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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Monitoring Composite Material Pressure Vessels with a Fiber-Optic/Microelectronic Sensor System

We discuss the concept of an integrated, fiber-optic/microelectronic distributed sensor system that can monitor composite material pressure vessels for Air Force space systems to provide assessments of the overall health and integrity of the vessel throughout its entire operating history from birth to end of life. The fiber optic component would include either a semiconductor light emitting diode or diode laser and a multiplexed fiber optic sensing network incorporating Bragg grating sensors capable of detecting internal temperature and strain. The microelectronic components include a power source, a pulsed laser driver, time domain data acquisition hardware, a microprocessor, a data storage device, and a communication interface. The sensing system would be incorporated within the composite during its manufacture. The microelectronic data acquisition and logging system would record the environmental conditions to which the vessel has been subjected to during its storage and transit, e.g., the history of thermal excursions, pressure loading data, the occurrence of mechanical impacts, the presence of changing internal strain due to aging, delamination, material decomposition, etc. Data would be maintained din non-volatile memory for subsequent readout through a microcomputer interface.

Klimcak, C.↗
DOE OSTI2021

The ATLAS Fast TracKer system

The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited $\eta$-$\phi$ region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Pattern recognition with parallel associative memory

An examination is conducted of the feasibility of searching targets in aerial photographs by means of a parallel associative memory (PAM) that is based on the nearest-neighbor algorithm; the Hamming distance is used as a measure of closeness, in order to discriminate patterns. Attention has been given to targets typically used for ground-control points. The method developed sorts out approximate target positions where precise localizations are needed, in the course of the data-acquisition process. The majority of control points in different images were correctly identified.

Toth, Charles K.↗
DOE OSTI2018

Testing the possibility of magnetic domain imaging based on circular & linear dichroism using photoemission electron microscopy

In recent years, an increasing number of memory and spintronic devices have been developed exploiting the combination of ferromagnetic (FM) and anti-ferromagnetic (aFM) materials. Consequently, magnetic imaging based on continuous-wave (CW) ultraviolet (UV) (λ = 266nm and longer wavelength) photoemission electron microscopy (PEEM) is gaining considerable attention due to the possibility of determining magnetizations for FM and aFM materials with 10 nm lateral resolution at video rate image acquisition. This PEEM-based approach exploits the polarization-dependent photoemission yield, which is subject to the polarization vector and the FM or aFM magnetization direction. Because of this unique attribute, magnetic imaging using PEEM when coupled to a laser with multiple illumination geometries allows for characterizing in-plane and out-of-plane magnetizations. This concept, however, has not been tested using a deep-UV laser (λ = 213nm), which has a much broader application space than the longer wavelength excitation used in previous reports. The purpose of this project in FY17 was to show the proof-of-concept of magnetic circular dichroism (MCD)-PEEM imaging using a λ = 210nm pulsed laser. Our results demonstrated the feasibility of in-plane and out-of-plane magnetic imaging with the limitations in the lateral resolution, data acquisition time, and signal-to-noise ratio anticipated for using a pulsed laser of moderate power. The project goal for FY18 is to construct the automated polarization-controlled data acquisition, and to establish the new lab facility in anticipation of acquiring a state-of-the-art high-power 213nm CW laser, planned to be installed in FY19. We successfully demonstrate the former by measuring dielectric stacks with polarization-dependent photoemission yield. Extrapolating from our result, we conclude that the capability of PEEM-based magnetic imaging using a CW deep UV laser could be a potential game-changer for scientific investigations and technological developments of magnetic materials and spintronic devices. In addition, polarization controlled PEEM imaging shows the potential for ellipsometry imaging of embedded nanomaterials exploiting their subtle differences in optical constants with respect to their surrounding dielectrics.

36 MATERIALS SCIENCE↗
NASA NTRS1985

Fast Dual Analog-to-Digital Converter

Unit delivers blocks of quadrature data to computer memory. Contains 105 integrated circuit packages in 19 by 3 1/2 inch (48.26 by 8.39 cm) rack mounted drawer with internal force air blower. Intended for synchronous sampling of quadrature pairs of data, samples with minimal skew (about 10 nanoseconds) using video-type high-speed sampling technology. Unit equipped for computer controlled self-testing. Originally developed for planetary radar data-acquisition system.

