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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Generating Animated Displays of Spacecraft Orbits

Tool for Interactive Plotting, Sonification, and 3D Orbit Display (TIPSOD) is a computer program for generating interactive, animated, four-dimensional (space and time) displays of spacecraft orbits. TIPSOD utilizes the programming interface of the Satellite Situation Center Web (SSCWeb) services to communicate with the SSC logic and database by use of the open protocols of the Internet. TIPSOD is implemented in Java 3D and effects an extension of the preexisting SSCWeb two-dimensional static graphical displays of orbits. Orbits can be displayed in any or all of the following seven reference systems: true-of-date (an inertial system), J2000 (another inertial system), geographic, geomagnetic, geocentric solar ecliptic, geocentric solar magnetospheric, and solar magnetic. In addition to orbits, TIPSOD computes and displays Sibeck's magnetopause and Fairfield's bow-shock surfaces. TIPSOD can be used by the scientific community as a means of projection or interpretation. It also has potential as an educational tool.

Candey, Robert M.↗
NASA NTRS2018

The Ozone Monitoring Instrument: Overview of 14 Years in Space

This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

KNMI↗
NASA NTRS2018

Enriching the Twitter Stream Increasing Data Mining Yield and Quality Using Machine Learning

Social media data streams are important sources of real-time and historical global information for science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we are exploring the Twitter data stream for its potential in augmenting the validation program of NASA Earth science missions, specifically the Global Precipitation Measurement (GPM) mission. We have implemented a tweet processing infrastructure that outputs classified precipitation tweets. Inputs are "passive" tweets, along with a smaller number of tweets from "active" participants, i.e., those knowingly contributing to our effort. The "active" tweets, presumably of higher quality, enrich the Twitter stream. "Active" sources include data scraped from other social media (e.g., public Facebook posts) and data from existing crowdsourcing programs (e.g., mPING reports). In addition, there is likely relevant precipitation information in images and documents that are the end points of links often included in tweets. Information derived from these "active" sources could then be tweeted into the Twitter stream, thus enriching its quality. The objective of our current work is to mine these tweet­ linked images and documents, using neural networks, to increase the information content and quality related to precipitation. For images, we classified them as either precipitation-related or not. For training and validation, we used images obtained via the Google custom search API. We created two models: (1) by training a simple Convolutional Neural Network and (2) by using transfer learning principles to adapt a pre-trained object recognition model. For documents, both those linked to tweets and the tweet contents, we trained Hierarchical Attention Networks to determine precipitation occurrence, type, and intensity. For training and validation, we used a keyword-filtered tweet data set labelled with ground truth data from Dark Sky (an API to retrieve weather-related labels) and the National Severe Storms Laboratory's Multi­ Radar/Multi-Sensor (MRMS) system. Our results demonstrated the efficacy of our machine learning approaches for enriching the Twitter stream, to derive information potentially useful for validation of earth science satellite data.

Albayrak, Arif↗
NASA NTRS2019

Return to Service of a Liquid Hydrogen Storage Sphere

One, of two, 850,000 gallon liquid hydrogen storage spheres, at NASA's Kennedy Space Center, was decommissioned in 2010. This tank had an abnormally high heat leak that was investigated and determined to be the result of a large void in the perlite insulation. The insulation void was subsequently filled, and the tank was refurbished for its planned use in the Space Launch Systems (SLS) program. Return to service of this tank began in December of 2017 with a partial liquid hydrogen fill. Since that time, routine measurement of the liquid level have been recorded in order to establish a new boiloff rate and associated heat leak. This data shows the perlite top off activities have resulted in a much reduced, and within design specification, heat leak.

air leak↗
NASA NTRS2019

Return to Service of a Liquid Hydrogen Storage Sphere

One, of two, 850,000 gallon liquid hydrogen storage spheres, at NASA's Kennedy Space Center, was decommissioned in 2010. This tank had an abnormally high heat leak that was investigated and determined to be the result of a large void in the perlite insulation. The insulation void was subsequently filled, and the tank was refurbished for its planned use in the Space Launch Systems (SLS) program. Return to service of this tank began in December of 2017 with a partial liquid hydrogen fill. Since that time, routine measurement of the liquid level have been recorded in order to establish a new boiloff rate and associated heat leak. This data shows the perlite top off activities have resulted in a much reduced, and within design specification, heat leak.

