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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 1,693 records · Page 94

Mesoscale and large-scale variability of the Antarctic circumpolar current

This investigation of the physical oceanography of the Southern Ocean will carry out two parallel efforts during the years preceding the launch of TOPEX/POSEIDON. First, the Geosat data will be used to develop a preliminary descriptive picture of the mesoscale and large-scale, low-frequency surface circulation of the Southern Ocean. Some of this analysis of Geosat data has already begun. For example, as a measure of the geographical distribution of mesoscale variability, a color-coded map of the standard deviation of sea level from two years of Geosat data is shown. Efforts are presently under way to investigate the seasonal and year-to-year variability of this mesoscale energy. The data are also being used to generate low-pass filtered fields of sea level from which the temporal evolution of large-scale variability in the Southern Ocean may be investigated. The second parallel effort is the development and test of modeling and data assimilation techniques that will later be applied to TOPEX/POSEIDON data during the postlaunch phase. One objective of the modeling and data assimilation is to investigate the relation between mesoscale sea level variations and eddy flux in the Southern Ocean. Uncertainties in present estimates of the various components of meridional oceanic heat transport are large. The evidence presented indicates that the very energetic mesoscale variability in the ACC apparently accounts for much of the estimated 0.45x10(exp 15) watts of poleward heat transport across the ACC required to balance the heat budget. Eddy variability is strongly coherent vertically in the ACC, at least in the vicinity of Drake Passage where nearly all of the historical in situ data have been collected.

Chelton, Dudley B.↗

Do gamma-ray burst sources repeat?

The demonstration of repeated gamma-ray bursts from an individual source would severely constrain burst source models. Recent reports of evidence for repetition in the first BATSE burst catalog have generated renewed interest in this issue. Here, we analyze the angular distribution of 585 bursts of the second BATSE catalog (Meegan et al. 1994). We search for evidence of burst recurrence using the nearest and farthest neighbor statistic ad the two-point angular correlation function. We find the data to be consistent with the hypothesis that burst sources do not repeat; however, a repeater fraction of up to about 20% of the bursts cannot be excluded.

Meegan, C. A.↗

Do gamma-ray burst sources repeat?

The demonstration of repeated gamma-ray bursts from an individual source would severely constrain burst source models. Recent reports (Quashnock and Lamb, 1993; Wang and Lingenfelter, 1993) of evidence for repetition in the first BATSE burst catalog have generated renewed interest in this issue. Here, we analyze the angular distribution of 585 bursts of the second BATSE catalog (Meegan et al., 1994). We search for evidence of burst recurrence using the nearest and farthest neighbor statistic and the two-point angular correlation function. We find the data to be consistent with the hypothesis that burst sources do not repeat; however, a repeater fraction of up to about 20% of the observed bursts cannot be excluded.

Meegan, Charles A.↗

An Initial Strategy for Commercial Industry Awareness of the International Space Station

While plans are being developed to utilize the ISS for scientific research, and human and microgravity experiments, it is time to consider the future of the ISS as a world-wide commercial marketplace developed from a government owned, operated and controlled facility. Commercial industry will be able to seize this opportunity to utilize the ISS as a unique manufacturing platform and engineering testbed for advanced technology. NASA has begun the strategic planning of the evolution and commercialization of the ISS. The Pre-Planned Program Improvement (P3I) Working Group at NASA is assessing the future ISS needs and technology plans to enhance ISS performance. Some of these enhancements will allow the accommodation of commercial applications and the Human Exploration and Development of Space mission support. As this information develops, it is essential to disseminate this information to commercial industry, targeting not only the private and public space sector but also the non-aerospace commercial industries. An approach is presented for early distribution of this information via the ISS Evolution Data book that includes ISS baseline system information, baseline utilization and operations plans, advanced technologies, future utilization opportunities, ISS evolution and Design Reference Missions (DRM). This information source and tool can be used as catalyst in the commercial world for the generation of ideas and options to enhance the current capabilities of the ISS.

