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DOE OSTI2024

Dataset: Breaking the barrier of human-annotated training data for machine-learning-aided plant research using aerial imagery

This dataset supports the implementation described in the manuscript "Breaking the Barrier of Human-Annotated Training Data for Machine-Learning-Aided Biological Research Using Aerial Imagery." It comprises UAV aerial imagery used to execute the code available at https://github.com/pixelvar79/GAN-Flowering-Detection-paper. For detailed information on dataset usage and instructions for implementing the code to reproduce the study, please refer to the GitHub repository.

generative and adversarial learning↗

DOE OSTI2024

Developing Data-Driven Synthetic Infrastructure Models for Resilience Analysis

Research on infrastructure resilience has produced promising methods to simulate and optimize complex networks to improve performance. However, restrictions on sharing infrastructure models and the steep cost of developing and maintaining infrastructure models presents a roadblock to adoption. To overcome this limitation, this research focuses on methods to create data-driven infrastructure models that will help improve infrastructure resilience and security. The analysis couples incomplete utility data, geospatial data, machine learning, and synthetic network generation methods to rapidly develop and update infrastructure models. The methods are validated using realistic utility models and site-specific data, with a focus on Puerto Rico due to its unique infrastructure challenges and available data. This research highlights promising opportunities for the use of synthetic network generation and machine learning to create infrastructure models when very little data is available. Results demonstrate that hybrid methods, which combine sparse utility data with synthetic models, can enhance model accuracy, and machine learning can predict model attributes using training data from other models. However, the complexity of infrastructure systems means that even minor changes in network connectivity can significantly impact simulation results. Resilience analysis using synthetic infrastructure models shows that while some system behaviors are preserved, the magnitude of disruptions may not be accurately represented, indicating the need for more research and validation before using synthetic models for critical infrastructure investment decisions. The framework outlined in this report represents a significant advance to infrastructure model development and could be applied to additional domains and sites. Future research will continue to streamline and validate methods to help reduce roadblocks to resilience analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2014

NASA's Astromaterials Database: Enabling Research Through Increased Access to Sample Data, Metadata and Imagery

The Astromaterials Acquisition & Curation Office at NASA's Johnson Space Center (JSC) is the designated facility for curating all of NASA's extraterrestrial samples. Today, the suite of collections includes the lunar samples from the Apollo missions, cosmic dust particles falling into the Earth's atmosphere, meteorites collected in Antarctica, comet and interstellar dust particles from the Stardust mission, asteroid particles from Japan's Hayabusa mission, solar wind atoms collected during the Genesis mission, and space‐exposed hardware from several missions. To support planetary science research on these samples, JSC's Astromaterials Curation Office hosts NASA's Astromaterials Curation digital repository and data access portal [http://curator.jsc.nasa.gov/], providing descriptions of the missions and collections, and critical information about each individual sample. Our office is designing and implementing several informatics initiatives to better serve the planetary research community. First, we are re‐hosting the basic database framework by consolidating legacy databases for individual collections and providing a uniform access point for information (descriptions, imagery, classification) on all of our samples. Second, we continue to upgrade and host digital compendia that summarize and highlight published findings on the samples (e.g., lunar samples, meteorites from Mars). We host high resolution imagery of samples as it becomes available, including newly scanned images of historical prints from the Apollo missions. Finally we are creating plans to collect and provide new data, including 3D imagery, point cloud data, micro CT data, and external links to other data sets on selected samples. Together, these individual efforts will provide unprecedented digital access to NASA's Astromaterials, enabling preservation of the samples through more specific and targeted requests, and supporting new planetary science research and collaborations on the samples.

