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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1944

Use of Internal Coolant as a Means of Permitting Increase in Engine Take-Off Power

Engine tests, together with estimates made at Langley Memorial Aeronautical Laboratory, indicate that a 25-percent increase in take-off power can be obtained with present-day aircraft engines without increasing either the knock limit of the fuel or the external cooling requirements of the engine. This increase in power with present fuels and present external cooling is made possible through the use of an internal coolant inducted through the inlet manifold. Estimates on aircraft indicate that this 25-percent increase in power will permit an approximate usable increase of 8.5 percent in the take-off load of existing military airplanes. This increase in load is equivalent to an increase in the weight of gasoline normally carried of between 30 and 65 percent.

FUELS, ANTIKNOCK↗
NASA NTRS1998

On the Information Content of Program Traces

Program traces are used for analysis of program performance, memory utilization, and communications as well as for program debugging. The trace contains records of execution events generated by monitoring units inserted into the program. The trace size limits the resolution of execution events and restricts the user's ability to analyze the program execution. We present a study of the information content of program traces and develop a coding scheme which reduces the trace size to the limit given by the trace entropy. We apply the coding to the traces of AIMS instrumented programs executed on the IBM SPA and the SCSI Power Challenge and compare it with other coding methods. Our technique shows size of the trace can be reduced by more than a factor of 5.

Frumkin, Michael↗
NASA NTRS1999

Three-Dimensional Simulations of Electron Beams Focused by Periodic Permanent Magnets

A fully three-dimensional (3D) model of an electron beam focused by a periodic permanent magnet (PPM) stack has been developed. First, the simulation code MAFIA was used to model a PPM stack using the magnetostatic solver. The exact geometry of the magnetic focusing structure was modeled; thus, no approximations were made regarding the off-axis fields. The fields from the static solver were loaded into the 3D particle-in-cell (PIC) solver of MAFIA where fully 3D behavior of the beam was simulated in the magnetic focusing field. The PIC solver computes the time-integration of electromagnetic fields simultaneously with the time integration of the equations of motion of charged particles that move under the influence of those fields. Fields caused by those moving charges are also taken into account; thus, effects like space charge and magnetic forces between particles are fully simulated. The electron beam is simulated by a number of macro-particles. These macro-particles represent a given charge Q amounting to that of several million electrons in order to conserve computational time and memory. Particle motion is unrestricted, so particle trajectories can cross paths and move in three dimensions under the influence of 3D electric and magnetic fields. Correspondingly, there is no limit on the initial current density distribution of the electron beam, nor its density distribution at any time during the simulation. Simulation results including beam current density, percent ripple and percent transmission will be presented, and the effects current, magnetic focusing strength and thermal velocities have on beam behavior will be demonstrated using 3D movies showing the evolution of beam characteristics in time and space. Unlike typical beam optics models, this 3D model allows simulation of asymmetric designs such as non- circularly symmetric electrostatic or magnetic focusing as well as the inclusion of input/output couplers.

Kory, Carol L.↗
NASA NTRS2018

A Systems Architecting Methodology Using Bloom’s Taxonomy to Promote Creative Engineering Synthesis

Architecting complex systems requires high-level cognitive processing and extensive knowledge of the system elements, functions, relationships, and constraints. This paper describes a systems architecting methodology implemented through cognitive psychological creative processes using Bloom’s taxonomy as a framework to generate the expert knowledge required to effectively and systematically synthesize new systems. Systems architecting activities were carried out to identify, develop, and capture factual and conceptual knowledge relevant to the system subject matter and functional elements, as well as to facilitate active processing of the knowledge through remembering, understanding, applying, analyzing, evaluating, and creating. Dual channel and limited capacity principles of learning were incorporated into the format of the systems engineering tools developed to assist with information processing and retention. Meta-cognitive strategies associated with memory and creative idea generation were implemented into the methodology to effectively and efficiently develop system alternatives using the full collection of knowledge. Synthesis of an orbiting sample capture and orientation system architecture to enable spacecraft-based on orbit capture of a Mars sample container for a potential Mars Sample Return campaign was used as a case study.

