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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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DOE OSTI2020

Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage

Data acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Collider, the experiments at CERN need to meet challenging requirements to record data with a much higher occupancy in the detectors. The DAQ system will receive and deliver data with a significantly increased trigger rate, one million events per second, and capacity, terabytes of data per second. An effective way to meet these requirements is to decouple real-time data acquisition from event selection. Data fragments can be temporarily stored in a large distributed key-value store. Fragments belonging to the same event can be then queried on demand, by the data selection processes. Implementing such a model relies on a proper combination of emerging technologies, such as persistent memory, NVMe SSDs, scalable networking, and data structures, as well as high performance, scalable software. In this paper, we present DAQDB (Data Acquisition Database) — an open source implementation of this design that was presented earlier, with an extensive evaluation of this approach, from the single node to the distributed performance. Furthermore, we complement our study with a description of the challenges faced and the lessons learned while integrating DAQDB with the existing software framework of the ATLAS experiment.

Abed Abud, Adam↗

DOE OSTI2012

Effect of intranasal manganese administration on neurotransmission and spatial learning in rats

The effect of intranasal manganese chloride (MnCl{sub 2}·4H{sub 2}O) exposure on spatial learning, memory and motor activity was estimated in Morris water maze task in adult rats. Three-month-old male Wistar rats received for 2 weeks MnCl{sub 2}·4H{sub 2}O at two doses the following: 0.2 mg/kg b.w. (Mn0.2) or 0.8 mg/kg b.w. (Mn0.8) per day. Control (Con) and manganese-exposed groups were observed for behavioral performance and learning in water maze. ANOVA for repeated measurements did not show any significant differences in acquisition in the water maze between the groups. However, the results of the probe trial on day 5, exhibited spatial memory deficits following manganese treatment. After completion of the behavioral experiment, the regional brain concentrations of neurotransmitters and their metabolites were determined via HPLC in selected brain regions, i.e. prefrontal cortex, hippocampus and striatum. ANOVA demonstrated significant differences in the content of monoamines and metabolites between the treatment groups compared to the controls. Negative correlations between platform crossings on the previous platform position in Southeast (SE) quadrant during the probe trial and neurotransmitter turnover suggest that impairment of spatial memory and cognitive performance after manganese (Mn) treatment is associated with modulation of the serotonergic, noradrenergic and dopaminergic neurotransmission in the brain. These findings show that intranasally applied Mn can impair spatial memory with significant changes in the tissue level and metabolism of monoamines in several brain regions. -- Highlights: ► Intranasal exposure to manganese in rats impairs spatial memory in the water maze. ► Regional changes in levels of neurotransmitters in the brain have been identified. ► Cognitive disorder correlates with modulation of 5-HT, NA and DA neurotransmission.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Mass Spectrometry Imaging Quick View

MSI QuickView is a software designed to provide a graphical user interface (GUI) for greatly speeding up experimental feedback (visualization and analysis) of mass spectrometry imaging (MSI or IMS) data during data acquisition. Often different software loads the entire data set, i.e., all lines of data into computer memory (RAM). This causes out of memory errors for larger datasets. We solved this in MSI QuickView by reading in the data one line at a time. Only the required information (e.g. the final pixel values for that line of heat map) is maintained in RAM. Interim analysis options include the mean intensity vs. m/z spectrum, intensity vs. time spectrums for up to 6 different m/z values or ranges chosen by the user and heat maps for each line. This assists in validating the usefulness of the particular experiment after scanning the first few lines. In addition, the tool facilitates further processing and analysis of the massive datasets. The user can manually pick different m/z values, time ranges, scroll through the spectra for any line in the data without having to load it in manually, save multiple images, change aspect ratios for the heat maps, and process the heat maps in multiple ways including overlaying images at different m/z values, displaying up to 9 different heat maps, alignment of scans along each line etc. There is no manipulation of the data required by the user to visualize the data.

