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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

From "Below Dignity" to "Above It All": Origins and Early History of Underwater Neutral Buoyancy Simulation of Weightlessness for EVA Procedures Development and Training

An attempt to clarify some vague memories of underwater studies of astronaut capabilities in space led Dr. John Charles to become acquainted with Sam Mattingly, one of the pioneers in the field, and to greater insights into Mattingly's work simulating Gemini EVAs in the mid-1960s. Charles recounted major accomplishments by Environmental Research Associates (ERA), Mattingly's company for contracting with NASA Langley on several early studies. ERA's work was considered within the context of contemporary efforts to simulate weightlessness and the widespread development of neutral buoyancy facilities after ERA's successful demonstration for Gemini 12.

Charles, John B.↗
NASA NTRS1999

Plasma membrane ordering agent pluronic F-68 (PF-68) reduces neurotransmitter uptake and release and produces learning and memory deficits in rats

A substantial body of evidence indicates that aged-related changes in the fluidity and lipid composition of the plasma membrane contribute to cellular dysfunction in humans and other mammalian species. In the CNS, reductions in neuronal plasma membrane order (PMO) (i.e., increased plasma membrane fluidity) have been attributed to age as well as the presence of the beta-amyloid peptide-25-35, known to play an important role in the neuropathology of Alzheimer's disease (AD). These PMO increases may influence neurotransmitter synthesis, receptor binding, and second messenger systems as well as signal transduction pathways. The effects of neuronal PMO on learning and memory processes have not been adequately investigated, however. Based on the hypothesis that an increase in PMO may alter a number of aspects of synaptic transmission, we investigated several neurochemical and behavioral effects of the membrane ordering agent, PF-68. In cell culture, PF-68 (nmoles/mg SDS extractable protein) reduced [3H]norepinephrine (NE) uptake into differentiated PC-12 cells as well as reduced nicotine stimulated [3H]NE release. The compound (800-2400 microg/kg, i.p., resulting in nmoles/mg SDS extractable protein in the brain) decreased step-through latencies and increased the frequencies of crossing into the unsafe side of the chamber in inhibitory avoidance training. In the Morris water maze, PF-68 increased the latencies and swim distances required to locate a hidden platform and reduced the time spent and distance swam in the previous target quadrant during transfer (probe) trials. PF-68 did not impair performance of a well-learned working memory task, the rat delayed stimulus discrimination task (DSDT), however. Studies with 14C-labeled PF-68 indicated that significant (pmoles/mg wet tissue) levels of the compound entered the brain from peripheral (i.p.) injection. No PF-68 related changes were observed in swim speeds or in visual acuity tests in water maze experiments, rotorod performance, or in tests of general locomotor activity. Furthermore, latencies to select a lever in the DSDT were not affected. These results suggest that PF-68 induced deficits in learning and memory without confounding peripheral motor, sensory, or motivational effects at the tested doses. Furthermore, none of the doses induced a conditioned taste aversion to a novel 0.1% saccharin solution indicating a lack of nausea or gastrointestinal malaise induced by the compound. The data indicate that increases in neuronal plasma membrane order may have significant effects on neurotransmitter function as well as learning and memory processes. Furthermore, compounds such as PF-68 may also offer novel tools for studying the role of neuronal PMO in mnemonic processes and changes in PMO resulting from age-related disorders such as AD.

Poloxamer/pharmacology↗
NASA NTRS1989

Methods and decision making on a Mars rover for identification of fossils

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Eberlein, Susan↗
NASA NTRS2019

Application of Machine Learning Techniques to Delay Tolerant Network Routing

This dissertation discusses several machine learning techniques to improve routing in delay tolerant networks (DTNs). These are networks in which there may be long one-way trip times, asymmetric links, high error rates, and deterministic as well as non-deterministic loss of contact between network nodes, such as interplanetary satellite networks, mobile ad hoc networks and wireless sensor networks. This work uses historical network statistics to train a multi-label classifier to predict reliable paths through the network. In addition, a clustering technique is used to predict future mobile node locations. Both of these techniques are used to reduce the consumption of resources such as network bandwidth, memory and data storage that is required by replication routing methods often used in opportunistic DTN environments. Thesis contributions include: an emulation tool chain developed to create a DTN test bed for machine learning, the network and software architecture for a machine learning based routing method, the development and implementation of classification and clustering techniques and performance evaluation in terms of machine learning and routing metrics.

