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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Real-time data display for AFTI/F-16 flight testing

Advanced fighter technologies to improve air to air and air to surface weapon delivery and survivability is demonstrated. Real time monitoring of aircraft operation during flight testing is necessary not only for safety considerations but also for preliminary evaluation of flight test results. The complexity of the AFTI/F-16 aircraft requires an extensive capability to accomplish real time data goals; that capability and the resultant product are described. Previously announced in STAR as N83-13095

Harney, P. F.↗
DOE OSTI2011

Medium Truck Duty Cycle Data from Real-World Driving Environments: Project Interim Report

Since the early part of the 20th century, the US trucking industry has provided a safe and economical means of moving commodities across the country. At the present time, nearly 80% of the US domestic freight movement involves the use of trucks. The US Department of Energy (DOE) is spearheading a number of research efforts to improve heavy vehicle fuel efficiencies. This includes research in engine technologies (including hybrid and fuel cell technologies), lightweight materials, advanced fuels, and parasitic loss reductions. In addition, DOE is developing advanced tools and models to support heavy vehicle truck research, and is leading the 21st Century Truck Partnership whose stretch goals involve a reduction by 50% of the fuel consumption of heavy vehicles on a ton-mile basis. This Medium Truck Duty Cycle (MTDC) Project is a critical element in DOE s vision for improved heavy vehicle energy efficiency and is unique in that there is no other national database of characteristic duty cycles for medium trucks. It involves the collection of real-world data for various situational characteristics (rural/urban, freeway/arterial, congested/free-flowing, good/bad weather, etc.) and looks at the unique nature of medium trucks drive cycles (stop-and-go delivery, power takeoff, idle time, short-radius trips), to provide a rich source of data that can contribute to the development of new tools for fuel efficiency and modeling, provide DOE a sound basis upon which to make technology investment decisions, and provide a national archive of real-world-based medium-truck operational data to support heavy vehicle energy efficiency research. The MTDC project involves a two-part field operational test (FOT). For the Part-1 FOT, three vehicles, each from two vocations (urban transit and dry-box delivery) were instrumented for one year of data collection. The Part-2 FOT will involve the towing/recovery and utility vocations. The vehicles participating in the MTDC project are doing so through gratis partnerships in return for early access to the results of this study. Partnerships such as these are critical to FOTs in which real-world data is being collected. In Part 1 of the project, Oak Ridge National Laboratory(ORNL) established partnerships with the H.T. Hackney Company, one of the largest wholesale distributors in the country, distributing products to 21 states; and with the Knoxville Area Transit (KAT), the City of Knoxville s transit system, operating services across the city of Knoxville and parts of Knox co. These partnerships and agreements provided ORNL access to three Class-7 2005/2007 International day-cab tractors, model 8600, which regularly haul 28 ft pup trailers (H.T. Hackney Co) and three Class-7 2005 Optima LF-34 buses (KAT), for collection of duty cycle data. In addition, ORNL has collaborated with the Federal Motor Carrier Safety Administration (FMCSA) to determine if there were possible synergies between this duty cycle data collection effort and FMCSA s need to learn more about the operation and duty cycles of the second-largest fuel consuming commercial vehicle category in the US. FMCSA s primary interest was in collecting safety data relative to the driver, carrier, and vehicle. In order to collect the duty cycle and safety-related data, ORNL developed a data acquisition and wireless communication system that was placed on each test vehicle. Each signal recorded in this FOT was collected by means of one of the instruments incorporated into each data acquisition system (DAS). Native signals were obtained directly from the vehicle s J1939 and J1708 data buses. A VBOX II Lite collected Global Positioning System related information including speed, acceleration, and spatial location information at a rate of 5 Hz, and communicated this data via the CAN (J1939) protocol. The Air-Weigh LoadMaxx, a self-weighing system which determines the vehicle s gross weight by means of pressure transducers and posts the weight to the vehicle s J1939 data bus, was used to collect vehicle payload information. A cellular modem, the Raven X EVDO V4221, facilitated the communication between the eDAQ-lite (the data collection engine of the system) and the user, via the internet. The modem functioned as a wireless gateway, allowing data retrievals and system checks to be performed remotely. Also, and in partnership with FMCSA, two additional safety sensors were installed on the combination vehicles: the MGM e-Stroke brake monitoring system and the Tire SafeGuard tire pressure monitoring system. Both of these systems posted data to the J1939 data bus, enabling these signals to be read without any additional DAS interface hardware. Seventy-three signals from the different deployed sensors and available vehicle systems were collected. Because of the differences in vehicle data buses (i.e., J1939 and J1708 data buses), not all desired signals were available for both types of vehicles.