Jorgensen, Catherine A.↗

A Model for Generation of Martian Surface Dust, Soil and Rock Coatings: Physical vs. Chemical Interactions, and Palagonitic Plus Hydrothermal Alteration

This model is one of many possible scenarios to explain the generation of the current surface material on Mars using chemical, magnetic and spectroscopic data from Mars and geologic analogs from terrestrial sites. One basic premise is that there are physical and chemical interactions of the atmospheric dust particles and that these two processes create distinctly different results. Physical processes distribute dust particles on rocks, forming physical rock coatings, and on the surface between rocks forming soil units; these are reversible processes. Chemical reactions of the dust/soil particles create alteration rinds on rock surfaces or duricrust surface units, both of which are relatively permanent materials. According to this model the mineral components of the dust/soil particles are derived from a combination of "typical" palagonitic weathering of volcanic ash and hydrothermally altered components, primarily from steam vents or fumeroles. Both of these altered materials are composed of tiny particles, about 1 micron or smaller, that are aggregates of silicates and iron oxide/oxyhydroxide/sulfate phases. Additional information is contained in the original extended abstract.

Bishop, J. L.↗

A Case Study of the Impact of AIRS Temperature Retrievals on Numerical Weather Prediction

Large errors in numerical weather prediction are often associated with explosive cyclogenesis. Most studes focus on the under-forecasting error, i.e. cases of rapidly developing cyclones which are poorly predicted in numerical models. However, the over-forecasting error (i.e., to predict an explosively developing cyclone which does not occur in reality) is a very common error that severely impacts the forecasting skill of all models and may also present economic costs if associated with operational forecasting. Unnecessary precautions taken by marine activities can result in severe economic loss. Moreover, frequent occurrence of over-forecasting can undermine the reliance on operational weather forecasting. Therefore, it is important to understand and reduce the prdctions of extreme weather associated with explosive cyclones which do not actually develop. In this study we choose a very prominent case of over-forecasting error in the northwestern Pacific. A 960 hPa cyclone develops in less than 24 hour in the 5-day forecast, with a deepening rate of about 30 hPa in one day. The cyclone is not versed in the analyses and is thus a case of severe over-forecasting. By assimilating AIRS data, the error is largely eliminated. By following the propagation of the anomaly that generates the spurious cyclone, it is found that a small mid-tropospheric geopotential height negative anomaly over the northern part of the Indian subcontinent in the initial conditions, propagates westward, is amplified by orography, and generates a very intense jet streak in the subtropical jet stream, with consequent explosive cyclogenesis over the Pacific. The AIRS assimilation eliminates this anomaly that may have been caused by erroneous upper-air data, and represents the jet stream more correctly. The energy associated with the jet is distributed over a much broader area and as a consequence a multiple, but much more moderate cyclogenesis is observed.

Reale, O.↗

Development of a Common Research Model for Applied CFD Validation Studies

The development of a wing/body/nacelle/pylon/horizontal-tail configuration for a common research model is presented, with focus on the aerodynamic design of the wing. Here, a contemporary transonic supercritical wing design is developed with aerodynamic characteristics that are well behaved and of high performance for configurations with and without the nacelle/pylon group. The horizontal tail is robustly designed for dive Mach number conditions and is suitably sized for typical stability and control requirements. The fuselage is representative of a wide/body commercial transport aircraft; it includes a wing-body fairing, as well as a scrubbing seal for the horizontal tail. The nacelle is a single-cowl, high by-pass-ratio, flow-through design with an exit area sized to achieve a natural unforced mass-flow-ratio typical of commercial aircraft engines at cruise. The simplicity of this un-bifurcated nacelle geometry will facilitate grid generation efforts of subsequent CFD validation exercises. Detailed aerodynamic performance data has been generated for this model; however, this information is presented in such a manner as to not bias CFD predictions planned for the fourth AIAA CFD Drag Prediction Workshop, which incorporates this common research model into its blind test cases. The CFD results presented include wing pressure distributions with and without the nacelle/pylon, ML/D trend lines, and drag-divergence curves; the design point for the wing/body configuration is within 1% of its max-ML/D. Plans to test the common research model in the National Transonic Facility and the Ames 11-ft wind tunnels are also discussed.