Krenn, A. G.↗
NASA NTRSDate not supplied

HALE-X -- A USFS-NASA Partnership with Swift Engineering to Demonstrate Sustained IR Imagery for Weeks to Months with Next Generation Solar-electric Uncrewed Aircraft Systems UAS

HALE-X (High Altitude Long Endurance experiment) is an innovative partnership between the US Forest Service, NASA and Swift Engineering designed to test high altitude UAS capabilities for providing persistent, real-time mapping and intelligence over a wildfire incident. Platform and payload testing is scheduled to occur during summer 2021 at SpacePort America and adjacent airspace in New Mexico.

HALE-X↗
NASA NTRSDate not supplied

An Approach to Reasoning Service Migration in Data and Reasoning Fabric (DRF) Implementation

In this paper we consider service placement problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, we estimate for each potential location the response time, consumed energy and total cost; formulate an optimization problem for cost minimization given the users QoS constraints and network infrastructure limitations; and solve it using nonlinear programming tools. The approach is applied to trajectory re-planning use case to handle a no-fly zone contingency in real time.

Vahram Stepanyan↗
NASA NTRSDate not supplied

Comparison of the Nowcast of Aerospace Ionizing Radiation System (NAIRAS) With ISS Measurements

The Nowcast of Aerospace Ionizing Radiation System (NAIRAS) is a sophisticated physics-based model that has been providing real-time global predictions of cosmic radiation exposure, pertinent to both galactic and solar sources, to air travelers for a decade. The utility of NAIRAS, however, extends beyond the atmospheric ionizing radiation environment. The recently developed NAIRAS 3.0 version demonstrates an expansion of its domain to the space radiation environment. This extension incorporates an additional trapped inner belt proton source, coupled with altitude-dependent and rigidity-dependent geomagnetic shielding for galactic cosmic rays (GCR) and solar energetic particle (SEP) protons. The latest version of NAIRAS operates in two modes: real-time global predictions of the atmospheric radiation environment and a user-specified run-on-request service for global dosimetric calculations or predictions of dosimetric and particle flux quantities along user-uploaded flight path. It is available to the public at the Community Coordinated Modeling Center (CCMC). In this work, we present the validation exercises that have been conducted using the Automated Radiation Measurements for Aerospace Safety (ARMAS) onboard the International Space Station (ISS), thereby establishing NAIRAS's efficacy in predicting space radiation exposure. As such, NAIRAS 3.0 holds significant potential for human safety and technological advancement in aerospace travel and exploration.

Daniel Phoenix↗
NASA NTRSDate not supplied

The Effect of a SEP Event on Astronauts Doing a Spacewalk As Computed By the Nowcast of Aerospace Ionizing Radiation System (NAIRAS)

The Nowcast of Aerospace Ionizing Radiation System (NAIRAS) is a sophisticated physics-based model that has been providing real-time global predictions of cosmic radiation exposure, pertinent to both galactic and solar sources, to air travelers for a decade. The utility of NAIRAS, however, extends beyond the atmospheric ionizing radiation environment. The recently developed NAIRAS 3.0 version demonstrates an expansion of its domain to the space radiation environment. This extension incorporates an additional trapped inner belt proton source, coupled with altitude-dependent and rigidity-dependent geomagnetic shielding for galactic cosmic rays (GCR) and solar energetic particle (SEP) protons. The latest version of NAIRAS operates in two modes: real-time global predictions of the atmospheric radiation environment and a user-specified run-on-request service for global dosimetric calculations or predictions of dosimetric and particle flux quantities along user-uploaded flight path. It is available to the public at the Community Coordinated Modeling Center (CCMC). In this work, we present the computations of the dose in the ISS vicinity during the SEP event of August 8, 2023; which happened a day before a scheduled spacewalk. We demonstrate that astronauts would not have suffered a dose equivalent in excess of 1 mSv if the event happened a day later. As such, NAIRAS 3.0 holds significant potential for human safety and technological advancement in aerospace travel and exploration.