Carson, JamesP.↗

NASA NTRS2012

NASA Tech Briefs, August 2012

Topics covered include: Mars Science Laboratory Drill; Ultra-Compact Motor Controller; A Reversible Thermally Driven Pump for Use in a Sub-Kelvin Magnetic Refrigerator; Shape Memory Composite Hybrid Hinge; Binding Causes of Printed Wiring Assemblies with Card-Loks; Coring Sample Acquisition Tool; Joining and Assembly of Bulk Metallic Glass Composites Through Capacitive Discharge; 670-GHz Schottky Diode-Based Subharmonic Mixer with CPW Circuits and 70-GHz IF; Self-Nulling Lock-in Detection Electronics for Capacitance Probe Electrometer; Discontinuous Mode Power Supply; Optimal Dynamic Sub-Threshold Technique for Extreme Low Power Consumption for VLSI; Hardware for Accelerating N-Modular Redundant Systems for High-Reliability Computing; Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry; High-Thermal-Conductivity Fabrics; Imidazolium-Based Polymeric Materials as Alkaline Anion-Exchange Fuel Cell Membranes; Electrospun Nanofiber Coating of Fiber Materials: A Composite Toughening Approach; Experimental Modeling of Sterilization Effects for Atmospheric Entry Heating on Microorganisms; Saliva Preservative for Diagnostic Purposes; Hands-Free Transcranial Color Doppler Probe; Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer LogScope; TraceContract; AIRS Maps from Space Processing Software; POSTMAN: Point of Sail Tacking for Maritime Autonomous Navigation; Space Operations Learning Center; OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems; Large Eddy Simulation (LES) of Particle-Laden Temporal Mixing Layers; Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing; Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery; 3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer; Social Networking Adapted for Distributed Scientific Collaboration; General Methodology for Designing Spacecraft Trajectories; Hemispherical Field-of-View Above-Water Surface Imager for Submarines; and Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly.

Source record↗

NASA NTRS2018

Range and Intensity Image-Based Terrain and Vehicle Relative Pose Estimation System

A navigation system includes an image acquisition device for acquiring a range image of a target vehicle, at least one processor, a memory including a target vehicle model and computer readable program code, where the processor and the computer readable program code are configured to cause the navigation system to convert the range image to a point cloud having three dimensions, compute a transform from the target vehicle model to the point cloud, and use the transform to estimate the target vehicle's attitude and position for capturing the target vehicle.

Gill, Nathaniel↗

DOE OSTI2019

Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm

With the development of data-driven techniques, building energy prediction on a district level has attracted increasing attention in recent years for revealing energy use patterns and reduction potentials. However, data acquisition in large building groups is difficult and adjacent buildings also interact with each other. To reduce data cost and incorporate the inter-building impact with the data-driven building energy model, this study proposes a deep learning predictive approach that fuses the building network model with a long short-term memory learning model for district-scale building energy modeling. The building network was constructed based on correlations between the energy use intensity of buildings, which can significantly reduce the computational complexity of the deep learning models for energy dynamic prediction. Five typical building groups with energy use data from 2015 to 2018 on two institutional campuses were selected to perform the validation experiment with TensorFlow. Based on the prediction error assessments, the results suggest that for total building energy use intensity prediction, the proposed model can achieve a mean absolute percentage error of 6.66% and a root mean square error of 0.36 kWh/m 2 , compared to 12.05% and 0.63 kWh/m 2 of the conventional artificial neural network model and to 11.06% and 0.89 kWh/m 2 for the support vector regression model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1971

The automation of the stellar proper motion survey

A microdensitometer, scanning pairs of star plates of identical areas of the sky taken a decade apart, is coupled to a magnetic tape unit through a data acquisition system. This system performs an image density threshold level selection for each plate and a buffer memory system to smooth the data flow as well as analog and digital display controls. The data from the tape are processed later by a large scale high speed computer which reconstructs the scanned images, discovers, measures, and documents stellar proper motions by precise comparison of corresponding areas of the two star plates to detect those images which have moved at least 0.10 seconds annually in the time interval between the exposures.

Newcomb, J. S.↗

NASA NTRS1990

Wave-particle interactions on the FAST satellite

NASA's Fast Auroral Snapshot, or 'FAST' satellite, scheduled for launch in 1993, will investigate the plasma physics of the low altitude auroral zone from a 3500-km apogee polar orbit. FAST will give attention to wave, double-layer, and soliton production processes due to electrons and ions, as well as to wave-wave interactions, and the acceleration of electrons and ions by waves and electric fields. FAST will employ an intelligent data-handling system capacle of data acquisition at rates of up to 1 Mb/sec, in addition to a 1-Gbit solid-state memory. The data need be gathered for only a few minutes during passes through the auroral zone, since the most interesting auroral phenomena occur in such narrow regions as auroral arcs, electrostatic shocks, and superthermal electron bursts.

