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At least 37 records · Page 2

Frequency Event Categorization in Power Distribution Systems Using Micro PMU Measurements

Frequency is an important metric for power stability. To enhance the situational awareness in power distribution systems, this article proposes a data-driven approach that utilizes the data from micro phasor measurement units (μPMU) to categorize frequency events observed in distribution feeders. The proposed approach has three layers, each of which analyzes if a frequency event is propagated from the transmission system, formed inside a distribution feeder or falsely produced by instantaneous frequency (IF) estimation algorithms, respectively. In the first layer, the Granger causality is utilized to compare the causal relations from measurements across different locations to decide if an event is propagated from the transmission side. In the second layer, a trained sparse coding dictionary is utilized to unmix the physical causes of a frequency event. In the third layer, a moving z-score based event-pair detector is applied to identify if a frequency event is algorithm-induced. The proposed approach is tested using the μPMU measurements collected from Lawrence Berkeley National Laboratory (LBNL) and Riverside Public Utility (RPU).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multiobjective and categorical global optimization of photonic structures based on ResNet generative neural networks

Abstract We show that deep generative neural networks, based on global optimization networks (GLOnets), can be configured to perform the multiobjective and categorical global optimization of photonic devices. A residual network scheme enables GLOnets to evolve from a deep architecture, which is required to properly search the full design space early in the optimization process, to a shallow network that generates a narrow distribution of globally optimal devices. As a proof-of-concept demonstration, we adapt our method to design thin-film stacks consisting of multiple material types. Benchmarks with known globally optimized antireflection structures indicate that GLOnets can find the global optimum with orders of magnitude faster speeds compared to conventional algorithms. We also demonstrate the utility of our method in complex design tasks with its application to incandescent light filters. These results indicate that advanced concepts in deep learning can push the capabilities of inverse design algorithms for photonics.

Jiang, Jiaqi↗

Hyper Parameter Tuning in Neural Optical Image Categorizer for the E-log (NOICE

The Fermilab Accelerator Division Electronic logbook (E-log) is a record of all the activities and events in the Division for the past 10 years and more. The Elog search function is a valuable resource and the institutional memory of the accelerator complex. About 300,000 files are stored in the E-log, of which the vast majority are images attached to entries and comments. The visual information contained in the images is not presently searchable. The goal of team NOICE (Neural Optical Image Categorizer for the E-log) was to design a neural network able to produce label categories for these images for use by searches. The group developed a dataset and trained a convolutional neural network (CNN) with optimized hyperparameter. Final performance metrics are presented.

Njekeu, Terence Franck↗

Technical Basis for Proposed Changes to DOE-STD-1194-2019, Nuclear Material Attractiveness Determination and Categorization

The Department of Energy (DOE)’s Technical Standard DOE-STD-1194-2019 (dated September 2019), Nuclear Materials Control and Accountability, provides key guidance for the determination of Special Nuclear Material (SNM) attractiveness levels. Attractiveness levels are a key component in the security categorization of SNM processed, used, and stored at DOE facilities. Upon review, the writing team identified specific components relating to the determination of attractiveness levels that could be modified to improve clarity, reduce burden on sites, and/or better align with the graded safeguards principle that is central to the DOE’s nuclear security program. The report outlines the original verbiage, issues with implementation of that verbiage, proposed new verbiage, and the expected benefits thus serving as the technical basis for the proposed changes.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Semiannual Categorical Process Report - January Through June 2023

The Sandia National Laboratories, in California (SNL/CA) is a research and development facility, owned by the U.S. Department of Energy’s National Nuclear Security Administration agency (DOE/NNSA). The laboratory is located in the City of Livermore (the City) and is comprised of approximately 410 acres. The SNL/CA facility is operated by National Technology and Engineering Solutions of Sandia, LLC (NTESS) under a contract with the DOE/NNSA. The DOE/ NNSA’s Sandia Field Office (SFO) oversees the operations of the site. North of the SNL/CA facility is the Lawrence Livermore National Laboratory (LLNL), in which SNL/CA’s sewer system combines with before discharging to the City’s Publicly Owned Treatment Works (POTW) for final treatment and processing. The City’s POTW authorizes the wastewater discharge from SNL/CA via the assigned Wastewater Discharge Permit #1251 (the Permit), which is issued to the DOE/NNSA’s main office for Sandia National Laboratories, located in New Mexico (SNL/NM). The Monitoring and Reporting Condition 2.B of the Permit requires compliance with the semiannual reporting requirements contained in federal categorical pretreatment standards regulations (40 CFR 403.12). These regulations set numerical limits on the concentration of pollutants allowed to discharge from certain categories of industrial processes. This report is submitted to the City to satisfy this reporting requirement.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Blueprint: Stakeholder-Specific Vulnerability Categorization Guidance

