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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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NASA NTRS1990

ACTS Multibeam Communications Package - Technology for the 1990S

To maintain its competitive position in the 1990s, satellite communications must evolve to provide new services and to reduce the costs of supplying existing services. NASA's Advanced Communications Technology Satellite (ACTS) program is directed toward developing the technology base that will support this evolution. The ACTS communications payload is optimized for digital communications using a time-division multiple access format. Scanning spot-beam antennas provide high-performance on-demand service to the earth communication stations. On-board processing and switching allow full connectivity in a single-hop network architecture. ACTS employs Ka-band (30/20 GHz) links for communications traffic and includes techniques for mitigating rain fades. Scheduled to be launched by a Space Shuttle in 1992, ACTS will provide in-orbit technology verification and support experimental communications networks for up to four years.

Graebner, John C.↗

NASA NTRS2004

[The Engineering and Technical Services Directorate at the Glenn Research Center]

My name is James Moon and I am a senior at Tennessee State University where my major is Aeronautical and Industrial Technology with a concentration in industrial electronics. I am currently serving my internship in the Engineering and Technical Services Directorate at the Glenn Research Center (GRC). The Engineering and Technical Service Directorate provides the services and infrastructure for the Glenn Research Center to take research concepts to reality. They provide a full range of integrated services including engineering, advanced prototyping and testing, facility management, and information technology for NASA, industry, and academia. Engineering and Technical Services contains the core knowledge in Information Technology (IT). This includes data systems and analysis, inter and intranet based systems design and data security. Including the design and development of embedded real-time s o h a r e applications for flight and supporting ground systems, Engineering and Technical Services provide a wide range of IT services and products specific to the Glenn Research Center research and engineering community. In the 7000 Directorate I work directly in the 7611 organization. This organization is known as the Aviation Environments Technical Branch. My mentor is Vincent Satterwhite who is also the Branch Chief of the Aviation Environments Technical Branch. In this branch, I serve as the Assistant program manager of the Engineering Technology Program. The Engineering Technology Program (ETP) is one of three components of the High School L.E.R.C.I.P. This is an Agency-sponsored, eight-week research-based apprenticeship program designed to attract traditionally underrepresented high school students that demonstrate an aptitude for and interest in mathematics, science, engineering, and technology.

Moon, James↗

DOE OSTI2012

Task 1. Monitoring real time materials degradation. NRC extended In-situ and real-time Monitoring

The overall objective of this project was to perform a scoping study to identify, in concert with the nuclear industry, those sensors and techniques that have the most promising commercial viability and fill a critical inspection or monitoring need. Candidates to be considered include sensors to monitor real-time material degradation, characterize residual stress, monitor and inspect component fabrication, assess radionuclide and associated chemical species concentrations in ground water and soil, characterize fuel properties, and monitor severe accident conditions. Under Task 1—Monitoring Real-Time Materials Degradation—scoping studies were conducted to assess the feasibility of potential inspection and monitoring technologies (i.e., a combination of sensors, advanced signal processing techniques, and data analysis methods) that could be utilized in LWR and/or advanced reactor applications for continuous monitoring of degradation in-situ. The goal was to identify those techniques that appear to be the most promising, i.e., those that are closest to being both technically and commercially viable and that the nuclear industry is most likely to pursue. Current limitations and associated issues that must be overcome before commercial application of certain techniques have also been addressed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2017

A-Train Datalist - A New GES DISC Service to Allow One-Stop Shopping for A-Train Data

The currently available services at the Goddard Earth Sciences Data Information Services Center (GES DISC) only allow users to select variables from a single data set at a time. Because entire variables from a data set are often displayed, user selection of variables of interest can be overwhelming. At the American Geophysical Union (AGU) 2016 Fall Meeting, GES DISC unveiled a new service called Datalist: a collection of predefined or user-defined data variables from one or more archived data sets. Our science support team has been curating Datalists and providing added value to the user community.Originally known as Afternoon Constellation, A-Train includes six currently on polar-orbiting Earth observation satellites: OCO-2, GCOM-W1, Aqua, CALIPSO, CloudSat, and Aura, which travel a few minutes apart from each other. This constellation arrangement has enabled coordinated science observations further forming comprehensive pictures of Earth weather and climate that are readily for use in crucial studies such as climate change.GES DISC Datalists are based on the software architecture of the new GES DISC website (also unveiled at the AGU 2016 Fall Meeting). The GES DISC science support team has created a Datalist to support the A-Train Data Depot (ATDD). Using pre-defined Datalist should hopefully save users significant effort in their data searches.

