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DOE OSTI2025

Forty-year hydropower generation reanalysis for Conterminous United States

First published in 2022, the RectifHyd dataset provides hydrologically consistent estimates of monthly net generation for approximately 1,500 hydropower plants in the United States, addressing a gap in industrial surveys that have collected monthly generation data from only ~10% of plants post-2003. Here we present RectifHydPlus—an extended and enhanced dataset that improves on both the proxy information and temporal downscaling methodology adopted in RectifHyd. In addition to providing updated estimates of historical monthly generation for 590 plants with >10 MW nameplate capacity from 1980 through 2019, RectifHydPlus adds a hydrological control dataset that isolates the influence of historical water availability on generation. The new hydrological control dataset is suited to applications seeking to represent the capabilities of the contemporary fleet subject to historical interannual variability in climate. RectifHydPlus also includes a forty-year, daily-resolution, spill-adjusted water release time series for each dam, allowing users to aggregate generation estimates to the desired temporal resolution.

Hydroelectricity↗

NASA NTRSDate not supplied

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗

NASA NTRS1995

Systolic Processor Array For Recognition Of Spectra

Spectral signatures of materials detected and identified quickly. Spectral Analysis Systolic Processor Array (SPA2) relatively inexpensive and satisfies need to analyze large, complex volume of multispectral data generated by imaging spectrometers to extract desired information: computational performance needed to do this in real time exceeds that of current supercomputers. Locates highly similar segments or contiguous subsegments in two different spectra at time. Compares sampled spectra from instruments with data base of spectral signatures of known materials. Computes and reports scores that express degrees of similarity between sampled and data-base spectra.

Chow, Edward T.↗

NASA NTRS2017

MiniWall Tool for Analyzing CFD and Wind Tunnel Large Data Sets

It is challenging to review and assimilate large data sets created by Computational Fluid Dynamics (CFD) simulations and wind tunnel tests. Over the past 10 years, NASA Ames Research Center has developed and refined a software tool dubbed the "MiniWall" to increase productivity in reviewing and understanding large CFD‐generated data sets. Under the recent NASA ERA project, the application of the tool expanded to enable rapid comparison of experimental and computational data. The MiniWall software is browser based so that it runs on any computer or device that can display a web page. It can also be used remotely and securely by using web server software such as the Apache HTTP Server. The MiniWall software has recently been rewritten and enhanced to make it even easier for analysts to review large data sets and extract knowledge and understanding from these data sets. This paper describes the MiniWall software and demonstrates how the different features are used to review and assimilate large data sets.

Data Analysis↗

NASA NTRS2026

Towards an Improved Understanding of the Antarctic Coastal Zone and Its Contribution to Future Global Sea Level

Understanding the coastal zone of the Antarctic Ice Sheet (AIS), where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate and sea level. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the AIS, the Southern Ocean and their global connections in the coming centuries. The AIS remains the largest source of uncertainty in future sea-level projections. Bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, and is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground- and ship-based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography data sets identifies significant data gaps and their regional distribution, framed in the context of current ice-sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next-generation data set of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice-sheet dynamics, reducing uncertainties in sea-level rise projections and improving predictions of future ocean and climate changes.

Kenichi Matsuoka↗

NASA NTRS1980

Automated frequency standard stability data reduction

A design using a medium sized computer, a fiber optic communication link, and a desk top computer to reduce data collected at a remote site for analysis of frequency standard tests is described. Data generated at the Interim Frequency Standards Test Facility is collected on magnetic tape, which is then transported to a Sigma 5 computer. An Allan variance (two sample variance) is then calculated. The Allan variance (sigma vs tau) is then written to a data file in the Sigma 5. A fiber optic communication link between the Sigma 5 and a desk top computer was designed to transmit data in the Sigma 5 file to the desk top computer. A program was written for the desk top computer that will automatically access the data file in the Sigma 5, process the data and provide a data plot.