Vulnerability management is a process of discovering, analyzing, and handling new or reported security vulnerabilities in systems to prevent the systems from being exploited, to reduce risk, and to protect assets. For vulnerability analysis, handling, and response, the prioritization of organizational and analyst resources must precede. The Common Vulnerability Scoring System (CVSS) is a standard prioritization method that is used to rate the severity of security vulnerabilities in systems by assigning numerical severity scores, but it does not provide clear guidelines of how the numerical severity scores might inform decisions. The Stakeholder-Specific Vulnerability Categorization (SSVC) provides a method for prioritizing vulnerabilities based on the needs of the stakeholders involved in the vulnerability management process. Instead of the numerical scoring used in the CVSS, the SSVC focuses on contextual decision-making to determine how quickly and effectively an organization should respond to vulnerabilities. The main functionality of the SSVC accommodates the diversity of the stakeholders in the vulnerability management process, including finders, vendors, coordinators, deployers, and others. So, the SSVC should be designed to be used by any of these stakeholders, and it should be customizable to enable specific stakeholder decision models and risk appetites.

33 ADVANCED PROPULSION SYSTEMS↗

Cleanroom air sampler counts, categorizes, and records particle data

Light scattering particle counter monitors particles in a clean room. It categorizes and records the particles according to size and functions simultaneously in three separate areas. The counter uses a transducer head to transform light signals into electric signals.

Nelson, M. B.↗

Automatic categorization of land-water cover types of the Green Swamp, Florida, using Skylab multispectral scanner (S-192) data

The techniques used and the results achieved in the successful application of Skylab Multispectral Scanner (EREP S-192) high-density digital tape data for the automatic categorizing and mapping of land-water cover types in the Green Swamp of Florida were summarized. Data was provided from Skylab pass number 10 on 13 June 1973. Significant results achieved included the automatic mapping of a nine-category and a three-category land-water cover map of the Green Swamp. The land-water cover map was used to make interpretations of a hydrologic condition in the Green Swamp. This type of use marks a significant breakthrough in the processing and utilization of EREP S-192 data.

Coker, A. E.↗

Software error data collection and categorization

Software errors detected during development of an interactive special purpose editor system were studied. This product was followed during nine months of coding, unit testing, function testing, and system testing. A new error categorization scheme was developed.

Ostrand, T. J.↗

Diamond like carbon coatings: Categorization by atomic number density

Dense diamond-like hydrocarbon films grown at the NASA Lewis Research Center by radio frequency self bias discharge and by direct ion beam deposition were studied. A new method for categorizing hydrocarbons based on their atomic number density and elemental composition was developed and applied to the diamond-like hydrocarbon films. It was shown that the diamond-like hydrocarbon films are an entirely new class of hydrocarbons with atomic number densities lying between those of single crystal diamond and adamantanes. In addition, a major review article on these new materials was completed in cooperation with NASA Lewis Research Center personnel.

Angus, John C.↗

Vector quantizer designs for joint compression and terrain categorization of multispectral imagery

Two vector quantizer designs for compression of multispectral imagery and their impact on terrain categorization performance are evaluated. The mean-squared error (MSE) and classification performance of the two quantizers are compared, and it is shown that a simple two-stage design minimizing MSE subject to a constraint on classification performance has a significantly better classification performance than a standard MSE-based tree-structured vector quantizer followed by maximum likelihood classification. This improvement in classification performance is obtained with minimal loss in MSE performance. The results show that it is advantageous to tailor compression algorithm designs to the required data exploitation tasks. Applications of joint compression/classification include compression for the archival or transmission of Landsat imagery that is later used for land utility surveys and/or radiometric analysis.

