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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 523 records · Page 29

System-Availability And Resource-Allocation Program

ACARA analyzes availability, life-cycle cost, and scheduling of resources. Uses statistical Monte Carlo method to simulate capacity states of system as well as failure and repair of components. Failures of components modeled mathematically by use of combination of exponential and Weibull probability distributions. Schedules replacement of components to optimize performance of system. Made to comply with any constraints on production of components, capacities of resupply vehicles, spares kept on site, crews, and/or equipment. Written in APL2.

Viterna, L. A.↗

Electronic Photography at the NASA Langley Research Center

An electronic photography facility has been established in the Imaging & Photographic Technology Section, Visual Imaging Branch, at the NASA Langley Research Center (LaRC). The purpose of this facility is to provide the LaRC community with access to digital imaging technology. In particular, capabilities have been established for image scanning, direct image capture, optimized image processing for storage, image enhancement, and optimized device dependent image processing for output. Unique approaches include: evaluation and extraction of the entire film information content through scanning; standardization of image file tone reproduction characteristics for optimal bit utilization and viewing; education of digital imaging personnel on the effects of sampling and quantization to minimize image processing related information loss; investigation of the use of small kernel optimal filters for image restoration; characterization of a large array of output devices and development of image processing protocols for standardized output. Currently, the laboratory has a large collection of digital image files which contain essentially all the information present on the original films. These files are stored at 8-bits per color, but the initial image processing was done at higher bit depths and/or resolutions so that the full 8-bits are used in the stored files. The tone reproduction of these files has also been optimized so the available levels are distributed according to visual perceptibility. Look up tables are available which modify these files for standardized output on various devices, although color reproduction has been allowed to float to some extent to allow for full utilization of output device gamut.

Holm, Jack↗

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that the authors' techniques allow more accurate estimation of the global system loading, resulting in fewer object migrations than local methods. The authors' method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive load-balancing methods. Results from a preliminary analysis of another system and from simulation with a synthetic load provide some evidence of more general applicability.

LOAD CONTROL↗

Load Balancing Using Time Series Analysis for Soft Real Time Systems with Statistically Periodic Loads

This thesis provides design and analysis of techniques for global load balancing on ensemble architectures running soft-real-time object-oriented applications with statistically periodic loads. It focuses on estimating the instantaneous average load over all the processing elements. The major contribution is the use of explicit stochastic process models for both the loading and the averaging itself. These models are exploited via statistical time-series analysis and Bayesian inference to provide improved average load estimates, and thus to facilitate global load balancing. This thesis explains the distributed algorithms used and provides some optimality results. It also describes the algorithms' implementation and gives performance results from simulation. These results show that our techniques allow more accurate estimation of the global system load ing, resulting in fewer object migration than local methods. Our method is shown to provide superior performance, relative not only to static load-balancing schemes but also to many adaptive methods.

REAL TIME↗

Airfoil Design Using a Coupled Euler and Integral Boundary Layer Method with Adjoint Based Sensitivities

The objective of this paper is to present a control theory approach for the design of airfoils in the presence of viscous compressible flows. A coupled system of the integral boundary layer and the Euler equations is solved to provide rapid flow simulations. An adjunct approach consistent with the complete coupled state equations is employed to obtain the sensitivities needed to drive a numerical optimization algorithm. Design to target pressure distribution is demonstrated on an RAE 2822 airfoil at transonic speed.

Edwards, S.↗

Leonid Storm Flux Analysis From One Leonid MAC Video AL50R

A detailed meteor flux analysis is presented of a seventeen-minute portion of one videotape, collected on November 18, 1999, during the Leonid Multi-instrument Aircraft Campaign. The data was recorded around the peak of the Leonid meteor storm using an intensified CCD camera pointed towards the low southern horizon. Positions of meteors on the sky were measured. These measured meteor distributions were compared to a Monte Carlo simulation, which is a new approach to parameter estimation for mass ratio and flux. Comparison of simulated flux versus observed flux levels, seen between 1:50:00 and 2:06:41 UT, indicate a magnitude population index of r = 1.8 +/- 0.1 and mass ratio of s = 1.64 +/- 0.06. The average spatial density of the material contributing to the Leonid storm peak is measured at 0.82 +/- 0.19 particles per square kilometer per hour for particles of at least absolute visual magnitude +6.5. Clustering analysis of the arrival times of Leonids impacting the earth's atmosphere over the total observing interval shows no enhancement or clumping down to time scales of the video frame rate. This indicates a uniformly random temporal distribution of particles in the stream encountered during the 1999 epoch. Based on the observed distribution of meteors on the sky and the model distribution, recommendations am made for the optimal pointing directions for video camera meteor counts during future ground and airborne missions.

