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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A novel data gaps filling method for solar PV output forecasting

This study proposes a modified gaps filling method, expanding the column mean imputation method and evaluated using randomly generated missing values comprising 5%, 10%, 15%, and 20% of the original data on power output. The XGBoost algorithm was implemented as a forecasting model using the original and processed datasets and two sources of solar radiation data, namely, Shortwave Radiation (SWR) from Advanced Himawari Imager 8 (AHI-8) and Surface Solar Radiation Downward (SSRD) from ERA5 global reanalysis data. Further, the accuracy of the two sets of forecasted power output was evaluated using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Results show that by applying the proposed gap filling method and using SWR in forecasting solar photovoltaic (PV) output, the improvement in the RMSE and MAE values range from 12.52% to 24.30% and from 21.10% to 31.31%, respectively. Meanwhile, using SSRD, the improvement in the RMSE values range from 14.01% to 28.54% and MAE values from 22.39% to 35.53%. To further evaluate the accuracy of the proposed gap-filling method, the proposed method could be validated using different datasets and other forecasting methods. Future studies could also consider applying the said method to datasets with data gaps higher than 20%.

Energy & Fuels↗
DOE OSTI2026

Life Cycle Inventories and Data Gap Analysis for Rare Earth Elements: Neodymium and Dysprosium from Mining to Magnets

The United States demand for Neodymium-Iron-Boron (NdFeB) magnets, produced from rare earth elements (REEs) such as (Nd) and Dysprosium (Dy), far exceeds its nascent domestic production capacity, rendering it reliant on vulnerable global supply chains dominated by China. To guide research and development investments in securing U.S. REE supply, defensible benchmark metrics across environmental, economic, and social dimensions are needed. In this study, we built globally-representative, process-based cradle-to-cradle life cycle inventories for Nd and Dy in NdFeB magnets lifecycles, encompassing primary material acquisition, beneficiation, smelting and refining, metal processing, specialty alloy and chemical transformation, subcomponent manufacturing, consumer application (use phase) and end-of-life management. We carried out detailed literature review, and applied process engineering principles to build industry-representative upscaled life cycle inventories for both metals. We used these models to conduct bottom-up literature review and gap analysis on existing literature, compilation of data sources for each life cycle stage (and transformations where necessary), and a preliminary technoeconomic analysis (TEA)/life cycle costing analysis (LCCA). Findings from this work emphasize the need for metal specific, representative REE LCIs to establish robust benchmarks for advancing sustainable REE technologies and guiding R&D in REE supply chains.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1984

Spectral Information from Gapped Data. a Comparison of Technique

The fast Fourier transformations (FFT) is used to estimate power spectra of continuous signals evenly sampled on discrete domains. The problem of finding power spectra on unevenly sampled domains, in particular a regularly spaced domain with gaps is discussed. The analysis of the ACRIM solar bolometric intensity data, obtained with a 3/5 on and 2/5 off duty cycle of approximately 100 minutes, would benefit from the techniques. The comparative effectiveness of three different analysis techniques applied to synthetic data generated on gapped domain is reported.

Kuhn, J. R.↗
NASA NTRS1977

A hybrid technique for spacecraft attitude interpolation with arbitrary attitude data gaps

An algorithm for obtaining sufficiently accurate estimates of a system parameter Y, given a data record of the parameter in which at arbitrary times no direct observations of Y exist, and describing the variance of these estimates, is proposed. The method provides estimates at all requested times, and the variance of the estimates is maintained as close to the variance of directly measured data as the quality of input information will allow. Three classes of information are used: (1) the measured data record of Y and the statistical extension of this record into time intervals of no direct measurement, obtained by a modification of standard autocorrelation techniques; (2) an a priori indicator of the behavior of Y; and (3) one or more indirect indicators of Y based on observation of other system parameters. The application of the algorithm to the SEASAT-A attitude determination under conditions of sensor field-of-view limitations and sun occultations is presented.

Treder, A. J.↗
NASA NTRSDate not supplied

Economic Impact Assessments (EIA) of application of GEOGLOWS in Ecuador: Data Gaps, Limitations and Recommendations

