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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 487 records · Page 27

Development of a Safety Hazards Risk Assessment Tool for Uncrewed Aircraft System Traffic Management during Preflight Planning

Tremendous growth in the uncrewed and remotely piloted vehicle market is expected in low-altitude, uncontrolled airspace, resulting in potential decreases in safety without systems that support monitoring, assessing, and mitigating risk. At NASA, the System-Wide Safety (SWS) project has been developing a suite of data-driven tools to predict hazards so that the potential risks that these hazards pose can be mitigated. Services to predict various hazards have been developed, including battery capacity, proximity to static obstacles, population risks, global positioning system signal strength, radio frequency spectrum interference risk, and vertiport congestion. These services can monitor hazards along a flight path and if any risks posed by these hazards exceed a threshold, the uncrewed aircraft system (UAS) fleet manager can be alerted to mitigate the risk by modifying the flight path, changing the scheduled departure or arrival times, and/or diverting the vehicle to an alternate vertiport. These services were originally developed to monitor and assess risks during flight, but they have been adapted to assess hazard risks prior to departure so that a fleet manager can evaluate the potential risks for a fleet of UAS along their planned flight paths. These services have been integrated into a prototype tool called the Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD), developed at NASA Ames Research Center. The tool consists of a dashboard which provides a comprehensive overview for a number of risks and a map display that shows the details of the hazards along each flight’s path. Based on the findings from three previous studies, the SDSP-CD has been updated with new design elements and functions. In this paper, we describe lessons learned from the previous studies, changes made to the interface, and the feedback received during a follow-up usability study. Overall, participants reported that there is a substantial benefit of having a fleet manager use a consolidated dashboard to assess hazards for the vehicles in their fleet and to provide situational awareness to potential risks so that they can be mitigated prior to flight. Once the SDSP-CD matures, it will need to be integrated into flight and mission planning tools. Some initial thoughts on how this integration should be accomplished are shared in this paper. Finally, the functional differences between preflight vs. in-flight risk assessment and the differences in fleet manager vs. UAS pilot roles that may require different information and user interactions are discussed.

preflight↗

Elastic Stacker

Stacker is a library and command-line tool for interacting with components of the Elastic Stack remotely using their APIs. For example, Stacker allows the user to persist API resources to disk and re-create them using the same APIs, potentially allowing configuration to be kept in sync across multiple Elastic Stack instances.

Taliaferro, JamesP.↗

Design, Development and Testing Plan for Energy Efficiency Algorithms Related to Building-Integrated Cooling, Heating, and Power Systems

Building-integrated cooling, heating and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. It is estimated that the total CHP technical potential in the commercial building sector is approximately 76 GW, but only a small fraction of it is actually deployed. Advanced control and monitoring systems that realize the full potential of these CHP systems can transform this capacity into an asset for both the owner and the grid and also accelerate the adoption of these systems in the building sector. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. It has been demonstrated by several studies that as much as 30% of building energy use is wasted. Much of the waste results from the inability to anticipate load variations (design day vs. non-design day operations; diurnal variation of loads), identify improper operation, and efficiently operate, control and maintain building systems. Moreover, many buildings, even those with adequate control infrastructure, lack knowledgeable staff to operate and maintain energy systems. Operators of buildings with CHP systems will constantly need to make tradeoffs (economic dispatch) between onsite power generation and purchasing power, between onsite heat production from distributed generation versus heating/cooling from conventional systems, and different passive and active load management measures. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of a clean, efficient, reliable and affordable next-generation integrated energy systems. This report lists the components for which PM, real-time CxV and AFDD algorithms will be developed, how the algorithms will be tested, and metrics that will be used to validate the algorithms and easy of deployment. Deployment of these algorithms in the field will result in savings reduction in energy consumption of between 10% and 20%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Implementation Plan for Combined Heat and Power Systems VOLTTRON Controller: Performance Monitoring and Real-Time Commissioning Algorithm Verification