Guillaume Gronoff↗
DOE OSTI2018

NREL and San Diego Gas & Electric Company

San Diego Gas & Electric Company (SDG&EA(R)) and NREL are collaborating to evaluate advanced metering infrastructure (AMI)-based controls for grid operations. With millions of new smart meters being deployed around the country, this collaboration will take the lead in determining how to generate insights from the AMI data, and to use these insights for real-time operations. Smart meters ensure availability of pervasive and continuous data from the grid-edge, a service that is not possible with traditional grid sensors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1994

The Use of a Two-Dimensional, Time-Dependent Cloud Model to Predict Convective and Stratiform Clouds and Precipitation

A two-dimensional, time-dependent cloud model has been used in two field projects to forecast the convective development during the day from the morning sounding. In effect, the cloud model gives a dynamic analysis of the sounding as affected by heating and evaporation at the earth's surface, divergence of the winds throughout the atmosphere, and cloud shadow effects. During the initial project, the Cooperative Huntsville Meteorological Experiment, the results were mixed. Model runs were easily made when soundings were available. but displaying the results in a meaningful and useful way was the limiting factor. In a later experiment, the North Dakota Thunderstorm Project, the problem of displaying results was overcome and soundings were available from the local weather service forecast office with a high degree of reliability. The experimental model correctly forecasts convective development about 80% of the time, and precipitation or no precipitation more than 70% of the time.

Kopp, Fred J.↗
DOE OSTI2025

An On-Demand Electric Transit Case Study of New Rochelle, New York

This work explores the extent to which an on-demand mobility service utilizing lightweight electric vehicles (EVs) provides community and sustainability benefits in New Rochelle, New York. Travel and survey data from September 2019 through 2023 are used to describe the system and estimate impacts on travelers. The system was found to be used more by women (nearly 60%) and younger demographics (>65% under the age of 42), with peak use in the middle of the day and a grocery store as a top origin and destination. The service is utilized primarily for short trips (86% under 2 miles), and the small, right-sized EVs have carbon dioxide emissions associated with charging the fleet that are roughly one-quarter of the fleet emissions of conventional hybrid vans and nearly 50 times less than a fleet of diesel buses. Mapping current socio-spatial dynamics of travel demand can inform equity performance, as well as assist future planning and service area development and possible extensions to similar smaller, lower-density environments that are nearby and connected to major metropolitan areas. The findings in this case study suggest on-demand electric transit may be a significant and growing space for advancing clean and highly valued public mobility services. Sustainable public transport interventions that consider right-sized, electric, on-demand vehicles can help achieve improved accessibility and reduce energy use and greenhouse gas emissions. This work was presented at the Transportation Research Board (TRB) 2025 Annual Meeting on January 7, 2025.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

State Estimation-Based Distributed Energy Resource Optimization for Distribution Voltage Regulation in Telemetry-Sparse Environments Using a Real-Time Digital Twin

Real-time state estimation using a digital twin can overcome the lack of in-field measurements inside an electric feeder to optimize grid services provided by distributed energy resources (DERs). Optimal reactive power control of DERs can be used to mitigate distribution system voltage violations caused by increased penetrations of photovoltaic (PV) systems. In this work, a new technology called the Programmable Distribution Resource Open Management Optimization System (ProDROMOS) issued optimized DER reactive power setpoints based-on results from a particle swarm optimization (PSO) algorithm wrapped around OpenDSS time-series feeder simulations. This paper demonstrates the use of the ProDROMOS in a RT simulated environment using a power hardware-in-the-loop PV inverter and in a field demonstration, using a 678 kW PV system in Grafton (MA, USA). The primary contribution of the work is demonstrating a RT digital twin effectively provides state estimation pseudo-measurements that can be used to optimize DER operations for distribution voltage regulation.

Darbali-Zamora, Rachid↗
NASA NTRS1992

Data distribution satellite

The Data Distribution Satellite (DDS), operating in conjunction with the planned space network, the National Research and Education Network and its commercial derivatives, would play a key role in networking the emerging supercomputing facilities, national archives, academic, industrial, and government institutions. Centrally located over the United States in geostationary orbit, DDS would carry sophisticated on-board switching and make use of advanced antennas to provide an array of special services. Institutions needing continuous high data rate service would be networked together by use of a microwave switching matrix and electronically steered hopping beams. Simultaneously, DDS would use other beams and on board processing to interconnect other institutions with lesser, low rate, intermittent needs. Dedicated links to White Sands and other facilities would enable direct access to space payloads and sensor data. Intersatellite links to a second generation ATDRS, called Advanced Space Data Acquisition and Communications System (ASDACS), would eliminate one satellite hop and enhance controllability of experimental payloads by reducing path delay. Similarly, direct access would be available to the supercomputing facilities and national data archives. Economies with DDS would be derived from its ability to switch high rate facilities amongst users needed. At the same time, having a CONUS view, DDS would interconnect with any institution regardless of how remote. Whether one needed high rate service or low rate service would be immaterial. With the capability to assign resources on demand, DDS will need only carry a portion of the resources needed if dedicated facilities were used. Efficiently switching resources to users as needed, DDS would become a very feasible spacecraft, even though it would tie together the space network, the terrestrial network, remote sites, 1000's of small users, and those few who need very large data links intermittently.