In 2022, the United Nations launched the Early Warnings for All (EW4ALL) Program to establish global early warning systems by 2027. To assess the impact of the substantial $3.1 billion annual investment over five years, EW4ALL will consider factors that will require national coordination for the data needed for these assessments. In 2023, Ecuador was identified as one of the world's most climate-vulnerable countries, emphasizing the need to enhance its early warning systems. In 2020, the SERVIR Amazonia hub implemented the GEOGLOWS streamflow forecast service in collaboration with Ecuador's national meteorological agency (INAMHI). GEOGloWS provides 15-day ensemble forecasts and 80 years of historical streamflow data for every river worldwide through a free web service. The World Meteorological Organization has recognized this initiative as essential in contributing to the UN's call to ensure an 'Early Warning for All' by 2027. In 2023, as part of NASA's continuous efforts to fund research for Policy-Relevant Implementations, an economic impact assessment (EIA) was performed to understand the potential socioeconomic benefits of Early streamflow predictions in Ecuador using the GEOGLOWS service. Preliminary findings highlighted that gaps remain in effectively integrating socioeconomic and Earth observation (EO) data to capture the total value of these predictions. Implementing GEOGLOWS has led to valuable hydrological forecasts; however, the total economic benefits have yet to be documented. This study addresses the gaps and makes recommendations for future work that should focus on capturing the socio-economic benefits and costs associated with these forecasts, including their impact on decision-making at national and local levels. Despite the daily use of GEOGLOWS by key figures, including the President of Ecuador, the need for comprehensive recommendations and assessments is urgent.

Reetwika Basu↗
DOE OSTI2022

Electricity demand in South Asia – data gaps and pathways for research and modeling

South Asia is one of the fastest growing regions - economically and energy-wise in the world. However, there are significant uncertainties in how the energy demand would grow given the rapidly rising incomes, urbanization, industrialization, access to energy, warming climate and technological change. The transition to clean energy in the region is a priority and is critical to limiting emissions in the region and increasing regional energy security. The power sector will play an important role in decarbonization of energy systems, lowering emissions in other sectors through electrification. However, as existing end uses are scaled up more and new end uses are electrified, the temporal and spatial patterns of electricity consumption could change. These changes have implications for the magnitude, shape, and timing of peak demand, which in turn affects the power sector’s investments and operations, and ability to provide reliable power. In this report, we outline key uncertainties in demand growth that South Asian countries would face in the near to medium term, along with summarizing insights from stakeholder consultations we held over the past 6 months.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A Comparison of Time Series Gap-Filling Methods to Impute Solar Radiation Data

Complete solar resource datasets play a critical role at every stage of solar project phases. However, measured or modeled solar resource data come with significant uncertainties and usually suffer from several issues, including but not limited to, data gaps, data quality issue, etc. In order to mitigate these issues an appropriate data imputation method should be implemented to build a complete and reliable temporal (and spatial) database. Being motivated by this, in this study we compare the performances of eight different gap filling methods extensively by creating random and artificial data gaps in (i) hourly irradiance data for one year using a few locations of the National Solar Radiation Database (NSRDB) and (ii) one-minute ground measurement dataset from Surface Radiation Budget Network (SURFRAD) stations.

clearness index↗
NASA NTRSDate not supplied

Identifying Large Transients within ARTEMIS Solar Wind Data for Nightside Time Domain Electromagnetic Sounding

Mysteries regarding the Moon’s internal composition persist. By studying the induced magnetic fields produced by the Moon in response to changes in the magnetic field of the surrounding solar wind, inferences can be made regarding the associated eddy currents and thus regarding the electrical conductivities of the lunar regions hosting these currents. In this manner, a greater understanding of the Moon’s inner geophysical properties can be garnered. This investigative strategy, known as electromagnetic sounding, can be employed using magnetic field data from the ARTEMIS satellites. In particular, data taken from time intervals in which one satellite is within the lunar wake and within 500 km of the surface while the other is relatively far from the surface immersed within the pristine solar wind. Per Faraday’s Law, the steeper the magnetic transient from the solar wind, the greater the current induced within the Moon, and per Ampère’s Law, the greater this induced current, the larger the magnetic field it produces. Larger signals generally feature higher signal-to-noise ratios (SNRs). Thus, larger transients tend to produce more valuable data in terms of sounding. The enhanced separation between source signal and reaction signal via the aforementioned positioning of the probes during time intervals of interest augments the SNRs as well. Here we discuss tools developed in Python (making use of the PySPEDAS package) that expedites the task of identifying large magnetic transients within these time frames of interest. These exceptional changes in magnetic field are then evaluated for use in electromagnetic sounding as described above. We have identified 51 major transient events (during times of interest) from 8/1/2011 to 7/31/2021. One key hurdle we overcame was identifying and navigating data gaps. These data gaps would often interfere with our time intervals of interest, necessitating an algorithm to avoid them.

