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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Differential sea-state bias: A case study using TOPEX/POSEIDON data

We used selected data from the NASA altimeter TOPEX/POSEIDON to calculate differences in range measured by the C and Ku-band altimeters when the satellite overflew 5 to 15 m waves late at night. The range difference is due to free electrons in the ionosphere and to errors in sea-state bias. For the selected data the ionospheric influence on Ku range is less than 2 cm. Any difference in range over short horizontal distances is due only to a small along-track variability of the ionosphere and to errors in calculating the differential sea-state bias. We find that there is a barely detectable error in the bias in the geophysical data records. The wave-induced error in the ionospheric correction is less than 0.2% of significant wave height. The equivalent error in differential range is less than 1% of wave height. Errors in the differential sea-state bias calculations appear to be small even for extreme wave heights that greatly exceed the conditions on which the bias is based. The results also improved our confidence in the sea-state bias correction used for calculating the geophysical data records. Any error in the correction must influence Ku and C-band ranges almost equally.

Stewart, Robert H.↗
NASA NTRS1997

A Dayside Auroral Energy Desposition Case Study Using the Polar Ultraviolet Imager

In this letter, we report preliminary results from a study of dayside auroral energy deposition during quiet times using global auroral images acquired by the Ultraviolet Imager experiment on the Polar spacecraft. Solar wind plasma and interplanetary magnetic field measurements from the Wind spacecraft and kp values were used to characterize the state of the magnetosphere. The auroral oval was observed for a two- hour period in spring and summer during relatively quiet times (k(sub p) approx. 0 to 1). We find that, although the nightside energy deposition rate varied by an order of magnitude to as low as 1 x 10(exp 16) ergs per second (1 GW), the dayside was much less variable and remained between 4 and IO GW.

Brittnacher, M. J.↗
NASA NTRS2007

Rapid Geometry Creation for Computer-Aided Engineering Parametric Analyses: A Case Study Using ComGeom2 for Launch Abort System Design

ComGeom2, a tool developed to generate Common Geometry representation for multidisciplinary analysis, has been used to create a large set of geometries for use in a design study requiring analysis by two computational codes. This paper describes the process used to generate the large number of configurations and suggests ways to further automate the process and make it more efficient for future studies. The design geometry for this study is the launch abort system of the NASA Crew Launch Vehicle.

Hawke, Veronica↗
NASA NTRS2009

Case Study: Using The OMG SWRADIO Profile and SDR Forum Input for NASA's Space Telecommunications Radio System

The Space Telecommunication Radio System (STRS) standard is a Software Defined Radio (SDR) architecture standard developed by NASA. The goal of STRS is to reduce NASA s dependence on custom, proprietary architectures with unique and varying interfaces and hardware and support reuse of waveforms across platforms. The STRS project worked with members of the Object Management Group (OMG), Software Defined Radio Forum, and industry partners to leverage existing standards and knowledge. This collaboration included investigating the use of the OMG s Platform-Independent Model (PIM) SWRadio as the basis for an STRS PIM. This paper details the influence of the OMG technologies on the STRS update effort, findings in the STRS/SWRadio mapping, and provides a summary of the SDR Forum recommendations.

Briones, Janette C.↗
NASA NTRS2010

A Case Study: Using Delmia at Kennedy Space Center to Support NASA's Constellation Program

The presentation examines the use of Delmia (Digital Enterprise Lean Manufacturing Interactive Application) for digital simulation in NASA's Constellation Program. Topics include an overview of the Kennedy Space Center (KSC) Design Visualization Group tasks, NASA's Constellation Program, Ares 1 ground processing preliminary design review, and challenges and how Delmia is used at KSC, Challenges include dealing with large data sets, creating and maintaining KSC's infrastructure, gathering customer requirements and meeting objectives, creating life-like simulations, and providing quick turn-around on varied products,

Kickbusch, Tracey↗
NASA NTRS2007

A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues

Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.

Tucker, David A.↗
NASA NTRS2016

On the Performance of Adaptive Data Rate over Deep Space Ka-Bank Link: Case Study Using Kepler Data

Future missions envisioned for both human and robotic exploration demand increasing communication capacity through the use of Ka-band communications. The Ka-band channel, being more sensitive to weather impairments, presents a unique trade-offs between data storage, latency, data volume and reliability. While there are many possible techniques for optimizing Ka-band operations such as adaptive modulation and coding and site-diversity, this study focus exclusively on the use of adaptive data rate (ADR) to achieve significant improvement in the data volume-availability tradeoff over a wide range of link distances for near Earth and Mars exploration. Four years of Kepler Ka-band downlink symbol signal-to-noise (SNR) data reported by the Deep Space Network were utilized to characterize the Ka-band channel statistics at each site and conduct various what-if performance analysis for different link distances. We model a notional closed-loop adaptive data rate system in which an algorithm predicts the channel condition two-way light time (TWLT) into the future using symbol SNR reported in near-real time by the ground receiver and determines the best data rate to use. Fixed and adaptive margins were used to mitigate errors in channel prediction. The performance of this closed-loop adaptive data rate approach is quantified in terms of data volume and availability and compared to the actual mission configuration and a hypothetical, optimized single rate configuration assuming full a priori channel knowledge.

