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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Fission Meter Information Barrier Attribute Measurement System - NA-243 FNI/UKC FY2017 Task 1-2 Report

An SNM attribute Information Barrier (IB) system was developed for a 2011 US/UK Exercise. The system was modified and extensively tested in a 2013-2014 US-UK Measurement Campaign. This work demonstrated rapid deployment of an IB system for potential treaty use. The system utilizes an Ortec Fission Meter neutron multiplicity counter and custom computer code. The system demonstrates a proof-of-principle automated Pu-240 mass determination with an information barrier. After a software start command is issued, the system automatically acquires and downloads data, performs an analysis, and displays the results. This system conveys the results of a Pu mass threshold measurements in a way the does not reveal sensitive information. In full IB mode, only the pass/fail result is displayed as a “Mass <= Threshold Amount” or “Mass >= Threshold Amount” as shown in Figure 4. This can easily be adapted to a red/green “lights” display similar to the Detective IB system for Pu isotopics as shown in Figure 6. In test mode, more detailed information is displayed. The code can also read in, analyze, and display results from previously acquired or simulated data. Because the equipment is commercial-off-the-shelf (COTS), the system demonstrates a low-cost short-lead-time technology for treaty SNM attribute measurements. A deployed system will likely require integration of additional authentication and tamper-indicating technologies. This will be discussed for the project in this and future progress reports.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Scenarios and Spectra Set for CTBT OSI Information Barrier Testing

The Comprehensive Nuclear-Test-Ban Treaty limits radiation measurements during an on-site inspection to those isotopes the States Parties have agreed are appropriate for the purpose of determining if a nuclear explosion has occurred without revealing irrelevant confidential information. To accomplish this, the radiation detectors used will need to have information barriers that are proven to function reliably over the wide range of possible inspection uses and scenarios. In order to provide a basis set of spectra for testing proposed information barrier systems, PNNL and LLNL defined a set of treaty-compliant and non-compliant scenarios and then independently developed a set of spectra relevant to those scenarios. Real spectra were utilized to the extent possible, but often computer simulations were necessary. These spectra will next be used to assess the performance of an INL information barrier system.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

Options for Providing Radiation Protection Shelter Quality Information to U.S. Local, State and Federal Government Agencies

This report describes available information on protection that can be provided by buildings from exposure to radioactive contamination in the environment, and options for how this information can be provided to government organizations across the United States. This information is potentially useful for planning how to protect the public in the event of an atmospheric release of radioactivity including, for example, from a Radiological Dispersal Device, an Improvised Nuclear Device detonation, or a Nuclear Power Plant accident. During these incidents, knowledge of the radiation protection provided by buildings is critical to predicting and assessing radiation dose to the population, and the associated health risk. These dose assessments inform emergency plans and decisions including, for example, identifying areas in which people should be sheltered in place, and determining when controlled population evacuations should be made.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Background Information on the Power Quality Requirements in IEEE Std 1547-2018

The revised Institute of Electrical and Electronics Engineers (IEEE) 1547-2018, Standard for Interconnection and Interoperability of Distributed Energy Resources with Associated Electric Power Systems Interfaces, was published in April 2018. This standard is one of the foundational documents in the United States needed for integrating distributed energy resources (DERs), including solar energy systems, and energy storage systems with the electric distribution grid. The revised standard contains 11 chapters (clauses) and 8 annexes that comprise 136 pages. The revision is significantly different from the 2003 version, and it contains new concepts and new technical requirements. Each clause specifies information or requirements that apply to certain aspects that are important to the interconnection of DERs to the electric power system. Implementing the requirements necessitates a careful study of the underlying technical concepts and requires appropriate information to calculate relevant settings and configurations. This document provides informative material on the requirements related to electrical power quality in IEEE Std 1547-2018, with the intent to equip the reader with basic knowledge and background information to improve understanding and use of the requirements specified.

14 SOLAR ENERGY↗
DOE OSTI2022

Ontologies: The Gateway to Knowledge-Enabled Information Services at Los Alamos National Laboratory

At LANL, we use ontologies to capture and maintain essential organizational knowledge and support tools and frameworks for information discovery. Ontologies capture knowledge, creating meaningful structures for finding and interpreting information. Information in a human context that provides meaning and data that is organized and communicated. This report provides information about LANL's ontology efforts and challenges.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Scalable Technologies Achieving Risk-Informed Condition-Based Predictive Maintenance Enhancing the Economic Performance of Operating Nuclear Power Plants