Gural, Peter S.↗

Isolating Curvature Effects in Computing Wall-Bounded Turbulent Flows

The flow over the zero-pressure-gradient So-Mellor convex curved wall is simulated using the Navier-Stokes equations. An inviscid effective outer wall shape, undocumented in the experiment, is obtained by using an adjoint optimization method with the desired pressure distribution on the inner wall as the cost function. Using this wall shape with a Navier-Stokes method, the abilities of various turbulence models to simulate the effects of curvature without the complicating factor of streamwise pressure gradient can be evaluated. The one-equation Spalart-Allmaras turbulence model overpredicts eddy viscosity, and its boundary layer profiles are too full. A curvature-corrected version of this model improves results, which are sensitive to the choice of a particular constant. An explicit algebraic stress model does a reasonable job predicting this flow field. However, results can be slightly improved by modifying the assumption on anisotropy equilibrium in the model's derivation. The resulting curvature-corrected explicit algebraic stress model possesses no heuristic functions or additional constants. It lowers slightly the computed skin friction coefficient and the turbulent stress levels for this case (in better agreement with experiment), but the effect on computed velocity profiles is very small.

Rumsey, Christopher L.↗

Providing Effective Access to Shared Resources: A COIN Approach

Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user's satisfaction in the system falls below a preset minimal level. Since such goals will usually conflict with one another, either implicitly or explicitly the manager must determine the relative importance of the goals, encapsulating that into an overall utility function rating the possible behaviors of the entire system. Here we demonstrate a distributed, robust, and adaptive way to optimize that overall function. Our approach is to interpose adaptive agents between each user and the system, where each such agent is working to maximize its own private utility function. In turn, each such agent's function should be both relatively easy for the agent to learn to optimize, and 'aligned' with the overall utility function of the system manager - an overall function that is based on but in general different from the satisfaction functions of the individual users. To ensure this we enhance the COllective INtelligence (COIN) framework to incorporate user satisfaction functions in the overall utility function of the system manager and accordingly in the associated private utility functions assigned to the users agents. We present experimental evaluations of different COIN-based private utility functions and demonstrate that those COIN-based functions outperform some natural alternatives.

Airiau, Stephane↗

Providing Effective Access to Shared Resources: A COIN Approach

Managers of systems of shared resources typically have many separate goals. Examples are efficient utilization of the resources among its users and ensuring no user s satisfaction in the system falls below a preset minimal level. Since such goals will usually conflict with one another, either implicitly or explicitly the manager must determine the relative importance of the goals, encapsulating that into an overall utility function rating the possible behaviors of the entire system. Here we demonstrate a distributed, robust, and adaptive way to optimize that overall function. Our approach is to interpose adaptive agents between each user and the system, where each such agent is working to maximize its own private utility function. In turn, each such agent's function should be both relatively easy for the agent to learn to optimize, and "aligned" with the overall utility function of the system manager - an overall function that is based on but in general different from the satisfaction functions of the individual users. To ensure this we enhance the Collective INtelligence (COIN) framework to incorporate user satisfaction functions in the overall utility function of the system manager and accordingly in the associated private utility functions assigned to the users agents. We present experimental evaluations of different COIN-based private utility functions and demonstrate that those COIN-based functions outperform some natural alternatives.

Airiau, Stephane↗

Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

The standard VLBI analysis models the distribution of measurement noise as Gaussian. Because the price of recording bits is steadily decreasing, thermal errors will soon no longer dominate. As a result, it is expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become increasingly relevant for optimal analysis. We discuss the advantages of modeling the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen flow assumption pioneered by Treuhaft and Lanyi. We then apply these correlated noise spectra to the weighting of VLBI data analysis for two case studies: X/Ka-band global astrometry and Earth orientation. In both cases we see improved results when the analyses are weighted with correlated noise models vs. the standard uncorrelated models. The X/Ka astrometric scatter improved by approx.10% and the systematic Delta delta vs. delta slope decreased by approx. 50%. The TEMPO Earth orientation results improved by 17% in baseline transverse and 27% in baseline vertical.

