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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Hypersonic Inflatable Aerodynamic Decelerator (HIAD) Technology Development Overview

The successful flight of the Inflatable Reentry Vehicle Experiment (IRVE)-3 has further demonstrated the potential value of Hypersonic Inflatable Aerodynamic Decelerator (HIAD) technology. This technology development effort is funded by NASA's Space Technology Mission Directorate (STMD) Game Changing Development Program (GCDP). This paper provides an overview of a multi-year HIAD technology development effort, detailing the projects completed to date and the additional testing planned for the future. The effort was divided into three areas: Flexible Systems Development (FSD), Mission Advanced Entry Concepts (AEC), and Flight Validation. FSD consists of a Flexible Thermal Protection Systems (FTPS) element, which is investigating high temperature materials, coatings, and additives for use in the bladder, insulator, and heat shield layers; and an Inflatable Structures (IS) element which includes manufacture and testing (laboratory and wind tunnel) of inflatable structures and their associated structural elements. AEC consists of the Mission Applications element developing concepts (including payload interfaces) for missions at multiple destinations for the purpose of demonstrating the benefits and need for the HIAD technology as well as the Next Generation Subsystems element. Ground test development has been pursued in parallel with the Flight Validation IRVE-3 flight test. A larger scale (6m diameter) HIAD inflatable structure was constructed and aerodynamically tested in the National Full-scale Aerodynamics Complex (NFAC) 40ft by 80ft test section along with a duplicate of the IRVE-3 3m article. Both the 6m and 3m articles were tested with instrumented aerodynamic covers which incorporated an array of pressure taps to capture surface pressure distribution to validate Computational Fluid Dynamics (CFD) model predictions of surface pressure distribution. The 3m article also had a duplicate IRVE-3 Thermal Protection System (TPS) to test in addition to testing with the Aerocover configuration. Both the Aerocovers and the TPS were populated with high contrast targets so that photogrammetric solutions of the loaded surface could be created. These solutions both refined the aerodynamic shape for CFD modeling and provided a deformed shape to validate structural Finite Element Analysis (FEA) models. Extensive aerothermal testing has been performed on the TPS candidates. This testing has been conducted in several facilities across the country. The majority of the testing has been conducted in the Boeing Large Core Arc Tunnel (LCAT). HIAD is continuing to mature testing methodology in this facility and is developing new test sample fixtures and control methodologies to improve understanding and quality of the environments to which the samples are subjected. Additional testing has been and continues to be performed in the NASA LaRC 8ft High Temperature Tunnel, where samples up to 2ft by 2ft are being tested over representative underlying structures incorporating construction features such as sewn seams and through-thickness quilting. With the successful completion to the IRVE-3 flight demonstration, mission planning efforts are ramping up on the development of the HIAD Earth Atmospheric Reenty Test (HEART) which will demonstrate a relevant scale vehicle in relevant environments via a large-scale aeroshell (approximately 8.5m) entering at orbital velocity (approximately 7km/sec) with an entry mass on the order of 4MT. Also, the Build to Print (BTP) hardware built as a risk mitigation for the IRVE-3 project to have a "spare" ready to go in the event of a launch vehicle delivery failure is now available for an additional sub-orbital flight experiment. Mission planning is underway to define a mission that can utilize this existing hardware and help the HIAD project further mature this technology.

Hughes, Stephen J.↗
NASA NTRS1990

Exact Chord-Length Distribution For SEU Calculations

Computed rates of SEU's more accurate. Exact integral chord-length distribution derived for use in calculations of rates of single-event upsets (SEU's) (changes in logic states) caused by impingement of cosmic rays or other ionizing radiation on electronic logic circuits.

Buehler, Martin G.↗
NASA NTRS1994

Open Solutions to Distributed Control in Ground Tracking Stations

The advent of high speed local area networks has made it possible to interconnect small, powerful computers to function together as a single large computer...This paper examines a model for tracking stations and their requirements for inter-processor communications in the next century.

lan↗
NASA NTRS2001

Task Assignment Heuristics for Distributed CFD Applications

CFD applications require high-performance computational platforms: 1. Complex physics and domain configuration demand strongly coupled solutions; 2. Applications are CPU and memory intensive; and 3. Huge resource requirements can only be satisfied by teraflop-scale machines or distributed computing.