duty cycles↗
NASA NTRS2002

Novel Advancements in Internet-Based Real-Time Data Technologies

AZ Technology has been working with NASA MSFC (Marshall Space Flight Center) to find ways to make it easier for remote experimenters (RPI's) to monitor their International Space Station (ISS) payloads in real-time from anywhere using standard/familiar devices. That effort resulted in a product called 'EZStream' which is in use on several ISS-related projects. Although the initial implementation is geared toward ISS, the architecture and lessons learned are applicable to other space-related programs. This paper begins with a brief history on why Internet-based real-time data is important and where EZStream or products like it fit in the flow of data from orbit to experimenter/researcher. A high-level architecture is then presented along with explanations of the components used. A combination of commercial-off-the-shelf (COTS), Open Source, and custom components are discussed. The use of standard protocols is shown along with some details on how data flows between server and client. Some examples are presented to illustrate how a system like EZStream can be used in real world applications and how care was taken to make the end-user experience as painless as possible. A system such as EZStream has potential in the commercial (non-ISS) arena and some possibilities are presented. During the development and fielding of EZStream, a lot was learned. Good and not so good decisions were made. Some of the major lessons learned will be shared. The development of EZStream is continuing and the future of EZStream will be discussed to shed some light over the technological horizon.

Myers, Gerry↗
DOE OSTI2022

Hypothesis-Agnostic Network-Based Analysis of Real-World Data Suggests Ondansetron is Associated with Lower COVID-19 Any Cause Mortality

Background: The COVID-19 pandemic generated a massive amount of clinical data, which potentially hold yet undiscovered answers related to COVID-19 morbidity, mortality, long-term effects, and therapeutic solutions.Objectives: The objectives of this study were (1) to identify novel predictors of COVID-19 any cause mortality by employing artificial intelligence analytics on real-world data through a hypothesis-agnostic approach and (2) to determine if these effects are maintained after adjusting for potential confounders and to what degree they are moderated by other variables.Methods: A Bayesian statistics-based artificial intelligence data analytics tool (bAIcis®) within the Interrogative Biology® platform was used for Bayesian network learning and hypothesis generation to analyze 16,277 PCR+ patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated Bayesian networks that enabled unbiased identification of significant predictors of any cause mortality for specific COVID-19 patient populations. These findings were further analyzed by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping.Results: We found that in the COVID-19 PCR+ patient cohort, early use of the antiemetic agent ondansetron was associated with decreased any cause mortality 30 days post-PCR+ testing in mechanically ventilated patients.Conclusions: The results demonstrate how a real-world COVID-19-focused data analysis using artificial intelligence can generate unexpected yet valid insights that could possibly support clinical decision making and minimize the future loss of lives and resources.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Local Weather Station Design and Development for Cost-Effective Environmental Monitoring and Real-Time Data Sharing

Current weather monitoring systems often remain out of reach for small-scale users and local communities due to their high costs and complexity. This paper addresses this significant issue by introducing a cost-effective, easy-to-use local weather station. Utilizing low-cost sensors, this weather station is a pivotal tool in making environmental monitoring more accessible and user-friendly, particularly for those with limited resources. It offers efficient in-site measurements of various environmental parameters, such as temperature, relative humidity, atmospheric pressure, carbon dioxide concentration, and particulate matter, including PM 1, PM 2.5, and PM 10. The findings demonstrate the station’s capability to monitor these variables remotely and provide forecasts with a high degree of accuracy, displaying an error margin of just 0.67%. Furthermore, the station’s use of the Autoregressive Integrated Moving Average (ARIMA) model enables short-term, reliable forecasts crucial for applications in agriculture, transportation, and air quality monitoring. Furthermore, the weather station’s open-source nature significantly enhances environmental monitoring accessibility for smaller users and encourages broader public data sharing. With this approach, crucial in addressing climate change challenges, the station empowers communities to make informed decisions based on real-time data. In designing and developing this low-cost, efficient monitoring system, this work provides a valuable blueprint for future advancements in environmental technologies, emphasizing sustainability. The proposed automatic weather station not only offers an economical solution for environmental monitoring but also features a user-friendly interface for seamless data communication between the sensor platform and end users. This system ensures the transmission of data through various web-based platforms, catering to users with diverse technical backgrounds. Furthermore, by leveraging historical data through the ARIMA model, the station enhances its utility in providing short-term forecasts and supporting critical decision-making processes across different sectors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

PvaPy streaming framework for real-time data processing

User facility upgrades, new measurement techniques, advances in data analysis algorithms as well as advances in detector capabilities result in an increasing amount of data collected at X-ray beamlines. Some of these data must be analyzed and reconstructed on demand to help execute experiments dynamically and modify them in real time. In turn, this requires a computing framework for real-time processing capable of moving data quickly from the detector to local or remote computing resources, processing data, and returning results to users. In this paper, we discuss the streaming framework built on top of PvaPy, a Python API for the EPICS pvAccess protocol. We describe the framework architecture and capabilities, and discuss scientific use cases and applications that benefit from streaming workflows implemented on top of this framework. We also illustrate the framework's performance in terms of achievable data-processing rates for various detector image sizes.