Evans, Cindy↗

NASA NTRS1986

PCDS as a tool in teaching and research at the University of Michigan

The Space Physics Research Laboratory's (SPRL) use of the Pilot Climate Data System (PCDS) is discussed. For this purpose, a computer center was established to provide the hardware and software necessary to fully utilize existing data bases for research and teaching purposes. A schematic of the SPRL network is given. The core of the system consists of two VAX 11/750s and a VAX 8600, networked through ETHERNET to several LSI 11/23 microprocessors. Much of the system is used for external communications with major networks and data centers. A VAX 11/750 provides DECNET services through the SPAN network to the PCDS. A functional diagram of PCDS usage is given. The browsing capabilities of the PCDS are used to generate data files, which are later transferred to the SPRL center for further data manipulation and display. This mode of operation for classroom instruction will be used to effectively use terminals and to simplify usage of the data base. The Atmosphere Explorer data base has been used successfully in a similar manner in courses related to the thermosphere and ionosphere. The main motivation to access the PCDS was to complement research efforts related to the High Resolution Doppler Imager (HRDI), to be flown on the Upper Atmosphere Research Satellite (UARS).

Abreu, V.↗

DOE OSTI2025

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data↗

NASA NTRS1983

Research and technology: Report, FY 1982

Sensor systems, data analysis programs, agriculture and resources inventory survey through aerospace remote sensing (AgRISTARS), applied research and data analysis, joint research project, and testing and evaluation are reported.

Source record↗

NASA NTRS1991

Examining several Southern Ocean data sets

Several datasets regarding the ocean in the Southern Hemisphere are combined into a coregistered format to analyze the use of the data in multidisciplinary research. The datasets are described detailing bathymetric climatological data on surface pigment concentration, eddy-kinetic-energy measurements, surface wind-stress magnitudes, sea-surface temperatures, surface densities, and nitrate concentrations. The data are combined in a common projection which facilitates the comparison of the fields, and the combined data yield insights regarding such phenomena as bottom topography, surface heat and moisture fluxes, and divergences in flow. The number of available datasets is shown to be good, and the data can be used to develop working hypotheses on the relationships between physical and biogeochemical processes.

Mcclain, Charles R.↗

NASA NTRS2006

Solutions Network Formulation Report. Integration of OMI and TES Aerosol Products into the EPA Regional Planning Organizations' FASTNET Aerosol Tracking and Analysis Tool

Every year, more than 280 million visitors tour our Nation s most treasured parks and wilderness areas. Unfortunately, many visitors are unable to see the spectacular vistas they expect because of white or brown haze in the air. Most of this haze is not natural; it is air pollution, carried by the wind often hundreds of miles from its origin. Some of the pollutants have been linked to serious health problems, such as asthma and other lung disorders, and even premature death. In addition, nitrates and sulfates contribute to acid rain formation, which contaminates rivers and lakes and erodes buildings and historical monuments. The U.S. Environmental Protection Agency RPOs (Regional Planning Organizations) have been tasked with monitoring and determining the nature and origin of haze in Class I scenic areas, and finding ways to reduce haze in order to improve visibility in these areas. The RPOs have developed an Internet-based air quality DST (Decision Support Tool) called FASTNET (Fast Aerosol Sensing Tools for Natural Event Tracking). While FASTNET incorporates a few satellite datasets, most of the data utilized by this DST comes from ground-based instrument networks. The problem is that in many areas the sensors are sparsely located, with long distances between them, causing difficulties in tracking haze over the United States, determining its source, and analyzing its content. Satellite data could help to fill in the data gaps and to supplement and verify ground-recorded air quality data. Although satellite data are now being used for air quality research applications, such data are not routinely used for environmental decision support, in part because of limited resources, difficulties with interdisciplinary data interpretation, and the need for advanced inter-agency partnerships. As a result, the validation and verification of satellite data for air quality operational system applications has been limited This candidate solution evaluates the usefulness of OMI (Ozone Monitoring Instrument) and TES (Tropospheric Emission Spectrometer) air quality data for the RPOs by comparing OMI and TES data with ground-based data that are acquired during identified episodes of air pollution. The air quality data from OMI and TES are of different spectral ranges than data from satellites currently included in FASTNET, giving them potential advantages over the existing satellites. If the OMI and TES data are shown to be useful to the RPOs, they would then be integrated into the FASTNET DST for use on an operational basis.