Gao, Jay L.↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES-Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50 m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
NASA NTRS2018

Comparisons of Bispectral and Polarimetric Retrievals of Marine Boundary Layer Cloud Microphysics: Case Studies Using a LES- Satellite Retrieval Simulator

Many passive remote-sensing techniques have been developed to retrieve cloud microphysical properties from satellite-based sensors, with the most common approaches being the bispectral and polarimetric techniques. These two vastly different retrieval techniques have been implemented for a variety of polar-orbiting and geostationary satellite platforms, providing global climatological data sets. Prior instrument comparison studies have shown that there are systematic differences between the droplet size retrieval products (effective radius) of bispectral (e.g., MODIS, Moderate Resolution Imaging Spectroradiometer) and polarimetric (e.g., POLDER, Polarization and Directionality of Earth's Reflectances) instruments. However, intercomparisons of airborne bispectral and polarimetric instruments have yielded results that do not appear to be systematically biased relative to one another. Diagnosing this discrepancy is complicated, because it is often difficult for instrument intercomparison studies to isolate differences between retrieval technique sensitivities and specific instrumental differences such as calibration and atmospheric correction. In addition to these technical differences the polarimetric retrieval is also sensitive to the dispersion of the droplet size distribution (effective variance), which could influence the interpretation of the droplet size retrieval. To avoid these instrument-dependent complications, this study makes use of a cloud remote-sensing retrieval simulator. Created by coupling a large-eddy simulation (LES) cloud model with a 1-D radiative transfer model, the simulator serves as a test bed for understanding differences between bispectral and polarimetric retrievals. With the help of this simulator we can not only compare the two techniques to one another (retrieval intercomparison) but also validate retrievals directly against the LES cloud properties. Using the satellite retrieval simulator, we are able to verify that at high spatial resolution (50m) the bispectral and polarimetric retrievals are highly correlated with one another within expected observational uncertainties. The relatively small systematic biases at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric retrieval but generally maintains a constant mean value.

Miller, Daniel J.↗
NASA NTRS2018

Evaluating the Socioeconomic Impacts of Rapid Assembly and Deployment of Geospatial Data in Wildfire Emergency Response Planning: A Case Study Using the NASA RECOVER Decision Support System (DSS)

Today’s extended fire seasons and large fire footprints have prompted state and federal land management agencies to devote increasingly larger portions of their budget to wildfire management. As fire costs continue to rise, timely and comprehensive fire information becomes increasingly critical to response and rehabilitation efforts. The NASA Rehabilitation Capability Convergence for Ecosystem Recovery (RECOVER) post-fire decision support system is a server-based application designed to rapidly provide land managers with the information needed to develop a comprehensive rehabilitation plan. This study tested the efficacy of RECOVER through structured interviews with land managers (n=15) who used RECOVER and were responsible for post-fire rehabilitation efforts on over 645 000 ha of fire-affected lands. Although the benefit of better-informed decisions is difficult to quantify, the results of this study illustrate RECOVER’s decision support capabilities provided information to land managers that either validated or altered their decisions on post-fire treatments estimated at over $1.2 million (USD) and saved nearly 800 hours of staff time by streamlining data collection as well as communication with local stakeholders and partnering agencies.

William Toombs↗
NASA NTRS2020

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover “mothership.” Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a “local GPS”) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed.

Dille, Michael↗
NASA NTRS2020

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors Mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗
NASA NTRS2020

Air Quality Monitoring Case Study Using Mobile Low-cost Sensors mounted on Trash-Trucks: Methods Development and Lessons Learned

Air quality monitoring (AQM) is crucial for cities to develop management plans supporting population health. However, there is a dearth of measurements due to the high cost of standard reference instruments. Mobile AQM using low-cost sensors deployed on routine fleets of vehicles can enable the continuous detection of fine-scale pollutant variations in cities at a lower cost. New methods need to be developed to interpret these measurements. This paper presents three such methods. First, we propose a technique to identify aerosol hotspots. Second, we employ techniques published previously to assess the generalizable map of fine and coarse particle number concentrations, to understand qualitatively the contribution of local and regional sources across the region sampled. By using the raw number concentration of differently sized particles from the Optical Particle Counters (OPCs) instead of the noisier mass concentrations, we obtain more robust results. Third, in order to evaluate source signatures in cities, we propose another technique, in which we cluster the entire range of aerosol size-distribution measurements acquired. The properties of each cluster provide insight into the aerosol source characteristics in the sampling environment. We test these methods using a dataset we collected by mounting OPCs on two trash-trucks in Cambridge, Massachusetts.

Drive-by sensing↗
NASA NTRS2020

Integrated Demand Management: CTOP User Interface Enhancements

NASA's Integrated Demand Management research activity developed a concept for a novel use of the FAA's Collaborative Trajectory Options Program (CTOP) decision support software to support a particular type of traffic management use case. The research team used an emulation of CTOP software to prototype and test the concept, and developed several enhancements to the CTOP user interface that were well received by the stakeholder community. This document provides a detailed description of these enhancements and their operation that could be used to support their incorporation into the official CTOP software.

IDM↗