A-Train data ordering↗

NASA NTRS1987

The use of satellites in non-goestationary orbits for unloading geostationary communication satellite traffic peaks. Volume 2: Technical report

The part of the geostationary (GEO) orbital arc used for United States domestic fixed, communications service is rapidly becoming filled with satellites. One of the factors currently limiting its utilization is that communications satellites must be designed to have sufficient capacity to handle peak traffic leads, and thus are under utilized most of the time. A solution is to use satellites in suitable non-geostationary orbits to unload the traffic peaks. Three different designs for a non-geostationary orbit communications satellite system are presented for the 1995 time frame. The economic performance is analyzed and compared with geostationary satellites for two classes of service, trunking and customer premise service. The result is that the larger payload of the non-geostationary satellite offsets the burdens of increased complexity and worse radiation environment to give improved economic performance. Depending on ground terminal configuration, the improved economic performance of the space segment may be offset by increased ground terminal expenses.

Price, K.↗

NASA NTRS2019

Implementing Polar Projections with OGC Services for the Enhancement of AIRS NRT Visualization in LANCE

The Atmospheric Infrared Sounder (AIRS) NRT product is one important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). The LANCE processing of AIRS NRT products and the image generation are performed at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The Open Geospatial Consortium (OGC) services are being utilized to access AIRS NRT images. The ongoing AIRS NRT imagery enhancement work includes adding a new set of the images in polar projections. Polar projections are commonly used for mapping Antarctica and Arctic regions. We have implemented more precise south polar (EPSG:3031) projection and north polar (EPSG:3413) projection making our OGC service instances more useful and interoperable. Thus, AIRS NRT data can be easily accessed and integrated with other applications. It greatly increases the impact of our data on researches in polar regions.In this presentation, we will introduce the optimized processing workflow for OGC services from data access with spatial-temporal index to data visualization with different SLD, and demonstrate how to use open source software to provide more precise map images in polar projections.

Zhao, Peisheng↗

NASA NTRSDate not supplied

Weather Guidance for UAS Urban Medical Transport Missions

Unmanned aircraft will revolutionize healthcare services by providing efficient and expeditious delivery of life-saving transplant organs and supplies to hospitals in urban environments, where road traffic and congestion can slow delivery times and endanger lives. Bell has developed the Autonomous Pod Transport (APT) vehicle to serve this market, with entry into service in mid-2020s. Adverse weather conditions can introduce risks and inefficiencies in urban environments leading to flight delays and cancellations. In 2018, National Aeronautics and Space Administration (NASA) and Bell entered into a cooperative agreement, under the Systems Integration and Operationalization (SIO) program to tackle key challenges to enable future commercial unmanned aircraft operations. The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) at the University of Massachusetts, Amherst, joined this team to demonstrate weather avoidance technologies for remotely piloted and autonomous vehicles. CASA has developed the ‘City Warn’ hazard alerting platform to gather weather information from various weather sensors and models, and based on user (or mission) preferences for alerting and on user (or unmanned aircraft) locations, the platform shares timely weather intelligence with users and the systems used by them for remote operations. This presentation discusses the weather avoidance solution developed during this project, leading up to the demonstration of the end-to-end system in Fall 2020. The presentation will cover the following topics: 1) goals related to weather avoidance 2) the design requirements process, including the results of pilot interviews, 3) weather observation and avoidance needs 4) selection of regional and national weather data sets 5) design of the weather graphical interface and 6) considerations for real-time weather alerting. The end-to-end system that was developed will be discussed, along with the results from the demonstration flight. The presentation will conclude with insights from the project team on lessons learned and best practices on weather avoidance technologies for the industry going ahead.

weather avoidance↗

NASA NTRS2021

Weather Guidance for UAS Urban Medical Transport Missions

weather avoidance↗

DOE OSTI2013

Framework for Real-Time All-Hazards Global Situational Awareness

Information systems play a pivotal role in emergency response by making consequence analysis models based on up-to-date data available to decision makers. While consequence analysis models have been used for years on local scales, their application on national and global scales has been constrained by lack of non-proprietary data. This chapter describes how this has changed using a framework for real-time all-hazards situational awareness called the Energy Awareness and Resiliency Standardized Services (EARSS) as an example. EARSS is a system of systems developed to collect non-proprietary data from diverse open content sources to develop a geodatabase of critical infrastructures all over the world. The EARSS system shows that it is feasible to provide global disaster alerts by producing valuable information such as texting messages about detected hazards, emailing reports about affected areas, estimating an expected number of impacted people and their demographic characteristics, identifying critical infrastructures that may be affected, and analyzing potential downstream effects. This information is provided in real-time to federal agencies and subscribers all over the world for decision making in humanitarian assistance and emergency response. The system also uses live streams of power outages, weather, and satellite surveillance data as events unfold. This, in turn, is combined with other public domain or open content information, such as media reports and postings on social networking websites, for complete coverage of the situation as events unfold. Working with up-to-date information from the EARSS system, emergency responders on the ground could pre-position their staff and resources, such as emergency generators and ice, where they are most needed.