Dudukovich, Rachel M.↗
NASA NTRS1997

A Report of Bethune-Cookman College NASA JOVE Projects

This document is the final report for the Joint Venture (JOVE) in Space Sciences, and describes the tasks, performed with the support of the contract. These tasks include work in: (1) interfacing microprocessor systems to high performance parallel interface chips, SCSI drive and memory, needed for the implementation of a Space Optical Data Recorder; (2) designing a digital interface architecture for a microprocessor controlled sensors monitoring unit for a NASA Jitter Attenuation and Dynamics Experiment (JADE) project; (3) developing an enhanced back-propagation training algorithm; (4) studying the effect of simulated spaceflight on Aortic Contractility; (5) developing a course in astronomy; and (6) improving internet access by running cables, and installing hubs in various places on the campus; and (7) researching the characteristics of Nd:YALO laser resonator.

Agba, Lawrence C.↗
NASA NTRS2014

Assessment of Shape Memory Alloys - From Atoms To Actuators - Via In Situ Neutron Diffraction

As shape memory alloys (SMAs) become an established actuator technology, it is important to identify the fundamental mechanisms responsible for their performance by understanding microstructure performance relationships from processing to final form. Yet, microstructural examination of SMAs at stress and temperature is often a challenge since structural changes occur with stress and temperature and microstructures cannot be preserved through quenching or after stress removal, as would be the case for conventional materials. One solution to this dilemma is in situ neutron diffraction, which has been applied to the investigation of SMAs and has offered a unique approach to reveal the fundamental micromechanics and microstructural aspects of bulk SMAs in a non-destructive setting. Through this technique, it is possible to directly correlate the micromechanical responses (e.g., internal residual stresses, lattice strains), microstructural evolutions (e.g., texture, defects) and phase transformation properties (e.g., phase fractions, kinetics) to the macroscopic actuator behavior. In this work, in situ neutron diffraction was systematically employed to evaluate the deformation and transformation behavior of SMAs under typical actuator conditions. Austenite and martensite phases, yield behavior, variant selection and transformation temperatures were characterized for a polycrystalline NiTi (49.9 at. Ni). As the alloy transforms under thermomechanical loading, the measured textures and lattice plane-level variations were directly related to the cyclic actuation-strain characteristics and the dimensional instability (strain ratcheting) commonly observed in this alloy. The effect of training on the shape memory characteristics of the alloy and the development of two-way shape memory effect (TWSME) were also assessed. The final conversion from a material to a useful actuator, typically termed shape setting, was also investigated in situ during constrained heatingcooling and subsequent shape recovery experiments. Neutron diffraction techniques are also being applied to the investigation of novel high temperature SMAs with the objective of designing alloys with better stability, higher transition temperatures and ultimately superior durability.

Shape Memory Alloys↗
NASA NTRS2015

On the Recovery Stress of a Ni50.3Ti29.7Hf20 High Temperature Shape Memory Alloy

Recovery stress in shape memory alloys (SMAs), also known as blocking stress, is an important property generally obtained during heating under a dimensional constraint as the material undergoes the martensitic phase transformation. This property has been instinctively utilized in most SMA shape-setting procedures, and has been used in numerous applications such as fastening and joining, rock splitting, safety release mechanisms, reinforced composites, medical devices, and many other applications. The stress generation is also relevant to actuator applications where jamming loads (e.g., in case the actuator gets stuck and is impeded from moving) need to be determined for proper hardware sizing. Recovery stresses in many SMA systems have been shown to reach stresses in the order of 800 MPa, achieved via thermo-mechanical training such as pre-straining, heat treatments or other factors. With the advent of high strength, high temperature SMAs, recovery stress data has been rarely probed, and there is no information pertinent to the magnitudes of these stresses. Thus, the purpose of this work is to investigate the recovery stress capability of a precipitation strengthened, Ni50.3Ti29.7Hf20 (at.) high temperature SMA in uniaxial tension and compression. This material has been shown to exhibit outstanding strength and stability during constant-stress, thermal cycling, but no data exists on constant-strain thermal cycling. Several training routines were implemented as part of this work including isothermal pre-straining, isobaric thermal cycling, and isothermal cyclic training routines. Regardless of the training method used, the recovery stress was characterized using constant-strain (strain-controlled condition) thermal cycling between the upper and lower cycle temperatures. Preliminary results indicate recovery stresses in excess of 1.5 GPa were obtained after a specific training routine. This stress magnitude is significantly higher than conventional NiTi stress generation capability.