Moons↗
DOE OSTI2026

Data Centers Gap Analysis [Slides]

Data centers and other large loads are a significant driver of unprecedented, near-term demand growth in the United States. Power system planners, utilities, regulators, and other stakeholders are grappling with how to integrate data centers on the system without comprising reliability, resiliency, and energy affordability. NLR is pursuing work to develop a siting and decision-making tool that would draw on power systems modeling expertise to achieve granular representation of trade-offs involved in data center sitting and development. This slide deck supports the same workstream by reviewing the literature to identify mitigation options to facilitate near-term integration of large loads and by presenting options for pursuing data development and/or modeling projects to improve representation of siting options.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

A Critical Review of High Burnup Fuel Fragmentation, Relocation, and Dispersal under Loss-Of-Coolant Accident Conditions

High burnup fuel in excess of ~6268 GWd/MTU has been observed to severely fragment when subjected to temperature transient conditions as in a loss-of-coolant accident. In the event of cladding failure, the severely fragmented fuel can relocate into the balloon region and potentially disperse through the burst opening into the reactor’s primary system. This observation has led to implementation of several independent test programs designed to focus on various aspects of fuel fragmentation, relocation, and dispersal. The purpose of this review is to perform a critical, holistic assessment of fuel fragmentation, relocation, and dispersal under loss-of-coolant conditions to identify data gaps in the experimental data base. Phenomena have been identified and well defined through the various testing programs, and general agreement regarding the governing parameters (temperature, burnup, heating rate, cladding deformation, etc.) has been established. However, there is a significant data gap connecting research to commercial application. Furthermore, previous research attempted to evaluate the problem holistically, but has yet to provide a comprehensive understanding of the problem. Major identified data gaps consist of (1) a comprehensive understanding of pretransient fuel rod conditions (fuel temperature, fuel stress, rod internal pressures, microstructure, etc.), (2) definition of prototypic loss-of-coolant accident conditions (heating rate, fuel temperatures, fuel stress), (3) identification of the differences between nuclear and electrical integral loss-of-coolant accident tests, and connection of fuel rod performance (cladding ballooning, burst opening, potential relocation, fragmentation susceptibility, etc.) to fuel fragmentation, relocation, and dispersal severity. Finally, the content of this manuscript provides a clear path for connecting testing and data acquisition to commercial application by providing concrete means for filling data gaps and prioritized testing regimes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A Comparison of Time-Series Gap-Filling Methods to Impute Solar Radiation Data: Preprint

Complete solar resource data sets play a critical role at every stage of solar energy projects; however, measured or modeled solar resource data come with significant uncertainties and usually suffer from several issues, including, but not limited to, data gaps and data quality issues. To mitigate these issues, an appropriate data imputation method should be implemented to build a complete and reliable temporal (and spatial) database. Motivated by this, in this study, we extensively compare the performance of eight different gap-filling methods by creating random and artificial data gaps in (i) hourly irradiance data for 1 year using a few locations of the National Solar Radiation Database (NSRDB) and (ii) 1-minute ground measurement data sets from the Surface Radiation Budget Network (SURFRAD) and the National Renewable Energy Laboratory (NREL) stations.

clearness index↗
DOE OSTI2021

Evaluation of Time-Series Gap-Filling Methods for Solar Irradiance Applications

A complete solar resource data set is essential for any stage of a solar energy project - from feasibility studies to daily operations. But measured or modeled solar resource data are prone to data gaps and data quality issues. To mitigate these issues, a data imputation process should be implemented to obtain a complete and reliable temporal and spatial data series. This study focused on imputing temporal scales by applying random and artificial data gaps and then implementing eight imputation methods, including the Kalman filtering and smoothing and stine interpolations. These methods were implemented on 1-minute to half hourly irradiance data for 1 year using a few locations from the National Solar Radiation Database (NSRDB) and ground measurement data set. The results demonstrated that some of the simpler methods, such as the stine and linear interpolation methods, were the relatively best models based on the statistical metrics for imputing NSRDB and ground measurement data, respectively.

14 SOLAR ENERGY↗
DOE OSTI2024

An Open-Source Framework for Characterizing Urban Energy Models: Integrating Top-Down and Bottom-Up Methods to Predict Residential Buildings Characteristics: Preprint