Vassberg, John C.↗

Detecting Abnormal Machine Characteristics in Cloud Infrastructures

In the cloud computing environment resources are accessed as services rather than as a product. Monitoring this system for performance is crucial because of typical pay-peruse packages bought by the users for their jobs. With the huge number of machines currently in the cloud system, it is often extremely difficult for system administrators to keep track of all machines using distributed monitoring programs such as Ganglia1 which lacks system health assessment and summarization capabilities. To overcome this problem, we propose a technique for automated anomaly detection using machine performance data in the cloud. Our algorithm is entirely distributed and runs locally on each computing machine on the cloud in order to rank the machines in order of their anomalous behavior for given jobs. There is no need to centralize any of the performance data for the analysis and at the end of the analysis, our algorithm generates error reports, thereby allowing the system administrators to take corrective actions. Experiments performed on real data sets collected for different jobs validate the fact that our algorithm has a low overhead for tracking anomalous machines in a cloud infrastructure.

Bhaduri, Kanishka↗

Uncertainty Quantification of Inducer Natural Frequency using Conditional Assessment of Modeling and Modal Testing of Simpler Systems

The low pressure fuel pump inducer of the new Space Launch System RS25 core stage engine operates in a highly complex environment that substantially affects its modal characteristics. Some of the more important effects are fluid-added mass resulting from operation within a light liquid (Hydrogen), and the magnification of this effect due to tight tip clearance. Since higher order cavitation has been identified as a significant harmonic driver, knowledge of the natural frequency of potentially excitable modes is critical for safe operation, but this frequency cannot be measured during the severe operational environment. A comprehensive testing and analysis program has therefore been performed over the last four years to identify the nominal value and uncertainty of the frequency by modeling and testing four simpler structures which share some of the characteristics of the operational inducer. This testing was used to assess and adjust modeling techniques and excellent correlation was achieved. Identification of the uncertainty in the inducer frequency itself was still problematic, however. This difficulty led to an investigation of Bayesian uncertainty quantification techniques, and to the application of the relatively simple technique of Multi-Variate Normal conditional distributions to calculate the inducer natural frequency uncertainty. Assumptions on prior distributions of uncertainty of the fluid-added mass and tip clearance effect are initially applied to models of each of the simple structures and the inducer itself, and these uncertainties are propagated to generate natural frequencies using design of experiments. Simple response surfaces are then created from this data in order to calculate a Covariance Matrix relating all of these natural frequencies. Finally, the results from modal test of the simple structures are considered to be observations and used to calculate the conditional variance of the desired inducer frequencies. As this method is less rigorous than more complicated Bayesian methods reported in the literature, a conservative factor is applied to the result, but the resulting uncertainty is still significantly less than originally estimated and will greatly assist certification of the inducer for use in the engine.

Uncertainty Quantification↗

Uncertainty Quantification of Inducer Eigenvalues using Conditional Assessment of Models and Modal Test of Simpler Systems

