Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “parallel sensing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

A Brief Overview of Relevant Silicon Carbide Electronics and Sensor Development for Long Duration Venus Surface Exploration

This presentation concentrates on the potential of long duration Venus surface missions, and the role of Silicon Carbide (SiC) electronics and sensor advancements in such exploration. For example, SiC integrated circuit (IC) electronics have matured to a state where a simple long-life scientific probe is feasible for extended Venus surface operations. These electronics have been demonstrated for more than a year at 500˚C, and 60 days in high-fidelity simulated Venus surface conditions [1-2]. Further, high temperature chemical sensing technology, including SiC-based gas sensors, integrated with SiC electronics can enable future exploration of the Venus surface atmosphere [3]. Continued maturation of these high temperature electronics and sensors has been part of the Long-Lived In-Situ Solar System Explorer (LLISSE) project to provide an operational system for in situ exploration of the Venus surface up to 60 days [4]. A key focus of this work includes increasing the complexity and decreasing the power consumption of the ICs which will pave the way to enhanced capabilities, such as long-duration Venus seismic measurements and other mission capabilities currently under development. This is in parallel to work expanding the capabilities of the sensor technology to provide science measurements on the Venus surface. This presentation will give an overview of possible extended duration Venus surface exploration and some of the SiC-based technologies that can enable this exploration.

high temperature Venus surface electronics sensors↗
NASA NTRS1991

Monte-Carlo methods make Dempster-Shafer formalism feasible

One of the main obstacles to the applications of Dempster-Shafer formalism is its computational complexity. If we combine m different pieces of knowledge, then in general case we have to perform up to 2(sup m) computational steps, which for large m is infeasible. For several important cases algorithms with smaller running time were proposed. We prove, however, that if we want to compute the belief bel(Q) in any given query Q, then exponential time is inevitable. It is still inevitable, if we want to compute bel(Q) with given precision epsilon. This restriction corresponds to the natural idea that since initial masses are known only approximately, there is no sense in trying to compute bel(Q) precisely. A further idea is that there is always some doubt in the whole knowledge, so there is always a probability p(sub o) that the expert's knowledge is wrong. In view of that it is sufficient to have an algorithm that gives a correct answer a probability greater than 1-p(sub o). If we use the original Dempster's combination rule, this possibility diminishes the running time, but still leaves the problem infeasible in the general case. We show that for the alternative combination rules proposed by Smets and Yager feasible methods exist. We also show how these methods can be parallelized, and what parallelization model fits this problem best.

Kreinovich, Vladik YA.↗
NASA NTRS2015

Biomimetic Fly Eye Sensor for Real-Time Target Tracking

The project objective is to design, build, and demonstrate a biomimetic (inspired by biology) smart sensor based on the common house fly eye for real-time target tracking in three dimensions (3-D). The sensor makes use of revolutionary optical sensor design resulting in significantly improved motion detection capabilities when compared with conventional optical sensors. The design is motivated by the parallel nature of the flys vision system and its demonstrated hyperacuity or precision of visual localization beyond the conventional resolution limit. This means that the sensor is able to accurately detect very fast motion and small changes in motion. The analog architecture of the sensor allows for real-time solution at adjustable bandwidths depending on the application. The low cost, exceptionally lightweight, small form factor, low power requirements, and low computation requirements of the sensor make it ideally suited to many aeronautics applications that have limitations on weight, power, and processing time. The sensor is modular and can be easily adapted in scale and manufactured for a wide variety of sensing applications. Advanced target tracking algorithms will be developed to allow the sensor to track a target in 3-D. These algorithms will be implemented in the smart sensors hardware to enable real-time target tracking.