Building-integrated cooling, heating, and power (CHP) systems are more efficient than conventional systems at providing local power and thermal energy, and favorable fuel prices are bound to spur their increased adoption. However, to realize the full benefit of the CHP systems, we must ensure persistence of energy efficient operations. Much of the inefficiency in the current building operations can be eliminated by use of automated performance monitoring (PM), real-time commissioning verification (CxV) and automated fault detection and diagnostic (AFDD) tools. Automation can help system operators make intelligent decisions. Remote and continuous monitoring of system conditions and performance will enable better management and integration of CHP with existing building systems. Continuous PM, real-time CxV, and AFDD could alleviate burdens for operations staff, enhance operations and maintenance (O&M), and improve reliability of building and CHP systems. To address the O&M challenges and to provide a means to maximize the rate-of-return of building-integrated CHP systems, the Building Technologies Office (BTO) within the U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) initiated a project to design, develop, and field test a VOLTTRON™-based supervisory controller and associated open-source algorithms. These algorithms will ensure real-time optimal operation of a building-integrated CHP system, support electric grid reliability, and lead to achieving the goal of clean, efficient, reliable, and affordable next-generation integrated energy system. Previous report listed the components for which PM, real-time CxV, and AFDD algorithms will be developed, how the algorithms will be tested, and the metrics that will be used to validate the algorithms and their ease of deployment. Deployment of these algorithms in the field will result in a reduction in energy consumption of between 10% and 20% (for both CHP and conventional building systems). This report builds upon the previous report by detailing the process by which PNNL will implement performance monitoring and real-time commissioning algorithms for CHP systems in conjunction with the use of the VOLTTRON CHP economic dispatch agent in host facilities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Application of shuttle EVA systems to payloads. Volume 1: EVA systems and operational modes description

Descriptions of the EVA system baselined for the space shuttle program were provided, as well as a compendium of data on available EVA operational modes for payload and orbiter servicing. Operational concepts and techniques to accomplish representative EVA payload tasks are proposed. Some of the subjects discussed include: extravehicular mobility unit, remote manipulator system, airlock, EVA translation aids, restraints, workstations, tools and support equipment.

Source record↗

AAFE RADSCAT 13.9-GHz measurements and analysis - Wind-speed signature of the ocean

The Advanced Applications Flight Experiment Radiometer Scatterometer, or 'AAFE RADSCAT', was developed as a research tool for the evaluation of the use of microwave remote sensors in gathering data on wind speed at the ocean's surface. The most important function of AAFE RADSCAT was to furnish a data base of ocean normalized radar cross section (NRCS) measurements as a function of surface wind vector at 13.9 GHz. The NRCS measurements cover a wide parametric range of incidence and azimuth angles and winds. Attention is presently given to analyses of data from the 26 RADSCAT flights during which the quality of the sensors and the surface wind measurements were felt to be understood; subsets of the data base are used to model the relationship between the Ku-band radar signature and the ocean surface wind vector.

Schroeder, L. C.↗

Determination of U, V, and W from single station Doppler radar radial velocities

The ST/MST (stratosphere troposphere/mesosphere stratosphere troposphere) clear air Doppler radar, or wind profiler, is an important tool in observational meteorology because of its capability to remote observe dynamic parameters of the atmosphere. There are difficulties in transforming the observed radial velocities into meteorological wind components. How this problem has been treated in the past is reviewed, and some of the analysis is recast to a form more suited to the high diagnostic abilities of a number of fixed beam configurations with reference to a linear wind field. The results, in conjunction with other works which treats problems such as the effects of finite sample volumes in the presence of nonhomogeneous atmospheric reflectivity, have implications important to the design of both individual MST/ST radars and MST/ST radar networks. The key parameters to uncoupling terms in the scaling equations are w sub x and w sub y. Whenever the stratiform condition, which states that these two parameters are negligible, is satisfied, a five beam ST radar may determine unbiased values of u, v, and w for sample volumes directly above the radar. The divergence and partial deformation of the flow may also be determined. Three beam systems can determine w and w sub z, but are unable to obtain u and v wind components uncontaminated by vertical sheer terms, even when the stratiform condition is satisfied.

Clark, W. L.↗

Kinetic aspects of magnetotail dynamics - Observations

The observed kinetic (as opposed to fluid) aspects of particle behavior in the geomagnetic tail are discussed. Such behavior has been observed from thermal plasma energies to energies a few MeV or more. The importance of recognizing and analyzing the kinetic behavior of tail particles is that it provides a powerful diagnostic tool for inferring the state of the local and remote environment and the mechanisms responsible for observed tail dynamics, and a way of determining when fluid analyses (relying upon moments such as bulk velocity and temperature) may be misleading. Thus kinetic analyses provide a valuable complement to fluid-dynamics-based studies of the collective behavior of geomagnetic tail particles. Observed kinetic effects can be analyzed to examine spatial gradients; convection electric fields, distances to source regions, source-region characteristics, magnetic-field topology, heating/acceleration mechanism, boundary characteristics, and remote mechanisms affecting local particle distributions.