Adajian, Rama↗
NASA NTRS1985

Feasibility of self-structured current accessed bubble devices in spacecraft recording systems

The self-structured, current aperture approach to magnetic bubble memory is described. Key results include: (1) demonstration that self-structured bubbles (a lattice of strongly interacting bubbles) will slip by one another in a storage loop at spacings of 2.5 bubble diameters, (2) the ability of self-structured bubbles to move past international fabrication defects (missing apertures) in the propagation conductors (defeat tolerance), and (3) moving bubbles at mobility limited speeds. Milled barriers in the epitaxial garnet are discussed for containment of the bubble lattice. Experimental work on input/output tracks, storage loops, gates, generators, and magneto-resistive detectors for a prototype device are discussed. Potential final device architectures are described with modeling of power consumption, data rates, and access times. Appendices compare the self-structured bubble memory from the device and system perspectives with other non-volatile memory technologies.

Nelson, G. L.↗
NASA NTRS1975

Landsat 2 on-board computer

The Landsat Spacecraft Project (formerly known as ERTS) was based essentially on the use of Nimbus spacecraft hardware. It was soon recognized that the availability of only 30 stored command locations (which were sufficient for the Nimbus mission) would limit the operation of the Landsat 1 mission with much higher power sensors, recorders, and wideband communications being cycled on and off throughout the orbit. The solution described is a simple memory with hard wired logic, of a design that can interface with the existing hardware, without modifications. The design was implemented using an existing APO (Advanced Onboard Processor) and a 4096 word X 18 bit plated wire memory. (The AOP has been subsequently designated the NASA Standard Spacecraft Computer.)

Lesko, J. G., Jr.↗
NASA NTRS2006

Valve Health Monitoring System Utilizing Smart Instrumentation

The valve monitoring system is a stand alone unit with network capabilities for integration into a higher level health management system. The system is designed for aiding in failure predictions of high-geared ball valves and linearly actuated valves. It performs data tracking and archiving for identifying degraded performance. The data collection types are cryogenic cycles, total cycles, inlet temperature, body temperature torsional strain, linear bonnet strain, preload position, total travel and total directional changes. Events are recorded and time stamped in accordance with the IRIG B True Time. The monitoring system is designed for use in a Class 1 Division II explosive environment. The basic configuration consists of several instrumentation sensor units and a base station. The sensor units are self contained microprocessor controlled and remotely mountable in three by three by two inches. Each unit is potted in a fire retardant substance without any cavities and limited to low operating power for maintaining safe operation in a hydrogen environment. The units are temperature monitored to safeguard against operation outside temperature limitations. Each contains 902-928 MHz band digital transmitters which meet Federal Communication Commission's requirements and are limited to a 35 foot transmission radius for preserving data security. The base-station controller correlates data from the sensor units and generates data event logs on a compact flash memory module for database uploading. The entries are also broadcast over an Ethernet network. Nitrogen purged National Electrical Manufactures Association (NEMA) Class 4 enclosures are used to house the base-station

Jensen, Scott L.↗
NASA NTRS1989

Method and apparatus for implementing a traceback maximum-likelihood decoder in a hypercube network

A method and a structure to implement maximum-likelihood decoding of convolutional codes on a network of microprocessors interconnected as an n-dimensional cube (hypercube). By proper reordering of states in the decoder, only communication between adjacent processors is required. Communication time is limited to that required for communication only of the accumulated metrics and not the survivor parameters of a Viterbi decoding algorithm. The survivor parameters are stored at a local processor's memory and a trace-back method is employed to ascertain the decoding result. Faster and more efficient operation is enabled, and decoding of large constraint length codes is feasible using standard VLSI technology.

Pollara-Bozzola, Fabrizio↗
NASA NTRS2022

Can Machine Learning Reveal Precursors of Reversals of the Geomagnetic Axial Dipole Field?