Gorman, John D.↗

Categorization and prioritization of flight deck information

The paper describes an experiment whose objectives were to: (1) make initial inferences about categories into which pilots place information; and (2) empirically determine how pilots mentally represent flight deck information, and how their cognitive processes of categorization and prioritization act upon those representations.

Jonsson, Jon E.↗

A Framework for Categorizing Important Project Variables

While substantial research has led to theories concerning the variables that affect project success, no universal set of such variables has been acknowledged as the standard. The identification of a specific set of controllable variables is needed to minimize project failure. Much has been hypothesized about the need to match project controls and management processes to individual projects in order to increase the chance for success. However, an accepted taxonomy for facilitating this matching process does not exist. This paper surveyed existing literature on classification of project variables. After an analysis of those proposals, a simplified categorization is offered to encourage further research.

Parsons, Vickie S.↗

Satellite Conjunction "Probability," "Possibility," and "Plausibility": A Categorization of Competing Conjunction Assessment Risk Assessment Paradigms

A number of different conjunction assessment (CA) risk analysis methods and metrics have been proposed in the critical literature, and they vary widely in purport and form. However, they tend to be proposed individually and episodically, so that it is difficult for a CA practitioner to take stock of the possibilities, under- stand their fundamental differences, and make informed choices for their particular CA risk assessment enterprise. The present study seeks to collect the major proposals for risk assessment methods and parameters and organize them categorically, under the proposed divisions of “probability,” “plausibility,” and “possibility,” as well as formulate what appears for each to be its fundamental question and, where applicable, null hypothesis. This activity can, through a bottom-up approach, provide some of the building blocks for an overarching CA philosophy, as well as establish concepts and terminology potentially useful to the broader discussion of these topics.

Hejduk, M. D.↗

Satellite Conjunction “Probability,” “Plausibility,” and “Possibility”: A Categorization of Competing Satellite Conjunction Assessment Risk Analysis Paradigms

A number of different conjunction assessment (CA) risk analysis methods and metrics have been proposed in the critical literature, and they vary widely in purport and form. However, they tend to be proposed individually and episodically, so that it is difficult for a CA practitioner to take stock of the possibilities, under- stand their fundamental differences, and make informed choices for their particular CA risk assessment enterprise. The present study seeks to collect the major proposals for risk assessment methods and parameters and organize them categorically, under the proposed divisions of “probability,” “plausibility,” and “possibility,” as well as formulate what appears for each to be its fundamental question and, where applicable, null hypothesis. This activity can, through a bottom-up approach, provide some of the building blocks for an overarching CA philosophy, as well as establish concepts and terminology potentially useful to the broader discussion of these topics.

Hejduk, M. D.↗

Software Error Incident Categorizations in Aerospace

Since the first use of computers in space and aircraft, software errors have occurred. These errors can manifest as loss-of-life or less catastrophically. As the demand for automation increases, software in safety-critical systems should be designed to be tolerant to the most likely software faults. This paper categorizes historic aerospace software errors to determine trends of how and where automation is most likely to fail. A distinction between software producing wrong (erroneous) output versus no output (fail-silent) is introduced. Of the historical incidents analyzed, 87% were from software acting unexpectedly rather than simply stopping. Rebooting was found to be ineffective to clear erroneous behavior, and only partially effective for silent software. Errors were traced back to the software logic itself in 62% of cases, 13% within configurable data, and 25% introduced through input. Thirty percent (30%) of unexpected software behavior was caused by the absence of software and 20% was due to “unknown-unknowns”. These findings indicate that to achieve fault tolerance in safety-critical systems, backup strategies must be employed to detect and respond to erroneous software behavior beyond only fail-silent cases, and robust off-nominal testing should be performed to uncover unanticipated situations.