The low pressure fuel pump inducer of the new Space Launch System RS25 core stage engine operates in a highly complex environment that substantially affects its modal characteristics. Some of the more important effects are fluid-added mass resulting from operation within a light liquid (Hydrogen), and the magnification of this effect due to tight tip clearance. Since higher order cavitation has been identified as a significant harmonic driver, knowledge of the natural frequency of potentially excitable modes is critical for safe operation, but this frequency cannot be measured during the severe operational environment. A comprehensive testing and analysis program has therefore been performed over the last four years to identify the nominal value and uncertainty of the frequency by modeling and testing four simpler structures which share some of the characteristics of the operational inducer. This testing was used to assess and adjust modeling techniques and excellent correlation was achieved. Identification of the uncertainty in the inducer frequency itself was still problematic, however. This difficulty led to an investigation of Bayesian uncertainty quantification techniques, and to the application of the relatively simple technique of Multi-Variate Normal conditional distributions to calculate the inducer natural frequency uncertainty. Assumptions on prior distributions of uncertainty of the fluid-added mass and tip clearance effect are initially applied to models of each of the simple structures and the inducer itself, and these uncertainties are propagated to generate natural frequencies using design of experiments. Simple response surfaces are then created from this data in order to calculate a Covariance Matrix relating all of these natural frequencies. Finally, the results from modal test of the simple structures are considered to be observations and used to calculate the conditional variance of the desired inducer frequencies. As this method is less rigorous than more complicated Bayesian methods reported in the literature, a conservative factor is applied to the result, but the resulting uncertainty is still significantly less than originally estimated and will greatly assist certification of the inducer for use in the engine.

Uncertainty Quantification↗

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗

Field Test Bed for Vadose-Zone Monitoring Approaches - 20404

In the Central Plateau at the U.S. Department of Energy Hanford Site, a large inventory of contaminants resides in unsaturated sediments within the approximately 100-meter-thick vadose zone, posing a potential continuing risk to groundwater. Vadose zone remedies used to address these contaminants will require performance monitoring to provide feedback during implementation and for long-term verification that remedial action objectives have been met. Passive approaches may also need long-term monitoring to demonstrate that the flux of contaminants from the vadose zone to the groundwater are below thresholds established to meet groundwater protection goals. Collection of physical (e.g., groundwater or sediment) samples is a common method for identifying contaminant concentration distributions, but this approach is limited by the number of locations and the frequency with which data can be collected. In situ vadose zone measurements have evolved over the past few years to include key measurements of water content, soil water pressure, temperature, and chemical concentration. However, the current generation of sensors is designed for relatively short-term use in near-surface soils or sediments. Geophysical methods have been evolving but are also limited in that they have not been designed for the specific long-term vadose zone monitoring needs at the Hanford Site. Overall, monitoring under unsaturated conditions can be difficult due to the need to install and maintain instrumentation over a large area and depth and the need to identify preferential flow pathways due to geologic and chemical heterogeneities over long periods. Thus, a vadose zone monitoring test bed was initiated to address these challenges and identify cost-effective approaches for implementation and postclosure monitoring of the deep vadose zone. The monitoring test bed is expected to provide valuable field-scale information for the design of vadose zone monitoring systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrated Transmission-Distribution Multi-Period Switching for Wildfire Risk Mitigation: Improving Speed and Scalability with Distributed Optimization: Preprint

With increasingly severe wildfire conditions driven by climate change, utilities must manage the risk of wildfire ignitions from electric power lines. During "public safety power shutoff'" events, utilities de-energize power lines to reduce wildfire ignition risk, which may result in load shedding. Distributed energy resources provide flexibility that can help support the system to reduce load shedding when lines are de-energized. We investigate a coordinated transmission-distribution optimization problem that balances wildfire risk mitigation and load shedding. We model distribution systems that include battery energy storage systems which may support loads when transmission lines are de-energized. This multi-period integrated transmission-distribution optimal switching problem jointly optimizes line switching decisions, the generators' setpoints, load shedding, and the batteries' states of charge, resulting in significant computational challenges. To improve scalability, we decompose the problem over both space and time and apply a distributed optimization algorithm. Using a large-scale synthetic California test case with realistic distribution models and real wildfire risk data, we show that distributed optimization can solve large-scale multi-period switching problems that are otherwise intractable for centralized solvers. We also discuss challenges and future directions for improving the distributed algorithm's convergence performance as the number of time periods increases.