Recovery Stress↗
NASA NTRS1999

STS-103 Crew Training

The Hubble Space Telescope (HST) team is preparing for NASA's third scheduled service call to Hubble. This mission, STS-103, will launch from Kennedy Space Center aboard the Space Shuttle Discovery. The seven flight crew members are Commander Curtis L. Brown, Pilot Scott J. Kelly, European Space Agency (ESA) astronaut Jean-Francois Clervoy who will join space walkers Steven L. Smith, C. Michael Foale, John M. Grunsfeld, and ESA astronaut Claude Nicollier. The objectives of the HST Third Servicing Mission (SM3A) are to replace the telescope's six gyroscopes, a Fine-Guidance Sensor, an S-Band Single Access Transmitter, a spare solid-state recorder and a high-voltage/temperature kit for protecting the batteries from overheating. In addition, the crew plans to install an advanced computer that is 20 times faster and has six times the memory of the current Hubble Space Telescope computer. To prepare for these extravehicular activities (EVAs), the SM3A astronauts participated in Crew Familiarization sessions with the actual SM3A flight hardware. During these sessions the crew spent long hours rehearsing their space walks in the Guidance Navigation Simulator and NBL (Neutral Buoyancy Laboratory). Using space gloves, flight Space Support Equipment (SSE), and Crew Aids and Tools (CATs), the astronauts trained with and verified flight orbital replacement unit (ORU) hardware. The crew worked with a number of trainers and simulators, such as the High Fidelity Mechanical Simulator, Guidance Navigation Simulator, System Engineering Simulator, the Aft Shroud Door Trainer, the Forward Shell/Light Shield Simulator, and the Support Systems Module Bay Doors Simulator. They also trained and verified the flight Orbital Replacement Unit Carrier (ORUC) and its ancillary hardware. Discovery's planned 10-day flight is scheduled to end with a night landing at Kennedy.

Source record↗
NASA NTRS1973

The control of a manipulator by a computer model of the cerebellum.

Extension of previous work by Albus (1971, 1972) on the theory of cerebellar function to an application of a computer model of the cerebellum to manipulator control. Following a discussion of the cerebellar function and of a perceptron analogy of the cerebellum, particularly in regard to learning, an electromechanical model of the cerebellum is considered in the form of an IBM 1800 computer connected to a Rancho Los Amigos arm with seven degrees of freedom. It is shown that the computer memory makes it possible to train the arm on some representative sample of the universe of possible states and to achieve satisfactory performance.

Albus, J. S.↗
NASA NTRSDate not supplied

Using Long-Short Term Memory Models to Predict Solar Active Regions Emergence

We train Long Short-Term Memory (LSTM) models that predict the formation of active regions (ARs), the main source of eruptive solar activity. Using the Doppler shift velocity, the continuum intensity and the magnetic field full-disk maps from SDO/HMI we have created time-series datasets of acoustic power and magnetic flux which are used to train Long Short-Term Memory (LSTM) models on predicting decreases in continuum intensity 12 hours in advance. Testing of the models' performance was done on data from 5 ARs, unseen from the model during training. The model predicted the emergence of AR11726, AR13165 and AR13179, 10, 29 and 5 hours in advance, and variations of this model achieved average RMSE values of 0.11 for both active and quiet parts of the solar disc, showing the ability of the model to capture acoustic power anomalies and predict continuum intensity variations. This work sets the foundations for the very first ML-aided prediction of solar ARs.