Wallis, D. E.↗
NASA NTRS1994

VLSI-based Video Event Triggering for Image Data Compression

Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

Williams, Glenn L.↗
NASA NTRS2009

Digital Beamforming Scatterometer

This paper discusses scatterometer measurements collected with multi-mode Digital Beamforming Synthetic Aperture Radar (DBSAR) during the SMAP-VEX 2008 campaign. The 2008 SMAP Validation Experiment was conducted to address a number of specific questions related to the soil moisture retrieval algorithms. SMAP-VEX 2008 consisted on a series of aircraft-based.flights conducted on the Eastern Shore of Maryland and Delaware in the fall of 2008. Several other instruments participated in the campaign including the Passive Active L-Band System (PALS), the Marshall Airborne Polarimetric Imaging Radiometer (MAPIR), and the Global Positioning System Reflectometer (GPSR). This campaign was the first SMAP Validation Experiment. DBSAR is a multimode radar system developed at NASA/Goddard Space Flight Center that combines state-of-the-art radar technologies, on-board processing, and advances in signal processing techniques in order to enable new remote sensing capabilities applicable to Earth science and planetary applications [l]. The instrument can be configured to operate in scatterometer, Synthetic Aperture Radar (SAR), or altimeter mode. The system builds upon the L-band Imaging Scatterometer (LIS) developed as part of the RadSTAR program. The radar is a phased array system designed to fly on the NASA P3 aircraft. The instrument consists of a programmable waveform generator, eight transmit/receive (T/R) channels, a microstrip antenna, and a reconfigurable data acquisition and processor system. Each transmit channel incorporates a digital attenuator, and digital phase shifter that enables amplitude and phase modulation on transmit. The attenuators, phase shifters, and calibration switches are digitally controlled by the radar control card (RCC) on a pulse by pulse basis. The antenna is a corporate fed microstrip patch-array centered at 1.26 GHz with a 20 MHz bandwidth. Although only one feed is used with the present configuration, a provision was made for separate corporate feeds for vertical and horizontal polarization. System upgrades to dual polarization are currently under way. The DBSAR processor is a reconfigurable data acquisition and processor system capable of real-time, high-speed data processing. DBSAR uses an FPGA-based architecture to implement digitally down-conversion, in-phase and quadrature (I/Q) demodulation, and subsequent radar specific algorithms. The core of the processor board consists of an analog-to-digital (AID) section, three Altera Stratix field programmable gate arrays (FPGAs), an ARM microcontroller, several memory devices, and an Ethernet interface. The processor also interfaces with a navigation board consisting of a GPS and a MEMS gyro. The processor has been configured to operate in scatterometer, Synthetic Aperture Radar (SAR), and altimeter modes. All the modes are based on digital beamforming which is a digital process that generates the far-field beam patterns at various scan angles from voltages sampled in the antenna array. This technique allows steering the received beam and controlling its beam-width and side-lobe. Several beamforming techniques can be implemented each characterized by unique strengths and weaknesses, and each applicable to different measurement scenarios. In Scatterometer mode, the radar is capable to.generate a wide beam or scan a narrow beam on transmit, and to steer the received beam on processing while controlling its beamwidth and side-lobe level. Table I lists some important radar characteristics

Rincon, Rafael F.↗
DOE OSTI2018

Scalable Proximity-Based Methods for Large-Scale Analysis of Atom Probe Data

Powered by recent advances in data acquisition technologies, today's state-of-the-art atom probe microscopes yield data sets with sizes ranging from a few million atoms to billions of atoms. Analysis of these atomic data sets within rea-sonable turnaround times is a pressing data analysis challenge for material scientists currently equipped with software systems that do not scale to these massive data sets. Here, we present the shared memory component of a larger ongoing effort to develop a multi-feature data analysis framework capable of analyzing atom probe data of all sizes and scales from desktop multicore machines to large-scale high-performance computing platforms with hybrid (shared and distributed memory) architectures. Our focus here is on a broad class of popular atom probe data analysis methods that rely on core time-consuming k-NN queries. We present a scalable, heuristic algorithm for k-NN queries using three-dimensional range trees. To demonstrate its efficacy, the k-NN algorithm is integrated with two use cases of atom probe data analysis methods and the resulting analysis times are shown to speedup by over 20X on a 32-core Cray XC40 node using workloads up to 8 million atoms, which is already beyond the at-scale capabilities of existing atom probe software. Using this k-NN algorithm, we also introduce a novel parameter estimation method for a class of cluster finding methods, called friends-of-friends (FoF) methods, to completely bypass their expensive pre-processing steps. In each case, we validate the results on a variety of control data sets.

