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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

A Survey of Logic Formalisms to Support Mishap Analysis

Mishap investigations provide important information about adverse events and near miss incidents. They are intended to help avoid any recurrence of previous failures. Over time, they can also yield statistical information about incident frequencies that helps to detect patterns of failure and can validate risk assessments. However, the increasing complexity of many safety critical systems is posing new challenges for mishap analysis. Similarly, the recognition that many failures have complex, systemic causes has helped to widen the scope of many mishap investigations. These two factors have combined to pose new challenges for the analysis of adverse events. A new generation of formal and semi-formal techniques have been proposed to help investigators address these problems. We introduce the term mishap logics to collectively describe these notations that might be applied to support the analysis of mishaps. The proponents of these notations have argued that they can be used to formally prove that certain events created the necessary and sufficient causes for a mishap to occur. These proofs can be used to reduce the bias that is often perceived to effect the interpretation of adverse events. Others have argued that one cannot use logic formalisms to prove causes in the same way that one might prove propositions or theorems. Such mechanisms cannot accurately capture the wealth of inductive, deductive and statistical forms of inference that investigators must use in their analysis of adverse events. This paper provides an overview of these mishap logics. It also identifies several additional classes of logic that might also be used to support mishap analysis.

Johnson, Chris↗
NASA NTRS2005

Vision and "Hand-Eye" Coordination for the Fujitsu HOAP-2 Humanoid Robot

Software was developed for a Fujitsu HOAP-2 humanoid robot to demonstrate that such "human form" robots can be used to perform useful tasks in an unknown environment; specifically, that they can operate with or in the place of humans to carry out construction operations necessary for space exploration, such as building or maintaining planetary surface habitats for humans. This paper describes the autonomous vision and hand-eye coordination software that enables the HOAP-2 to locate and manipulate objects. Simple vision and pattern detection algorithms including color filtering, noise filtering, image segmentation, orientation filters, and a feedback controlled tracking system enable the robot to locate marked building materials in the workspace. Experimentally determined spatial mappings associate locations in the visual field with the arm joint angles and trajectories necessary to reach these locations, allowing the robot to reach for and manipulate the building materials. These capabilities, when combined with locomotion capabilities, enable the robot to operate autonomously in an unknown workspace.

Moore, Jeffrey D.↗
NASA NTRS2003

Dual beam optical interferometer

A dual beam interferometer device is disclosed that enables moving an optics module in a direction, which changes the path lengths of two beams of light. The two beams reflect off a surface of an object and generate different speckle patterns detected by an element, such as a camera. The camera detects a characteristic of the surface.

Gutierrez, Roman C.↗
NASA NTRS2008

Method and system for sensing and identifying foreign particles in a gaseous environment

An optical method and system sense and identify a foreign particle in a gaseous environment. A light source generates light. An electrically-conductive sheet has an array of holes formed through the sheet. Each hole has a diameter that is less than one quarter of the light's wavelength. The sheet is positioned relative to the light source such that the light is incident on one face of the sheet. An optical detector is positioned adjacent the sheet's opposing face and is spaced apart therefrom such that a gaseous environment is adapted to be disposed there between. Alterations in the light pattern detected by the optical detector indicate the presence of a foreign particle in the holes or on the sheet, while a laser induced fluorescence (LIF) signature associated with the foreign particle indicates the identity of the foreign particle.

Choi, Sang H.↗
NASA NTRS2010

Fine alignment of a large segmented mirror

A system for aligning a segmented mirror includes a source of radiation directed along a first axis to the segmented mirror and a beamsplitter removably inserted along the first axis for redirecting radiation from the first axis to a second axis, substantially perpendicular to the first axis. An imaging array is positioned along the second axis for imaging the redirected radiation, and a knife-edge configured for cutting the redirected radiation is serially positioned to occlude and not occlude the redirected radiation, effectively providing a variable radiation pattern detected by the imaging array for aligning the segmented mirror.

Dey, Thomas William↗
NASA NTRS1961

Morphology of Magnetic Storms

This publication is a product of the continuing study of the properties of charged particles and fields in space being conducted by The RAND Corporation under contract No. NAS5-276 for the National Aeronautics and Space Administration. Magnetic storms, revealed by world-wide changes in the intensity of the earth's magnetic field, and emphasized by disturbances in electromagnetic communication channels, form detectable patterns on the surface of the earth and above it. The author draws together data from various times, places, and altitudes and, coupling these with what is known or inferred about the aurora, the ionosphere, and the relationship between them and the earth's radiation belts, creates a picture of what is believed to occur during a magnetic storm.