SMD↗
NASA NTRS2008

Characterization of Ni19.5Ti50.5Pd25Pt5 High-Temperature Shape Memory Alloy Springs and their Potential Application in Aeronautics

Shape memory alloys (SMAs) have been used as actuators in many different industries since the discovery of the shape memory effect, but the use of SMAs as actuation devices in aeronautics has been limited due to the temperature constraints of commercially available materials. Consequently, work is being done at NASA's Glenn Research Center to develop new SMAs capable of being used in high temperature environments. One of the more promising high-temperature shape memory alloys (HTSMAs) is Ni19.5Ti50.5Pd25Pt5. Recent work has shown that this material is capable of being used in operating environments of up to 250 C. This material has been shown to have very useful actuation capabilities, demonstrating repeatable strain recoveries up to 2.5% in the presence of an externally applied load. Based on these findings, further work has been initiated to explore potential applications and alternative forms of this alloy, such as springs. Thus, characterization of Ni19.5Ti50.5Pd25Pt5 springs, including their mechanical response and how variations in this response correlate to changes in geometric parameters, are discussed. The effects of loading history, or training, on spring behavior were also investigated. A comparison of the springs with wire actuators is made and the benefits of using one actuator form as opposed to the other discussed. These findings are used to discuss design considerations for a surge-control mechanism that could be used in the centrifugal compressor of a T-700 helicopter engine.

Stebner, Aaron↗
NASA NTRS2008

Effect of Upper-Cycle Temperature on the Load-Biased, Strain-Temperature Response of NiTi

Over the past decade, interest in shape memory alloy based actuators has increased as the primary benefits of these solid-state devices have become more apparent. However, much is still unknown about the characteristic behavior of these materials when used in actuator applications. Recently we have shown that the maximum temperature reached during thermal cycling under isobaric conditions could significantly affect the observed mechanical response of NiTi (55 wt% Ni), especially the amount of transformation strain available for actuation and thus work output. This investigation extends that original work to ascertain whether further increases in the upper-cycle temperature would produce additional improvement in the work output of the material, which has a stress-free Af of 113 oC, and to determine the optimum cyclic conditions. Thus, isobaric, thermal-cycle experiments were conducted in the aforementioned alloy at various stress levels from 50-300 MPa using upper-cycle temperatures of 165, 200, 230, 260, 290, 320 and 350 oC. The data indicated that the amount of applied stress influenced the transformation strain available in the system, as would be expected. However, the maximum temperature reached during the thermal excursion also plays a role in determining the transformation strain, with the maximum transformation strain being developed by thermal cycling to 290 oC. In situ, neutron diffraction showed that the differences in transformation strain were related to differences in martensite texture within the microstructure when cycling to different upper-cycle temperatures. Hence, understanding this effect is important to optimizing the operation of SMA-based actuators and could lead to new methods for processing and training shape memory alloys for optimal performance.

Padula, Santo, II↗
NASA NTRS2011

Effect of Upper-Cycle Temperature on the Load-Biased, Strain-Temperature Response of NiTi

Over the past decade, interest in shape memory alloy based actuators has increased as the primary benefits of these solid-state devices have become more apparent. However, much is still unknown about the characteristic behavior of these materials when used in actuator applications. Recently we have shown that the maximum temperature reached during thermal cycling under isobaric conditions could significantly affect the observed mechanical response of NiTi (55 wt% Ni), especially the amount of transformation strain available for actuation and thus work output. The investigation we report here extends that original work to ascertain whether further increases in the upper-cycle temperature would produce additional changes in the work output of the material, which has a stress-free austenite finish temperature of 113 C, and to determine the optimum cyclic conditions. Thus, isobaric, thermal-cycle experiments were conducted on the aforementioned alloy at various stresses from 50-300 MPa using upper-cycle temperatures of 165, 200, 230, 260, 290, 320 and 350 C. The data indicated that the amount of applied stress influenced the transformation strain, as would be expected. However, the maximum temperature reached during the thermal excursion also plays an equally significant role in determining the transformation strain, with the maximum transformation strain observed during thermal cycling to 290 C. In situ neutron diffraction at stress and temperature showed that the differences in transformation strain were mostly related to changes in martensite texture when cycling to different upper-cycle temperatures. Hence, understanding this effect is important to optimizing the operation of SMA-based actuators and could lead to new methods for processing and training shape memory alloys for optimal performance.