Mitchell, D. G.↗

Using Transparent Informed Prefetching (TIP) to reduce file read latency

As processor performance gains continue to outstrip Input/Output gains, I/O performance is becoming critical to overall system performance. File read latency is the most significant bottleneck for high performance I/O. Other aspects of I/O performance benefit from recent advances in disk bandwidth and throughput resulting from disk arrays, and in write performance derived from buffered write behind and the Log-structured File System. The access gap problem limiting improvements in read latency is exacerbated by distributed file systems operating over networks with diverse bandwidth. Focus is on extending the power of caching and prefetching to reduce file read latencies by exploiting hints from high-levels of a system. Such Transparent Informed Prefetching, TIP, and its benefits are described. It is argued that hints that disclose high level knowledge are a means for transferring optimization information across, without violating, module boundaries. How TIP can be used to convert the high throughput of new technologies such as disk arrays and log-structured file systems into low latency for applications is discussed. Our preliminary experiments show reductions in wall - clock execution time of 13 percent and 20 percent for a multiple module compilation tool (make) accessing data on a local disk and remote Coda file server, respectively, and a reduction of 30 percent for a text search (grep) remotely accessing many small files.

Patterson, R. H.↗

Simulation of arthroscopic surgery using MRI data

With the availability of Magnetic Resonance Imaging (MRI) technology in the medical field and the development of powerful graphics engines in the computer world the possibility now exists for the simulation of surgery using data obtained from an actual patient. This paper describes a surgical simulation system which will allow a physician or a medical student to practice surgery on a patient without ever entering an operating room. This could substantially lower the cost of medial training by providing an alternative to the use of cadavers. This project involves the use of volume data acquired by MRI which are converted to polygonal form using a corrected marching cubes algorithm. The data are then colored and a simulation of surface response based on springy structures is performed in real time. Control for the system is obtained through the use of an attached analog-to-digital unit. A remote electronic device is described which simulates an imaginary tool having features in common with both arthroscope and laparoscope.

Heller, Geoffrey↗

Wavelet and Fractal Analysis of Remotely Sensed Surface Temperature with Applications to Estimation of Surface Sensible Heat Flux Density

Wavelet and fractal analyses have been used successfully to analyze one-dimensional data sets such as time series of financial, physical, and biological parameters. These techniques have been applied to two-dimensional problems in some instances, including the analysis of remote sensing imagery. In this respect, these techniques have not been widely used by the remote sensing community, and their overall capabilities as analytical tools for use on satellite and aircraft data sets is not well known. Wavelet and fractal analyses have the potential to provide fresh insight into the characterization of surface properties such as temperature and emissivity distributions, and surface processes such as the heat and water vapor exchange between the surface and the lower atmosphere. In particular, the variation of sensible heat flux density as a function of the change In scale of surface properties Is difficult to estimate, but - in general - wavelets and fractals have proved useful in determining the way a parameter varies with changes in scale. We present the results of a limited study on the relationship between spatial variations in surface temperature distribution and sensible heat flux distribution as determined by separate wavelet and fractal analyses. We analyzed aircraft imagery obtained in the thermal infrared (IR) bands from the multispectral TIMS and hyperspectral MASTER airborne sensors. The thermal IR data allows us to estimate the surface kinetic temperature distribution for a number of sites in the Midwestern and Southwestern United States (viz., San Pedro River Basin, Arizona; El Reno, Oklahoma; Jornada, New Mexico). The ground spatial resolution of the aircraft data varied from 5 to 15 meters. All sites were instrumented with meteorological and hydrological equipment including surface layer flux measuring stations such as Bowen Ratio systems and sonic anemometers. The ground and aircraft data sets provided the inputs for the wavelet and fractal analyses, and the validation of the results.

Schieldge, John↗

Working Toward a Healthy Planet

Using information from NASA s Earth Science Public Health Applications Program, Dr. Maynard will address how remote sensing data and associated technologies can be used toward a better understanding of the links among human health, the environment and weather/climate - and, how this increased understanding plus improved information sharing can empower local health and environmental decision-makers to better predict climate-related health problems, take preventive measures, and improve response actions. Remotely-sensed data and observations are providing powerful new tools for addressing climate and environment-related human health problems through increased capabilities for monitoring and surveillance of parameters useful to such problems as infectious and vector-borne diseases, air and water quality, harmful algal blooms, UV radiation, contaminant and pathogen transport in air and water, and thermal stress. NASA s multi-disciplinary scientific team is demonstrating how satellites from their unique vantage point in space can serve as sentinels for weather, climate, and health problems through studies on asthma, malaria, Rift Valley Fever, Asian and African dust, and West Nile Virus

Maynard, Nancy G.↗

Field Tested Service Oriented Robotic Architecture: Case Study

This paper presents the lessons learned from six years of experiments with planetary rover prototypes running the Service Oriented Robotic Architecture (SORA) developed by the Intelligent Robotics Group (IRG) at NASA Ames Research Center. SORA relies on proven software methods and technologies applied to the robotic world. Based on a Service Oriented Architecture and robust middleware, SORA extends its reach beyond the on-board robot controller and supports the full suite of software tools used during mission scenarios from ground control to remote robotic sites. SORA has been field tested in numerous scenarios of robotic lunar and planetary exploration. The results of these high fidelity experiments are illustrated through concrete examples that have shown the benefits of using SORA as well as its limitations.