Vestine, E. H.↗
NASA NTRS2016

A Review of Recent Changes in Southern Ocean Sea Ice, Their Drivers and Forcings

Over the past 37years, satellite records show an increase in Antarctic sea ice cover that is most pronounced in the period of sea ice growth. This trend is dominated by increased sea ice coverage in the western Ross Sea, and is mitigated by a strong decrease in the Bellingshausen and Amundsen seas. The trends in sea ice areal coverage are accompanied by related trends in yearly duration. These changes have implications for ecosystems, as well as global and regional climate. In this review, we summarize the researchto date on observing these trends, identifying their drivers, and assessing the role of anthropogenic climate change. Whilst the atmosphere is thought to be the primary driver, the ocean is also essential in explaining the seasonality of the trend patterns. Detecting an anthropogenic signal in Antarctic sea ice is particularly challenging for a number of reasons: the expected response is small compared to the very high natural variability of the system; the observational record is relatively short; and the ability of global coupled climate models to faithfully represent the complex Antarctic climate system is in doubt.

Southern Ocean↗
NASA NTRSDate not supplied

Observing Supraglacial Lakes Using Deep Learning and PlanetScope Imagery

Supraglacial lakes (SGL)s result from melt water accumulation in topographic depressions on the surface of glaciers. SGLs primarily affect glacial dynamics through a positive feedback loop in which the albedo-lowering effect of SGLs can escalate surface melt leading to increases in lake extent and depth, amplifying the afore mentioned albedo-lowering effect. The implications of accelerated glacial melt include increased sea level rise and modifications to ocean primary productivity. SGLs are critical indicators of surface melt and its downstream impacts and should be monitored efficiently. In situ observations and measurements of SGLs are time consuming, cost-prohibitive and difficult to scale. Earth observation data and machine learning enable scalable monitoring of SGLs through pattern detection and quantification of lake evolution over time [1]. This work presents a model developed by training a convolutional neural network with imagery and labels from NASA Operation IceBridge and predicting SGLs in high temporal and spatial resolution PlanetScope imagery.

Supraglacial lake↗
DOE OSTI2017

Deep Packet/Flow Analysis using GPUs

Deep packet inspection (DPI) faces severe performance challenges in high-speed networks (40/100 GE) as it requires a large amount of raw computing power and high I/O throughputs. Recently, researchers have tentatively used GPUs to address the above issues and boost the performance of DPI. Typically, DPI applications involve highly complex operations in both per-packet and per-flow data level, often in real-time. The parallel architecture of GPUs fits exceptionally well for per-packet network traffic processing. However, for stateful network protocols such as TCP, their data stream need to be reconstructed in a per-flow level to deliver a consistent content analysis. Since the flow-centric operations are naturally antiparallel and often require large memory space for buffering out-of-sequence packets, they can be problematic for GPUs, whose memory is normally limited to several gigabytes. In this work, we present a highly efficient GPU-based deep packet/flow analysis framework. The proposed design includes a purely GPU-implemented flow tracking and TCP stream reassembly. Instead of buffering and waiting for TCP packets to become in sequence, our framework process the packets in batch and uses a deterministic finite automaton (DFA) with prefix-/suffix- tree method to detect patterns across out-of-sequence packets that happen to be located in different batches. In conclusion, evaluation shows that our code can reassemble and forward tens of millions of packets per second and conduct a stateful signature-based deep packet inspection at 55 Gbit/s using an NVIDIA K40 GPU.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Deep Packet/Flow Analysis using GPUs