Lopez-Benitez, N.↗
NASA NTRS1985

An efficient algorithm for estimating noise covariances in distributed systems

An efficient computational algorithm for estimating the noise covariance matrices of large linear discrete stochatic-dynamic systems is presented. Such systems arise typically by discretizing distributed-parameter systems, and their size renders computational efficiency a major consideration. The proposed adaptive filtering algorithm is based on the ideas of Belanger, and is algebraically equivalent to his algorithm. The earlier algorithm, however, has computational complexity proportional to p to the 6th, where p is the number of observations of the system state, while the new algorithm has complexity proportional to only p-cubed. Further, the formulation of noise covariance estimation as a secondary filter, analogous to state estimation as a primary filter, suggests several generalizations of the earlier algorithm. The performance of the proposed algorithm is demonstrated for a distributed system arising in numerical weather prediction.

Dee, D. P.↗
NASA NTRS2006

The Low-Noise Potential of Distributed Propulsion on a Catamaran Aircraft

The noise shielding potential of an inboard-wing catamaran aircraft when coupled with distributed propulsion is examined. Here, only low-frequency jet noise from mid-wing-mounted engines is considered. Because low frequencies are the most difficult to shield, these calculations put a lower bound on the potential shielding benefit. In this proof-of-concept study, simple physical models are used to describe the 3-D scattering of jet noise by conceptualized catamaran aircraft. The Fast Scattering Code is used to predict noise levels on and about the aircraft. Shielding results are presented for several catamaran type geometries and simple noise source configurations representative of distributed propulsion radiation. Computational analyses are presented that demonstrate the shielding benefits of distributed propulsion and of increasing the width of the inboard wing. Also, sample calculations using the FSC are presented that demonstrate additional noise reduction on the aircraft fuselage by the use of acoustic liners on the inboard wing trailing edge. A full conceptual aircraft design would have to be analyzed over a complete mission to more accurately quantify community noise levels and aircraft performance, but the present shielding calculations show that a large acoustic benefit could be achieved by combining distributed propulsion and liner technology with a twin-fuselage planform.

Posey, Joe W.↗
NASA NTRS1998

Model-Trained Neural Networks and Electronic Holography Demonstrated to Detect Damage in Blades

Detect Damage in Blades Electronic holography can show damaged regions in fan blades at 30 frames/sec. The electronic holograms are transformed by finite-element-model-trained artificial neural networks to visualize the damage. The trained neural networks are linked with video and graphics to visualize the bending-induced strain distribution, which is very sensitive to damage. By contrast, it is very difficult to detect damage by viewing the raw, speckled, characteristic fringe patterns. For neural-network visualization of damage, 2 frames or 2 fields are used, rather than the 12 frames normally used to compute the displacement distribution from electronic holograms. At the NASA Lewis Research Center, finite element models are used to compute displacement and strain distributions for the vibration modes of undamaged and cracked blades. A model of electronic time-averaged holography is used to transform the displacement distributions into finite-element-resolution characteristic fringe patterns. Then, a feedforward neural network is trained with the fringe-pattern/strain-pattern pairs, and the neural network, electronic holography, and video are implemented on a workstation. Now that the neural networks have been tested successfully at 30 frames/sec on undamaged and cracked cantilevers, the electronic holography and neural-network processing are being adapted for onsite damage inspection of twisted fan blades and rotormounted blades. Our conclusion is that model-trained neural nets are effective when they are trained with good models whose application is well understood. This work supports the aeromechanical testing portion of the Advanced Subsonic Technology Project.

Decker, Arthur J.↗
NASA NTRS2019

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web↗
NASA NTRS1985

An algorithm for computing the number of distinct spectral vectors in thematic mapper data

A computationally efficient method was developed to compute the number of distinct spectral vectors and their frequency of occurrence in Landsat-4 Thematic Mapper (TM) data. The algorithm first partitions the image into spectrally disjoint subsets and then computes the frequency distribution of distinct spectral vectors within each subset from a multidimensional histogram. The overall frequency distribution is tabulated by accumulating the results from each subset. The number of distinct spectral vectors could be used as a measure of potential storage compaction of alternate data representations for data compression, or as a measure of information content in the comparison of spectral band combinations and/or spatial resolutions for an image. Results from processing three 512 x 512 pixel Landsat-4 TM images and one Landsat-4 Multispectral Scanner (MSS) image are presented as examples. An algorithm for computing the frequency distribution of distinct spectral vectors in MSS data is given in the Appendix.

