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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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A two-page fact sheet on the capabilities and core services of the Livewire Data Platform, a growing catalog of transportation and mobility-related data that empowers researchers and community planners to easily and securely share and preserve data that support projects and decision making.
A two-page fact sheet on the capabilities and core services of the Livewire Data Platform, a growing catalog of transportation and mobility-related data that empowers researchers and community planners to easily and securely share and preserve data that support projects and decision making.
The development of B-1 aircraft rigid wind tunnel data for use in subsequent tasks of the Airloads Research Study is described. Data from the Rockwell International external structural loads data bank were used to generate coefficients of rigid airload shear, bending moment, and torsion at specific component reference stations or both symmetric and asymmetric loadings. Component stations include the movable wing, horizontal and vertical stabilizers, and forward and aft fuselages. The coefficient data cover a Mach number range from 0.7 to 2.2 for a wing sweep position of 67.5 degree.
This report describes research conducted to use data science and machine learning methods to distinguish targeted genome editing versus natural mutation and sequencer machine noise. Genome editing capabilities have been around for more than 20 years, and the efficiencies of these techniques has improved dramatically in the last 5+ years, notably with the rise of CRISPR-Cas technology. Whether or not a specific genome has been the target of an edit is concern for U.S. national security. The research detailed in this report provides first steps to address this concern. A large amount of data is necessary in our research, thus we invested considerable time collecting and processing it. We use an ensemble of decision tree and deep neural network machine learning methods as well as anomaly detection to detect genome edits given either whole exome or genome DNA reads. The edit detection results we obtained with our algorithms tested against samples held out during training of our methods are significantly better than random guessing, achieving high F1 and recall scores as well as with precision overall.
Collecting large driving datasets is important for data-driven transportation research and studied in naturalistic driving [3]. Due to the standard implementation of a Controller Area Network (CAN) bus for a vehicle’s inter-module communication, many off-the-shelf devices can easily transform a vehicle into a rich data collection utility [2]. Vehicles with Adaptive Cruise Control (ACC) are an example of a feature resulting in emergent traffic behavior when scaled [4]. While these utilities were designed with particular data use cases, data may be publicly shared to benefit other researchers through online tools like CyVerse [1]. However, such data should only be shared when any private information is removed. This private information may exist as a set of GPS coordinates, since the start and end points of a trip may designate a driver’s place of residence or work. When considering larger continuously-collected data sets with a focus on naturalistic driving, many drivers are needed to make data collection feasible. Removal of private information becomes much more of a challenge since every driver may uniquely define their geographic privacy. This project aims to build upon the foundation of libpanda [2] by adding features of edge-based data privacy enforcement. In it’s current form, libpanda uses a GPS in conjunction with a CAN interface to record data. Libpanda feature s a set of startup and shutdown scripts to perform automatic data collection and upload. With additional support hardware on a Raspberry Pi, the Pi can maintain power on vehicle shutdown to automatically upload data before shutdown.
The convergence of data-intensive and extreme-scale computing enables an integrated software and data ecosystem for scientific discovery. Developments in this realm will fuel transformative research in data-driven interdisciplinary domains. Geocomputation provides computing paradigms in Geographic Information Systems (GIS) for interactive computing of geographic data, processes, models, and maps. Because GIS is data-driven, the computational scalability of a geocomputation workflow is directly related to the scale of the GIS data layers, their resolution and extent, as well as the velocity of the geo-located data streams to be processed. Unique in high user interactivity and low end-to-end latency requirements, geocomputation applications will dramatically benefit from the convergence of high-end data analytics (HDA) and high-performance computing (HPC). The application level challenge, however, is to identify and eliminate computational bottlenecks that arise along a geocomputation workflow. Indeed, poor scalability at any of the workflow components is detrimental to the entire end-to-end pipeline. Here, we study a large geocomputation use case in flood inundation mapping that handles multiple national-scale geospatial datasets and targets low end-to-end latency. We discuss benefits and challenges for harnessing both HDA and HPC for data-intensive geospatial data processing and intensive numerical modeling of geographic processes. We propose an HDA+HPC geocomputation architecture design that couples HDA (e.g., Spark)-based spatial data handling and HPC-based parallel data modeling. Key techniques for coupling HDA and HPC to bridge the two different software stacks are reviewed and discussed.
This paper describes the software design patterns and vehicle interfaces that were employed to transition vehicle controllers from simulation environments to open-road field experiments. The approach relies on a life cycle that utilizes model-based design and code generation, along with agile software development, and both software and hardware-in-the-loop testing, with additional safety margins. Autonomous designs should consider the dynamics of mixed autonomy in traffic to safely operate among humans. The software that provides a vehicle’s behavior intelligence is often developed through simulation, which may have a mismatch between dynamics, or as a result of a reinforcement learning workflow, which may be a black box with challenges to analyze. In each of these cases, it is important to have research interfaces that provide strongly typed data streams accessible to researchers who are not software experts while continuing to satisfy safety and liveness constraints. This paper describes how we design the hardware platform interfaces and software design process for a mixed autonomy traffic experiment with a leader-follower scenario. Controller synthesis for these vehicles requires clearly articulated vehicle interfaces and software design patterns for successful onboard deployment. Testing strategies for such controllers are also described before algorithms are transitioned to full-scale field experiments with safety operators for the vehicles. Testing strategies include software-in-the-loop simulation testing, hardware-in-the-loop simulation, ghost-car testing, and read-only testing in live traffic. With our approach, we were not only able to validate our controller synthesized in scripts and simulation, but also able to scale deployment to multiple vehicles.
