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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Decision Support for Emergency Operations Centers

The Flood Disaster Mitigation Decision Support System (DSS) is a computerized information system that allows regional emergency-operations government officials to make decisions regarding the dispatch of resources in response to flooding. The DSS implements a real-time model of inundation utilizing recently acquired lidar elevation data as well as real-time data from flood gauges, and other instruments within and upstream of an area that is or could become flooded. The DSS information is updated as new data become available. The model generates realtime maps of flooded areas and predicts flood crests at specified locations. The inundation maps are overlaid with information on population densities, property values, hazardous materials, evacuation routes, official contact information, and other information needed for emergency response. The program maintains a database and a Web portal through which real-time data from instrumentation are gathered into the database. Also included in the database is a geographic information system, from which the program obtains the overlay data for areas of interest as needed. The portal makes some portions of the database accessible to the public. Access to other portions of the database is restricted to government officials according to various levels of authorization. The Flood Disaster Mitigation DSS has been integrated into a larger DSS named REACT (Real-time Emergency Action Coordination Tool), which also provides emergency operations managers with data for any type of impact area such as floods, fires, bomb

Harvey, Craig↗
NASA NTRS2011

Development of Jet Noise Power Spectral Laws

High-quality jet noise spectral data measured at the Aero-Acoustic Propulsion Laboratory (AAPL) at NASA Glenn is used to develop jet noise scaling laws. A FORTRAN algorithm was written that provides detailed spectral prediction of component jet noise at user-specified conditions. The model generates quick estimates of the jet mixing noise and the broadband shock-associated noise (BBSN) in single-stream, axis-symmetric jets within a wide range of nozzle operating conditions. Shock noise is emitted when supersonic jets exit a nozzle at imperfectly expanded conditions. A successful scaling of the BBSN allows for this noise component to be predicted in both convergent and convergent-divergent nozzles. Configurations considered in this study consisted of convergent and convergent- divergent nozzles. Velocity exponents for the jet mixing noise were evaluated as a function of observer angle and jet temperature. Similar intensity laws were developed for the broadband shock-associated noise in supersonic jets. A computer program called sJet was developed that provides a quick estimate of component noise in single-stream jets at a wide range of operating conditions. A number of features have been incorporated into the data bank and subsequent scaling in order to improve jet noise predictions. Measurements have been converted to a lossless format. Set points have been carefully selected to minimize the instability-related noise at small aft angles. Regression parameters have been scrutinized for error bounds at each angle. Screech-related amplification noise has been kept to a minimum to ensure that the velocity exponents for the jet mixing noise remain free of amplifications. A shock-noise-intensity scaling has been developed independent of the nozzle design point. The computer program provides detailed narrow-band spectral predictions for component noise (mixing noise and shock associated noise), as well as the total noise. Although the methodology is confined to single streams, efforts are underway to generate a data bank and algorithm applicable to dual-stream jets. Shock-associated noise in high-powered jets such as military aircraft can benefit from these predictions.

Khavaran, Abbas↗
NASA NTRS2011

Cosmic Ray Modulation in the Outer Heliosphere During the Minimum of Solar Cycle 23/24

We report a next generation model of galactic cosmic ray (GCR) transport in the three dimensional heliosphere. Our model is based on an accurate three-dimensional representation of the heliospheric interface. This representation is obtained by taking into account the interaction between partially ionized, magnetized plasma flows of the solar wind and the local interstellar medium. Our model reveals that after entering the heliosphere GCRs are stored in the heliosheath for several years. The preferred GCR entry locations are near the nose of the heliopause and at high latitudes. Low-energy (hundreds of MeV) galactic ions observed in the heliosheath have spent, on average, a longer time in the solar wind than those observed in the inner heliosphere, which would explain their cooled-off spectra at these energies. We also discuss radial gradients in the heliosheath and the implications for future Voyager observations.

Adams, James H., Jr.↗
NASA NTRS2011

AIRS-Observed Interrelationships of Anomaly Time-Series of Moist Process-Related Parameters and Inferred Feedback Values on Various Spatial Scales

In the beginning, a good measure of a GMCs performance was their ability to simulate the observed mean seasonal cycle. That is, a reasonable simulation of the means (i.e., small biases) and standard deviations of TODAY?S climate would suffice. Here, we argue that coupled GCM (CG CM for short) simulations of FUTURE climates should be evaluated in much more detail, both spatially and temporally. Arguably, it is not the bias, but rather the reliability of the model-generated anomaly time-series, even down to the [C]GCM grid-scale, which really matter. This statement is underlined by the social need to address potential REGIONAL climate variability, and climate drifts/changes in a manner suitable for policy decisions.

