Search NASA⌕ Search

SEARCH · Search NASA

Results for “Computing, Instrumentation”

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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

ICESat-2 Precision Orbit Determination

The ICESat-2 Precision Orbit Determination (POD) system computes the precise position of the laser altimeter instrument in inertial space, a measurement necessary for accurate geolocation of individual photon surface returns. ICESat-2 POD solutions are generated by the reduction of Global Positioning System (GPS) double-difference carrier phase observable residuals with NASA Goddard Space Flight Center's GEODYN software. Independent satellite laser ranging (SLR) measurements are withheld from the POD solutions and used as an independent arbiter of POD performance. Measurement model updates in the form of estimated GPS antenna phase center and satellite laser ranging retro-reflector tracking point offset vectors as well as a GPS antenna phase center variation map have led to significant improvement in POD performance. GPS residual analysis and orbit precision analysis show no significant anomalous temporal or geographic POD performance issues. The independent SLR residual analysis indicates that POD solutions have achieved a radial orbit accuracy just below 1.5 cm, thus exceeding the mission radial orbit accuracy requirement of 3.0 cm by more than a factor of 2. Future POD processing updates have been identified and will lead to even further improvements in POD performance.

T. C. Thomas↗
NASA NTRSDate not supplied

Simulations of OSIRIS-REx Atmospheric Entry for Comparisons with Data from the Imaging Campaign

Results from pre-flight flow and radiation simulations for the OSIRIS-REx Sample Return Capsule along a candidate entry trajectory are presented. These results are from pre-flight simulations in support of the observation campaign. Details of the methodology for computing temporal variation of spectral irradiance on an instrument onboard an aerial observation platform are presented along with a sampling of results. An attempt is made to use the methodology presented to assess the level of elemental sodium in the shock layer. The final paper will be based on the actual flight trajectory and will include comparisons of predictions with calibrated spectrometric data.

Spectrometric Imaging↗
DOE OSTI2011

Fast Simulation of Electromagnetic Showers in the ATLAS Calorimeter: Frozen Showers

One of the most time consuming process simulating pp interactions in the ATLAS detector at LHC is the simulation of electromagnetic showers in the calorimeter. In order to speed up the event simulation several parametrisation methods are available in ATLAS. In this paper we present a short description of a frozen shower technique, together with some recent benchmarks and comparison with full simulation. An expected high rate of proton-proton collisions in ATLAS detector at LHC requires large samples of simulated events (Monte Carlo) to study various physics processes. A detailed simulation of particle reactions ('full simulation') in the ATLAS detector is based on GEANT4 and is very accurate. However, due to complexity of the detector, high particle multiplicity and GEANT4 itself, the average CPU time spend to simulate typical QCD event in pp collision is 20 or more minutes for modern computers. During detector simulation the largest time is spend in the calorimeters (up to 70%) most of which is required for electromagnetic particles in the electromagnetic (EM) part of the calorimeters. This is the motivation for fast simulation approaches which reduce the simulation time without affecting the accuracy. Several of fast simulation methods available within the ATLAS simulation framework (standard Athena based simulation program) are discussed here with the focus on the novel frozen shower library (FS) technique. The results obtained with FS are presented here as well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Computerized method and system for designing an aerodynamic focusing lens stack

A computerized method and system for designing an aerodynamic focusing lens stack, using input from a designer related to, for example, particle size range to be considered, characteristics of the gas to be flowed through the system, the upstream temperature and pressure at the top of a first focusing lens, the flow rate through the aerodynamic focusing lens stack equivalent at atmosphere pressure; and a Stokes number range. Based on the design parameters, the method and system determines the total number of focusing lenses and their respective orifice diameters required to focus the particle size range to be considered, by first calculating for the orifice diameter of the first focusing lens in the Stokes formula, and then using that value to determine, in iterative fashion, intermediate flow values which are themselves used to determine the orifice diameters of each succeeding focusing lens in the stack design, with the results being output to a designer. In addition, the Reynolds numbers associated with each focusing lens as well as exit nozzle size may also be determined to enhance the stack design.