Knapp, L. J.↗

NASA NTRS2017

MiniWall Tool for Analyzing CFD and Wind Tunnel Large Data Sets

It is challenging to review and assimilate large data sets created by Computational Fluid Dynamics (CFD) simulations and wind tunnel tests. Over the past 10 years, NASA Ames Research Center has developed and refined a software tool dubbed the MiniWall to increase productivity in reviewing and understanding large CFD-generated data sets. Under the recent NASA ERA project, the application of the tool expanded to enable rapid comparison of experimental and computational data. The MiniWall software is browser based so that it runs on any computer or device that can display a web page. It can also be used remotely and securely by using web server software such as the Apache HTTP server. The MiniWall software has recently been rewritten and enhanced to make it even easier for analysts to review large data sets and extract knowledge and understanding from these data sets. This paper describes the MiniWall software and demonstrates how the different features are used to review and assimilate large data sets.

Computational Fluid Dyanmics↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

activity planning↗

NASA NTRS2022

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗

NASA NTRS2013

Determining Component Probability using Problem Report Data for Ground Systems used in Manned Space Flight

During the shuttle era NASA utilized a failure reporting system called the Problem Reporting and Corrective Action (PRACA) it purpose was to identify and track system non-conformance. The PRACA system over the years evolved from a relatively nominal way to identify system problems to a very complex tracking and report generating data base. The PRACA system became the primary method to categorize any and all anomalies from corrosion to catastrophic failure. The systems documented in the PRACA system range from flight hardware to ground or facility support equipment. While the PRACA system is complex, it does possess all the failure modes, times of occurrence, length of system delay, parts repaired or replaced, and corrective action performed. The difficulty is mining the data then to utilize that data in order to estimate component, Line Replaceable Unit (LRU), and system reliability analysis metrics. In this paper, we identify a methodology to categorize qualitative data from the ground system PRACA data base for common ground or facility support equipment. Then utilizing a heuristic developed for review of the PRACA data determine what reports identify a credible failure. These data are the used to determine inter-arrival times to perform an estimation of a metric for repairable component-or LRU reliability. This analysis is used to determine failure modes of the equipment, determine the probability of the component failure mode, and support various quantitative differing techniques for performing repairable system analysis. The result is that an effective and concise estimate of components used in manned space flight operations. The advantage is the components or LRU's are evaluated in the same environment and condition that occurs during the launch process.

Monaghan, Mark W.↗

DOE OSTI2025

Initial Characterization of the NREL Large-Amplitude Motion Platform

The Large Amplitude Motion Platform (LAMP) at NREL represents a significant advancement in the controlled testing of Wave Energy Converters (WECs) under laboratory conditions. Originally designed by E2M as a six-degree-of-freedom (DOF) Stewart platform for flight simulation, LAMP has been adapted by NREL to facilitate the mounting and evaluation of WECs. This adaptation enables dry testing of WECs using motion profiles similar to the ocean, facilitating the iterative design, testing, and validation of WEC performance prior to ocean deployments. This report presents the initial work completed to characterize LAMP, with particular emphasis on its stability and operational capabilities across various single and multi-degree-of-freedom (DOF) motion profiles. The report includes planned comparisons at three distinct mass payloads, aimed at assessing the platform's positional accuracy, frequency response, and endurance over extended runtime periods. These experimental tests are critical for establishing the platform's limitations and ensuring that the data generated during WEC validation is both accurate and reproducible. The outcomes of this study not only contribute to a deeper understanding of LAMP's capabilities but also lay the groundwork for future advancements in WEC testing methodologies. By providing robust and reliable performance data within a controlled laboratory setting, the findings are expected to significantly enhance the development and commercialization of marine energy technologies. This report presents the initial findings of the LAMP Characterization work and proposed steps to further understand and characterize LAMP. Data collected during this work can be found on MHKDR at: https://mhkdr.openei.org/submissions/602 Note that this report shares the measured/found instantaneous maximum operating range of LAMP. For most applications the maximum operating range cannot be used for system health and longevity. The operating range and capabilities of LAMP will be evaluated on a case-by-case basis, single-DOF position, velocity, and acceleration values presented in Table 4a-c, and Table 5 should be taken as instantaneous absolute maximum values. Future use of LAMP will likely be limited to smaller values.