This dataset contains collected dissolved oxygen (DO) and temperature measurements of the air, surface water, and underlying soil of a wetland at Old Woman Creek Estuarine Research Reserve in Huron, OH. Dissolved oxygen and temperature measurements were made in the first few centimeters of wetland sediment to assess how oxygen profiles changed over time with hydrological events. Measurements taken outside of the sediment were taken as comparison. Measurements were taken by hand with a PreSens Fibox 4 transmitter, paired with an oxygen dipping probe and temperature sensor, at each field outing. Measurements were taken approximately every 2 weeks around 10 AM EST. The PreSens_DO_Temp_Datafile.csv contains the recorded measurements, and the PreSens_InstallationMethods.csv describes the deployment of the sensor.
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. Activities during the study, include identification of basic functions dealing with man's research and/or servicing activities on orbit. A crew function taxonomy was prepared relative to these activities. Likely candidate experiments for shuttle sortie missions were selected through extensive review of experiment and mission descriptions. Crew functions and tasks were initially identified for more than fifty representative earth orbital experiments, and a comprehensive task analysis was conducted on these tasks for selected payloads.
There are no author-identified significant results in this report.
The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.
The investigators published a very large number of space science research papers, and in almost all cases these papers involved correlative multi-spacecraft studies. A tabulation of these research papers is provided. Quarterly progress reports for the second contractual period are included.
Tasks remaining to be completed are summarized for the following major project elements: (1) evaluation of crop yield models; (2) crop yield model research and development; (3) data acquisition processing, and storage; (4) related yield research: defining spectral and/or remote sensing data requirements; developing input for driving and testing crop growth/yield models; real time testing of wheat plant process models) and (5) project management and support.
An analytical study of linear-amplifying instabilities of a laminar boundary layer as found in the experimental data of the LaRC/8-foot laminar-flow control (LFC) experiment was completed and the results are presented. The LFC airfoil used for this experiment was a swept, supercritical design which removed suction air through spanwise slots. The amplification of small disturbances by linear processes on a swept surface such as this can be due to either Tollmien-Schlichting (TS) and/or crossflow (CF) mechanisms. This study consists of the examination of these two instabilities by both the commonly used incompressible (SALLY and MARIA) analysis and the more involved compressible (COSAL) analysis. A wide range of experimental test conditions with variations in Mach number, Reynolds number, and suction distributions were available for this study. Experimentally determined transition locations were found from thin-film techniques and were used to correlate the n-factors at transition for the range of test cases.
In-flight flow visualization results of the vortical flow on the forebody and leading-edge extensions (LEX) of an F-18 research aircraft have been presented for angles of attack from 15.8 to 42.5 deg and for sideslip angles up to 7.5 deg. Water tunnel results using a 3-percent scale F-18 model and a variety of wind tunnel results are used for comparison and interpretation of the flight results. The LEX vortex core breakdown point moved forward with increasing angle of attack. For a constant angle of attack, the windward LEX vortex core breakdown moves forward and inboard with sideslip and the leeward vortex core breakdown moves aft and outboard. For a constant angle of attack, the windward location of interaction moved aft with increasing sideslip and the leeward interaction moved forward.
An overview is presented of the services offered by the National Space Science Data Center (NSSDC). The NSSDC was established by the National Aeronautics and Space Administration (NASA) over 20 years ago to be the long-term archive for data from its space missions. NSSDC's goal is to provide the research community with data and attendant services in the most efficient, economical, and useful manner possible now and in the future. The organization is dedicated to getting the most scientific value out of NASA's initial investment in its missions. Each service available to scientists through the world is discussed. Also a contact person is identified for each service in case more information in needed.
During the First International Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), 80 gigabytes of image data were generated from a variety of satellite and airborne sensors in a multidisciplinary attempt to study energy and mass exchange between the land surface and the atmosphere. To make these data readily available to researchers with a range of image data handling experience and capabilities, unique image-processing software was designed to perform a variety of nonstandard image-processing manipulations and to derive a set of standard-format image products. The nonconventional features of the software include: (1) adding new layers of geographic coordinates, and solar and viewing conditions to existing data; (2) providing image polygon extraction and calibration of data to at-sensor radiances; and, (3) generating standard-format derived image products that can be easily incorporated into radiometric or climatology models. The derived image products consist of easily handled ASCII descriptor files, byte image data files, and additional per-pixel integer data files (e.g., geographic coordinates, and sun and viewing conditions). Details of the solutions to the image-processing problems, the conventions adopted for handling a variety of satellite and aircraft image data, and the applicability of the output products to quantitative modeling are presented. They should be of general interest to future experiment and data-handling design considerations.
A statistical survey and a preliminary analysis are made of icing data collected from scheduled flights over the United States and Canada from November 1951 to June 1952 by airline aircraft equipped with NACA pressure-type icing-rate meters. This interim report presents information obtained from a continuing program sponsored by the NACA with the cooperation of the airlines. An analysis of over 600 icing encounters logged by three airlines operating in the United States, one operating in Canada and one operating up the coast to Alaska, is presented. The icing conditions encountered provided relative frequencies of many icing-cloud variables, such as horizontal extent, vertical thickness, temperatures, icing rate, liquid-water content, and total ice accumulation. Liquid-water contents were higher than data from earlier research flights in layer-type clouds but slightly lower than previous data from cumulus clouds. Broken-cloud conditions, indicated by intermittent icing, accounted for nearly one-half of all the icing encounters. About 90 percent of the encounters did not exceed a distance of 120 miles, and continuous icing did not exceed 50 miles for 90 percent of the unbroken conditions. Icing cloud thicknesses measured during climbs and descents were less than 4500 feet for 90 percent of the vertical cloud traverses.