instrumentation errors↗

Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

The standard VLBI analysis models measurement noise as purely thermal errors modeled according to uncorrelated Gaussian distributions. As the price of recording bits steadily decreases, thermal errors will soon no longer dominate. It is therefore expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become more relevant for optimal analysis. This paper will discuss the advantages of including the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen ow model pioneered by Treuhaft and Lanyi. We will show examples of applying these correlated noise spectra to the weighting of VLBI data analysis.

thermal noise↗

Occultation Modeling for Radiation Obstruction Effects on Spacecraft Systems

A geometric occultation model has been developed to determine line-of-sight obstruction of radiation sources expected for different NASA space exploration mission designs. Example applications includes fidelity improvements for surface lighting conditions, radiation pressure, thermal and power subsystem modeling. The model makes use of geometric two dimensional shape primitives to most effectively model space vehicles. A set of these primitives is used to represent three dimensional obstructing objects as a two dimensional outline from the perspective of an observing point of interest. Radiation sources, such as the Sun or a Moon's albedo is represented as a collection of points, each of which is assigned a flux value to represent a section of the radiation source. Planetary bodies, such as a Martian moon, is represented as a collection of triangular facets which are distributed in spherical height fields for optimization. These design aspects and the overall model architecture will be presented. Specific uses to be presented includes a study of the lighting condition on Phobos for a possible future surface mission, and computing the incident flux on a spacecraft's solar panels and radiators from direct and reflected solar radiation subject to self-shadowing or shadowing by third bodies.

de Carufel, Guy↗

Trajectory Design to Mitigate Risk on the Transiting Exoplanet Survey Satellite (TESS) Mission

The Transiting Exoplanet Survey Satellite (TESS) will employ a highly eccentric Earth orbit, in 2:1 lunar resonance, reached with a lunar flyby preceded by 3.5 phasing loops. The TESS mission has limited propellant and several orbit constraints. Based on analysis and simulation, we have designed the phasing loops to reduce delta-V and to mitigate risk due to maneuver execution errors. We have automated the trajectory design process and use distributed processing to generate and to optimize nominal trajectories, check constraint satisfaction, and finally model the effects of maneuver errors to identify trajectories that best meet the mission requirements.

design↗

Detection of Chlorophyll and Leaf Area Index Dynamics from Sub-weekly Hyperspectral Imagery

Temporally rich hyperspectral time-series can provide unique time critical information on within-field variations in vegetation health and distribution needed by farmers to effectively optimize crop production. In this study, a dense time series of images were acquired from the Earth Observing-1 (EO-1) Hyperion sensor over an intensive farming area in the center of Saudi Arabia. After correction for atmospheric effects, optimal links between carefully selected explanatory hyperspectral vegetation indices and target vegetation characteristics were established using a machine learning approach. A dataset of in-situ measured leaf chlorophyll (Chll) and leaf area index (LAI), collected during five intensive field campaigns over a variety of crop types, were used to train the rule-based predictive models. The ability of the narrow-band hyperspectral reflectance information to robustly assess and discriminate dynamics in foliar biochemistry and biomass through empirical relationships were investigated. This also involved evaluations of the generalization and reproducibility of the predictions beyond the conditions of the training dataset. The very high temporal resolution of the satellite retrievals constituted a specifically intriguing feature that facilitated detection of total canopy Chl and LAI dynamics down to sub-weekly intervals. The study advocates the benefits associated with the availability of optimum spectral and temporal resolution spaceborne observations for agricultural management purposes.

Houborg, Rasmus↗

Investigation of the Potential for Lidar & Polarimeter Combined Aerosol Retrievals Using Various Instrument Combinations