16 TIDAL AND WAVE POWER↗

NASA NTRS1988

Time-accurate unsteady aerodynamic and aeroelastic calculations for wings using Euler equations

A time-accurate approach to simultaneously solve the Euler flow equations and modal structural equations of motion is presented for computing aeroelastic responses of wings. The Euler flow eauations are solved by a time-accurate finite difference scheme with dynamic grids. The coupled aeroelastic equations of motion are solved using the linear acceleration method. The aeroelastic configuration adaptive dynamic grids are time accurately generated using the aeroelastically deformed shape of the wing. The unsteady flow calculations are validated wih experiment, both for a semi-infinite wing and a wall-mounted cantilever rectangular wings. Aeroelastic responses are computed for a rectangular wing using the modal data generated by the finite-element method. The robustness of the present approach in computing unsteady flows and aeroelastic responses that are beyond the capability of earlier approaches using the potential equations are demonstrated.

Guruswamy, Guru P.↗

NASA NTRS2003

Development of a Flexible Framework of Common Hypersonic Navier-Strokes Meshes for the Space Shuttle Orbiter

A flexible framework for the development of block structured volume grids for hypersonic Navier-Stokes flow simulations was developed for analysis of the Shuttle Orbiter Columbia. The development of the flexible framework, resulted in an ability to quickly generate meshes to directly correlate solutions contributed by participating groups on a common surface mesh, providing confidence for the extension of the envelope of solutions and damage scenarios. The framework draws on the experience of NASA Langely and NASA Ames Research Centers in structured grid generation, and consists of a grid generation process that is implemented through a division of responsibilities. The nominal division of labor consisted of NASA Johnson Space Center coordinating the damage scenarios to be analyzed by the Aerothermodynamics Columbia Accident Investigation (CAI) team, Ames developing the surface grids that described the computational volume about the orbiter, and Langely improving grid quality of Ames generated data and constructing the final volume grids. Distributing the work among the participants in the Aerothermodynamic CIA team resulted in significantly less time required to construct complete meshes than possible by any individual participant. The approach demonstrated that the One-NASA grid generation team could sustain the demand for new meshes to explore new damage scenarios within a aggressive timeline.

Alter, Stephen J.↗

NASA NTRS2004

Development of a Flexible Framework for Hypersonic Navier-Stoke Space Shuttle Orbiter Meshes

A flexible framework constructing block structured volume grids for hypersonic Navier-Strokes flow simulations was developed for the analysis of the Shuttle Orbiter Columbia. The development of the framework, which was partially basedon the requirements of the primary flow solvers used resulted in an ability to directly correlate solutions contributed by participating groups on a common surface mesh. A foundation was built through the assessment of differences between differnt solvers, which provided confidence for independent assessment of other damage scenarios by team members. The framework draws on the experience of NASA Langley and NASA Ames Research Centers in structured grid generation, and consists of a grid generation, and consist of a grid generation process implemented through a division of responsibilities. The nominal division of labor consisted of NASA Johnson Space Center coordinating the damage scenarios to be analyzed by the Aerothermodynamics Columbia Accident Investigation (ACAI) team, Ames developing the surface grids that described the computational volume about the Orbiter, and Langley improving grid quality of Ames generated data and constructing the final computational volume grids. Distributing the work among the participant in th ACAI team resulted in significantl less time required to construct complete meshes than possible by any individual participant. The approach demonstrated that the One-NASA grid generation team could sustain the demand of for five new meshes to explore new damage scenarios within an aggressive time-line.