47 OTHER INSTRUMENTATION↗
DOE OSTI2011

Arachne - A web-based event viewer for MINERvA

Neutrino interaction events in the MINERvA detector are visually represented with a web-based tool called Arachne. Data are retrieved from a central server via AJAX, and client-side JavaScript draws images into the user's browser window using the draft HTML 5 standard. These technologies allow neutrino interactions to be viewed by anyone with a web browser, allowing for easy hand-scanning of particle interactions. Arachne has been used in MINERvA to evaluate neutrino data in a prototype detector, to tune reconstruction algorithms, and for public outreach and education.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2010

Improving image segmentation by learning region affinities

We utilize the context information of other regions in hierarchical image segmentation to learn new regions affinities. It is well known that a single choice of quantization of an image space is highly unlikely to be a common optimal quantization level for all categories. Each level of quantization has its own benefits. Therefore, we utilize the hierarchical information among different quantizations as well as spatial proximity of their regions. The proposed affinity learning takes into account higher order relations among image regions, both local and long range relations, making it robust to instabilities and errors of the original, pairwise region affinities. Once the learnt affinities are obtained, we use a standard image segmentation algorithm to get the final segmentation. Moreover, the learnt affinities can be naturally unutilized in interactive segmentation. Experimental results on Berkeley Segmentation Dataset and MSRC Object Recognition Dataset are comparable and in some aspects better than the state-of-art methods.

47 OTHER INSTRUMENTATION↗
DOE OSTI2010

Hierarchical image segmentation for learning object priors

The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Results of First Outdoor Comparison Between Absolute Cavity Pyrgeometer (ACP) and Infrared Integrating Sphere (IRIS) Radiometer at PMOD (Presentation)

The ACP and IRIS are developed to establish a world reference for calibrating pyrgeometers with traceability to SI units. The two radiometers are unwindowed with negligible spectral dependence, and traceable to SI units through the temperature scale (ITS-90). The first outdoor comparison between the two designs was held from January 28 to February 8, 2013 at the Physikalisch-Metorologisches Observatorium Davos (PMOD). The difference between the irradiance measured by ACP and that of IRIS was within 1 W/m2. A difference of 5 W/m2 was observed between the irradiance measured by ACP&IRIS and that of the interim World Infrared Standard Group (WISG).

14 SOLAR ENERGY↗
DOE OSTI2015

Methods for synchronizing a countdown routine of a timer key and electronic device

A timer key relating to monitoring a countdown time of a countdown routine of an electronic device is disclosed. The timer key comprises a processor configured to respond to a countdown time associated with operation of the electronic device, a display operably coupled with the processor, and a housing configured to house at least the processor. The housing has an associated structure configured to engage with the electronic device to share the countdown time between the electronic device and the timer key. The processor is configured to begin a countdown routine based at least in part on the countdown time, wherein the countdown routine is at least substantially synchronized with a countdown routine of the electronic device when the timer key is removed from the electronic device. A system and method for synchronizing countdown routines of a timer key and an electronic device are also disclosed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Imaging, object detection, and change detection with a polarized multistatic GPR array

A polarized detection system performs imaging, object detection, and change detection factoring in the orientation of an object relative to the orientation of transceivers. The polarized detection system may operate on one of several modes of operation based on whether the imaging, object detection, or change detection is performed separately for each transceiver orientation. In combined change mode, the polarized detection system performs imaging, object detection, and change detection separately for each transceiver orientation, and then combines changes across polarizations. In combined object mode, the polarized detection system performs imaging and object detection separately for each transceiver orientation, and then combines objects across polarizations and performs change detection on the result. In combined image mode, the polarized detection system performs imaging separately for each transceiver orientation, and then combines images across polarizations and performs object detection followed by change detection on the result.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Point pattern match-based change detection in a constellation of previously detected objects

A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Convergence and Commercial Momentum - Industrial Internet of Things Evolution

Industrial instrumentation and sensors are purpose-built for applications. Rugged and proven for field applications in harsh environments, such as on an oil platform or in a copper mine 5,000-feet below ground, these instruments require reliability and performance. Before the turn of the millennium, industrial technology-and information technology (IT) in particular-drove these systems, and they often exceeded the abilities of consumer products. However, as we stand today, commercial Internet of Things (IoT) technology has advanced rapidly, with industrial control systems lagging in intelligence and features. Experienced owner-operators of industrial facilities recognize the buzz surrounding the Industrial Internet of Things (IIoT) but often shun the notion of consumer-grade devices being installed and integrated into an operational control system. During the International Society of Automation (ISA) Process Control and Safety Forum (PCS) in Houston, Texas, in November 2016, ISA’s Communication Division convened a panel to focus on IIoT. Experienced industrial and control engineers on the panel expressed concerns and reservations with IIoT. Whereas some acknowledged an interest in the topic, others did not recognize it as an inevitable part of the industrial controls landscape. Granted, IIoT is still mostly a vision in the instrumentation and automation landscape; however, its place on stage is coming into view. During the opening session of PCS 2016, ISA President Jim Keaveney rhetorically asked the audience if IoT had peaked and also wondered if “cyber” would be the next area for innovation. This paper will explore the nexus of “domestic” IoT and how product evolution will drive its development toward that of IIoT.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

47 OTHER INSTRUMENTATION↗