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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

Simultaneous compression of the passively mode-locked pulsewidth and pulse train

Simultaneous compression of the passively mode-locked pulse width and pulse train have been achieved by using a plano-convex unstable resonator hybrided by a nonlinear Sagnac ring interferometer. The greater than 30 mJ single pulse energy of a lone oscillator and less than or equal to 10 ps pulsewidth have been obtained. Using this system, the LAGEOS and ETALON satellites' laser ranging have been performed successfully.

Yang, Xiang-Chun↗

Design of a Low-Energy FARAD Thruster

The design of an electrodeless thruster that relies on a pulsed, rf-assisted discharge and electromagnetic acceleration using an inductive coil is presented. The thruster design is optimized using known performance,scaling parameters, and experimentally-determined design rules, with design targets for discharge energy, plasma exhaust velocity; and thrust efficiency of 100 J/pulse, 25 km/s, and 50%, respectively. Propellant is injected using a high-speed gas valve and preionized by a pulsed-RF signal supplied by a vector inversion generator, allowing for current sheet formation at lower discharge voltages and energies relative to pulsed inductive accelerators that do not employ preionization. The acceleration coil is designed to possess an inductance of at least 700 nH while the target stray (non-coil) inductance in the circuit is 70 nH. A Bernardes and Merryman pulsed power train or a pulse compression power train provide current to the acceleration coil and solid-state components are used to switch both powertrains.

Polzin, K. A.↗

Metronome Use for Coordination of Breaths and Cardiac Compressions Delivered by Minimally-Trained Caregivers During Two-Person CPR

Astronaut crew medical officers (CMO) aboard the International Space Station (ISS) receive 40 hours of medical training over 18 months before each mission, including two-person cardiopulmonary resuscitation (2CPR) as recommended by the American Heart Association (AHA). Recent studies have concluded that the use of metronomic tones improves the coordination of 2CPR by trained clinicians. 2CPR performance data for minimally-trained caregivers has been limited. The goal of this study was to determine whether use of a metronome by minimally-trained caregivers (CMO analogues) would improve 2CPR performance. 20 pairs of minimally-trained caregivers certified in 2CPR via AHA guidelines performed 2CPR for 4 minutes on an instrumented manikin using 3 interventions: 1) Standard 2CPR without a metronome [NONE], 2) Standard 2CPR plus a metronome for coordinating compression rate only [MET], 3) Standard 2CPR plus a metronome for coordinating both the compression rate and ventilation rate [BOTH]. Caregivers were evaluated for their ability to meet the AHA guideline of 32 breaths-240 compressions in 4 minutes. All (100%) caregivers using the BOTH intervention provided the required number of ventilation breaths as compared with the NONE caregivers (10%) and MET caregivers (0%). For compressions, 97.5% of the BOTH caregivers were not successful in meeting the AHA compression guideline; however, an average of 238 compressions of the desired 240 were completed. None of the caregivers were successful in meeting the compression guideline using the NONE and MET interventions. This study demonstrates that use of metronomic tones by minimally-trained caregivers for coordinating both compressions and breaths improves 2CPR performance. Meeting the breath guideline is important to minimize air entering the stomach, thus decreasing the likelihood of gastric aspiration. These results suggest that manifesting a metronome for the ISS may augment the performance of 2CPR on orbit and thus may increase the level of care.

Hurst, Victor, IV↗

LVQ and backpropagation neural networks applied to NASA SSME data

Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network.