Temerin, M. A.↗

NASA NTRS2008

A Topographical Lidar System for Terrain-Relative Navigation

An imaging lidar system is being developed for use in navigation, relative to the local terrain. This technology will potentially be used for future spacecraft landing on the Moon. Systems like this one could also be used on Earth for diverse purposes, including mapping terrain, navigating aircraft with respect to terrain and military applications. The system has been field-tested aboard a helicopter in the Mojave Desert. When this system was designed, digitizers with sufficient sampling rate (2 GHz) were only available with very limited memory. Also, it was desirable to limit the amount of data to be transferred between the digitizer and the mass storage between individual frames. One of the novelty design features of this system was to design the system around the limited amount of memory of the digitizer. The system is required to operate over an altitude (distance) range from a few meters to approximately 1 km, but for each scan across the full field of view, the digitizer memory is only able to hold data for an altitude range no more than 100 m. Data acquisition methods in support of the limited 100 m wide altitude range are described.

Liebe, Carl Christian↗

NASA NTRS1986

CID-720 aircraft high-environment flight instrumentation system

The high-environment flight instrumentation system was designed to acquire Langley's structural response data during the full scale transport-controlled impact demonstration test. There was only one opportunity for data acquisition. Thus, a high reliability and crashworthy design approach was implemented. The approach featured multi-level redundancy and a vigorous quality assurance testing program. Complying with an accelerated schedule, the instrumentation system was developed, tested and shipped within 18 months to Dryden Flight Research Facility. The flight instrumentation system consists of two autonomous data systems, DAS #1 and #2, and an excellent checkout subsystem. Each data system is partitioned into four pallets. The system was designed to operate on manned and unmanned flights. There are 176 data channels per data system. These channels are sequentially sampled and encoded into 1 megabit/sec pulse code modulation (PCM) data signal. To increase the probability of success, a special PCM distribution subsystem was developed. This subsystem distributes the PCM signal to two transmitters, one delay memory, and eight recorder tracks. The data on four of these trackes was digitally delayed approximately 300 msec to maximize data acquisition during impact. Therefore each data system's data is redundantly recorded onboard and on the ground. There are two time code generators. Parallel time from each is encoded into both data systems. Serial time from each is redundantly recorded on both onboard recorders. Instrumentation power is independent of aircraft power and self-contained.

Calloway, R. S.↗

NASA NTRS1988

Fast Data Acquisition For Mass Spectrometer

New equipment has speed and capacity to process time-of-flight data. System relies on fast, compact waveform digitizer with 32-k memory coupled to personal computer. With digitizer, system captures all mass peaks on each 25- to 35-microseconds cycle of spectrometer.

Lincoln, K. A.↗

NASA NTRS1986

Multipurpose aircraft monitoring with a smart recorder

This paper describes a microprocessor-based flight recorder the 'Smart Recorder' - which was developed and installed on a King Air aircraft used for commercial charter service. The recorder is used as a research tool for developing monitoring strategies and processing algorithms to: (1) characterize the typical flight environment encountered by the host aircraft, (2) develop technology for automated engine trend monitoring, and (3) implement a crash recording capability. Initially the recorder was used as an adaptive data acquisition system, monitoring engine sensors and flight instruments and then modifying its data acquisition in response to the perceived aircraft situation. Data collected in this manner were stored in a removable bubble memory and subsequently analyzed in the laboratory. Later, on-board processing was implemented to better utilize the available storage capacity.

White, J. H.↗

NASA NTRS1988

KAM (Knowledge Acquisition Module): A tool to simplify the knowledge acquisition process

Analysts, knowledge engineers and information specialists are faced with increasing volumes of time-sensitive data in text form, either as free text or highly structured text records. Rapid access to the relevant data in these sources is essential. However, due to the volume and organization of the contents, and limitations of human memory and association, frequently: (1) important information is not located in time; (2) reams of irrelevant data are searched; and (3) interesting or critical associations are missed due to physical or temporal gaps involved in working with large files. The Knowledge Acquisition Module (KAM) is a microcomputer-based expert system designed to assist knowledge engineers, analysts, and other specialists in extracting useful knowledge from large volumes of digitized text and text-based files. KAM formulates non-explicit, ambiguous, or vague relations, rules, and facts into a manageable and consistent formal code. A library of system rules or heuristics is maintained to control the extraction of rules, relations, assertions, and other patterns from the text. These heuristics can be added, deleted or customized by the user. The user can further control the extraction process with optional topic specifications. This allows the user to cluster extracts based on specific topics. Because KAM formalizes diverse knowledge, it can be used by a variety of expert systems and automated reasoning applications. KAM can also perform important roles in computer-assisted training and skill development. Current research efforts include the applicability of neural networks to aid in the extraction process and the conversion of these extracts into standard formats.