wing position measurement system↗
DOE OSTI2023

Multimodal microscopy of extended defects in β-Ga 2 O 3 (010) EFG crystals

Beta-phase gallium oxide (β-Ga 2 O 3 ) has attracted attention in recent years as a potentially low cost, large area substrate and active layer material for high power, high temperature power electronics and sensing devices. However, growth of β-Ga 2 O 3 crystals is complicated by easily activated (100) and (001) cleavage planes, the presence of low angle grain boundaries (LAGBs) and twins, and the potential formation of polycrystalline grains. In this study, β-Ga 2 O 3 crystals were grown by the edge-defined film-fed growth technique with an (010) principal face. Two crystals with apparently randomly formed high angle grain boundaries (HAGBs) were selected and analyzed by electron backscatter diffraction, electron channeling contrast imaging, and cathodoluminescence to investigate the nature of the LAGBs and the source of the HAGB formation. It was discovered that planar LAGBs lying parallel to the (010) plane exist in the region immediately preceding the start of an HAGB. Increased misorientation across the LAGB was observed, approaching the initiation of a new grain. We present multimodal microscopy characterization, correlating misorientation and variation in optoelectronic properties with LAGBs and the associated dislocations.

14 SOLAR ENERGY↗
DOE OSTI2017

Test Methodologies for Hydrogen Sensor Performance Assessment: Chamber vs. Flow Through Test Apparatus: Preprint

Certification of hydrogen sensors to standards often prescribes using large-volume test chambers [1, 2]. However, feedback from stakeholders such as sensor manufacturers and end-users indicate that chamber test methods are often viewed as too slow and expensive for routine assessment. Flow through test methods potentially are an efficient, cost-effective alternative for sensor performance assessment. A large number of sensors can be simultaneously tested, in series or in parallel, with an appropriate flow through test fixture. The recent development of sensors with response times of less than 1s mandates improvements in equipment and methodology to properly capture the performance of this new generation of fast sensors; flow methods are a viable approach for accurate response and recovery time determinations, but there are potential drawbacks. According to ISO 26142 [1], flow through test methods may not properly simulate ambient applications. In chamber test methods, gas transport to the sensor can be dominated by diffusion which is viewed by some users as mimicking deployment in rooms and other confined spaces. Alternatively, in flow through methods, forced flow transports the gas to the sensing element. The advective flow dynamics may induce changes in the sensor behaviour relative to the quasi-quiescent condition that may prevail in chamber test methods. One goal of the current activity in the JRC and NREL sensor laboratories [3, 4] is to develop a validated flow through apparatus and methods for hydrogen sensor performance testing. In addition to minimizing the impact on sensor behaviour induced by differences in flow dynamics, challenges associated with flow through methods include the ability to control environmental parameters (humidity, pressure and temperature) during the test and changes in the test gas composition induced by chemical reactions with upstream sensors. Guidelines on flow through test apparatus design and protocols for the evaluation of hydrogen sensor performance are being developed. Various commercial sensor platforms (e.g., thermal conductivity, catalytic and metal semiconductor) were used to demonstrate the advantages and issues with the flow through methodology.

14 SOLAR ENERGY↗
DOE OSTI2016

A performance model for the communication in fast multipole methods on high-performance computing platforms

Exascale systems are predicted to have approximately 1 billion cores, assuming gigahertz cores. Limitations on affordable network topologies for distributed memory systems of such massive scale bring new challenges to the currently dominant parallel programing model. Currently, there are many efforts to evaluate the hardware and software bottlenecks of exascale designs. It is therefore of interest to model application performance and to understand what changes need to be made to ensure extrapolated scalability. The fast multipole method (FMM) was originally developed for accelerating N-body problems in astrophysics and molecular dynamics but has recently been extended to a wider range of problems. Its high arithmetic intensity combined with its linear complexity and asynchronous communication patterns make it a promising algorithm for exascale systems. In this paper, we discuss the challenges for FMM on current parallel computers and future exascale architectures, with a focus on internode communication. We focus on the communication part only; the efficiency of the computational kernels are beyond the scope of the present study. We develop a performance model that considers the communication patterns of the FMM and observe a good match between our model and the actual communication time on four high-performance computing (HPC) systems, when latency, bandwidth, network topology, and multicore penalties are all taken into account. To our knowledge, this is the first formal characterization of internode communication in FMM that validates the model against actual measurements of communication time. The ultimate communication model is predictive in an absolute sense; however, on complex systems, this objective is often out of reach or of a difficulty out of proportion to its benefit when there exists a simpler model that is inexpensive and sufficient to guide coding decisions leading to improved scaling. The current model provides such guidance.