EPICS pvAccess↗
DOE OSTI2016

Improved tomographic reconstruction of large-scale real-world data by filter optimization

In advanced tomographic experiments, large detector sizes and large numbers of acquired datasets can make it difficult to process the data in a reasonable time. At the same time, the acquired projections are often limited in some way, for example having a low number of projections or a low signal-to-noise ratio. Direct analytical reconstruction methods are able to produce reconstructions in very little time, even for large-scale data, but the quality of these reconstructions can be insufficient for further analysis in cases with limited data. Iterative reconstruction methods typically produce more accurate reconstructions, but take significantly more time to compute, which limits their usefulness in practice. In this paper, we present the application of the SIRT-FBP method to large-scale real-world tomographic data. The SIRT-FBP method is able to accurately approximate the simultaneous iterative reconstruction technique (SIRT) method by the computationally efficient filtered backprojection (FBP) method, using precomputed experiment-specific filters. We specifically focus on the many implementation details that are important for application on large-scale real-world data, and give solutions to common problems that occur with experimental data. We show that SIRT-FBP filters can be computed in reasonable time, even for large problem sizes, and that precomputed filters can be reused for future experiments. Reconstruction results are given for three different experiments, and are compared with results of popular existing methods. The results show that the SIRT-FBP method is able to accurately approximate iterative reconstructions of experimental data. Furthermore, they show that, in practice, the SIRT-FBP method can produce more accurate reconstructions than standard direct analytical reconstructions with popular filters, without increasing the required computation time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Simultaneous real-time data collection methods

This paper describes the development of electronic test equipment which executes, supervises, and reports on various tests. This validation process uses computers to analyze test results and report conclusions. The test equipment consists of an electronics component and the data collection and reporting unit. The PC software, display screens, and real-time data-base are described. Pass-fail procedures and data replay are discussed. The OS2 operating system and Presentation Manager user interface system were used to create a highly interactive automated system. The system outputs are hardcopy printouts and MS DOS format files which may be used as input for other PC programs.

Klincsek, Thomas↗
NASA NTRS1994

Single Stage Rocket Technology's real time data system

The Single Stage Rocket Technology (SSRT) Delta Clipper Experimental (DC-X) Program is a United States Air Force Ballistic Missile Defense Organization (BMDO) rapid prototyping initiative that is currently demonstrating technology readiness for reusable suborbital rockets. The McDonnell Douglas DC-X rocket performed technology demonstrations at the U.S. Army White Sands Missile Range in New Mexico from April-October in 1993. The DC-X Flight Operations Control Center (FOCC) contains the ground control system that is used to monitor and control the DC-X vehicle and its Ground Support Systems (GSS). The FOCC is operated by a flight crew of three operators. Two operators manage the DC-X Flight Systems and one operator is the Ground Systems Manager. A group from McDonnell Douglas Aerospace at KSC developed the DC-X ground control system for the FOCC. This system is known as the Real Time Data System (RTDS). The RTDS is a distributed real time control and monitoring system that utilizes the latest available commercial off-the-shelf computer technology. The RTDS contains front end interfaces for the DC-X RF uplink/downlink and fiber optic interfaces to the GSS equipment. This paper describes the RTDS architecture and FOCC layout. The DC-X applications and ground operations are covered.

Voglewede, Steven D.↗
DOE OSTI2025

A Digital Twin for an Inverter-Based Resource Power Plant: Real-time data streaming unlocks situation awareness

Here, this study presents the development and successful implementation of a digital twin specifically designed for a grid-connected IBR power plant. By integrating a reduced-order model of the IBR system and dynamically updating the grid impedance with real-time data, the digital twin effectively captures and replicates the behavior of the physical system. Its accuracy and reliability are validated through critical test scenarios, including a three-phase fault and a line-tripping event. The results confirm that the digital twin closely emulates its physical counterpart, demonstrating its strong potential for real-time analysis, system monitoring, and predictive decision making in modern power systems.