disaster consequence management↗

DOE OSTI2012

Activities in support of continuing the service of nuclear power plant concrete structures

In general, nuclear power plant concrete structure s performance has been very good; however, aging of concrete structures occurs with the passage of time that can potentially result in degradation if is effects are not controlled. Safety-related nuclear power plant concrete structures are described. In-service inspection and testing requirements in the U.S. are summarized. The interaction of the license renewal process and concrete structures is noted. A summary of operating experience related to aging of nuclear power plant concrete structures is provided. Several candidate areas are identified where additional research would be beneficial for aging management of nuclear power plant concrete structures. Finally, an update on recent activities at Oak Ridge National Laboratory related to aging management of nuclear power plant concrete structures is provided.

aging↗

DOE OSTI2019

HeadCount (Automated & Anonymous In-Vehicle Occupancy Detection and Counting) [SWR 19-14]

The HeadCount software is filling a transportation information gap by counting how many people take each rideshare ride. The transportation industry is undergoing rapid transformation. Personally-driven trips via privately owned vehicles are being replaced by commercial services such as ride-hailing and car-sharing. In the same time, municipalities have increasingly expressed interest in the movement of people, rather than just vehicles. However, there is a lack of technology to collect vehicle occupancy data to quantify the movement of people at a large scale. Existing means of counting vehicle occupants have proven insufficient for a variety of reasons. Most notably, these include complicated installations (outfitted seatbelt sensors with dedicated wiring), reliance on technology adoption (cell phone signal counting), driver participation (manual survey entry), etc. These limitations have hindered all interested stakeholders: vehicle fleet owners continue to be unaware of the number of serviced customers, researchers still rely on hand written survey information, and municipalities have no reliable technology to enforce occupancy-based measures (HOV lanes, passenger-based tolls, etc.). Therefore, an automated in-vehicle occupancy detection and counting system was designed to collect vehicle occupancy data with minimal human effort involved. This technology is the first of its kind with low cost, simple installation, and high accuracy. In fact, the device correctly identified the number of occupants in 99.7% of cases. Occupancy detection relates to many applications, ranging from energy intensity quantification and incentivizing high occupancy vehicle to fleet management and optimization.

Moniot, Matthew↗

NASA NTRS1988

Machine vision for real time orbital operations

Machine vision for automation and robotic operation of Space Station era systems has the potential for increasing the efficiency of orbital servicing, repair, assembly and docking tasks. A machine vision research project is described in which a TV camera is used for inputing visual data to a computer so that image processing may be achieved for real time control of these orbital operations. A technique has resulted from this research which reduces computer memory requirements and greatly increases typical computational speed such that it has the potential for development into a real time orbital machine vision system. This technique is called AI BOSS (Analysis of Images by Box Scan and Syntax).

Vinz, Frank L.↗

NASA NTRSDate not supplied

Crew Health and Performance Integrated Data Service Platform (CHP-IDSP): Project Updates

Future human exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting crew autonomy for future exploration missions. An integrated data services platform is needed to mitigate these risks by supporting a new generation of technologies and employing advanced analytical and predictive modeling techniques to enable crew autonomy for future exploration missions. The Crew Health and Performance Integrated Data System Platform (CHP-IDSP) project is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. This cohesive integration point will streamline the management of CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.) and facilitate situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the ongoing development effort of the path-to-flight CHP-IDSP software and the demonstration of its core capabilities. This includes a brief history of the project, the human-centered process used to identify data needs and workflows feeding the development of scenarios and requirements, and current subsystem development status. Current integrations, including the Chiron exploration electronic health record application, will be discussed. Future work includes collaboration with additional CHP domains and a flight technology demonstration.

Software↗

NASA NTRS1988

Real-time space system control with expert systems

Many aspects of space system operations involve continuous control of real time processes. These processes include electrical power system monitoring, prelaunch and ongoing propulsion system health and maintenance, environmental and life support systems, space suit checkout, onboard manufacturing, and vehicle servicing including satellites, shuttles, orbital maneuvering vehicles, orbital transfer vehicles and remote teleoperators. Traditionally, monitoring of these critical real time processes has been done by trained human experts monitoring telemetry data. However, the long duration of future space missions and the high cost of crew time in space creates a powerful economic incentive for the development of highly autonomous knowledge based expert control procedures for these space systems.