Computer Science↗
NASA NTRS2001

Multimodal Neuroelectric Interface Development

This project aims to improve performance of NASA missions by developing multimodal neuroelectric technologies for augmented human-system interaction. Neuroelectric technologies will add completely new modes of interaction that operate in parallel with keyboards, speech, or other manual controls, thereby increasing the bandwidth of human-system interaction. We recently demonstrated the feasibility of real-time electromyographic (EMG) pattern recognition for a direct neuroelectric human-computer interface. We recorded EMG signals from an elastic sleeve with dry electrodes, while a human subject performed a range of discrete gestures. A machine-teaming algorithm was trained to recognize the EMG patterns associated with the gestures and map them to control signals. Successful applications now include piloting two Class 4 aircraft simulations (F-15 and 757) and entering data with a "virtual" numeric keyboard. Current research focuses on on-line adaptation of EMG sensing and processing and recognition of continuous gestures. We are also extending this on-line pattern recognition methodology to electroencephalographic (EEG) signals. This will allow us to bypass muscle activity and draw control signals directly from the human brain. Our system can reliably detect P-rhythm (a periodic EEG signal from motor cortex in the 10 Hz range) with a lightweight headset containing saline-soaked sponge electrodes. The data show that EEG p-rhythm can be modulated by real and imaginary motions. Current research focuses on using biofeedback to train of human subjects to modulate EEG rhythms on demand, and to examine interactions of EEG-based control with EMG-based and manual control. Viewgraphs on these neuroelectric technologies are also included.

Trejo, Leonard J.↗
NASA NTRS1996

Magnetospheric Atmospheric X-ray Imaging Experiment (MAXIE)

This report summarizes the activities sponsored by the Office of Naval Research for the Magnetospheric Atmospheric X-ray Imaging Experiment (MAXIE). The MAXIE instrument was developed as a joint activity of Lockheed, The Aerospace Corporation, and the University of Bergen, Norway. Lockheed was responsible for the overall management of the program, interfacing with the appropriate government agencies, the overall electrical and mechanical design, flight software, environmental testing, spacecraft integration activities, on orbit checkout, and data processing activities. The Magnetospheric Atmospheric X-ray Imaging Experiment (MAXIE), the ONR 401 experiment, is the first in a new class of satellite-borne remote sensing instruments. The primary innovation is the ability to obtain rapid, sequential, images with high sensitivity of the earth's X ray aurora from a low altitude polar orbiting satellite. These images can be used to identify dynamic temporal variations in the three-dimensional (energy and position) distribution of electron precipitation into the atmosphere. MAXIE was launched on the TIROS NOAA-13 satellite on 9 August 1993. The experiment performed well during its turn-on sequence; however, the spacecraft bus failed on 21 August 1993. New spacebased technologies successfully used in MAXIE were mixed-mode ASIC microcircuits, a zero torque scanning system with associated viscoelastic damping, a paraffin stow release mechanism, a parallel integrating PHA processor, a low noise Si(Li) sensor telescope, and an advanced thermal cooling system. MAXIE's on orbit operation, control of penetrating particle backgrounds, and scientific data indicated good overall performance.

Imhof, W. L.↗
DOE OSTI2016

Quantum critical quasiparticle scattering within the superconducting state of CeCoIn 5

Here, the thermal conductivity κ of the heavy-fermion metal CeCoIn 5 was measured in the normal and superconducting states as a function of temperature T and magnetic field H, for a current and field parallel to the [100] direction. Inside the superconducting state, when the field is lower than the upper critical field H c2 , κ/T is found to increase as T→0, just as in a metal and in contrast to the behavior of all known superconductors. This is due to unpaired electrons on part of the Fermi surface, which dominate the transport above a certain field. The evolution of κ/T with field reveals that the electron-electron scattering (or transport mass m*) of those unpaired electrons diverges as H→H c2 from below, in the same way that it does in the normal state as H→H c2 from above. This shows that the unpaired electrons sense the proximity of the field-tuned quantum critical point of CeCoIn 5 at H*=H c2 even from inside the superconducting state. In conclusion, the fact that the quantum critical scattering of the unpaired electrons is much weaker than the average scattering of all electrons in the normal state reveals a k-space correlation between the strength of pairing and the strength of scattering, pointing to a common mechanism, presumably antiferromagnetic fluctuations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1934