Doniere, Timothy F.↗

Laboratory-Model Integrated-System FARAD Thruster

Pulsed inductive plasma accelerators are spacecraft propulsion devices in which energy is stored in a capacitor and then discharged through an inductive coil. The device is electrodeless, inducing a plasma current sheet in propellant located near the face of the coil. The propellant is accelerated and expelled at a high exhaust velocity (order of 10 km/s) through the interaction of the plasma current with an induced magnetic field. The Faraday Accelerator with RF-Assisted Discharge (FARAD) thruster [1,2] is a type of pulsed inductive plasma accelerator in which the plasma is preionized by a mechanism separate from that used to form the current sheet and accelerate the gas. Employing a separate preionization mechanism in this manner allows for the formation of an inductive current sheet at much lower discharge energies and voltages than those found in previous pulsed inductive accelerators like the Pulsed Inductive Thruster (PIT). In a previous paper [3], the authors presented a basic design for a 100 J/pulse FARAD laboratory-version thruster. The design was based upon guidelines and performance scaling parameters presented in Refs. [4, 5]. In this paper, we expand upon the design presented in Ref. [3] by presenting a fully-assembled and operational FARAD laboratory-model thruster and addressing system and subsystem-integration issues (concerning mass injection, preionization, and acceleration) that arose during assembly. Experimental data quantifying the operation of this thruster, including detailed internal plasma measurements, are presented by the authors in a companion paper [6]. The thruster operates by first injecting neutral gas over the face of a flat, inductive acceleration coil and at some later time preionizing the gas. Once the gas is preionized current is passed through the acceleration coil, inducing a plasma current sheet in the propellant that is accelerated away from the coil through electromagnetic interaction with the time-varying magnetic field. Neutral gas is injected over the face of the acceleration coil through a fast-acting valve that feeds a central distribution manifold. The thruster is designed to preionize the gas using an RF-frequency ringing signal produced by a discharging Vector Inversion Generator (VIG). The acceleration stage consists of a multiple-turn, multiple-strand spiral induction coil (see Fig. 1, left panel) and is designed for operation at discharge energies on the order of 100 J/pulse. Several different pulsed power train modules can be used to drive current through the acceleration coil. One such power train is based upon the Bernardes and Merryman circuit topology, which restricts voltage reversal on the capacitor banks and can be clamped to eliminate current reversal in the coil. A second option is a pulse-compression-ring power train (see Fig. 1, right panel), which takesa temporally broad, low current pulse and transforms it into a short, high current pulse.

Polzin, K.A.↗

Wave/current interaction model

The wave-current interaction for the application to remote sensing data via numerical simulations and data comparison is modelled. Using the field data of surface current shear, wind condition and ambient wave spectrum, the numerical simulations of directional wave spectrum evolution were used to interpret and to compare with the aircraft data from Radar Ocean Wave Spectrometer (ROWS) and Surface Contour Radar (SCR) across the front during Frontal Air Sea Interaction Experiment (FASINEX). The wave-ice interaction was inspired by the observation of large amplitude waves hundreds of kms inside the ice pack in the Weddell Sea, resulting in breakup of the ice pack. The developed analysis of processes includes the refraction of waves at the pack edge, the effects of pack compression on wave propagation, wave train stability and buckling stability in the ice pack. Sources of pack compression and interaction between wave momentum and pack compression are investigated. Viscous camping of propagating waves in the marginal ice zone are also studied. The analysis suggests an explanation for the change in wave dispersion observed from the ship and the sequence of processes that cause ice pack breakup, pressure ridge formation and the formation of open bands of water.

Liu, A. K.↗

A Comparison of Two Control Display Unit Concepts on Flight Management System Training

One of the biggest challenges for a pilot in the transition to a 'glass' cockpit is understanding the flight management system (FMS). Because of both the complex nature of the FMS and the pilot-FMS interface, a large portion of transition training is devoted to the FMS. The current study examined the impact of the primary pilot-FMS interface, the control display unit (CDU), on FMS training. Based on the hypothesis that the interface design could have a significant impact on training, an FMS simulation with two separate interfaces was developed. One interface was similar to a current-generation design, and the other was a multiwindows CDU based on graphical user interface techniques. For both application and evaluation reasons, constraints were applied to the graphical CDU design to maintain as much similarity as possible with the conventional CDU. This preliminary experiment was conducted to evaluate the interface effects on training. Sixteen pilots with no FMS experience were used in a between-subjects test. A time-compressed, airline-type FMS training environment was simulated. The subjects were trained to a fixed-time criterion, and performance was measured in a final, full-mission simulation context. This paper describes the technical approach, simulation implementation, and experimental results of this effort.

Abbott, Terence S.↗

Trains of Magnetic Holes and Magnetic Humps in the Heliosheath

This paper discusses the existence of trains (sequences) of magnetic holes and magnetic humps in the heliosheath, based on Voyager 1 observations made in the intervals DOY 312.9707 - 317.0879, 2005 and DOY 185.2762 - 186.7957, 2005. These two trains represent a class of compressive fluctuations in the heliosheath. Varying from one region or time interval to another, this class of fluctuations probably depends on the varying conditions upstream the Termination Shock and its nature. The trains of magnetic holes in the heliosheath resemble certain magnetic field strength fluctuations observed in planetary magnetosheaths.