Knowlton, Kelly↗

NASA NTRS2005

ESTIMATING THE BENEFIT OF TRMM TROPICAL CYCLONE DATA IN SAVING LIVES

The Tropical Rainfall Measuring Mission (TRMM) is a joint NASA/JAXA research mission launched in late 1997 to improve our knowledge of tropical rainfall processes and climatology (Kummerow et ai., 2000; Adler et ai., 2003). In addition to being a highly successful research mission, its data are available in real time and operational weather agencies in the U.S. and internationally are using TRMM data and images to monitor and forecast hazardous weather (tropical cyclones, floods, etc.). For example, in 2004 TRMM data were used 669 times for determining tropical cyclone location fixes (National Research Council, 2004). TRMM flies at a relatively low altitude, 400 km, and requires orbit adjustment maneuvers to maintain altitude against the small drag of the atmosphere. There is enough fuel used for these maneuvers remaining on TRMM for the satellite to continue flying until 2011-12. However, most of the remaining fuel may be used to perform a controlled re-entry of the satellite into the Pacific Ocean. The fuel threshold for this operation will be reached in the summer of 2005, although the maneuver would actually occur in late 2006 or 2007. The full science mission would end in 2005 under the controlled re-entry option. This re-entry option is related to the estimated probability of injury (1/5,000) that might occur during an uncontrolled re-entry of the satellite. If the estimated probability of injury exceeds 1/10,000 a satellite is a candidate for a possible controlled re-entry. In the TRMM case the NASA Safety Office examined the related issues and concluded that, although TRMM exceeded the formal threshold, the use of TRMM data in the monitoring and forecasting of hazardous weather gave a public safety benefit that compensated for TRMM slightly exceeding the orbital debris threshold (Martin, 2002). This conclusion was based in part on results of an independent panel during a workshop on benefits of TRMM data in concluded that the benefit of TRMM data in saving lives through its use in operational forecasting could not be quantified. The objective of this paper is to describe a possible technique to estimate the number of lives saved per year and apply it to the TRMM case and the use of its data in monitoring and forecasting tropical cyclones.

Adler, Robert F.↗

NASA NTRS2014

Full Scale Advanced Systems Testbed (FAST): Capabilities and Recent Flight Research

At the NASA Armstrong Flight Research Center research is being conducted into flight control technologies that will enable the next generation of air and space vehicles. The Full Scale Advanced Systems Testbed (FAST) aircraft provides a laboratory for flight exploration of these technologies. In recent years novel but simple adaptive architectures for aircraft and rockets have been researched along with control technologies for improving aircraft fuel efficiency and control structural interaction. This presentation outlines the FAST capabilities and provides a snapshot of the research accomplishments to date. Flight experimentation allows a researcher to substantiate or invalidate their assumptions and intuition about a new technology or innovative approach Data early in a development cycle is invaluable for determining which technology barriers are real and which ones are imagined Data for a technology at a low TRL can be used to steer and focus the exploration and fuel rapid advances based on real world lessons learned It is important to identify technologies that are mature enough to benefit from flight research data and not be tempted to wait until we have solved all the potential issues prior to getting some data Sometimes a stagnated technology just needs a little real world data to get it going One trick to getting data for low TRL technologies is finding an environment where it is okay to take risks, where occasional failure is an expected outcome Learning how things fail is often as valuable as showing that they work FAST has been architected to facilitate this type of testing for control system technologies, specifically novel algorithms and sensors Rapid prototyping with a quick turnaround in a fly-fix-fly paradigm Sometimes it's easier and cheaper to just go fly it than to analyze the problem to death The goal is to find and test control technologies that would benefit from flight data and find solutions to the real barriers to innovation. The FAST vehicle is a flexible laboratory for nascent technologies that would benefit from early life cycle flight research data It provides a robust and safe environment where innovative techniques can be explored in a fly-fix-fly rapid prototyping paradigm IRAC Simple adaptive control technologies can provide real benefits without undo complexity Adverse pilot/adaptive system interactions can be mitigated and tools have been developed to evaluate those interactions ICP Substantial fuel savings can be achieved over a broad range of vehicles and configurations with intelligent control solutions LVAC The AAC design is robust and effective for the SLS mission, and promises to provide benefits to other platforms as well OCLA Hopefully will show that structural feedback can be seamlessly integrated with performance and stability objectives All of these control technologies have been implemented into the same baseline control law and could be combined into one control solution that answers many pressing questions for modern vehicle configurations

flight controls↗

NASA NTRS2003

Application of a Split-Fiber Probe to Velocity Measurement in the NASA Research Compressor