Wharton, S. W.↗
NASA NTRS2010

Static Load Distribution in Ball Bearings

A numerical procedure for computing the internal loading distribution in statically loaded, single-row, angular-contact ball bearings when subjected to a known combined radial and thrust load is presented. The combined radial and thrust load must be applied in order to avoid tilting between inner and outer rings. The numerical procedure requires the iterative solution of Z + 2 simultaneous nonlinear equations - where Z is the number of the balls - to yield an exact solution for axial and radial deflections, and contact angles. Numerical results for a 218 angular-contact ball bearing have been compared with those from the literature and show significant differences in the magnitudes of the ball loads, contact angles, and the extent of the loading zone.

Ricci, Mario↗
NASA NTRS2011

Numerical Prediction of Radiation Measurements Taken in the X2 Facility for Mars and Titan Gas Mixtures

Thermochemical relaxation behind a normal shock in Mars and Titan gas mixtures is simulated using a CFD solver, DPLR, for a hemisphere of 1 m radius; the thermochemical relaxation along the stagnation streamline is considered equivalent to the flow behind a normal shock. Flow simulations are performed for a Titan gas mixture (98% N2, 2% CH4 by volume) for shock speeds of 5.7 and 7.6 km/s and pressures ranging from 20 to 1000 Pa, and a Mars gas mixture (96% CO2, and 4% N2 by volume) for a shock speed of 8.6 km/s and freestream pressure of 13 Pa. For each case, the temperatures and number densities of chemical species obtained from the CFD flow predictions are used as an input to a line-by-line radiation code, NEQAIR. The NEQAIR code is then used to compute the spatial distribution of volumetric radiance starting from the shock front to the point where thermochemical equilibrium is nominally established. Computations of volumetric spectral radiance assume Boltzmann distributions over radiatively linked electronic states of atoms and molecules. The results of these simulations are compared against experimental data acquired in the X2 facility at the University of Queensland, Australia. The experimental measurements were taken over a spectral range of 310-450 nm where the dominant contributor to radiation is the CN violet band system. In almost all cases, the present approach of computing the spatial variation of post-shock volumetric radiance by applying NEQAIR along a stagnation line computed using a high-fidelity flow solver with good spatial resolution of the relaxation zone is shown to replicate trends in measured relaxation of radiance for both Mars and Titan gas mixtures.

Palmer, Grant↗
NASA NTRSDate not supplied

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗
NASA NTRS1990

ER-2 lidar measurements of stratocumulus cloud top structure on July 14, 1987

On July 14, 1987 NASA's ER-2 high altitude aircraft flew a mission to measure the structure of stratocumulus clouds off the coast of California. A flight pattern was executed so that the two-dimensional variability of the clouds could be detected. The technique of analysis of the lidar data to measure cloud tops follows. First each signal is searched for its maximum in return strength. This maximum is caused by scattering of the laser light off cloud particles or from the ocean surface. Next the variance of the signal return above the level of maximum backscatter is determined. Cloud top is assigned to a level (above the level of maximum backscatter) where the backscatter exceeds the average variance. This two-step process is necessary because the level of maximum backscatter does not correspond to the cloud top. Ocean surface returns are easily separated from cloud returns in this process, described in detail by Boers, Spinhirne, and Hart (1988). Analysis of the data so far has shown that there were very few breaks in the clouds. Furthermore the layer top was very flat with local oscillations not exceeding 30 m. Such small cloud top variations are still well within the range of detectability, because the precision of this technique of cloud top detection has previously been established to be 13 to 15 m. Data are presently being analyzed to compute cloud top distributions and fractional cloudiness. The aim of this research is to relate the fractional cloudiness to the mean thermodynamic structure of the boundary layer. Researchers plan to compute spectral scales of the cloud top variability in two dimensions to determine the orientation of the clouds with respect to the mean wind. Furthermore the lidar derived cloud top distribution will be used in the computation of the thermodynamic and radiation budget of the boundary layer.

Boers, Reinout↗
NASA NTRS1991

Partitioning of unstructured problems for parallel processing

Many large-scale computational problems are based on unstructured computational domains. Primary examples are unstructured grid calculations based on finite volume methods in computational fluid dynamics, or structural analysis problems based on finite element approximations. The question of how to distribute such unstructured computational domains over a large number of processors in a MIMD machine with distributed memory is addressed. A graph theoretical framework for these problems is established. Based on this framework three decomposition algorithms are introduced. In particular a new decomposition algorithm is discussed, which is based on the computation of an eigenvector of the Laplacian matrix associated with the graph. Numerical comparisons on large-scale two- and three-dimensional problems demonstrate the superiority of the new spectral bisection algorithm.

Simon, H. D.↗