, exploratory approach to evaluating the effect of TSW spill. Spring adult steelhead passage numbers estimated using hydroacoustics were notably lower than during the fall study period, and that was consistent with our analysis of PIT tagged fish likely to be in the vicinity during each study period. Detections of fish in BlueView sampling areas upstream of the TSW and powerhouse were not correlated with detections of fish passing hydroacoustic sampling areas, which suggests that fish approaching the face of the dam can move around the forebay before passing. Other fish detected in the forebay in large numbers, such as shad, were able to be filtered out of steelhead passage counts and did not appear to be influencing hydroacoustic passage rate estimates. A pulse of passage at the initial TSW opening was weakly evident, but trends across 4- and 8-hour operational periods did not show a distinct decline in passage over time as TSW operation continued. Our findings do not indicate a reason to choose one 8-hour period over two 4-hour periods, or vice versa. This suggests that the duration of spill periods can be chosen based on operational or other considerations. Passage rates were consistently higher during the daytime TSW discharge periods, relative to nighttime TSW discharge periods. The experimental design of the current study used start times near dawn for day periods and near dusk for night periods.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1987

A critical assessment of wind tunnel results for the NACA 0012 airfoil

A large body of experimental results, obtained in more than 40 wind tunnels on a single, well-known two-dimensional configuration, has been critically examined and correlated. An assessment of some of the possible sources of error has been made for each facility, and data which are suspect have been identified. It was found that no single experiment provided a complete set of reliable data, although one investigation stands out as superior in many respects. However, from the aggregate of data the representative properties of the NACA 0012 airfoil can be identified with reasonable confidence over wide ranges of Mach number, Reynolds number, and angles of attack. This synthesized information can now be used to assess and validate existing and future wind tunnel results and to evaluate advanced Computational Fluid Dynamics codes.

Mccroskey, W. J.↗

NASA NTRS1988

A critical assessment of wind tunnel results for the NACA 0012 airfoil

A large body of experimental results, obtained in more than 40 wind tunnels on a single, well known two-dimensional configuration, was critically examined and correlated. An assessment of some of the possible sources of error was made for each facility, and data which are suspect were identified. It was found that no single experiment provided a complete set of reliable data, although an investigation stands out as superior in many respects. However, from the aggregate of data the representative properties of the NACA 0012 airfoil can be identified with reasonable confidence over wide range of Mach numbers, Reynolds number, and angles of attack. This synthesized information can now be used to assess and validate existing and future wind tunnel results and to evaluate advanced Computational Fluid Dynamics codes.

Mccroskey, W. J.↗

DOE OSTI2022

Multi-Kernel Adaptive Support Vector Machine for Scalable Predictive Maintenance

Application of data-driven solutions across an industry is challenging, since the data are often stored locally, and increasing privacy and security concerns restrict access to the data. In addition, it is highly unlikely that all potential data patterns are captured in a single data source. Because it is highly unlikely that all potential data patterns are captured in a single data source, machine learning (ML) models developed from a single source cannot be robust enough. An alternative is to train the ML model at each source and develop a distributed knowledge discovery and aggregation approach to build global knowledge. In this paper, we develop and demonstrate a distributed ML model, federated transfer learning (FTL), using a multi-kernel-based adaptive support vector machine (MK-A-SVM). For federated learning (FL), the multi-kernel (MK) approach enables feature-specific model aggregation under data heterogeneity; whereas for transfer learning (TL) the adaptive model enables utilization of an aggregated model from a different task. The proposed approach is validated using nuclear power plant (NPP) vertical motor-driven pump data to predict the health condition of vertical motor-driven pumps as an anomaly detection. The efficiency of the proposed approach is also quantified and compared with neural network.

42 ENGINEERING↗

NASA NTRS2021

Trend Detection of Atmospheric Time Series: Incorporating Appropriate Uncertainty Estimates and Handling Extreme Events

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to, 1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry; 2) describe a range of trend-detection methods; and 3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short- and long-term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to, 1) review trend detection methods for addressing different levels of data complexity in different chemical species; 2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability; 3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates; and 4) present an advanced method of quantifying regional trends based on the inter-site correlations of multi-site data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

Trace gas↗

NASA NTRS1990

Is it possible to identify a trend in problem/failure data

One of the major obstacles in identifying and interpreting a trend is the small number of data points. Future trending reports will begin with 1983 data. As the problem/failure data are aggregated by year, there are just seven observations (1983 to 1989) for the 1990 reports. Any statistical inferences with a small amount of data will have a large degree of uncertainty. Consequently, a regression technique approach to identify a trend is limited. Though trend determination by failure mode may be unrealistic, the data may be explored for consistency or stability and the failure rate investigated. Various alternative data analysis procedures are briefly discussed. Techniques that could be used to explore problem/failure data by failure mode are addressed. The data used are taken from Section One, Space Shuttle Main Engine, of the Calspan Quarterly Report dated April 2, 1990.

Church, Curtis K.↗

NASA NTRS2019

Standard Component Commodity Usage Guides (CUGs) for Charge-Coupled Devices (CCDs)

Communicating risk and reliability information within NASA Goddard’s missions is crucial to continuing the development of new technology and ensuring GSFC missions achieve their science objectives. The Reliability and Risk Assessment Branch (Code 371) within the SMA directorate is one of GSFC’s leaders in communicating this information to missions, and one tool 371 engineers use to provide this information is the Commodity Usage Guides (CUGs). CUGs are helpful in compiling various critical parameters and heritage information for standard payload components, ensuring project personnel inherit the lessons learned from previous experiences. The purpose of this project was to create CUGs for CCDs used within GSFC missions. To formulate a CUG applicable data was aggregated into the CUG template for Charge-Coupled Devices (CCDs)--electro-optical components used to convert photons into digital images and data. CCDs can easily be adapted to a variety of mission requirements making them widely used at GSFC, and therefore suitable for CUGs. Once the CUGs for CCDs are completed the information can be distributed to engineers, scientists and other project members to ensure the lessons learned are passed on to the next mission.

Christman, Jerika H.↗

NASA NTRSDate not supplied

Cross-Measurement Comparisons for a CFD Validation Dataset on Mach 2.5 Axisymmetric Turbulent Shock-Wave/Boundary-Layer Interactions

Experimental data for a shock-wave/boundary-layer interaction has been collected using multiple measurement techniques. Unfortunately, diversity of methods for acquisition begets an aggregation of data which does not directly quantify the same properties of the flowfield. The objective in this paper was to (a) present the collection of flowfield measurements in one venue in a format more usable for those validating CFD models against the data, (b) evaluate the degree to which the experimental data support each other, and (c) highlight the differences and relative advantages/shortcomings of each measurement techniques. To present the various measured quantities into common format, CFD results from a companion paper also submitted for presentation at this meeting are utilized. For the case where the boundary layer remains attached, there is agreement between the various measurements as well as with Reynolds-averaged Navier-Stokes simulation solutions. As the impinging shock strength is increased beyond the point of separating the boundary layer, the congruity of the data wanes. Generally, agreement among the measurements exceeds the degree to which the CFD solutions agree with experiments. This suggests that unmodeled physical phenomena, such as transient motion of the reflected shock and separation bubble, give rise to the discrepancies observed in the computational results.

Shock-wave Boundary-layer interaction↗