The primary objective of the research presented in this report is to develop scalable technologies that are deployable across plant assets and across the nuclear fleet to achieve risk-informed predictive maintenance (PdM) strategies at commercial nuclear power plants (NPPs). Over the years, the nuclear fleet has relied on labor-intensive and time-consuming preventive maintenance (PM) programs, driving up operation and maintenance (O&M) costs to achieve high capacity factors. A well-constructed risk-informed PdM approach for an identified plant asset has been developed in this research, taking advantage of advancements in data analytics, machine learning (ML), artificial intelligence (AI), physics-informed modeling, and visualization. These technologies would allow commercial NPPs to reliably transition from current labor-intensive PM programs to a technology driven PdM program, eliminating unnecessary O&M costs. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report (1) reflects the results of work by LWRS Program researchers with PSEG, Nuclear LLC-owned Salem and Hope Creek Nuclear Power Plants; (2) presents utilization of circulating water system (CWS) heterogeneous data and fault modes from both the Salem and Hope Creek nuclear power plant sites to develop salient fault signatures associated with each fault mode; (3) describes the integration of component-level predictive models into a robust system-level model enabled by the federated-transfer learning; (4) describes the development of physics-informed model of circulating water pump and motor; (5) develops a scalable risk and economic model; and (6) outlines the development of a user-centric visualization application. The outcomes presented in this report lays the foundation and provides a much-needed technical basis to focus on explainability and trustworthiness of ML and AI-based technologies, as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Resumen del Informe de Progreso del PR100: Resultados Preliminares del Modelo y Conjuntos de Datos Solares y Eólica de Alta Resolución

El estudio de Resiliencia y Transiciones a 100% Energia Renovable de Puerto Rico (PR100) es un estudio de 2 anos de la Oficina de Movilizacion de la Red del Departamento de Energia y seis laboratorios nacionales para analizar exhaustivamente las rutas dirigidas por las personas interesadas hacia un futuro de energia limpia en Puerto Rico. En el Ano 1 del estudio, el equipo PR100, creo y analizo los modelos que alcanzan las metas de energia renovable para Puerto Rico y los objetivos de resiliencia energetica a corto y largo plazo. Este informe, que resume el progreso en el Ano 1, proporciona las consideraciones que pueden informar posibles decisiones de fondos e implementacion potenciales por parte de las agencias federales y locales clave y partes interesadas. El resumen de este informe sigue a la publicacion en julio 2022 de un Informe de Seis Meses de Progreso de PR100. (en ingles y espanol), asi como webinarios publicos en febrero 2022 para lanzar el estudio y julio 2022 para presentar la actualizacion a 6 meses. Un informe final por escrito y visuales por la web seran publicados a finales del 2023. Todas las publicaciones y eventos publicos asociados con el estudio estaran disponibles en ingles y espanol. This report is also available in English https://www.nrel.gov/docs/fy23osti/85018.pdf.

14 SOLAR ENERGY↗
DOE OSTI2023

The Value of Sharing and Consolidating Critical Community, Electricity, and Natural Hazard Information

The California Public Utilities Commission (CPUC) sought support for the development of database schema specifications for a bi-directional data portal that would foster cross-jurisdictional collaboration necessary to improve resilient energy infrastructure planning processes. This technical assistance activity involved Berkeley Lab researchers reviewing 34 local/tribal government hazard mitigation plans to assess (1) the natural hazards that communities are most concerned about; (2) the variety of–and terminology used to describe–critical community infrastructure; and (3) the availability of GIS information that could be incorporated into CPUC-mandated "Microgrid Planning Portals". In addition, we develop a common, but generic data taxonomy showing what fields to collect to encourage consolidating and sharing of this information in the future. Finally, we partnered with the Bishop Paiute tribal government to demonstrate the value of combining electricity infrastructure, natural hazard layers, and critical community infrastructure into a series of maps. The project demonstrated that a single system containing both electric utility and community infrastructure data—as well as information about natural hazards—will help the state of California, the IOUs, first responders, and long-term planners better prepare for—and thus lower their exposure to these ongoing and emerging hazards. The project also identified a number of challenges that will need to be overcome before it is possible to stand up a single system to display this information.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Radioisotope Identification with List-Mode Gamma Ray Data: A rigorous assessment on the value of temporal information applied to radioisotope identification.

This work explores the potential of utilizing temporal data from gamma-ray detectors, known as list-mode data, to enhance radioisotope identification. Traditional identification methods, which rely on full gamma-ray spectrum analysis, often require long dwell times and struggle with “confuser” sources, or spectra with similarly spaced spectral peaks. We hypothesize that by leveraging the probabilistic nature of nuclear decay and the time-encoded information from decay sequences and interactions with surrounding materials, we can improve classification accuracy over static spectral analysis. This research rigorously examines the temporal content of list-mode data through exploratory data analysis via correlation discovery and information theory. We further propose a basic classification model that can utilize spectral or temporal data (or both) to determine if the incorporation of temporal information can improve radioisotope identification. The findings suggest that the temporal information present in list-mode gamma-ray data has merit and should be further investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Maximized Information Gain of Next Generation Pulsed Power Using Optimized Design of Z-Machine Experiments