Stevens, Grady H.↗
DOE OSTI2024

Mobility Energy Productivity Evaluation of On-Demand Transit: A Case Study in Arlington, Texas

On-demand transit (ODT) systems are increasing in number and size. To evaluate and quantify outcomes, the research team utilizes the mobility energy productivity (MEP) metric, which is a holistic accessibility measure, to analyze and compare the mobility of various transportation modes in Arlington, Texas. The MEP tool is applied to the ODT system in Arlington, Texas, as well as to five existing transportation modes (driving, transportation network company, transit, biking, and walking). Six ODT scenarios are also analyzed and compared. The analysis is focused on the opportunities that an ODT system presents for transportation disadvantaged communities (DACs) with low rates of car ownership. Although driving received the highest MEP score—a finding typical for a U.S.A. city— the results for the ODT system reveal that it serves those in DACs effectively, helping to achieve an equity design goal. ODT improved the average MEP score across the service area by 83% when considering only accessible, nonprivate vehicle modes (biking, transit, and ODT). For the ODT scenarios, decreasing the wait time by 50% compared with the baseline scenario led to a nearly 160% increase in the MEP score, whereas increasing the ODT travel speed by 21% led to an 80% improvement in the MEP score. As analyzed through the MEP tool, here this paper demonstrates how ODT can enhance mobility, particularly for DACs. The results of an MEP analysis can be used by researchers and transit agencies to compare transportation modes and improve the effectiveness of transportation systems across a service area.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Monitoring microstructural evolution of alloy 617 with non-linear acoustics for remaining useful life prediction; multiaxial creep-fatigue and creep-ratcheting

The research built upon a prior investigation to develop a unified constitutive model for design-­by-­analysis of the intermediate heat exchanger (IHX) for a very high temperature reactor (VHTR) design of next generation nuclear plants (NGNPs). Model development requires a set of failure data from complex mechanical experiments to characterize the material behavior. Therefore uniaxial and multiaxial creep-­fatigue and creep-­ratcheting tests were conducted on the nickel-­base Alloy 617 at 850 and 950°C. The time dependence of material behavior, and the interaction of time dependent behavior (e.g., creep) with ratcheting, which is an increase in the cyclic mean strain under load-­controlled cycling, are major concerns for NGNP design. This research project aimed at characterizing the microstructure evolution mechanisms activated in Alloy 617 by mechanical loading and dwell times at elevated temperature. The acoustic harmonic generation method was researched for microstructural characterization. It is a nonlinear acoustics method with excellent potential for nondestructive evaluation, and even online continuous monitoring once high temperature sensors become available. It is unique because it has the ability to quantitatively characterize microstructural features well before macroscale defects (e.g., cracks) form. The nonlinear acoustics beta parameter was shown to correlate with microstructural evolution using a systematic approach to handle the complexity of multiaxial creep-­fatigue and creep-­ratcheting deformation. Mechanical testing was conducted to provide a full spectrum of data for: thermal aging, tensile creep, uniaxial fatigue, uniaxial creep-­fatigue, uniaxial creep-ratcheting, multiaxial creep-fatigue, and multiaxial creep-­ratcheting. Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and Optical Microscopy were conducted to correlate the beta parameter with individual microstructure mechanisms. We researched application of the harmonic generation method to tubular mechanical test specimens and pipes for nondestructive evaluation. Tubular specimens and pipes act as waveguides, thus we applied the acoustic harmonic generation method to guided waves in both plates and shells. Magnetostrictive transducers were used to generate and receive guided wave modes in the shell sample and the received signals were processed to show the sensitivity of higher harmonic generation to microstructure evolution. Modeling was initiated to correlate higher harmonic generation with the microstructure that will lead to development of a life prediction model that is informed by the nonlinear acoustics measurements.

36 MATERIALS SCIENCE↗