Bottom-up urban energy models are crucial for understanding current energy use patterns and informing design strategies. However, accurately characterizing these models to represent different communities remains a challenge due to the extensive data needed for simulating existing energy use behavior. This data includes information related to human activities and building characteristics, all of which correlate with socioeconomic factors. To overcome this challenge, we developed an automated framework that utilizes both top-down and bottom-up data, to predict unknown building and occupant characteristics that are needed for more accurate and equitable modeling and analytics. Our framework, integrated into the URBANopt district energy modeling platform, uses statistical data models from ResStock. URBANopt models co-located buildings and neighborhoods. At this scale there are data gaps in building characteristic data, such as materials, insulation, occupancy, income, and energy usage of the buildings. To address this data gap, we use ResStock data, representative at the census tract scale, and develop machine-learning and deeplearning techniques to disaggregate it to individual buildings. By mapping unique occupant, building and economic properties to URBANopt energy models, we gain detailed insights into the variability of building energy use across different neighborhoods. This insight helps deploy technologies for co-located buildings and supports targeted upgrades for communities with unique economic and demographic characteristics, ensuring energy equity. Accurate characterization of energy models allows us to develop equitable strategies tailored to diverse neighborhoods, whether underserved or affluent. Our automated framework streamlines energy modeling and provides a reliable tool for building energy characterization.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
NASA NTRS1982

Geographic science: Executive summary

The role that TM and MSS data play in the analysis of spatial patterns for land use/land cover, geomorphology studies, and the development of cartographic products is discussed. Tables listing geographic science data gaps, mission data requirements, and possible future remote sensing missions are included.

Source record↗
NASA NTRS2019

Frequency comparisons via GPS carrier-phase: jump processing, temperature compensation and zero/short-baseline noise-floors

GPS carrier-phase receivers have been used to produce high quality time/frequency comparisons between clocks and frequency standards. Current ways of processing the carrier-phase data, however, result in phase jumps and data gaps that make the data difficult to use effectively and repeatedly for long datasets. In addition, temperature fluctuations generally perturb receiver output detrimentally. We describe the steps of a simple but effective automated algorithm for comparing frequencies that can compensate for data gaps, day boundary jumps, and other phase jumps as well as for temperature disturbances. We describe process features and focus on zero-baseline noise-floors, measuring Allan deviations of the Deep Space Atomic Clock mission’s receiver down to 1x10-17 at 5x105 seconds, with an upper confidence level of 3x10-17. The zero-baseline noise floors we present give confidence in our algorithm and temperature compensation’s robustness.

Diener, William A.↗
NASA NTRS2023

KMT-2021-BLG-1150Lb: Microlensing Planet Detected Through a Densely Covered Planetary-Caustic Signal

Aims. Recently, there have been reports of various types of degeneracies in the interpretation of planetary signals induced by planetary caustics. In this work we check whether such degeneracies persist in the case of well-covered signals by analyzing the lensing event KMT-2021-BLG-1150, the light curve of which exhibits a densely and continuously covered short-term anomaly. Methods. In order to identify degenerate solutions, we thoroughly investigated the parameter space by conducting dense grid searches for the lensing parameters. We then checked the severity of the degeneracy among the identified solutions. Results. We identify a pair of planetary solutions resulting from the well-known inner-outer degeneracy, and find that interpreting the anomaly is not subject to any degeneracy other than the inner-outer degeneracy. The measured parameters of the planet separation (normalized to the Einstein radius) and mass ratio between the lens components are ( s , q ) in ∼ (1.297, 1.10 × 10 −3 ) for the inner solution and ( s , q ) out ∼ (1.242, 1.15 × 10 −3 ) for the outer solution. According to a Bayesian estimation, the lens is a planetary system consisting of a planet with a mass M p = 0.88 +0.38 −0.36 M J and its host with a mass M h = 0.73 +0.32 −0.30 M ⊙ lying toward the Galactic center at a distance D L = 3.8 +1.3 −1.2 kpc. By conducting analyses using mock data sets prepared to mimic those obtained with data gaps and under various observational cadences, we find that gaps in data can result in various degenerate solutions, while the observational cadence does not pose a serious degeneracy problem as long as the anomaly feature can be delineated.

Gravitational microlensing↗
NASA NTRS1985

Mission-oriented requirements for updating MIL-H-8501: Calspan proposed structure and rationale

This report documents the effort by Arvin/Calspan Corporation to formulate a revision of MIL-H-8501A in terms of Mission-Oriented Flying Qualities Requirements for Military Rotorcraft. Emphasis is placed on development of a specification structure which will permit addressing Operational Missions and Flight Phases, Flight Regions, Classification of Required Operational Capability, Categorization of Flight Phases, and Levels of Flying Qualities. A number of definitions is established to permit addressing the rotorcraft state, flight envelopes, environments, and the conditions under which degraded flying qualities are permitted. Tentative requirements are drafted for Required Operational Capability Class 1. Also included is a Background Information and Users Guide for the draft specification structure proposed for the MIL-H-8501A revision. The report also contains a discussion of critical data gaps and attempts to prioritize these data gaps and to suggest experiments that should be performed to generate data needed to support formulation of quantitative design criteria for the additional Operational Capability Classes 2, 3, and 4.

Chalk, C. R.↗