It is well known that the axial dipole part of Earth’s magnetic field reverses polarity, so that the magnetic North Pole becomes the South Pole and vice versa. The timing of reversals is well documented for the past 160 Myr, but the conditions that lead to a reversal are still not well understood. It is not known if there are reliable ‘precursors’ of reversals (events that indicate that a reversal is upcoming) or what they might be. We investigate if machine learning (ML) techniques can reliably identify precursors of reversals based on time-series of the axial magnetic dipole field. The basic idea is to train a classifier using segments of time-series of the axial magnetic dipole. This training step requires modification of standard ML techniques to account for the fact that we are interested in rare events—a reversal is unusual, while a non-reversing field is the norm. Without our tweak, the ML classifiers lead to useless predictions. Perhaps even more importantly, the usable observational record is limited to 0–2 Ma and contains only five reversals, necessitating that we determine if the data are even sufficient to reliably train and validate an ML algorithm. To answer these questions we use several ML classifiers (linear/non-linear support vector machines and long short-term memory networks), invoke a hierarchy of numerical models (from simplified models to 3-D geodynamo simulations), and two palaeomagnetic reconstructions (PADM2M and Sint-2000). The performance of the ML classifiers varies across the models and the observational record and we provide evidence that this is not an artefact of the numerics, but rather reflects how ‘predictable’ a model or observational record is. Studying models of Earth’s magnetic field via ML classifiers thus can help with identifying shortcomings or advantages of the various models. For Earth’s magnetic field, we conclude that the ability of ML to identify precursors of reversals is limited, largely due to the small amount and low frequency resolution of data, which makes training and subsequent validation nearly impossible. Put simply: the ML techniques we tried are not currently capable of reliably identifying an axial dipole moment (ADM) precursor for geomagnetic reversals. This does not necessarily imply that such a precursor does not exist, and improvements in temporal resolution and length of ADM records may well offer better prospects in the future.

Kyle Gwirtz↗
NASA NTRS1977

Spectral interpolation - Zero fill or convolution

Zero fill, or augmentation by zeros, is a method used in conjunction with fast Fourier transforms to obtain spectral spacing at intervals closer than obtainable from the original input data set. In the present paper, an interpolation technique (interpolation by repetitive convolution) is proposed which yields values accurate enough for plotting purposes and which lie within the limits of calibration accuracies. The technique is shown to operate faster than zero fill, since fewer operations are required. The major advantages of interpolation by repetitive convolution are that efficient use of memory is possible (thus avoiding the difficulties encountered in decimation in time FFTs) and that is is easy to implement.

Forman, M. L.↗
NASA NTRS1995

Alternative packet switch architectures for a 30/20 GHz FDMA/TDMA geostationary communication satellite network

This study has investigated alternatives for realizing a packet-based network switch for deployment on a communication satellite. The emphasis was on the avoidance of contention problems that can occur due to the simultaneous arrival of an excessive number of packets destined for the same downlink dwell. The study was to look ahead, beyond the current Advanced Communications Technology Satellite (ACTS) capability, to the next generation of satellites. The study has not been limited by currently available technology, but has used university and commercial research efforts as a basis for designs that can be readily constructed and launched within the next five years. Tradeoffs in memory requirement, power requirement, and architecture have been considered as a part of our study.