This project develops a Bayesian optimization approach to extracting insights from Z Machine experimental data to determine if and how these insights can be used to extrapolate to a larger facility. The primary goal is to address the scientific challenge of informing how confidently experimental conditions can be predicted on a next generation facility, the design of which requires the reliable extrapolation of current high energy density technologies to regimes yet unobserved, except by costly high-fidelity computational models. Maximizing the use of presently available data and understanding how it informs future endeavors is critically important to enable transformative pulsed power and the science of extreme conditions. We explore a Bayesian optimization approach to experimental design which combines information theory, experimental data, and computational modeling to explore how information gain can be maximized.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantum Information Encoding and Decoding for Quantum Sensi

This two-year theory project focused on theoretical investigations of novel paradigms for quantum sensing, building on information encoding and techniques from quantum error correction, quantum computing and other quantum information domains. The outcomes facilitate quantum information technology development, especially at the interface of quantum computing and quantum sensing. The results of the project show new use cases and new paradigms for quantum sensing beyond what has so far been considered. One outcome shows how quantum sensing opens new opportunities for fundamental physics such as the capability of single graviton detection. Another outcome reveals a new application of NISQ quantum computers with error correction for metrology, building on recent advances in practical quantum error correction implementation. The third outcome of the project creates new paradigms of back-action-evading sensing inspired by collective quantum information encoding, which achieves quantum sensing beyond the quantum limit without the use of entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Fossil Corals With Various Degrees of Preservation Can Retain Information About Biomineralization-Related Organic Material

Scleractinian corals typically form a robust calcium carbonate skeleton beneath their living tissue. This skeleton, through its trace element composition and isotope ratios, may record environmental conditions of water surrounding the coral animal. While bulk unrecrystallized aragonite coral skeletons can be used to reconstruct past ocean conditions, corals that have undergone significant diagenesis have altered geochemical signatures and are typically assumed to retain insufficient meaningful information for bulk or macrostructural analysis. However, partially recrystallized skeletons may retain organic molecular components of the skeletal organic matrix (SOM), which is secreted by the animal and directs aspects of the biomineralization process. Some SOM proteins can be retained in fossil corals and can potentially provide past oceanographic, ecological, and indirect genetic information. Here, we describe a dataset of scleractinian coral skeletons, aged from modern to Cretaceous plus a Carboniferous rugosan, characterized for their crystallography, trace element composition, and amino acid compositions. We show that some specimens that are partially recrystallized to calcite yield potentially useful biochemical information whereas complete recrystalization or silicification leads to significant alteration or loss of the SOM fraction. Our analysis is informative to biochemical-paleoceanographers as it suggests that previously discounted partially recrystallized coral skeletons may indeed still be useful at the microstructural level.

58 GEOSCIENCES↗
DOE OSTI2023

Knowledge-informed deep learning for hydrological model calibration: an application to Coal Creek Watershed in Colorado

Abstract. Deep learning (DL)-assisted inverse mapping has shown promise in hydrological model calibration by directly estimating parameters from observations. However, the increasing computational demand for running the state-of-the-art hydrological model limits sufficient ensemble runs for its calibration. In this work, we present a novel knowledge-informed deep learning method that can efficiently conduct the calibration using a few hundred realizations. The method involves two steps. First, we determine decisive model parameters from a complete parameter set based on the mutual information (MI) between model responses and each parameter computed by a limited number of realizations (∼50). Second, we perform more ensemble runs (e.g., several hundred) to generate the training sets for the inverse mapping, which selects informative model responses for estimating each parameter using MI-based parameter sensitivity. We applied this new DL-based method to calibrate a process-based integrated hydrological model, the Advanced Terrestrial Simulator (ATS), at Coal Creek Watershed, CO. The calibration is performed against observed stream discharge (Q) and remotely sensed evapotranspiration (ET) from the water year 2017 to 2019. Preliminary MI analysis on 50 realizations resulted in a down-selection of 7 out of 14 ATS model parameters. Then, we performed a complete MI analysis on 396 realizations and constructed the inverse mapping from informative responses to each of the selected parameters using a deep neural network. Compared with calibration using observations covering all time steps, the new inverse mapping improves parameter estimations, thus enhancing the performance of ATS forward model runs. The Nash–Sutcliffe efficiency (NSE) of streamflow predictions increases from 0.53 to 0.8 when calibrating against Q alone. Using ET observations, on the other hand, does not show much improvement on the performance of ATS modeling mainly due to both the uncertainty of the remotely sensed product and the insufficient coverage of the model ET ensemble in capturing the observation. By using observed Q only, we further performed a multiyear analysis and show that Q is best simulated (NSE > 0.8) by including in the calibration the dry-year flow dynamics that show more sensitivity to subsurface characteristics than the other wet years. Moreover, when continuing the forward runs till the end of 2021, the calibrated models show similar simulation performances during this evaluation period as the calibration period, demonstrating the ability of the estimated parameters in capturing climate sensitivity. Our success highlights the importance of leveraging data-driven knowledge in DL-assisted hydrological model calibration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Detecting flash drought events to inform adaptive water management