aDeep packet inspection (DPI) faces severe performance challenges in high-speed networks (40/100 GE) as it requires a large amount of raw computing power and high I/O throughputs. Recently, researchers have tentatively used GPUs to address the above issues and boost the performance of DPI. Typically, DPI applications involve highly complex operations in both per-packet and per-flow data level, often in real-time. The parallel architecture of GPUs fits exceptionally well for per-packet network traffic processing. However, for stateful network protocols such as TCP, their data stream need to be reconstructed in a per-flow level to deliver a consistent content analysis. Since the flow-centric operations are naturally anti-parallel and often require large memory space for buffering out-of-sequence packets, they can be problematic for GPUs, whose memory is normally limited to several gigabytes. In this work, we present a highly efficient GPU-based deep packet/flow analysi s framework. The proposed design includes a purely GPU-implemented flow tracking and TCP stream reassembly. Instead of buffering and waiting for TCP packets to become in sequence, our framework process the packets in batch and uses a deterministic finite automaton (DFA) with prefix-/suffix- tree method to detect patterns across out-of-sequence packets that happen to be located in different batches. Evaluation shows that our code can reassemble and forward tens of millions of packets per second and conduct a stateful signature-based deep packet inspection at 55 Gbit/s using an NVIDIA K40 GPU.

Gong, Qian↗
DOE OSTI2019

Data reduction methods, systems, and devices

Systems, methods, and apparatus are disclosed herein for data pattern detection and data reduction. Devices include an input port configured to receive data values that include a plurality of data units. The devices may also include a data analyzer configured to determine a test statistic based on at least some of the plurality of data units, the test statistic indicating a degree of difference between a first data unit and at least a second data unit, the second data unit being received at the input port before the first data unit. The data analyzer includes the first data unit in a first data block responsive to a determination that the test statistic indicates a low degree of difference, the determination being based on a comparison with a designated difference threshold, the first data block being a same data block as a second data block that includes the second data unit.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2017

Improved twin detection via tracking of individual Kikuchi band intensity of EBSD patterns

Twin detection via EBSD can be particularly challenging due to the fine scale of certain twin types – for example, compression and double twins in Mg. Even when a grid of sufficient resolution is chosen to ensure scan points within the twins, the interaction volume of the electron beam often encapsulates a region that contains both the parent grain and the twin, confusing the twin identification process. The degradation of the EBSD pattern results in a lower image quality metric, which has long been used to imply potential twins. However, not all bands within the pattern are degraded equally. This paper exploits the fact that parent and twin lattices share common planes that lead to the quality of the associated bands not degrading; i.e. common planes that exist in both grains lead to bands of consistent intensity for scan points adjacent to twin boundaries. Hence, twin boundaries in a microstructure can be recognized, even when they are associated with thin twins. Proof of concept was performed on known twins in Inconel 600, Tantalum, and Magnesium AZ31. This method was then used to search for undetected twins in a Mg AZ31 structure, revealing nearly double the number of twins compared with those initially detected by standard procedures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Detecting Multipartite Entanglement Patterns Using Single-Particle Green’s Functions

Here, we present a protocol for detecting multipartite entanglement in itinerant many-body electronic systems using single-particle Green’s functions. To achieve this, we first establish a connection between the quantum Fisher information and single-particle Green’s functions by constructing a set of witness operators built out of single electron creation and destruction operators in a doubled system. This set of witness operators is indexed by a momentum k. We compute the quantum Fisher information for these witness operators and show that for thermal ensembles it can be expressed as an autoconvolution of the single-particle spectral function. We then apply our framework to a one-dimensional fermionic system to showcase its effectiveness in detecting entanglement in itinerant electron models. We observe that the detected entanglement level is sensitive to the wave vector associated with witness operator. Our protocol will permit detecting entanglement in many-body systems using scanning tunneling microscopy and angle-resolved photoemission spectroscopy, two spectroscopies that measure the single-particle Green’s function. It offers the prospect of the experimental detection of entanglement through spectroscopies beyond the established route of measuring the dynamical spin response.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1997

Arc burst pattern analysis fault detection system

A method and apparatus are provided for detecting an arcing fault on a power line carrying a load current. Parameters indicative of power flow and possible fault events on the line, such as voltage and load current, are monitored and analyzed for an arc burst pattern exhibited by arcing faults in a power system. These arcing faults are detected by identifying bursts of each half-cycle of the fundamental current. Bursts occurring at or near a voltage peak indicate arcing on that phase. Once a faulted phase line is identified, a comparison of the current and voltage reveals whether the fault is located in a downstream direction of power flow toward customers, or upstream toward a generation station. If the fault is located downstream, the line is de-energized, and if located upstream, the line may remain energized to prevent unnecessary power outages.