Stehle, Roy↗
NASA NTRS2001

Development of a Hybrid RANS/LES Method for Turbulent Mixing Layers

Significant research has been underway for several years in NASA Glenn Research Center's nozzle branch to develop advanced computational methods for simulating turbulent flows in exhaust nozzles. The primary efforts of this research have concentrated on improving our ability to calculate the turbulent mixing layers that dominate flows both in the exhaust systems of modern-day aircraft and in those of hypersonic vehicles under development. As part of these efforts, a hybrid numerical method was recently developed to simulate such turbulent mixing layers. The method developed here is intended for configurations in which a dominant structural feature provides an unsteady mechanism to drive the turbulent development in the mixing layer. Interest in Large Eddy Simulation (LES) methods have increased in recent years, but applying an LES method to calculate the wide range of turbulent scales from small eddies in the wall-bounded regions to large eddies in the mixing region is not yet possible with current computers. As a result, the hybrid method developed here uses a Reynolds-averaged Navier-Stokes (RANS) procedure to calculate wall-bounded regions entering a mixing section and uses a LES procedure to calculate the mixing-dominated regions. A numerical technique was developed to enable the use of the hybrid RANS-LES method on stretched, non-Cartesian grids. With this technique, closure for the RANS equations is obtained by using the Cebeci-Smith algebraic turbulence model in conjunction with the wall-function approach of Ota and Goldberg. The LES equations are closed using the Smagorinsky subgrid scale model. Although the function of the Cebeci-Smith model to replace all of the turbulent stresses is quite different from that of the Smagorinsky subgrid model, which only replaces the small subgrid turbulent stresses, both are eddy viscosity models and both are derived at least in part from mixing-length theory. The similar formulation of these two models enables the RANS and LES equations to be solved with a single solution scheme and computational grid. The hybrid RANS-LES method has been applied to a benchmark compressible mixing layer experiment in which two isolated supersonic streams, separated by a splitter plate, provide the flows to a constant-area mixing section. Although the configuration is largely two dimensional in nature, three-dimensional calculations were found to be necessary to enable disturbances to develop in three spatial directions and to transition to turbulence. The flow in the initial part of the mixing section consists of a periodic vortex shedding downstream of the splitter plate trailing edge. This organized vortex shedding then rapidly transitions to a turbulent structure, which is very similar to the flow development observed in the experiments. Although the qualitative nature of the large-scale turbulent development in the entire mixing section is captured well by the LES part of the current hybrid method, further efforts are planned to directly calculate a greater portion of the turbulence spectrum and to limit the subgrid scale modeling to only the very small scales. This will be accomplished by the use of higher accuracy solution schemes and more powerful computers, measured both in speed and memory capabilities.

Georgiadis, Nicholas J.↗
NASA NTRSDate not supplied

Early Information Parameter-Set Analysis for Satellite Close Approaches using Machine Learning

Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc

Brianna I. Robertson↗
NASA NTRS2018

Shape Memory Alloy (SMA) Tires - A New Paradigm in Tire Performance

Tires for rover applications have had to deal with numerous challenges, risking mission failure and significantly increasing costs associated with missions. As a result, a new tire technology has been developed to overcome all of the limitations with the current approach. This presentation will highlight how this new technology has changed the paradigm for NASA's mission and will provide a glimpse at terrestrial applications where this technology may provide advantage.

Spring↗
NASA NTRS2016

Hexapod Robot

The project I am working on at NASA-Johnson Space Center in Houston, TX is a hexapod robot. This project was started by various engineers at the Trick Lab. The goal of this project is to have the hexapod track a yellow ball or possibly another object from left to right and up/down. The purpose is to have it track an object like a real creature. The project will consist of using software and hardware. This project started with a hexapod robot which uses a senor bar to track a yellow ball but with a limited field of vision. The sensor bar acts as the robots "head." Two servos will be added to the hexapod to create flexion and extension of the head. The neck and head servos will have to be programmed to be added to the original memory map of the existing servos. I will be using preexisting code. The main programming language that will be used to add to the preexisting code is C++. The trick modeling and simulation software will also be used in the process to improve its tracking and movement. This project will use a trial and error approach, basically seeing what works and what does not. The first step is to initially understand how the hexapod works. To get a general understanding of how the hexapod maneuvers and plan on how to had a neck and head servo which works with the rest of the body. The second step would be configuring the head and neck servos with the leg servos. During this step, limits will be programmed specifically for the each servo. By doing this, the servo is limited to how far it can rotate both clockwise and counterclockwise and this is to prevent hardware damage. The hexapod will have two modes in which it works in. The first mode will be if the sensor bar does not detect an object. If the object it is programmed to look for is not in its view it will automatically scan from left to right 3 times then up and down once. The second mode will be if the sensor bar does detect the object. In this mode the hexapod will track the object from left to right or up and down. The hexapod will eventually be able to track the object moving its head and body in sync with on another and being able to rotate its body at 360 degrees. This is the plans and possible end results for the hexapod robot I will be working on during my summer internship at NASA Johnson Space Center. Since working on the hexapod project I have gained an increase interest in robotics. I enjoy the process of critical thinking. Also will working on this project I was challenged in a way that made more passionate to strive even more to become an engineer. I've learned that asking questions is an important part of the learning process. Also I learn that much more is accomplished when teamwork is applied.

