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DOE OSTI2013

Climate Information Needs for Financial Decision Making

Climate Information Needs for Financial Decision Making (Final Report) This Department of Energy workshop award (grant #DE-SC0008480) provided primary support for the American Meteorological Society’s study on climate information needs for financial decision making. The goal of this study was to help advance societal decision making by examining the implications of climate variability and change on near-term financial investments. We explored four key topics: 1) the conditions and criteria that influence returns on investment of major financial decisions, 2) the climate sensitivity of financial decisions, 3) climate information needs of financial decision makers, and 4) potential new mechanisms to promote collaboration between scientists and financial decision makers. Better understanding of these four topics will help scientists provide the most useful information and enable financial decision makers to use scientific information most effectively. As a result, this study will enable leaders in business and government to make well-informed choices that help maximize long-term economic success and social wellbeing in the United States The outcomes of the study include a workshop, which brought together leaders from the scientific and financial decision making communities, a publication of the study report, and a public briefing of the results to the policy community. In addition, we will present the results to the scientific community at the AMS Annual Meeting in February, 2014. The study results were covered well by the media including Bloomberg News and E&E News. Upon request, we also briefed the Office of Science Technology Policy (OSTP) and the Council on Environmental Quality (CEQ) on the outcomes. We presented the results to the policy community through a public briefing in December on Capitol Hill. The full report is publicly available at www.ametsoc.org/cin. Summary of Key Findings The United States invests roughly $1.5 trillion U.S. dollars (USD) in capital assets each year across the public and private sectors (Orszag 2008; United States Census Bureau 2013). Extreme weather events create and exacerbate risks to these financial investments by contributing to: • Direct physical impacts on the investments themselves • Degradation of critical supporting infrastructure • Changes in the availability of key natural resources • Changes to workforce availability or capacity • Changes in the customer base • Supply chain disruptions • Legal liability • Shifts in the regulatory environment • Reductions in credit ratings Even small changes in weather can impact operations in critical economic sectors. As a result, maximizing returns on financial investments depends on accurately understanding and effectively accounting for these risks. Climate variability and change can either exacerbate existing risks or cause new sources of risk to emerge. Managing these risks most effectively will depend on scientific advances and increases in the capacity of financial decision makers to use the scientific knowledge that results. Barriers to using climate information must also be overcome. This study proposes three predefined levels of certainty for communicating about weather and climate risks: 1) possible (i.e., unknown likelihood or less than 50% chance of occurrence), 2) probable (greater than 50% chance of occurrence), and 3) effectively certain (at least 95% chance of occurrence). For example, it is effectively certain that a change in climate will alter weather patterns. It is probable that climate warming will cause increases in the intensity of some extreme events. It is possible that climate change will cause major and widespread disruptions to key planetary life-support services. Key recommendations of this study: 1) Identify climate-related risks and opportunities for financial decision making. 2) Create a framework to translate scientific information in clear and actionable terms for financial decision makers. 3) Analyze existing climate assessments and translate projected impacts into possible, probable, and effectively certain impacts. 4) Improve climate projections with respect to precipitation (timing, amount, and intensity), extreme events, and tails of probability distributions (i.e., low-probability but high-consequence events). 5) Increase spatial resolution of climate projections in order to provide climate information at the scale most relevant to financial investments. 6) Improve projections of the societal consequences of climate impacts through integrated assessments of physical, natural, and social sciences. 7) Create a user-friendly information repository and portal that provides easy access to information relevant to financial decision making. 8) Create and maintain opportunities to bring together financial decision makers, scientists, and service providers. Near-term financial decisions have long-term implications for the United States’ social and economic well-being that depend, in part, on climate variability and change. Investments will be most successful, and will advance the interests of society most effectively, if they are grounded in the best available knowledge & understanding.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

U.S. Efforts in Support of Examinations at Fukushima Daiichi - November 2022 Meeting Notes and Information Request Status