Lu, Hao↗
NASA NTRS2000

Development of a Vehicle Health Monitoring System for the Space Shuttle Solid Rocket Booster Program

During their brief flight, the space shuttle solid rocket boosters (SRBs) experience a severe environment. This environment in most cases is unknown. When the design engineers believe they understand the environments, something new occurs. For example, at water impact several SRBs have sustained noticeable structural damage. The severity of the damage is usually dependent upon the waves that the SRB encounter at splashdown. The space shuttle is presently scheduled to fly until 2030. To support the shuttle flight schedule, the avionics on the SRB's will need to be upgraded. The environments on the different sections of the SRB will need to be defined more completely to properly qualify the avionics for multiple flights. The combination of new avionics systems and unknown flight environments led Marshall Space Flight Center's (MSFC) SRB Project Office to request the Science and Engineering (S&E) Directorate to develop a stand-alone data acquisition system that could collect data from any area of the booster. The Enhanced Data Acquisition System (EDAS) was developed to meet this request. However, the EDAS has some technical drawbacks that needed resolved. To answer the EDAS problems, the SRB Project Office has funded MSFC's Avionics Department to begin investigating a new vehicle health monitoring (VHM) system. The major requirements are the system shall have 64 channels, have programmable sample rates up to 10,000 samples per second, have sufficient memory for a twenty minute flight and not interfere with existing operational flight avionics hardware. This paper will describe the effort to develop a VHM system that can meet the SRB requirements.

Crawford, Kevin↗
DOE OSTI2019

A Scalable Online Monitoring System Based on Elasticsearch for Distributed Data Acquisition in Cms

The part of the CMS Data Acquisition (DAQ) system responsible for data readout and event building is a complex network of interdependent distributed applications. To ensure successful data taking, these programs have to be constantly monitored in order to facilitate the timeliness of necessary corrections in case of any deviation from specified behaviour. A large number of diverse monitoring data samples are periodically collected from multiple sources across the network. Monitoring data are kept in memory for online operations and optionally stored on disk for post-mortem analysis. We present a generic, reusable solution based on an open source NoSQL database, Elasticsearch, which is fully compatible and non-intrusive with respect to the existing system. The motivation is to benefit from an off the-shelf software to facilitate the development, maintenance and support efforts. Elasticsearch provides failover and data redundancy capabilities as well as a programming language independent JSON-over-HTTP interface. The possibility of horizontal scaling matches the requirements of a DAQ monitoring system. The data load from all sources is balanced by redistribution over an Elasticsearch cluster that can be hosted on a computer cloud. In order to achieve the necessary robustness and to validate the scalability of the approach the above monitoring solution currently runs in parallel with an existing in-house developed DAQ monitoring system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1995

Laser-Induced Incandescence Calibration via Gravimetric Sampling

Various beam imaging and/or sheet forming optics delivered light at 1064 nm from a pulsed Nd:YAG laser for use either as a beam of 3 mm radius or as a laser sheet. Imaging measurements were performed with a grated intensified array camera equipped with an ultraviolet f4.5 lens and a 40 mm extension tube. Point measurements were performed using an ultraviolet 250 mm focal length lens to collect and focus the laser induced incandescence (LII) signal into a 1 meter long quartz optical fiber which directed the LII signal to a 1/4 meter monochromator. An aperture preceding the lens restricted the signal collection region to 1 cm along the laser beam at the center of the gravimetric chimney. Signals from the PMT were processed by a boxcar integrator whereas the images were captured digitally using a frame-grabber with 16 MByte of on-board memory. Both 'point' and planar measurements were made with detector gates of 250 ns to minimize possible morphology bias in collection of the LII signal. Additionally, the imaging measurements were performed with broadband spectral collection of the LII signal to maximize the signal and again minimize any potential effects of morphology dependent heating and/or cooling rates. Digital delay generators controlled the firing of he laser, detector gates and data acquisition. Neutral density filters were used for both sets of measurements to maintain signal levels within linear dynamic ranges of the detectors, the range being determined prior to experiments.

VanderWal, R. L.↗
DOE OSTI2022

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Abstract The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive detectors have greatly improved the acquisition speed of EELS spectra. However, the traditional way of core-loss edge recognition is experience based and human labor dependent, which limits the processing speed. So far, the low signal–noise ratio and the low jump ratio of the core-loss edges on the raw EELS spectra have been challenging for the automation of edge recognition. In this work, a convolutional-bidirectional long short-term memory neural network (CNN-BiLSTM) is proposed to automate the detection and elemental identification of core-loss edges from raw spectra. An EELS spectral database is synthesized by using our forward model to assist in the training and validation of the neural network. To make the synthesized spectra resemble the real spectra, we collected a large library of experimentally acquired EELS core edges. In synthesize the training library, the edges are modeled by fitting the multi-Gaussian model to the real edges from experiments, and the noise and instrumental imperfectness are simulated and added. The well-trained CNN-BiLSTM network is tested against both the simulated spectra and real spectra collected from experiments. The high accuracy of the network, 94.9%, proves that, without complicated preprocessing of the raw spectra, the proposed CNN-BiLSTM network achieves the automation of core-loss edge recognition for EELS spectra with high accuracy.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Rule-based mechanisms of learning for intelligent adaptive flight control