Alter, Stephen J.↗

NASA NTRS2015

Spacecube: A Family of Reconfigurable Hybrid On-Board Science Data Processors

SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science data processing systems developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. SpaceCube is based on the Xilinx Virtex family of FPGAs, which include processor, FPGA logic and digital signal processing (DSP) resources. These processing elements are leveraged to produce a hybrid science data processing platform that accelerates the execution of algorithms by distributing computational functions to the most suitable elements. This approach enables the implementation of complex on-board functions that were previously limited to ground based systems, such as on-board product generation, data reduction, calibration, classification, eventfeature detection, data mining and real-time autonomous operations. The system is fully reconfigurable in flight, including data parameters, software and FPGA logic, through either ground commanding or autonomously in response to detected eventsfeatures in the instrument data stream.

reconfigurable computing↗

DOE OSTI2025

Day-Ahead Probabilistic Forecasting of Net-Load and Demand Response Potentials with High Penetration of Behind-the-Meter Solar-plus-Storage

The goal of this project is to develop advanced methods for day-ahead net-load forecasting, by leveraging the state-of-the-art machine learning techniques. The developed models produce both point and probabilistic forecasts for a variety of use cases, and are versatile to work with different types of data sets. The innovation lies in the novel design of the architectures, leveraging the most recent advances in machine learning that have not been explored in power systems, accompanied by techniques in the broader artificial intelligence fields such as fuzzy systems. This project has achieved the following accomplishments: (1) preprocessing of over 10 data sets covering varying geographical regions, time horizons, and system levels, which form a robust foundation for training and evaluating forecasting models across a wide range of realistic grid scenarios; (2) development of an interactive web app that enables exploratory analysis of load and generation data, and supports better understanding of data trends, anomalies, and correlations, facilitating model development and stakeholder engagement; (3) implementation of over 10 benchmark models for point and probabilistic forecasting, which include a mix of conventional machine learning methods and state-of-the-art deep learning approaches, providing a comprehensive baseline for performance comparison and validation of the proposed models; (4) development of a fuzzy system based gradient boosting model, tailored for small (less than 3 years) data sets, which achieves a mean absolute percentage error (MAPE) of 4% for point forecasting and a 20% improvement in average pinball loss for probabilistic forecasting; (5) development of a Transformer (a state-of-the-art deep learning architecture) based neural network model, tailored for large (3 years or more) data sets, which achieves a MAPE of 2% for point forecasting and a 20% improvement in average pinball loss for probabilistic forecasting; (6) development of a methodology for quantifying DR potential, and extensions of the previous models for multi-target forecasting of net load and DR potential, which achieve a MAPE of 10% for DR potential.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1994

(abstract) Monitoring the Freeze/Thaw Transitions in Taiga Forests Using ERS-1 SAR

Automated recording stations have been installed at the Bonanza Creek Experimental Forest, a Long Term Ecological Research (LTER) site located near Fairbanks, Alaska, in a forest stand of the Tanana River floodplain underlain by discontinuous permafrost. These stations provide a continuous record of dielectric constant and temperature of tree trunks, and soil moisture and temperature profiles down to the root zone. Along with the weather stations deployed at the same location, these measurements provide a continuous record of the environmental and phenologic conditions of the forest during a complete seasonal cycle. At the same time, ERS-1 SAR imaged the study site repeatedly from space to provide radar backscatter measurements of the forest approximately three times a month. Here, we examine the temporal dynamic of ERS-1 SAR measurements in relation with the changing environmental and phenologic state of the forest canopy and of the forest ground layers during the winter/spring and fall/winter transitions of 1992 and 1993. During these transitions, we examine whether changes in radar backscatter observed by ERS-1 may be related to freezing or thawing of the soil and vegetation in order to determine the start and end of the growing season for the forest. The results of this analysis are used in turn to determine whether similar changes are observed over larger regions. Mosaics of SAR data generated along three different North-South Alaskan ERS-1 transects that intercept with our study site are used in combination with hourly air temperature and daily precipitation rates gathered at airport weather stations by the National Weather Service. Results obtained using ERS-1 data collected from January 1992 to mid-1993 will be discussed.

permafrost temporal dynamics Alaska ecology radar ↗