Padula, Santo, II↗
NASA NTRSDate not supplied

A Machine Learning Ready Dataset of Acoustic Power Maps for Detection of Active Region Emergence

The development of an accurate forecast for solar eruptive activity has become increasingly important in order to prevent any potential impact on activities in space and the Earth's environment. It is therefore crucial to detect active regions before they appear on the solar surface and create early warning capabilities for upcoming Space Weather disturbances. In this work, 9TB of solar data (SDO/HMI dopplergrams, magnetograms and continuum intensity maps) involving the emergence of 61 NOAA solar active regions since 2010 were processed using the NASA HECC capabilities. An acoustic power maps time-series dataset was created (for four different frequency ranges and processed to take into account the solar sphere geometric effect ) which can be used for understanding the dynamics of the solar surface and train a variety of ML models. The calculated acoustic power maps carry precursor information associated with the decrease in continuum intensity on the solar surface, verifying older helioseismology research. Our results show that a Long Short-Term Memory (LSTMs) model, with a modest layer depth and the right hyperparameters tuned, when trained on this solar acoustic power maps dataset can predict without false negatives a drop in intensity (associated with the emergence of the active region), up to 18 hours in advance.

SMD↗
NASA NTRS2001

Stabilized NADH as a Countermeasure for Jet Lag

Current remedies for jet lag (phototherapy, melatonin, stimulant, and sedative medications) are limited in efficacy and practicality. The efficacy of a stabilized, sublingual form of reduced nicotin amide adenine dinucleotide (NADH, ENADAlert, Menuco Corp.) as a countermeasure for jet lag was examined. Because NADH increases cellular production of ATP and facilitates dopamine synthesis, it may counteract the effects of jet lag on cognitive functioning and sleepiness. Thirty-five healthy, employed subjects participated in this double-blind, placebo-controlled study. Training and baseline testing were conducted on the West Coast before subjects flew overnight to the East Coast, where they would experience a 3-hour time difference. Upon arrival, individuals were randomly assigned to receive either 20 mg of sublingual stabilized ADH (n=18) or identical placebo tablets (n=17). All participants completed computer-administered tests (including CogScreen7) to assess changes in cognitive functioning, mood, and sleepiness in the morning and afternoon. Jet lag resulted in increased sleepiness for over half the participants and deterioration of cognitive functioning for approximately one third. The morning following the flight, subjects experienced lapses of attention in addition to disruptions in working memory, divided attention, and visual perceptual speed. Individuals who received NADH performed significantly better on 5 of 8 cognitive and psychomotor test measures (P less than or equal to 0.5) and showed a trend for better performance on the other three measures (P less than or equal to .l0). Subjects also reported less sleepiness compared with those who received placebo. No adverse effects were observed with NADH treatment. Stabilized NADH significantly reduced jet lag-induced disruptions of cognitive functioning, was easily administered, and was found to have no adverse side effects.

Kay, Gary G.↗
NASA NTRS2019

Further Development Of Aperture: A Precise Extremely Large Reflective Telescope Using Re-Configurable Elements: NASA Innovative Advanced Concepts (NIAC) - Phase II