A split-fiber probe was used to acquire unsteady data in a research compressor. The probe has two thin films deposited on a quartz cylinder 200 microns in diameter. A split-fiber probe allows simultaneous measurement of velocity magnitude and direction in a plane that is perpendicular to the sensing cylinder, because it has its circumference divided into two independent parts. Local heat transfer considerations indicated that the probe direction characteristic is linear in the range of flow incidence angles of +/- 35. Calibration tests confirmed this assumption. Of course, the velocity characteristic is nonlinear as is typical in thermal anemometry. The probe was used extensively in the NASA Glenn Research Center (GRC) low-speed, multistage axial compressor, and worked reliably during a test program of several months duration. The velocity and direction characteristics of the probe showed only minute changes during the entire test program. An algorithm was developed to decompose the probe signals into velocity magnitude and velocity direction. The averaged unsteady data were compared with data acquired by pneumatic probes. An overall excellent agreement between the averaged data acquired by a split-fiber probe and a pneumatic probe boosts confidence in the reliability of the unsteady content of the split-fiber probe data. To investigate the features of unsteady data, two methods were used: ensemble averaging and frequency analysis. The velocity distribution in a rotor blade passage was retrieved using the ensemble averaging method. Frequencies of excitation forces that may contribute to high cycle fatigue problems were identified by applying a fast Fourier transform to the absolute velocity data.

Lepicovsky, Jan↗

NASA NTRS2003

A High Temperature Cyclic Oxidation Data Base for Selected Materials Tested at NASA Glenn Research Center

The cyclic oxidation test results for some 1000 high temperature commercial and experimental alloys have been collected in an EXCEL database. This database represents over thirty years of research at NASA Glenn Research Center in Cleveland, Ohio. The data is in the form of a series of runs of specific weight change versus time values for a set of samples tested at a given temperature, cycle time, and exposure time. Included on each run is a set of embedded plots of the critical data. The nature of the data is discussed along with analysis of the cyclic oxidation process. In addition examples are given as to how a set of results can be analyzed. The data is assembled on a read-only compact disk which is available on request from Materials Durability Branch, NASA Glenn Research Center, Cleveland, Ohio.

Barrett, Charles A.↗

NASA NTRS1973

Development of flight experiment work performance and workstation interface requirements, part 1. Technical report and appendices A through G

A skill requirement definition method was applied to the problem of determining, at an early stage in system/mission definition, the skills required of on-orbit crew personnel whose activities will be related to the conduct or support of earth-orbital research. The experiment data base was selected from proposed experiments in NASA's earth orbital research and application investigation program as related to space shuttle missions, specifically those being considered for Sortie Lab. Concepts for two integrated workstation consoles for Sortie Lab experiment operations were developed, one each for earth observations and materials sciences payloads, utilizing a common supporting subsystems core console. A comprehensive data base of crew functions, operating environments, task dependencies, task-skills and occupational skills applicable to a representative cross section of earth orbital research experiments is presented. All data has been coded alphanumerically to permit efficient, low cost exercise and application of the data through automatic data processing in the future.

Hatterick, R. G.↗

NASA NTRS1992

Determination of the stability and control derivatives of the F/A-18 HARV from flight data using the maximum likelihood method

The research being conducted pertains to the determination of the stability and control derivatives of the F/A-18 High Alpha Research Vehicle (HARV) from flight data using the Maximum Likelihood Method. The document outlines the approach used in the parameter estimation (PID) process and briefly describes the mathematical modeling of the F/A-18 HARV and the maneuvers designed to generate a sufficient data base for the PID research.