Burlaga, Leonard↗

Assessment of Pseudoshock Models Against Experiment in a Low-Aspect-Ratio Isolator

A highly confined shock train is investigated in a direct-connect isolator facility with a Mach 2 inflow and a constant-area low-aspect-ratio rectangular test section. High-speed schlieren imaging, wall static pressure measurements, surface oil-flow visualization, and particle image velocimetry from this isolator are synthesized into a three-dimensional schematic of the shock train structure. Against this, the prevailing pseudoshock models in the literature are assessed to evaluate the validity of their underlying assumptions. None of the prevailing pseudoshock models are found to simultaneously model the pressure and Mach number profiles, indicating a gap in the model formation and underlying assumptions when applied to the experimental isolator of interest. The presence of distortion in the isolator flowfield, such as a wall-bounded vortex, is found to skew the structure of the shock train, altering the strength and distribution of the compressive pressure gradient. It is further observed that the separated flow morphology surrounding the shock train is not monolithic, as is typically assumed, adjusting the balance of compressive forces within the shock cells. These findings lead to the conclusion that existing flux-conserved modeling approaches require modification to be effective in distorted and highly confined cases, including closure models that capture the three-dimensional distorted structure of the approach flow and its evolution along the shock train.

Shock Train↗

BLOB: An unsupervised clustering approach to spatial preprocessing of MSS imagery

A basic concept of Multispectral Scanner data processing was developed for use in agricultural inventories; namely, to introduce spatial coordinates of each pixel into the vector description of the pixel and to use this information along with the spectral channel values in a conventional unsupervised clustering of the scene. The result is to isolate spectrally homogeneous field-like patches (called blobs). The spectral mean vector of a blob can be regarded as a defined feature and used in a conventional pattern recognition procedure. The benefits of use are: ease in locating training units in imagery; data compression of from 10 to 30 depending on the application; reduction of scanner noise and consequently potential improvements in classification/proportion estimation performances.

Kauth, R. J.↗

Blob - An unsupervised clustering approach to spatial preprocessing of MSS imagery

A basic concept of MSS data processing has been developed for use in agricultural inventories; namely, to introduce spatial coordinates of each pixel into the vector description of the pixel and to use this information along with the spectral channel values in a conventional unsupervised clustering of the scene. The result is to isolate spectrally homogeneous field-like patches (called 'blobs'). The spectral mean vector of a blob can be regarded as a defined feature and used in a conventional pattern recognition procedure. The benefits of use are: ease in locating training units in imagery; data compression of from 10 to 30 depending on the application; reduction of scanner noise and consequently potential improvements in classification/proportion estimation performances.

Kauth, R. J.↗

Rocket engine diagnostics using neural networks

Two problems in applying neural networks to fault detection and identification are (1) the complexity of the sensor data to fault mapping and (2) the lack of sufficient training data. Here, methods are derived and tested in an architecture which addresses these two problems. First, the sensor data to fault mapping is decomposed into three simpler mappings which perform sensor data compression, hypothesis generation, and sensor fusion. Efficient training is performed for each mapping separately. Second, the neural network which performs sensor fusion is structured to detect new unknown faults for which training examples were not presented. These methods were tested on a task of fault detection and identification in the Space Shuttle Main Engine (SSME). Results indicate that the decomposed neural network architecture can be trained efficiently, can identify faults for which it has been trained, and can detect the occurrence of faults for which it has not been trained.

Whitehead, Bruce A.↗

Learning and diagnosing faults using neural networks

Neural networks have been employed for learning fault behavior from rocket engine simulator parameters and for diagnosing faults on the basis of the learned behavior. Two problems in applying neural networks to learning and diagnosing faults are (1) the complexity of the sensor data to fault mapping to be modeled by the neural network, which implies difficult and lengthy training procedures; and (2) the lack of sufficient training data to adequately represent the very large number of different types of faults which might occur. Methods are derived and tested in an architecture which addresses these two problems. First, the sensor data to fault mapping is decomposed into three simpler mappings which perform sensor data compression, hypothesis generation, and sensor fusion. Efficient training is performed for each mapping separately. Secondly, the neural network which performs sensor fusion is structured to detect new unknown faults for which training examples were not presented during training. These methods were tested on a task of fault diagnosis by employing rocket engine simulator data. Results indicate that the decomposed neural network architecture can be trained efficiently, can identify faults for which it has been trained, and can detect the occurrence of faults for which it has not been trained.