Begody, Ericka↗
NASA NTRS2016

Engineering Design Tools for Shape Memory Alloy Actuators: CASMART Collaborative Best Practices and Case Studies

The primary goal of the Consortium for the Advancement of Shape Memory Alloy Research and Technology (CASMART) is to enable the design of revolutionary applications based on shape memory alloy (SMA) technology. In order to help realize this goal and reduce the development time and required experience for the fabrication of SMA actuation systems, several modeling tools have been developed for common actuator types and are discussed herein along with case studies, which highlight the capabilities and limitations of these tools. Due to their ability to sustain high stresses and recover large deformations, SMAs have many potential applications as reliable, lightweight, solid-state actuators. Their advantage over classical actuators can also be further improved when the actuator geometry is modified to fit the specific application. In this paper, three common actuator designs are studied: wires, which are lightweight, low-profile, and easily implemented; springs, which offer actuation strokes upwards of 200 at reduced mechanical loads; and torque tubes, which can provide large actuation forces in small volumes and develop a repeatable zero-load actuation response (known as the two-way shape memory effect). The modeling frameworks, which have been implemented in the design tools, are developed for each of these frequently used SMA actuator types. In order to demonstrate the versatility and flexibility of the presented design tools, as well as validate their modeling framework, several design challenges were completed. These case studies include the design and development of an active hinge for the deployment of a solar array or foldable space structure, an adaptive solar array deployment and positioning system, a passive air temperature controller for regulation flow temperatures inside of a jet engine, and a redesign of the Corvette active hatch, which allows for pressure equalization of the car interior. For each of the presented case studies, a prototype or proof-of-concept was fabricated and the experimental results and lessons learned are discussed. This analysis presents a collection of CASMART collaborative best practices in order to allow readers to utilize the available design tools and understand their modeling principles. These design tools, which are based on engineering models, can provide first-order optimal designs and are a basic and efficient method for either demonstrating design feasibility or refining design parameters. Although the design and integration of an SMA-based actuation system always requires application- and environment-specific engineering considerations, common modeling tools can significantly reduce the investment required for actuation system development and provide valuable engineering insight.

Design tools↗
NASA NTRS2015

Shape Memory Alloy Research and Development at NASA Glenn - Current and Future Progress

Shape memory alloys (SMAs) are a unique class of multifunctional materials that have the ability to recover large deformations or generate high stresses in response to thermal, mechanical and or electromagnetic stimuli. These abilities have made them a viable option for actuation systems in aerospace, medical, and automotive applications, amongst others. However, despite many advantages and the fact that SMA actuators have been developed and used for many years, so far they have only found service in a limited range of applications. In order to expand their applications, further developments are needed to increase their reliability and stability and to address processing, testing and qualification needed for large-scale commercial application of SMA actuators.

Challenges↗
NASA NTRS1982

Computational fluid dynamics - The coming revolution

The development of aerodynamic theory is traced from the days of Aristotle to the present, with the next stage in computational fluid dynamics dependent on superspeed computers for flow calculations. Additional attention is given to the history of numerical methods inherent in writing computer codes applicable to viscous and inviscid analyses for complex configurations. The advent of the superconducting Josephson junction is noted to place configurational demands on computer design to avoid limitations imposed by the speed of light, and a Japanese projection of a computer capable of several hundred billion operations/sec is mentioned. The NASA Numerical Aerodynamic Simulator is described, showing capabilities of a billion operations/sec with a memory of 240 million words using existing technology. Near-term advances in fluid dynamics are discussed.

Graves, R. A., Jr.↗