How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

Handelman, David A.↗
DOE OSTI2021

Drought legacies mediated by trait trade‐offs in soil microbiomes

Abstract Soil microbiomes play a key role in driving biogeochemical cycles of the Earth system. As drought frequency and intensity increase due to climate change, soil microbes and the processes they control will be impacted. Even after a drought ends, microbiomes and other systems take time to recover and may display a memory of previous climate conditions. Still, the mechanisms involved in these legacy effects remain unclear, making it difficult to predict climate and biogeochemical rates in the future. Here, we used a trait‐based microbiome model (DEMENTpy) to implement trade‐off‐mediated mechanisms that may lead to drought legacy effects on litter decomposition. Trade‐offs were assumed to follow the Y‐A‐S framework that defines three primary life‐history strategies of microorganisms: high growth Yield, resource Acquisition, and Stress tolerance. We represented cellular trade‐offs between osmolytes required for drought tolerance and investment in enzymes involved in litter decomposition. Simulations were run under varying levels of drought severity and dispersal. With high levels of dispersal, no legacy effects were predicted by DEMENTpy following drought. With limited dispersal, severe drought resulted in a persistent legacy of altered community‐level traits and reduced litter decomposition. Moderate drought resulted in a transient legacy that disappeared after two years, consistent with recent empirical observations in Southern California ecosystems. These results imply that greater movement along the trade‐off between enzyme investment and osmolyte production resulted in stronger legacy effects. More generally, factors that shift the position of a microbiome in YAS space may alter the legacy outcome following drought. Our trait‐based modeling study motivates additional empirical measurements to quantify YAS traits and trade‐offs that are needed to make accurate predictions of soil microbiome resilience and functioning. Also, our study illustrates an emerging approach for representing trait trade‐offs in microbiomes and vegetation that dictate ecosystem responses to drought and other environmental perturbations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1978

Contour Detector and Data Acquisition System for the Left Ventricular Outline

A real-time contour detector and data acquisition system is described for an angiographic apparatus having a video scanner for converting an X-ray image of a structure characterized by a change in brightness level compared with its surrounding into video format and displaying the X-ray image in recurring video fields. The real-time contour detector and data acqusition system includes track and hold circuits; a reference level analog computer circuit; an analog compartor; a digital processor; a field memory; and a computer interface.

Reiber, J. H. C.↗
NASA NTRS1989

The KAPTUR environment: An operations concept

This report presents a high-level specification and operations concept for KAPTUR, a development environment based on knowledge acquisition for preservation of tradeoffs and underlying rationales. KAPTUR is intended to do what its name implies: to capture knowledge that is required or generated during the development process, but that is often lost because it is contextual, i.e., it does not appear directly in the end-products of development. Such knowledge includes issues that were raised during development, alternatives that were considered, and the reasons for choosing one alternative over others. Contextual information is usually only maintained as a memory in a developer's mind. As time passes, the memories become more vague and individuals become unavailable, and eventually the knowledge is lost. KAPTUR seeks to mitigate this process of attrition by recording and organizing contextual knowledge as it is generated.

Source record↗
NASA NTRS1994

Sample Acquisition and Instrument Deployment (SAID)

This report details the interim progress for contract NASW-4818, Sample Acquisition and Instrument Deployment (SAID), a robotic system for deploying science instruments and acquiring samples for analysis. The system is a conventional four degree of freedom manipulator 2 meters in length. A baseline design has been achieved through analysis and trade studies. The design considers environmental operating conditions on the surface of Mars, as well as volume constraints on proposed Mars landers. Control issues have also been studied, and simulations of joint and tip movements have been performed. A passively braked shape memory actuator with the ability to measure load has been developed. The wrist also contains a mechanism which locks the lid output to the bucket so that objects can be grasped and released for instrument deployment. The wrist actuator has been tested for operational power and mechanical functionality at Mars environmental conditions. The torque which the actuator can produce has been measured. Also, testing in Mars analogous soils has been performed.

Boyd, Robert C.↗