Digital twins↗
NASA NTRS2006

LiveView3D: Real Time Data Visualization for the Aerospace Testing Environment

This paper addresses LiveView3D, a software package and associated data visualization system for use in the aerospace testing environment. The LiveView3D system allows researchers to graphically view data from numerous wind tunnel instruments in real time in an interactive virtual environment. The graphical nature of the LiveView3D display provides researchers with an intuitive view of the measurement data, making it easier to interpret the aerodynamic phenomenon under investigation. LiveView3D has been developed at the NASA Langley Research Center and has been applied in the Langley Unitary Plan Wind Tunnel (UPWT). This paper discusses the capabilities of the LiveView3D system, provides example results from its application in the UPWT, and outlines features planned for future implementation.

Schwartz, Richard J.↗
NASA NTRS1979

Wind tunnel real-time data acquisition system

The hardware configuration is described for the data acquisition system (DAS) which consists of an analog front end that can process up to 260 channels of data, a multichannel analog-to-digital subsystem that can process up to 50,000 samples of data per second, and a digital computer with standard and nonstandard devices, including graphics capability. Also described are the software configuration of the DAS and complex hardware/software interfaces providing, for example, automatic amplifier gain and offset adjustment for each data channel. Specific DAS applications are summarized, including the real time processing of dynamic deflection data, unsteady pressure measurements, and flutter and buffet data.

Cole, P.↗
NASA NTRS1990

Real-time data system: Incorporating new technology in mission critical environments

If the Space Station Freedom is to remain viable over its 30-year life span, it must be able to incorporate new information systems technologies. These technologies are necessary to enhance mission effectiveness and to enable new NASA missions, such as supporting the Lunar-Mars Initiative. Hi-definition television (HDTV), neural nets, model-based reasoning, advanced languages, CPU designs, and computer networking standards are areas which have been forecasted to make major strides in the next 30 years. A major challenge to NASA is to bring these technologies online without compromising mission safety. In past programs, NASA managers have been understandably reluctant to rely on new technologies for mission critical activities until they are proven in noncritical areas. NASA must develop strategies to allow inflight confidence building and migration of technologies into the trusted tool base. NASA has successfully met this challenge and developed a winning strategy in the Space Shuttle Mission Control Center. This facility, which is clearly among NASA's most critical, is based on 1970's mainframe architecture. Changes to the mainframe are very expensive due to the extensive testing required to prove that changes do not have unanticipated impact on critical processes. Systematic improvement efforts in this facility have been delayed due to this 'risk to change.' In the real-time data system (RTDS) we have introduced a network of engineering computer workstations which run in parallel to the mainframe system. These workstations are located next to flight controller operating positions in mission control and, in some cases, the display units are mounted in the traditional mainframe consoles. This system incorporates several major improvements over the mainframe consoles including automated fault detection by real-time expert systems and color graphic animated schematics of subsystems driven by real-time telemetry. The workstations have the capability of recording telemetry data and providing 'instant replay' for flight controllers. RTDS also provides unique graphics animated by real-time telemetry such as workstation emulation of the shuttle's flight instruments and displays of the remote manipulator system (RMS) position. These systems have been used successfully as prime operational tools since STS-26 and have supported seven shuttle missions.

Muratore, John F.↗
NASA NTRS1992

Menu-Driven Program Displays Data In Real Time

JPL/VIEW is menu-driven program retrieving and displaying incoming propagation data as they reach hard disk of data-acquisition-and-storage system. Real-time display enables operator to monitor progress of events and respond swiftly to errors during experiment or trial operation. Written in Microsoft C.

Mckeeman, John C.↗
NASA NTRS1976

Applications of the real-time data analysis system in the Ames 40- by 80-foot wind tunnel

The first major overhaul and refurbishment of the Ames 40- by 80-foot wind tunnel since it was put into operation in 1944 was recently completed. A substantial part of this refurbishment was devoted to providing this wind tunnel with a modern real time data acquisition and analysis system to increase the safety, efficiency, and accuracy of experimental investigations in this facility. Background leading to the requirements for the new system, major elements of the system, and some of the applications of the system are summarized. The potential of computerized data acquisition systems for wind tunnels in terms of long term trends in hardware and software costs, and the constraints which must be dealt with to achieve the full potential of computerized data acquisition systems are discussed.

Kelly, M. W.↗
DOE OSTI2016

ZEM: Integrated Framework for Real-Time Data and Model Analyses for Robust Environmental Management Decision Making - 16438

Typically environmental management (EM) problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly analysis, assimilation and integration into a series of models with different complexity for various types of model-based analyses. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian-Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is predominantly coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org) and incorporates the MADS computational tools (Model Analysis and Decision Support; http://mads.lanl.gov). We demonstrate the application of ZEM for data and model analyses at the LANL Chromium site. The ZEM framework will be released as open-source code and can be applied to any environmental management site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