Gettig, Gary A.↗

NASA NTRS1989

Advanced Software Development Workstation Project

The Advanced Software Development Workstation Project, funded by Johnson Space Center, is investigating knowledge-based techniques for software reuse in NASA software development projects. Two prototypes have been demonstrated and a third is now in development. The approach is to build a foundation that provides passive reuse support, add a layer that uses domain-independent programming knowledge, add a layer that supports the acquisition of domain-specific programming knowledge to provide active support, and enhance maintainability and modifiability through an object-oriented approach. The development of new application software would use specification-by-reformulation, based on a cognitive theory of retrieval from very long-term memory in humans, and using an Ada code library and an object base. Current tasks include enhancements to the knowledge representation of Ada packages and abstract data types, extensions to support Ada package instantiation knowledge acquisition, integration with Ada compilers and relational databases, enhancements to the graphical user interface, and demonstration of the system with a NASA contractor-developed trajectory simulation package. Future work will focus on investigating issues involving scale-up and integration.

Lee, Daniel↗

NASA NTRS2012

Development of an Integrated Data Acquisition System for a Small Flight Probe

In support of the SPRITE concept, an integrated data acquisition system has been developed and fabricated for preliminary testing. The data acquisition system has been designed to condition traditional thermal protection system sensors, store their data to an on-board memory card, and in parallel, telemeter to an external system. In the fall of 2010, this system was integrated into a 14 in. diameter, 45 degree sphere cone probe instrumented with thermal protection system sensors. This system was then tested at the NASA Ames Research Center Aerodynamic Heating Facility's arc jet at approximately 170 W/sq. cm. The first test in December 2010 highlighted hardware design issues that were redesigned and implemented leading to a successful test in February 2011.

Swanson, Gregory T.↗

NASA NTRS1991

Software manual for operating particle displacement tracking data acquisition and reduction system

The software manual is presented. The necessary steps required to record, analyze, and reduce Particle Image Velocimetry (PIV) data using the Particle Displacement Tracking (PDT) technique are described. The new PDT system is an all electronic technique employing a CCD video camera and a large memory buffer frame-grabber board to record low velocity (less than or equal to 20 cm/s) flows. Using a simple encoding scheme, a time sequence of single exposure images are time coded into a single image and then processed to track particle displacements and determine 2-D velocity vectors. All the PDT data acquisition, analysis, and data reduction software is written to run on an 80386 PC.

Wernet, Mark P.↗

NASA NTRS1988

Data-Acquisition System For Rotor Vibrations

New system trades hardware for software to reduce cost. Composite train of interspersed blade-detection pulses produced by gates at four probe ports on data-acquisition board. Pulses latch count from high-speed wraparound clock counter and initiate writing of count onto current address of memory. Result: time corresponding to each blade passage stamped into memory.

Posta, Stephen J.↗

NASA NTRS1991

Acquisition and improvement of human motor skills: Learning through observation and practice

Skilled movement is an integral part of the human existence. A better understanding of motor skills and their development is a prerequisite to the construction of truly flexible intelligent agents. We present MAEANDER, a computational model of human motor behavior, that uniformly addresses both the acquisition of skills through observation and the improvement of skills through practice. MAEANDER consists of a sensory-effector interface, a memory of movements, and a set of performance and learning mechanisms that let it recognize and generate motor skills. The system initially acquires such skills by observing movements performed by another agent and constructing a concept hierarchy. Given a stored motor skill in memory, MAEANDER will cause an effector to behave appropriately. All learning involves changing the hierarchical memory of skill concepts to more closely correspond to either observed experience or to desired behaviors. We evaluated MAEANDER empirically with respect to how well it acquires and improves both artificial movement types and handwritten script letters from the alphabet. We also evaluate MAEANDER as a psychological model by comparing its behavior to robust phenomena in humans and by considering the richness of the predictions it makes.

Iba, Wayne↗