Software↗

Historical Aerospace Software Errors Categorized to Influence Fault Tolerance

Since the first use of computers in space and aircraft, software errors have occurred. These errors can manifest as loss-of-life or less catastrophically. As the demand for automation increases, software in mission or safety-critical systems should be designed to be tolerant to the most likely software faults. This paper categorizes a set of 55 historic aerospace software error incidents from 1962 to 2023 to determine trends of how and where automation is most likely to fail, behaving unexpectedly. A distinction between software producing unexpected (erroneous) output versus no output (failsilent) is introduced. Of the historical incidents analyzed, 85% were from software producing wrong output rather than simply stopping. Rebooting was found to be ineffective to clear erroneous behavior, and not reliable to recover from silent failures. Error origin was within the code/logic itself in 58% of cases, 16% from configurable data, 15% from unexpected sensor input, and 11% from command/operator input. A substantial forty percent (40%) of unexpected software behavior was indicated by the absence of code, arising from unanticipated situations and missing requirements, and 16% of incidents were subjectively deemed “unknown-unknowns”. No incidents were found to be the result of programming language, compiler, tool, or operating system; and only sixteen percent (16%) of all incidents were considered errors traditional computer science/programming in nature. These findings indicate that for fault tolerance, erroneous automation behavior must be a primary consideration especially at critical moments, and reboot recoverability may not be viable. Special care should be taken to validate configurable data and commands prior to use. “Test-like-you-fly”, including hardware-in-the-loop combined with robust off-nominal testing should be used to uncover missing logic arising from unanticipated situations not covered by requirements alone. This study uniquely focuses on manifestations of unexpected flight software behavior, independent of ultimate root cause. We characterize software error behavior and origin to improve software design, test, and operations for resilience to the most common manifestations, and provide a rich dataset for further study.

Aerospace↗

Categorization of planets and exoplanets for Astrobiology.

Introduction: The number of exoplanets detected is astounding –and was not predicted. Note that Bo-rucki’s foundational paper for the Kepler mission in 1984 predicted:“...a detection rate of one planet per year of observation appears possible.”[1]. Even more astounding is the enormous diversity of exoplanets [2,3]. It is already clear from the data, that our Solar System does not bound the diversity and the range of processes seen in the exoplanets [2,3,4]. As telescopes improve it is certain that the number of exoplanets will become astronomical and the diversity will increase apace. The search for habitable locations and for evidence of life is a central part of the approach and excitement of exoplanet research [5,6]. Based on our experience to date we can expect that there will be enormous diversity in the types of habitability and life on exoplanets and that the Earth and our Solar System do not bound the possibilities for either habitability and life, and may not even provide a definite guide to selecting c and i-dates for detailed study from the enormous lists of exoplanets that will emerge. How can we develop a system for categorizing exoplanets in a way that allows for selection and prioritization in the search for diverse habitats and for diverse lifeforms?The short answer is we have no idea. In this short abstract I will venture some suggested approach-es. (see also[7]). To date, our solar system provides three classes for a habitable world:1) Earth. Water worlds, represented, of course, by Earth, and Earth-like worlds Venus and Mars. 2) Europa. Ice-covered worlds represented by Europa and including Enceladus and others, and 3) Titan. Cryogenic liquid covered worlds, represented by Titan. Earth and Europa world simply life made from carbon compounds in a water medium. Interest in these“ water worlds” is rooted in our understanding of life on Earth–the only example of life we have. The primary difference between Earth and Europa worlds is access to sunlight as an energy source on Earth. Titan represents the concept of carbon-based life in a cryogenic liquid such as CH4or C2H6 [8-13]. It is unlikely that Earth, Europa, and Titan represent the full range of possible classes of habitability for the many exoplanets that have been, or will be, discovered. It is also unlikely that life as we know it on Earth represents the full range of possible life on exoplanets. I am suggesting here that we start with these three classes (Earth, Europa, Titan) for exoplanet characterization and add others based on predicted types, such as “Hycean” worlds, a hypothetical type of planet with a hot, water-covered surface with a hydrogen dominated atmosphere [14] and the many examples considered in [15,16] and even imagined habitability and life forms [7] such as Sarr -a small, hot (500°C) rocky planet with an atmosphere over liquid sulfur. And that hosts only sulfur-based life. We are probably safe in the assumption that the richness and diversity of the exoplanets will exceed that of our collective imaginations.

Christopher P Mckay↗