Molnar, Gyula I.↗
NASA NTRS2012

Predicting Loss-of-Control Boundaries Toward a Piloting Aid

This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

Barlow, Jonathan↗
NASA NTRS2012

Toward a Model-Based Approach for Flight System Fault Protection

Use SysML/UML to describe the physical structure of the system This part of the model would be shared with other teams - FS Systems Engineering, Planning & Execution, V&V, Operations, etc., in an integrated model-based engineering environment Use the UML Profile mechanism, defining Stereotypes to precisely express the concepts of the FP domain This extends the UML/SysML languages to contain our FP concepts Use UML/SysML, along with our profile, to capture FP concepts and relationships in the model Generate typical FP engineering products (the FMECA, Fault Tree, MRD, V&V Matrices)

fault protection↗
NASA NTRS2013

Adaptive Disturbance Tracking Theory with State Estimation and State Feedback for Region II Control of Large Wind Turbines

A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.

Balas, Mark J.↗
NASA NTRS2014

Implementation and Validation of 3-D Ice Accretion Measurement Methodology

A research program has been implemented to develop and validate the use of a commercial 3-D laser scanning system to record ice accretion geometry in the NASA Icing Research Tunnel. A main component of the program was the geometric assessment of the 3-D laser scanning system on a 2-D (straight wing) and a 3-D (swept wing) airfoil geometries. This exercise consisted of comparison of scanned ice accretion to castings of the same ice accretion. The scan data were also used to create rapid prototype artificial ice shapes that were scanned and compared to the original ice accretion.The results from geometric comparisons on the straight wing showed that the ice shape models generated through the scanrapid prototype process compared reasonably well with the cast shapes. Similar results were obtained with the geometric comparisons on the swept wing. It was difficult to precisely compare the scans of the cast shapes to the original ice accretion scans because the cast shapes appear to have shrunk during the moldcasting process by as much as 0.10-inch. However the comparison of the local ice-shape features were possible and produced better results. The rapid prototype manufacturing process was shown to reproduce the original ice accretion scan normally within 0.01-inch.

Aerodynamics↗
NASA NTRS2014

Implementation and Validation of 3-D Ice Accretion Measurement Methodology

A research program has been implemented to develop and validate the use of a commercial 3-D laser scanning system to record ice accretion geometry in the NASA Icing Research Tunnel. A main component of the program was the geometric assessment of the 3- D laser scanning system on a 2-D (straight wing) and a 3-D (swept wing) airfoil geometries. This exercise consisted of comparison of scanned ice accretion to castings of the same ice accretion. The scan data were also used to create rapid prototype artificial ice shapes that were scanned and compared to the original ice accretion. The results from geometric comparisons on the straight wing showed that the ice shape models generated through the scan/rapid prototype process compared reasonably well with the cast shapes. Similar results were obtained with the geometric comparisons on the swept wing. It was difficult to precisely compare the scans of the cast shapes to the original ice accretion scans because the cast shapes appear to have shrunk during the mold/casting process by as much as 0.10-inch. However the comparison of the local ice-shape features were possible and produced better results. The rapid prototype manufacturing process was shown to reproduce the original ice accretion scan normally within 0.01-inch.

Icing↗
NASA NTRS2017

Vortex Generators in a Streamline-Traced, External-Compression Supersonic Inlet

Vortex generators within a streamline-traced, external-compression supersonic inlet for Mach 1.66 were investigated to determine their ability to increase total pressure recovery and reduce total pressure distortion. The vortex generators studied were rectangular vanes arranged in counter-rotating and co-rotating arrays. The vane geometric factors of interest included height, length, spacing, angle-of-incidence, and positions upstream and downstream of the inlet terminal shock. The flow through the inlet was simulated numerically through the solution of the steady-state, Reynolds-averaged Navier-Stokes equations on multi-block, structured grids using the Wind-US flow solver. The vanes were simulated using a vortex generator model. The inlet performance was characterized by the inlet total pressure recovery and the radial and circumferential total pressure distortion indices at the engine face. Design of experiments and statistical analysis methods were applied to quantify the effect of the geometric factors of the vanes and search for optimal vane arrays. Co-rotating vane arrays with negative angles-of-incidence positioned on the supersonic diffuser were effective in sweeping low-momentum flow from the top toward the sides of the subsonic diffuser. This distributed the low-momentum flow more evenly about the circumference of the subsonic diffuser and reduced distortion. Co-rotating vane arrays with negative angles-of-incidence or counter-rotating vane arrays positioned downstream of the terminal shock were effective in mixing higher-momentum flow with lower-momentum flow to increase recovery and decrease distortion. A strategy of combining a co-rotating vane array on the supersonic diffuser with a counter-rotating vane array on the subsonic diffuser was effective in increasing recovery and reducing distortion.

computational fluid dynamics↗
NASA NTRS2017

Aeroservoelastic Modeling of Body Freedom Flutter for Control System Design

The communication of this method is being used by NASA in the ongoing collaborations with groups interested in the X-56A flight test program. Model generation for body freedom flutter Addressing issues in: State Consistency, Low frequency dynamics, Unsteady aerodynamics. Applied approach to X-56A MUTT: Comparing to flight test data.