Napolitano, Marcello R.↗

NASA NTRS1999

Ocean-Atmosphere Interaction in Climate Changes

The diagram, which attests the El Nino teleconnection observed by the NASA Scatterometer (NSCAT) in 1997, is an example of the results of our research in air-sea interaction - the core component of our three-part contribution to the Climate Variability Program. We have established an interplay among scientific research, which turns spacebased data into knowledge, a push in instrument technology, which improves observations of climate variability, and an information system, which produces and disseminates new data to support our scientific research. Timothy Liu led the proposal for advanced technology, in response to the NASA Post-2002 Request for Information. The sensor was identified as a possible mission for continuous ocean surface wind measurement at higher spatial resolution, and with the unique capability to measure ocean surface salinity. He is participating in the Instrument Incubator Program to improve the antenna technology, and is initiating a study to integrate the concept on Japanese missions. He and his collaborators have set up a system to produce and disseminate high level (gridded) ocean surface wind/stress data from NSCAT and European missions. The data system is being expanded to produce real-time gridded ocean surface winds from Quikscat, and precipitation and evaporation from the Tropical Rain Measuring Mission. It will form the basis for a spacebased data analysis system which will include momentum, heat and water fluxes. The study on 1997 El Nino teleconnection illustrates our interdisciplinary and multisensor approach to study climate variability. The diagram shows that the collapse of trade wind and the westerly wind anomalies in the central equatorial Pacific led to the equatorial ocean warming. The equatorial wind anomalies are connected to the anomalous cyclonic wind pattern in the northeast Pacific. The anomalous warming along the west coast of the United States is the result of the movement of the pre-existing warm sea surface temperature anomalies with the cyclonic wind anomalies toward the coast. The results led to a new study which identifies decadal ocean variations in the Northeast Pacific. Three studies of oceanic responses to wind forcing caused by the seasonal change of monsoons, the passage of a typhoon, and the 1997 El Nino, were successfully conducted. Besides wind forcing, we continue to examine new techniques for estimating thermal and hydrologic fluxes, through the inverse ocean mixed-layer model, through divergence of atmospheric water transport, and by direct retrieval from radiances observed by microwave radiometers. Greenhouse warming has been linked to water vapor measured by two spaceborne sensors in two studies. In the first study, strong baroclinicity and deep convection were found to transport water vapor to the upper atmosphere and increase greenhouse trapping over the storm tracks of the North Pacific and Atlantic. In another study, the annual cycle of greenhouse warming were related to sea surface temperature (SST) and integrated water vapor, and the latitudinal dependence of the magnitudes and phases of the annual cycles were compared.

Liu, W. Timothy↗

NASA NTRS1993

Identification and interpretation of patterns in rocket engine data

The goal of our research is to analyze ground test data, to identify patterns associated with the anomalous engine behavior. On the basis of this analysis, it is the task of our project to develop a Pattern Identification and Detection System which detects anomalous engine behavior in the early stages of fault development significantly earlier than the indication provided by either redline detection mechanism or human expert analysis. Early detection of these anomalies is challenging because of the large amount of noise presence in the data. In the presence of this noise, early indication of anomalies becomes even more difficult to distinguish from fluctuations in normal steady state operation.

Lo, Ching F.↗

DOE OSTI2020

Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)

In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.

03 NATURAL GAS↗

NASA NTRS1998

The Data Acquisition and Control Systems of the Jet Noise Laboratory at the NASA Langley Research Center

The features of the data acquisition and control systems of the NASA Langley Research Center's Jet Noise Laboratory are presented. The Jet Noise Laboratory is a facility that simulates realistic mixed flow turbofan jet engine nozzle exhaust systems in simulated flight. The system is capable of acquiring data for a complete take-off assessment of noise and nozzle performance. This paper describes the development of an integrated system to control and measure the behavior of model jet nozzles featuring dual independent high pressure combusting air streams with wind tunnel flow. The acquisition and control system is capable of simultaneous measurement of forces, moments, static and dynamic model pressures and temperatures, and jet noise. The design concepts for the coordination of the control computers and multiple data acquisition computers and instruments are discussed. The control system design and implementation are explained, describing the features, equipment, and the experiences of using a primarily Personal Computer based system. Areas for future development are examined.

Jansen, B. J., Jr.↗