24 POWER TRANSMISSION AND DISTRIBUTION↗

More Data Needed for Failure Rate Estimation, Validation, and Uncertainty Reduction

Current Environmental Control and Life Support System (ECLSS) development and test activities are not generating data fast enough to provide statistically-supportable precise Orbital Replacement Unit (ORU) failure rate estimates for future missions. Accurate and precise failure rate estimates are critical for missions beyond Low Earth Orbit (LEO) because current risk mitigation approaches – namely regular resupply and rapid abort capabilities – will not be available. Safe operations will depend on mission planners’ ability to accurately forecast spares demand and efficiently provide the necessary resources. However, even after more than a decade of operations on board the International Space Station (ISS), a significant amount of uncertainty remains in failure rate estimates. Uncertain or inaccurate failure rates result in increased risk and spares mass for future missions. A Bayesian failure rate estimation approach, such as the one currently implemented by the ISS Program, can help reduce uncertainty by incorporating engineering judgement into failure rate estimates. However, experience on the ISS and with other complex systems shows that these prior failure rate estimates are often inaccurate. In addition, prior failure rate estimates are typically point values; some level of uncertainty must be added to convert these into probability distributions for Bayesian updating, and there are several potential methods for doing so. Due to the low rate of data collection, these subjective (and often inaccurate) prior estimates currently have a strong influence on the end result. This paper examines the challenges associated with failure rate estimation, validation, and uncertainty reduction in the context of ECLSS development for beyond-LEO missions. A variety of techniques for generating and updating Bayesian priors are discussed and evaluated using both real-world and simulated data. Potential solutions for improving failure rate estimation, including testing additional units, are analyzed and discussed, and a set of recommendations are provided for next-generation system development activities.

Supportability↗

Geospatial Analysis of Built Infrastructure and Modeled Household Driving Patterns

The level of access to opportunities for a location can be quantified in the amount of time it takes to travel from a departure point to the destinations that somebody would want or need to visit. Isochrone maps are geometric representations of the area accessible from a departure point within a set amount of time. Informed in part by the National Household Travel Survey, this report merges location data for amenities and opportunities across six frequent destination categories – employment, education, health, food, community, and transportation – with isochrone maps generated by the TravelTime API, whose departure points are census tract population-weighted centroids. Using a “Points-In-Polygon” analysis, destinations that fall within a census tract’s isochrone are tallied as accessible from the region within one of three time thresholds: 15-, 30-, and 45-minutes by the walking, cycling, public transit, and driving modes of travel. We find that access to a high number of jobs within a typical commute duration is negatively correlated with annual household vehicle miles traveled (VMT). The spatial distribution of our data suggests that the high household VMT frequently seen surrounding the edges of major cities may be related to worker commutes into the city core, and that the high household VMT frequently seen in rural tracts may be related to the longer travel distances required to access a variety of key opportunities from these areas.

99 GENERAL AND MISCELLANEOUS↗

Parallel grid generation algorithm for distributed memory computers

A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.

Moitra, Stuti↗

Energetic Potential for Demand Response in Detached Single Family Homes in Austin, TX

This study builds a generalized tool to quantify the maximum peak load reduction achievable with residential demand response and distributed energy resources (DERs). The tool is demonstrated by using empirical energy usage data from detached single family households within the service territory of Austin Energy - the local municipal utility in Austin, TX. The demand response optimization algorithm shifts energy usage of four controllable, high-consumption residential devices to off-peak hours: HVAC (heating, ventilation, and air conditioning) systems, electric water heaters, electric vehicles, and pool pumps. In addition, rooftop solar generation on individual residences is considered to reduce net load to the utility, and an energy storage system optimization model performing energy arbitrage further reduces peak demand. Results from the aggregate demand response and battery optimization study indicate that peak demand for the 2017 summer peak in Austin Energy could have been reduced by 26 MW or 2.9%. Here, by considering the combined effect of controllable consumer loads, solar generation, and energy storage systems, this study highlights the potential of strategic demand response and energy arbitrage to reduce peak demand at the distribution level.

14 SOLAR ENERGY↗