Leinweber, David↗

NASA NTRSDate not supplied

Evaluating Meteorological Dust Events and Machine-Learning Based Dust Identification in Geostationary Satellite Imagery

NASA scientists in the Short-term Prediction Research and Transition Center (SPoRT) developed a physically-based machine learning approach to identify dust in satellite imagery with a focus on night-time dust detection (Berndt et al. 201; DustTracker-AI). NASA/NOAA Geostationary Environmental Operational Satellite-16 (GOES-16) imagery was used for training and model inputs. The training, testing and validation data set consists of 28 events in the Southwest United States, capturing dust and null events in the region from 2018-2020.With 83 distinct images and millions of pixels a random forest model was trained and validated, correctly labeling 85% of dust pixels.For the first time, the model was run in near-real time production during the spring of 2022 and dust probability visualizations were made available to NOAA National Weather Service (NWS) forecasters to assess its utility for dust forecasting. Results indicated the model helped increase the confidence in the presence of dust and enabled dust tracking for a longer period of time into the night-time hours. Forecaster assessment and running the model in near real-time allowed for the team to determine the types of events missed, captured, and false alarms. To gain additional context on model performance,the SPoRT team sought to gather more detailed information on the training database(e.g., meteorological characteristics and drivers). The goal of this project was to identify the meteorological drivers for the dust events and create a database which synthesized information from observations, forecaster discussions, and analyses pertaining to the dust events to understand the types of events currently used to train the model. A more detailed meteorological synopsis was created for each dust event in the training, testing, and validation datasets. Following the completion of the database and documentation, the classification details revealed that 88% of the dust events were synoptically driven while mesoscale events were less prevalent in model datasets. Meteorological conditions found such as mixing layer depth and wind velocity had mean values of 645mb and 21kt respectively.With conditions of deep mixed layers and moderate to strong surface winds a mesoscale thunderstorm outflow event was considered and subsequently added to the model training data set to test the impact of additional mesoscale training data. The model was retrained and then qualitatively tested on a sample thunderstorm outflow case that the original model was unable to identify. Preliminary results showed potential that the addition of more mesoscale events included in the training data could help to better identify indistinct and localized dust events.

Connor Welch↗

NASA NTRS2016

Datalist: A Value Added Service to Enable Easy Data Selection

Imagine a user wanting to study hurricane events. This could involve searching and downloading multiple data variables from multiple data sets. The currently available services from the Goddard Earth Sciences Data and Information Services Center (GES DISC) only allow the user to select one data set at a time. The GES DISC started a Data List initiative, in order to enable users to easily select multiple data variables. A Data List is a collection of predefined or user-defined data variables from one or more archived data sets. Target users of Data Lists include science teams, individual science researchers, application users, and educational users. Data Lists are more than just data. Data Lists effectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services, all available from one-stop shopping. Data Lists are created based on the software architecture of the GES DISC Unified User Interface (UUI). The Data List service is completely data-driven, and a Data List is treated just as any other data set. The predefined Data Lists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend.

Datalist↗

DOE OSTI2021

ADDS-EVS: An agent-based deployment decision-support system for electric vehicle services

Rapid and sustainable development of the electric vehicle (EV) industry places the requirement for the plan of EV deployment. For public EV, existing models mainly focus on the charging facility design and fail to capture the multi-modal scenarios. In this work, we develop an agent-based decision-support system for multi-modal electric transits to locate the optimal combinations of key parameters, including the fleet size, the transit schedule, the charging facility design, and the routing strategy. We demonstrate the utilities of our system by simulating public EV services deployed to serve travel needs related to a transportation hub in New York City. To support the decision of the fleet size, we summarize system-level performances including the total satisfied demand, passengers' waiting time, vehicle idling time. The spatial and temporal patterns are extracted to serve a deeper understanding of system dynamics and service quality. Finally, we investigate the interaction between the fleet size design and the routing strategy. The results suggest a necessity of integrating the operation strategies into the planning phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

DERMS-RT (Distributed Energy Resource Management Solution using Real-Time Optimization) [SWR-20-46]

DERMS-RT provides a distributed energy resource management solution using real-time optimization to control different types of distributed energy resources (DERs) — such as rooftop PVs, battery energy storage systems, HVAC loads, electric water heater loads, and EV charging loads, and use these DERs to provide distribution voltage regulation and peak demand management services. The control approach implemented by DERM-RT is developed based on the real-time optimal power flow and distributed control previously developed by NREL researchers. The software codes are designed to provide modular DER management solution that can be easily applied to control heterogeneous DERs in distribution grids in coordination with centralized utility management systems. Also, DERMS-RT provides application programming interface (API) to extract useful grid model information from an open-source power system simulation software, use the information to solve the optimization problem, and apply the optimal set-points to the controlled DERs. In this way, DERMS-RT provides a plug-and-play function for implementing the real-time DER control on different utility system models, and it can be used as a simulation testbed to demonstrate the impact of real-time DER optimization on improving grid operations.

Ding, Fei↗