Russell, B. Don↗
DOE OSTI2019

A Flexible Framework for Building Occupancy Detection Using Spatiotemporal Pattern Networks

This paper presents a reliable, scalable, and transferable framework to predict occupancy in a building utilizing diverse, multi-modal information. We propose a new methodology for learning-driven occupancy detection built on the concepts of probabilistic graphical modeling and observable Markov chain modeling. To capture the relationship between multi-sensor data and occupancy, we propose this Occ-STPN framework that is flexible to support both multivariate and univariate formulations. While the multivariate Occ-STPN performs feature-level fusion of multiple predictors and occupancy time-series data, the univariate Occ-STPN involves decision fusion of occupancy predictions using individual predictors based on a mutual information weighted fusion scheme. We also propose a new metric to evaluate the performance of occupancy prediction algorithms. Two popular datasets are used to validate our approach and demonstrate that our framework is scalable in terms of the number of information sources (e.g., sensors) as well as it is possible to transfer trained models from one building to another without significant reduction in performance. Reliability of the algorithm is also tested by injecting noise into the datasets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A Flexible Framework for Building Occupancy Detection Using Spatiotemporal Pattern Networks: Preprint

This paper presents a reliable, scalable, and transferable framework to predict occupancy in a building utilizing diverse, multi-modal information. We propose a new methodology for learning-driven occupancy detection built on the concepts of probabilistic graphical modeling and observable Markov chain modeling. To capture the relationship between multi-sensor data and occupancy, we propose this Occ-STPN framework that is flexible to support both multivariate and univariate formulations. While the multivariate Occ-STPN performs feature-level fusion of multiple predictors and occupancy time-series data, the univariate Occ-STPN involves decision fusion of occupancy predictions using individual predictors based on a mutual information weighted fusion scheme. We also propose a new metric to evaluate the performance of occupancy prediction algorithms. Two popular datasets are used to validate our approach and demonstrate that our framework is scalable in terms of the number of information sources (e.g., sensors) as well as it is possible to transfer trained models from one building to another without significant reduction in performance. Reliability of the algorithm is also tested by injecting noise into the datasets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Patterning approach for detecting defect in device manufacturing

Compact handheld devices which were a dream in the past are now a reality; this has been enabled by miniaturization of circuit architectures including power devices. Scaling down of the design feature sizes does come with a price with an increase in systematic defects during chip manufacturing. There are generally two methods of inline defect detection adopted to monitor the semiconductor device fabrication—optical inspection and electron beam inspection. The optical inspection uses ultra-violet and deep ultra-violet (UV/DUV) light to find patterning defects on the wafer. While the electron-beam inspection uses electron charge and discharge measurement to find electrical connection defects, both are a costly procedure in terms of resources and time. The physical limit of feature resolution of the optical source is now making the defect inspection job difficult in miniaturized application specific integrated circuit (ASIC). This study is designed to test the patterning optimization approach on both inspection platforms. Using hotspot analysis weak locations are identified in the full chip design, and then they are verified in the inline wafer inspection. The criterion for hot-spot determination is also discussed in this paper.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Pattern Dictionary Method for Anomaly Detection

In this paper, we propose a compression-based anomaly detection method for time series and sequence data using a pattern dictionary. The proposed method is capable of learning complex patterns in a training data sequence, using these learned patterns to detect potentially anomalous patterns in a test data sequence. The proposed pattern dictionary method uses a measure of complexity of the test sequence as an anomaly score that can be used to perform stand-alone anomaly detection. We also show that when combined with a universal source coder, the proposed pattern dictionary yields a powerful atypicality detector that is equally applicable to anomaly detection. The pattern dictionary-based atypicality detector uses an anomaly score defined as the difference between the complexity of the test sequence data encoded by the trained pattern dictionary (typical) encoder and the universal (atypical) encoder, respectively. We consider two complexity measures: the number of parsed phrases in the sequence, and the length of the encoded sequence (codelength). Specializing to a particular type of universal encoder, the Tree-Structured Lempel–Ziv (LZ78), we obtain a novel non-asymptotic upper bound, in terms of the Lambert W function, on the number of distinct phrases resulting from the LZ78 parser. This non-asymptotic bound determines the range of anomaly score. As a concrete application, we illustrate the pattern dictionary framework for constructing a baseline of health against which anomalous deviations can be detected.

97 MATHEMATICS AND COMPUTING↗