Degree of Freedom↗
NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion systems core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

icing↗
NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion systems core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

upwind schemes↗
NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion system's core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

crysta↗
NASA NTRS2017

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗
NASA NTRS2016

A Quantum-Assisted Algorithm for Sampling Applications in Machine Learning

An increase in the efficiency of sampling from Boltzmann distributions would have a significant impact in deep learning and other machine learning applications. Recently, quantum annealers have been proposed as a potential candidate to speed up this task, but several limitations still bar these state-of-the-art technologies from being used effectively. One of the main limitations is that, while the device may indeed sample from a Boltzmann-like distribution, quantum dynamical arguments suggests it will do so with an instance-dependent effective temperature, different from the physical temperature of the device. Unless this unknown temperature can be unveiled, it might not be possible to effectively use a quantum annealer for Boltzmann sampling. In this talk, we present a strategy to overcome this challenge with a simple effective-temperature estimation algorithm. We provide a systematic study assessing the impact of the effective temperatures in the learning of a kind of restricted Boltzmann machine embedded on quantum hardware, which can serve as a building block for deep learning architectures. We also provide a comparison to k-step contrastive divergence (CD-k) with k up to 100. Although assuming a suitable fixed effective temperature also allows to outperform one step contrastive divergence (CD-1), only when using an instance-dependent effective temperature we find a performance close to that of CD-100 for the case studied here. We discuss generalizations of the algorithm to other more expressive generative models, beyond restricted Boltzmann machines.

Perdomo-Ortiz, Alejandro↗
NASA NTRS2019

Astrobiology Survey of a Lava Cave at Lava Beds National Monument by a Rover Carrying a Remote Sensing Instrument Payload

We report here on a survey of a lava tube cave by a rover that is instrumented for astrobiology missions. The NASA Ames testbed rover, CaveR, was deployed in Valentine Cave in Lava Beds National Monument (N. CA, USA) during August of 2018. The rover carried an instrument package consisting of Near Infrared and Visible Spectrometer System (NIRVSS) a point spectrometer operating in 1590-3400 nm range, sensitive to H2O and -OH bearing minerals, pyroxenes, and carbonates (Roush, et al 2018); the bore sighted Drill Operations Camera (DOC), a monochrome imager illuminated by LEDs at 410, 540, 640, 740, 905 and 940 nm; a Realsense ™ depth sensor system for 3D model generation; and a high resolution DSLR stereo camera. The payload was mounted on a tiltable instrument platform attached to the left side of the rover. The rover was driven manually in the cave by field operators, following instructions from a remote science operations team, and simulating a mission concept with science-guided autonomy. A simulated mission took place for 3 days with a team of 3 scientists selecting targets and interpreting data from the payload. To begin the mission, the rover drove along one wall of the cave imaging continuously with the Realsense in 20 m cave segments, three total. At the start of each day, the images from a 20m segment and a panorama stitched from them were provided to the science team to examine. The science team used these data to prioritize specific points along the cave wall for the collection of NIRVSS, DOC, and DSLR data. The objective of the data collection was to identify and study putative biological and mineralogical features in the cave. The data were delivered in xGDS, a customized mapping, planning, and data base management software developed at NASA Ames (Lee, et al 2013). Once the targets for further observations were selected, a plan for collecting the observations (positions in the cave and pointing for each requested observation) was constructed using xGDS and delivered to a rover team to execute the science data collection plan. Acquired data were delivered back to the science team for analysis. Preliminary results from the experiment illustrate the utility of the system (rover plus payload) to study the cave geology and mineralogy and its potential for identifying biomineral features.

Wong, Uland↗
NASA NTRS2019

Overview of Multi-Layer Metal Insulation Development for Small Stirling Convertors at NASA GRC

The small Stirling convertor currently under development at the NASA Glenn Research Center (GRC) is designed to produce one watt of electrical power from eight watts of heat. Previous radioisotope power systems (RPS) made use of the General-Purpose Heat Source (GPHS) which produces 250 watts of heat but is unsuitable for a one-watt Stirling convertor. The only heat source available is the Light-Weight Radioisotope Heating Unit (LWRHU) which produces one watt of heat and is primarily used to provide heat to electronics and instrumentation to maintain their appropriate operating temperature. Unfortunately, the LWRHU has a heat flux of 272 W/m-squared compared to the GPHS heat flux of 6000 W/m-squared which greatly increases the demands on the insulation to ensure that enough of the heat produced is available to the convertor and not lost to the environment. An analysis was performed that showed that the insulation must have a thermal conductivity of 0.005 W/m·K or better for the system to function. A multi-layer metal insulation package was designed and a prototype was fabricated and tested to investigate the feasibility of this design. The prototype did not meet the requirements; however, the improved thermal model generated using the test data will allow for a second iteration to be developed that has a much higher confidence and meets the performance requirements.

Goodell, Daniel D.↗