As a scientific community, we are motivated to achieve better observational capabilities for aerosols, to reduce uncertainties about aerosol’s role in climate. Encouraged by the National Academies Decadal Survey, many are looking to the synergy of lidar and polarimeter as a means of achieving improved measurements. Polarimetric observations of total-column radiances have excellent sensitivity to aerosol size distribution and absorption properties. Active lidar measurements have fewer wavelengths and view angles and therefore more limited sensitivity to aerosol microphysical properties such as complex refractive index. Yet the advantage of vertically resolved profiles is game-changing, especially given that models contain significant uncertainty about the vertical distribution of aerosol and that polarimeter and other passive retrievals must make assumptions about vertical distribution which can impact performance. To optimize the synergy, a joint polarimeter + lidar mission requires a joint retrieval. However, the exact instruments that will be launched on a future satellite are unknown, and the capabilities of polarimeters and lidars cover a large range. In this study, we perform information content analysis for a range of nominal instrument combinations. The methodology is ideal for assessing the impact of measurements and a priori information (assumptions and constraints) with respect to the desired retrieval products, and for comparing measurement systems. It has advantages that make it useful in advance of or in parallel with retrieval development, such as producing quantitatively useful comparisons even for retrieval scenarios that are significantly underdetermined and therefore impossible to retrieve without significant assumptions, and it is not impacted by retrieval-specific sources of error such as incomplete or incorrect convergence which can complicate the interpretation of a retrieval performance analysis. Here, we will derive the expected uncertainty in retrieved aerosol concentration, effective radius, fine mode fraction and single scattering albedo, for a combination of a polarimeter with various grades of lidar, from an elastic backscatter lidar, similar to the pathfinder CALIOP on the CALIPSO satellite, to a multi-wavelength high spectral resolution lidar.

Sharon P Burton↗

Adaptive Aerostructures for Revolutionary Civil Supersonic Transportation

To enable commercially viable civil supersonic transport (SST) aircraft, innovative solutions must be developed to meet noise and efficiency requirements for overland flight. This research effort consists of a multidisciplinary team of academic and industrial experts exploring for the first time the potential of small real-time geometric outer mold line (OML) reconfigurations to minimize sonic boom signatures and aircraft drag in response to changing ambient conditions, thereby enabling noise-compliant overland supersonic flight. The team utilizes recent advances in supersonic computational fluid dynamic (CFD) methods, new noise prediction tools, and new design approaches to consider embedded highly energy-dense shape memory alloy (SMA) actuators for local shape modifications to an SST aircraft leading to optimal low boom signature and low drag in different environments. This university-led program will provide strategic leadership toward technology convergence that advances NASA's Aerospace Research Mission Directorate's (ARMD) research objectives with regard to Thrust 2: “Innovation in Commercial Supersonic Aircraft” by exploring for the first time enabling low-boom operation across a range of flight conditions via structural adaptivity, and will promote education of the next generation of engineers. The overall research strategy is to pursue three critical areas: the design of configurations for reducing boom, SMA material development and modeling, and technology feasibility demonstration in a relevant environment. Initially, the team will identify potential applications where structure or geometry adaptivity provides a benefit in noise or drag across the entire flight envelope. For selected applications/structural locations, required OML geometry changes will be determined based on analysis of sonic boom ground signature and drag reduction using new design tools, trade studies, and atmospheric sensing techniques. Designs will be developed and evaluated against requirements on loading, stroke length, and operational temperature. New alloy formulations will be developed tailored for both autonomous and controlled actuation modes. As the SMA material development matures, integrated system-level factors will be investigated. Optimized designs for small-scale distributed adaptivity applications of maximum benefit will then be matured and tested, moving toward demonstration of the innovative technology approaches at a TRL 4-5 and showing that sonic booms can be reduced by reconfiguration on demand.

Koushik Datta↗

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗

On optimizing the sensor spacing for pressure measurements on wind turbine airfoils

This research article presents a robust approach to optimizing the layout of pressure sensors around an airfoil. A genetic algorithm and a sequential quadratic programming algorithm are employed to derive a sensor layout best suited to represent the expected pressure distribution and, thus, the lift force. The fact that both optimization routines converge to almost identical sensor layouts suggests that an optimum exists and is reached. By comparing against a cosine-spaced sensor layout, it is demonstrated that the underlying pressure distribution can be captured more accurately with the presented layout optimization approach. Conversely, a 39 %–55 % reduction in the number of sensors compared to cosine spacing is achievable without loss in lift prediction accuracy. Given these benefits, an optimized sensor layout improves the data quality, reduces unnecessary equipment and saves cost in experimental setups. While the optimization routine is demonstrated based on the generic example of the IEA 15 MW reference wind turbine, it is suitable for a wide range of applications requiring pressure measurements around airfoils.

17 WIND ENERGY↗