Abstract: Flash droughts are characterized by a rapid onset of drought conditions, a common feature among various indicators of these events. The lack of a standardized definition and indicator makes flash droughts particularly challenging to predict and manage. We test six state-of-the-art flash drought indicators using 41 years of daily data across all Hydrological Unit Code 4 (HUC4) regions in the contiguous United States. Our results show substantial disagreements among indicators, suggesting that the detection of a flash drought event strongly depends on the choice of indicator. From the perspective of informing management and operations, an open challenge remains: which flash drought indicator should be used to trigger operational adaptations? To this end, we propose a methodological framework that informs adaptive actions by regionally assessing the level of agreement between different indicators. The regional differences in hydroclimatic conditions are expected to be reflected in the level of agreement between indicators. To better inform adaptive actions, the framework will also consider the impacted sectoral water uses and their varying response times. The insights gained from this study improve the understanding of how these different flash drought indicators capture the different aspects of regional differences and impacted sectors. Furthermore, this information can support more targeted adaptive actions to mitigate adverse impacts through improved preparedness and response strategies.

climate resilience↗
NASA NTRS1972

Improved navigation by combining VOR/DME information with air or inertial data

The improvement was determined in navigational accuracy obtainable by combining VOR/DME information (from one or two stations) with air data (airspeed and heading) or with data from an inertial navigation system (INS) by means of a maximum-likelihood filter. It was found that the addition of air data to the information from one VOR/DME station reduces the RMS position error by a factor of about 2, whereas the addition of inertial data from a low-quality INS reduces the RMS position error by a factor of about 3. The use of information from two VOR/DME stations with air or inertial data yields large factors of improvement in RMS position accuracy over the use of a single VOR/DME station, roughly 15 to 20 for the air-data case and 25 to 35 for the inertial-data case. As far as position accuracy is concerned, at most one VOR station need be used. When continuously updating an INS with VOR/DME information, the use of a high-quality INS (0.01 deg/hr gyro drift) instead of a low-quality INS (1.0 deg/hr gyro drift) does not substantially improve position accuracy.

Bobick, J. C.↗
NASA NTRS1971

Information content of simulated space photographs as a function of various levels of image resolution.

The results of research are reported on the information content in simulated space photographs derivable as a function of various levels of image resolution. Whenever certain resource features could not be consistently identified on simulated low-resolution imagery, attempts were made to define the required level of image resolution that would allow a skilled interpreter to discriminate one feature from another. The results of this research, conducted within a chaparral-hardwood-grassland environment in California, indicate that simulated ERTS data contain sufficient information to allow an interpreter to discriminate between woody vegetation, grassland, and water bodies. However, if more detailed information is desired, the imagery must have a ground resolution of at least 50 ft, showing shape, size, texture, and shadow characteristics within each vegetation type. Spaceborne data, therefore, often will have to be supplemented by higher resolution aircraft imagery, depending on the types of resource information being sought.

Lauer, D. T.↗
NASA NTRS1972

On the dependence of information display quality requirements upon human characteristics and pilot/automatics relations

Present information display concepts for pilot landing guidance are outlined considering manual control as well as substitution of man by fully competent automatics. Display improvements are achieved by compressing the distributed indicators into an accumulative display and thus reducing information scanning. Complete integration of quantitative indications, outer loop information, and real world display in a pictorial information channel geometry constitutes an interface with human ability to differentiate and integrate for optimal manual control of the aircraft.

Wilckens, V.↗
NASA NTRS1972

ERISTAR: Earth Resources Information Storage, Transformation, Analysis, and Retrieval

The National Aeronautics and Space Administration (NASA) and the American Society for Engineering Education (ASEE) have sponsored faculty fellowship programs in systems engineering design for the past several years. During the summer of 1972 four such programs were conducted by NASA, with Auburn University cooperating with Marshall Space Flight Center (MSFC). The subject for the Auburn-MSFC design group was ERISTAR, an acronym for Earth Resources Information Storage, Transformation, Analysis and Retrieval, which represents an earth resources information management network of state information centers administered by the respective states and linked to federally administered regional centers and a national center. The considerations for serving the users and the considerations that must be given to processing data from a variety of sources are described. The combination of these elements into a national network is discussed and an implementation plan is proposed for a prototype state information center. The compatibility of the proposed plan with the Department of Interior plan, RALI, is indicated.

Source record↗