Aerodynamic rolling and yawing moments produced by floating wing-tip ailerons, as measured by spinning balance

The investigation described in this report was made to determine the effectiveness of floating wing-tip ailerons as an airplane control in the spin. In these tests the ailerons, not being balanced, were set parallel to the axis of rotation, which is probably very nearly the attitude that balanced floating ailerons would assume in a spin. The tests were made with the spinning balance in the N.A.C.A. 5-foot vertical tunnel. The model was tested with and without the ailerons in 12 spinning attitudes chosen to cover the probable spinning range. Rolling- and yawing-moment coefficients are given as measured for the model with and without the ailerons, and computed values are given for the ailerons alone. The addition of floating wing-tip ailerons to the model doubled the rolling-moment coefficient and increased the yawing-moment coefficient by 0.05 and more. Both moments were in a sense to oppose the spin.

Bamber, Millard J↗
NASA NTRS1997

A Low-Power High-Speed Smart Sensor Design for Space Exploration Missions

A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.

Fang, Wai-Chi↗
NASA NTRS1994

System and process for detecting and monitoring surface defects

A system and process for detecting and monitoring defects in large surfaces such as the field joints of the container segments of a space shuttle booster motor. Beams of semi-collimated light from three non-parallel fiber optic light panels are directed at a region of the surface at non-normal angles of expected incidence. A video camera gathers some portion of the light that is reflected at an angle other than the angle of expected reflectance, and generates signals which are analyzed to discern defects in the surface. The analysis may be performed by visual inspection of an image on a video monitor, or by inspection of filtered or otherwise processed images. In one alternative embodiment, successive predetermined regions of the surface are aligned with the light source before illumination, thereby permitting efficient detection of defects in a large surface. Such alignment is performed by using a line scan gauge to sense the light which passes through an aperture in the surface. In another embodiment a digital map of the surface is created, thereby permitting the maintenance of records detailing changes in the location or size of defects as the container segment is refurbished and re-used. The defect detection apparatus may also be advantageously mounted on a fixture which engages the edge of a container segment.

Mueller, Mark K.↗
DOE OSTI2019

Camellia: A Rapid Development Framework for Finite Element Solvers

We report the discontinuous Petrov–Galerkin (DPG) methodology of Demkowicz and Gopalakrishnan guarantees the optimality of the finite element solution in a user-controllable energy norm, and provides several features supporting adaptive schemes. The approach provides stability automatically; there is no need for carefully derived numerical fluxes (as in DG schemes) or for mesh-dependent stabilization terms (as in stabilized methods). In this paper, we focus on features of Camellia that facilitate implementation of new DPG formulations; chief among these is a rich set of features in support of symbolic manipulation, which allow, e.g., bilinear formulations in the code to appear much as they would on paper. Many of these features are general in the sense that they can also be used in the implementation of other finite element formulations. In fact, because DPG’s requirements are essentially a superset of those of other finite element methods, Camellia provides built-in support for most common methods. We believe, however, that the combination of an essentially “hands-free” finite element methodology as found in DPG with the rapid development features of Camellia are particularly winsome, so we focus on use cases in this class. In addition to the symbolic manipulation features mentioned above, Camellia offers support for one-irregular adaptive meshes in 1D, 2D, 3D, and space-time. It provides a geometric multigrid preconditioner particularly suited for DPG problems, and supports distributed parallel execution using MPI. For its load balancing and distributed data structures, Camellia relies on packages from the Trilinos project, which simplifies interfacing with other computational science packages. Camellia also allows loading of standard mesh formats through an interface with the MOAB package. Camellia includes support for static condensation to eliminate element-interior degrees of freedom locally, usually resulting in substantial reduction of the cost of the global problem. Finally, we include a discussion of the variational formulations built into Camellia, with references to those formulations in the literature, as well as an MPI performance study.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Searching for patterns in remote sensing image databases using neural networks

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Paola, Justin D.↗
NASA NTRSDate not supplied

Laser Absorption Spectroscopy Measurements of Post-Shock Non-Equilibrium Species in the NASA Ames Electric Arc Shock Tube