One of the pressing needs for space ultraviolet-visible astronomy is a design to allow larger mirrors than the James Webb Space Telescope primary. The diameter of the rocket fairing limits the mirror diameter such that all future missions calling for mirrors up to 16 meters in diameter or larger will require a mirror that is deployed post-launch. In response to the deployment requirement, we address the issues of this concept called "A Precise Extremely Large Reflective Telescope Using Reconfigurable Elements (APERTURE) with both hardware experiments and software simulations... We designed and built several fixtures with O-rings to hold a membrane. We established a coating process to make a membrane that was coated on one side with Cr and the other side with Cr-Terfenol-D-NiCo. The Terfenol-D (T-D hereafter) is the MSM (Magnetic Smart Memory) we use. We bought and established a procedure for measuring a deformation over time and purchased a Shack Hartmann system from Imagine Optic (https://www.imagine-optic.com). The first substrate we used was DuPont (TM) Kapton® polyimide film. Due to material creep, we found the stability over a 48-hour period with a Kapton substrate was not as good as desired (greater than 1 micron). We then switched to CP1 Polyimide. We found the CP1 much more stable to creep, being stable from about 3 hours to 48 hours to within a measurement error to below approximately 0.1 micron. We produced a 13 micron maximum deviation on a 50-millimeter-diameter piece of CP1 (25 microns thick). The T-D coating was about 2 microns, and the other layers, about 10 nanometers. The magnetic field at the base was about 0.1 teslas. We can make the T-D film at least 5 times thicker and the magnetic field at least 5 times stronger, and hence make deformations as much as 25 times larger. We have a formed a collaboration produced at the NIAC (NASA Innovative Advanced Concepts) mid-term review with Dr. Ron Shiri of Goddard Space Flight Center (GSFC) to explore making controlled deviations on lambda/14-lambda/20 scales which are required to bring a surface to the diffraction limit. We carried out only preliminary work on Si using a Coordinate Measuring Machine (CMM), which produced deviations on the 1 micron level. We are still working on a program to bring to GSFC a flat enough (radius of curvature greater than 10 microns) -coated a Si piece with Cr, T-D, NiCo. Then we plan to carry out tests with an interferometer. Further, we formed a new collaboration with Prof. Rajan Vaidyanathan of the University of Central Florida to replace the CP1 with a shape memory alloy (SMA). With his collaboration, we acquired new Federal funding outside of NASA to explore the use of SMAs (we use NiTi). Our preliminary results indicate that we can produce deformations greater than 1 micron on approximately 100 microns thick. Furthermore we have shown that the NiTi can deploy to better than 1 micron of its set original and then trained shape.

Re-Configurable Elements↗
NASA NTRS2021

Applying Machine Learning to Predict Alaskan Ionospheric Irregularities

In this work several machine-learning (ML) techniques for predicting ionospheric irregularities in the northern auroral zone were tested. The techniques include Ridge Regression, Long Short-Term Memory Neural Network (LSTM), Classification Neural Network (CNN), Autoencoder Classification Neural Network (ACNN), and LSTM Autoencoder Classification Neural Network (LACNN). These techniques were tested with the rate of total electron content (TEC) index (ROTI) data collected during 2008 and 2009 from a geodetic station in Fairbanks, Alaska (64.98°N, 147.50°W), which is in the auroral zone. Using ROTI data with the ML techniques, experiments were conducted to reach two goals: (1) examine what space weather measurements present good correlation with ROTI so that they may be helpful in ML-based prediction of ionospheric irregularities in the polar region; (2) predict ROTI hours and days ahead by training the neural network models with historical ROTI data alone. The Ridge Regression experiments indicate that a combination of measurements of local geomagnetic horizontal components, geomagnetic SYM-H index, 3-hour Kp and ap indices, and F10.7 solar flux index appears to be more correlated to the single-site ROTI measurements than other parameters. The neural network (NN) experiments show that although the LACNN model allows for predictions of non-irregularity and irregularity conditions defined by ROTI levels up to 3 hours in advance, with an overall accuracy ≥ 92%, a number of irregularity events can still be missed. Hence, further development is needed to reduce the number of missed events. In this paper, the models, data processing, model performance, prediction results, and potential applications are presented.

Pi, Xiaoqing↗
NASA NTRS2006

Development and Testing of an Axial Halbach Magnetic Bearing

The NASA Glenn Research Center has developed and tested a revolutionary Axial Halbach Magnetic Bearing. The objective of this work is to develop a viable non-contact magnetic thrust bearing utilizing Halbach arrays for all-electric flight, and many other applications. This concept will help to reduce harmful emissions, reduce the Nation s dependence on fossil fuels and mitigate many of the concerns and limitations encountered in conventional axial bearings such as bearing wear, leaks, seals and friction loss. The Axial Halbach Magnetic Bearing is inherently stable and requires no active feedback control system or superconductivity as required in many magnetic bearing designs. The Axial Halbach Magnetic Bearing is useful for very high speed applications including turbines, instrumentation, medical systems, computer memory systems, and space power systems such as flywheels. Magnetic fields suspend and support a rotor assembly within a stator. Advanced technologies developed for particle accelerators, and currently under development for maglev trains and rocket launchers, served as the basis for this application. Experimental hardware was successfully designed and developed to validate the basic principles and analyses. The report concludes that the implementation of Axial Halbach Magnetic Bearings can provide significant improvements in rotational system performance and reliability.

Eichenberg, Dennis J.↗