Whitehead, Bruce A.↗

Improved Compression of Wavelet-Transformed Images

A recently developed data-compression method is an adaptive technique for coding quantized wavelet-transformed data, nominally as part of a complete image-data compressor. Unlike some other approaches, this method admits a simple implementation and does not rely on the use of large code tables. A common data compression approach, particularly for images, is to perform a wavelet transform on the input data, and then losslessly compress a quantized version of the wavelet-transformed data. Under this compression approach, it is common for the quantized data to include long sequences, or runs, of zeros. The new coding method uses prefixfree codes for the nonnegative integers as part of an adaptive algorithm for compressing the quantized wavelet-transformed data by run-length coding. In the form of run-length coding used here, the data sequence to be encoded is parsed into strings consisting of some number (possibly 0) of zeros, followed by a nonzero value. The nonzero value and the length of the run of zeros are encoded. For a data stream that contains a sufficiently high frequency of zeros, this method is known to be more effective than using a single variable length code to encode each symbol. The specific prefix-free codes used are from two classes of variable-length codes: a class known as Golomb codes, and a class known as exponential-Golomb codes. The codes within each class are indexed by a single integer parameter. The present method uses exponential-Golomb codes for the lengths of the runs of zeros, and Golomb codes for the nonzero values. The code parameters within each code class are determined adaptively on the fly as compression proceeds, on the basis of statistics from previously encoded values. In particular, a simple adaptive method has been devised to select the parameter identifying the particular exponential-Golomb code to use. The method tracks the average number of bits used to encode recent runlengths, and takes the difference between this average length and the code parameter. When this difference falls outside a fixed range, the code parameter is updated (increased or decreased). The Golomb code parameter is selected based on the average magnitude of recently encoded nonzero samples. The coding method requires no floating- point operations, and more readily adapts to local statistics than other methods. The method can also accommodate arbitrarily large input values and arbitrarily long runs of zeros. In practice, this means that changes in the dynamic range or size of the input data set would not require a change to the compressor. The algorithm has been tested in computational experiments on test images. A comparison with a previously developed algorithm that uses large code tables (generated via Huffman coding on training data) suggests that the data-compression effectiveness of the present algorithm is comparable to the best performance achievable by the previously developed algorithm.

Kiely, Aaron↗

The effect of lossy image compression on image classification

We have classified four different images, under various levels of JPEG compression, using the following classification algorithms: minimum-distance, maximum-likelihood, and neural network. The training site accuracy and percent difference from the original classification were tabulated for each image compression level, with maximum-likelihood showing the poorest results. In general, as compression ratio increased, the classification retained its overall appearance, but much of the pixel-to-pixel detail was eliminated. We also examined the effect of compression on spatial pattern detection using a neural network.

Paola, Justin D.↗

Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

Huang, Yiteng↗

Isolator Shock Train Response to Dual-Mode Scramjet Throttling-Like Forcing

Typical dual-mode scramjet designs employ an isolator component situated between the inlet and combustor. The isolator fluidically buffers the inlet from the combustor via the formation of a shock train, an interconnected series of shock-boundary layer interactions. The isolator is required during ramjet-engine operation and at the lower edges of the scramjet operational envelope. In an operational engine, transient behavior imposes fluidic dynamics due to attitude adjustments, combustor throttling, aberrant resonances within the combustor, etc. To accommodate these transients, the shock train adjusts on both temporal and spatial scales. Sufficiently large downstream pressure increases in the combustor play a critical role during unstart, whereby strong compression waves propagate upstream in the isolator to ultimately force the shock train out the inlet, if it cannot stabilize to the pressure increase. This critically reduces the engine mass flow rate, potentially causing a catastrophic reduction in thrust and loss of the vehicle. A nearly instantaneous unstart can, in principle, be predicted by a ratio of the normal shock pressure jump in an inviscid isolator. However, lower-magnitude perturbations, below this bound, also induce unstarts. Understanding the transient behavior inherent in unsteady isolator operation is critical to reducing safety margin in isolator length and refining engine control algorithms to improve engine performance. The Isolator Dynamics Research Lab (IDRL) is a cold-flow, direct-connect isolator facility ideal for assessing the fundamental fluid dynamics of shock trains. The internal flow of a scramjet isolator is modeled using a 2D, symmetric Mach 2.5 nozzle followed by a 695 mm long, 25.4x50.8 mm rectangular isolator test section. A blockage cone on a high-speed ball screw actuator downstream of the isolator is pulsed to simulate the throttling behavior in an operational combustor. Wall flush high-speed static pressure transducers detect the streamwise shock train within the isolator. Time delays between the onset of the throttling and the response motion of the shock train are analyzed to assess the controlling scales and parameters. From this analysis, the response time of the isolator shock train system is found to depend primarily on the isolator back pressure time-rate-of-change but quickly saturates to a maximum propagation speed along the isolator. These results inform dual-mode scramjet engine designers of the critical parameters and limits of an unstart resistant engine.

scramjet↗