Flueckiger, Lorenzo↗

Use of the NASA Giovanni Data System for Geospatial Public Health Research: Example of Weather-Influenza Connection

The NASA Giovanni data analysis system has been recognized as a useful tool to access and analyze many different types of remote sensing data. The variety of environmental data types has allowed the use of Giovanni for different application areas, such as agriculture, hydrology, and air quality research. The use of Giovanni for researching connections between public health issues and Earths environment and climate, potentially exacerbated by anthropogenic influence, has been increasingly demonstrated. In this communication, the pertinence of several different data parameters to public health will be described. This communication also provides a case study of the use of remote sensing data from Giovanni in assessing the associations between seasonal influenza and meteorological parameters. In this study, logistic regression was employed with precipitation, temperature and specific humidity as predictors. Specific humidity was found to be associated (p 0.05) with influenza activity in both temperate and tropical climate. In the two temperate locations studied, specific humidity was negatively correlated with influenza; conversely, in the three tropical locations, specific humidity was positively correlated with influenza. Influenza prediction using the regression models showed good agreement with the observed data (correlation coefficient of 0.50.83).

public health↗

Earthdata User Interface (EUI) Library

As more remote sensing data moves to the cloud, the design tools we use to build user experiences and visualizations need to change and adapt to make the best use this new data reality. EUI 2.0, the next major iteration of the Earthdata User Interface Library, aims to make creating rich user experiences around NASA's Earth Observation System Data and Information System (EOSDIS) data easy and user-friendly. Building on a solid framework of design components, EUI 2.0 will be open source and have off-the-shelf integration with the Common Metadata Repository (CMR), basic mapping and visualization tools, a refreshed design toolkit for building apps and websites that fit the Earthdata design theme and guidelines. EUI 2.0 will allow for the rapid development of websites and applications based on EOSDIS tools and data holdings. It will also make use of cloud data availability to enable data visualization and analysis without the need to download and sync data.

Siarto, Jeff↗

Exploration Ground Data Systems (xGDS) Overview

xGDS supports rapid scientific decision making by synchronizing the time and mapped location of observation notes, instrument data, photos, video, samples and other data. xGDS is a suite of web tools, developed at NASA Ames Research Center to support remote science operations in analog missions and prototype new ideas for planetary exploration. During operations, xGDS displays science data in real-time with geographic context, supporting key decisions (e.g. sample site selection). Post-operations, xGDS enables efficient analysis of data by correlating data products in time and on the map. xGDS has been developed in close collaboration with science teams since 2009, and used enthusiastically by upwards of 100 scientists to support scientific field research and data analysis.

Ground Data System↗

Use of Remote Sensing for Decision Support in Africa

Over the past 30 years, the scientific community has learned a great deal about the Earth as an integrated system. Much of this research has been enabled by the development of remote sensing technologies and their operation from space. Decision makers in many nations have begun to make use of remote sensing data for resource management, policy making, and sustainable development planning. This paper makes an attempt to provide a survey of the current state of the requirements and use of remote sensing for sustainable development in Africa. This activity has shown that there are not many climate data ready decision support tools already functioning in Africa. There are, however, endusers with known requirements who could benefit from remote sensing data.

Policelli, Frederick S.↗

An Evaluation of Fractal Surface Measurement Methods for Characterizing Landscape Complexity from Remote-Sensing Imagery

The rapid increase in digital data volumes from new and existing sensors necessitates the need for efficient analytical tools for extracting information. We developed an integrated software package called ICAMS (Image Characterization and Modeling System) to provide specialized spatial analytical functions for interpreting remote sensing data. This paper evaluates the three fractal dimension measurement methods: isarithm, variogram, and triangular prism, along with the spatial autocorrelation measurement methods Moran's I and Geary's C, that have been implemented in ICAMS. A modified triangular prism method was proposed and implemented. Results from analyzing 25 simulated surfaces having known fractal dimensions show that both the isarithm and triangular prism methods can accurately measure a range of fractal surfaces. The triangular prism method is most accurate at estimating the fractal dimension of higher spatial complexity, but it is sensitive to contrast stretching. The variogram method is a comparatively poor estimator for all of the surfaces, particularly those with higher fractal dimensions. Similar to the fractal techniques, the spatial autocorrelation techniques are found to be useful to measure complex images but not images with low dimensionality. These fractal measurement methods can be applied directly to unclassified images and could serve as a tool for change detection and data mining.

Lam, Nina Siu-Ngan↗