The NASA Ames Electric Arc Shock Tube (EAST) is a unique facility capable of generating high enthalpy, shock-heated impulse gas flows representative of the kinetic and radiative conditions encountered by atmospheric entry vehicles. The facility maintains a successful history with emission spectroscopy, providing measurements of absolute radiance upon which various validation studies are anchored. The central objective of this work is to develop a comprehensive tunable diode laser absorption spectroscopy (TDLAS) sensing capability to provide complementary experimental insights to existing emission techniques. More specifically, a fast-scanning TDLAS-based diagnostic targeting the cyano radical (CN) in the near-infrared(near-IR) near 926.6 nm is employed in mixtures of 2.2% CH4in N2by mole for a sweep of incident shock velocities ranging 3.0-5.5 km/s and fill pressures 0.3-1.15 Torr. Laser scan rates up to 500 kHz probe multiple absorption features to provide quantitative measurements of temperature and species number density profiles behind the incident shock. In all instances, the temperature trend is consistent between emission-inferred and TDLAS-inferred measurements. However, at the lower-velocity conditions, there is an appreciable offset between the Data Parallel Line Relaxation Code (DPLR) simulation and experimental measurements. A similar behavior is observed in number density profiles, with emission measurements providing inferences of the CN(B) and CN(A) state, while TDLAS measurements provide an additional inference of the CN(X) state. In the fast-scanned experiments, measurement inferred number densities suggest a much faster production of CN at early times than captured by the model. This discrepancy motivates ongoing, additional spectroscopic and kinetics CN experiments to resolve the accuracy of modeling assumptions.

Efaine Chang↗
NASA NTRS1987

Synthetic aperture radar signal processing on the MPP

Satellite-borne Synthetic Aperture Radars (SAR) sense areas of several thousand square kilometers in seconds and transmit phase history signal data several tens of megabits per second. The Shuttle Imaging Radar-B (SIR-B) has a variable swath of 20 to 50 km and acquired data over 100 kms along track in about 13 seconds. With the simplification of separability of the reference function, the processing still requires considerable resources; high speed I/O, large memory and fast computation. Processing systems with regular hardware take hours to process one Seasat image and about one hour for a SIR-B image. Bringing this processing time closer to acquisition times requires an end-to-end system solution. For the purpose of demonstration, software was implemented on the present Massively Parallel Processor (MPP) configuration for processing Seasat and SIR-B data. The software takes advantage of the high processing speed offered by the MPP, the large Staging Buffer, and the high speed I/O between the MPP array unit and the Staging Buffer. It was found that with unoptimized Parallel Pascal code, the processing time on the MPP for a 4096 x 4096 sample subset of signal data ranges between 18 and 30.2 seconds depending on options.

Ramapriyan, H. K.↗
NASA NTRS2019

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗
DOE OSTI2021

The effect of a transducer’s spatial averaging on an elastodynamic guided wave’s wavenumber spectrum

Elastodynamic guided waves propagate in an elastic solid which makes it difficult, if not impractical, to place a receiving transducer in the direct path of the propagating wave (as one would for an acoustic wave in a fluid medium). Thus, to account for this, receiving transducers are often placed on the surface of the solid waveguide such that the transducer surface is parallel to the wave propagation direction. This transducer orientation introduces spatial averaging, which causes the received signal to have an altered signal amplitude and mode bias. We investigate both of these effects and present a simple model from which we derive a scaling-ratio expression that describes the effects of spatial averaging. Furthermore, we then test its performance using finite-element simulations that incorporate “real-world” assumptions (e.g., transient waves, piezoelectric effects, etc.). The results from the simulations demonstrate that the scaling-ratio can characterize the effects resulting from spatial averaging. The scaling-ratio expression will be particularly useful when designing experiments involving high frequency (small wavelength) guided waves. Lastly, the proposed scaling-ratio expression could be applied to other sensing methods, like Laser Doppler Vibrometry (LDV) or piezoelectric waveguides with inter-digitated transducers, because of its generality. However, the authors are careful to note that the scaling-ratio expression is not intended as a replacement of multi-physics analysis or good experimental design, and the effects of spatial averaging should be avoided whenever possible.

2DFFT↗