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2023 (FY2023) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during these meetings benefit operating, new, and advanced reactors. Significant safety insights have been and are continuing to be obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional benefits to the operating fleet and new LWR and non-LWR designs. U.S. evaluations of obtained examination information and input regarding future Daiichi examinations are of interest to several organizations within Japan. Since its inception, the U.S. has provided consensus input for high priority time-sequenced examination tasks and supporting research activities. In their Mid-to-Long-term Examination Plan for 1F investigations, TEPCO included all remaining U.S. consensus information requests and additional information requests they identified. TEPCO periodically provides reports on the status of these requests (reflecting D&D priorities, new insights from investigations, and new technologies that become available). Hence, U.S. experts agreed that it was appropriate for TEPCO to track and prioritize these information requests as D&D progresses. U.S. experts will continue to review and comment on the information obtained from examinations and, as needed, provide additional details and relevant background material to support future examinations. As documented in this report, several other items, such as additional details on information requests pertaining to ex-vessel examinations, relevant references from prior research, additional documents to provide insights regarding recent investigation findings, and reviews of recently released documents, were agreed to during the FY2023 meeting.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Portal and Repository for Information on Marine Renewable Energy (PRIMRE)

The Marine Renewable Energy (MRE) industry is in the early stages of development corresponding to low technology readiness levels (TRLs) where the ability of the MRE community (developers, researchers, academics, stakeholders, investors, and regulators) to work together to share knowledge, experience, and lessons learned is critical to the advancement of the entire MRE industry. Through collaboration on solving common problems, the MRE community has the potential to reduce cost and accelerate technology development. Currently, the US Department of Energy (US DOE) Water Power Technologies Office (WPTO) is addressing the challenge of storing, curating, and accessing MRE information by sponsoring development of MRE databases and information portals such as Tethys (https://tethys.pnnl.gov), OpenEI (https://openei.org), the MHK Data Repository (MHKDR, https://mhkdr.openei.org/), and a searchable MRE code catalog and open source code repository (MHKiT, currently under development), to name a few. These sites host scientific papers, news articles, reports, databases, open source codes, and stakeholder engagement information, but they are only a step towards facilitating global discovery and use. In short, there is an abundance of information available online, however it is located on many disparate sites and repositories that make the discovery of those data and information difficult. A DOE national laboratory team from the National Renewable Energy Laboratory (NREL), Pacific Northwest National Laboratory (PNNL), and Sandia National Laboratories (Sandia) is addressing the issues of data discoverability, shared knowledge, and interconnection of existing MRE databases and information portals. To meet the needs of the MRE community, as identified through multiple community outreach and engagement events, and described in this paper, the multi-lab team has developed an implementation plan for PRIMRE, the Portal and Repository for Information on Marine Renewable Energy. PRIMRE will provide broad access to information on engineering and technologies, resource characterization, device performance, and environmental effects of MRE projects. PRIMRE will facilitate the commercial development of the MRE industry by increasing the accessibility and discoverability of this information, integrating the databases and information portals described in this paper, and developing standards and guidelines. Providing consistent, easy access to information can help reduce duplication of effort and enable the MRE community to learn from past failures and build upon the successes of others to innovate and advance the commercialization of MRE technologies.

16 TIDAL AND WAVE POWER↗

NASA NTRS1995

SEDAC information gateway plan V(1)

This annual update of the Information Gateway Plan incorporates changes recommended by the Socioeconomic Data and Applications Center (SEDAC) User Working Group (UWG) and reflects comments and suggestions from users, collaborators, and the Contracting Officer Technical Representative (COTR). The Information Gateway Plan is a concise and specific plan that outlines SEDAC activities and services in support of the earth and social sciences and other user communities. The SEDAC Information Gateway effort is a primary means by which the Earth Observing System Data and Information System (EOSDIS) can link meaningfully with a broad range of social science data sources and users in ways that lead to tangible benefits to the American people. The SEDAC Information Gateway provides interdisciplinary access to socioeconomic and physical science data and information resources held by SEDAC and numerous other institutions and networks around the world. The Plan describes the areas of research of earth scientists and socioeconomic scientists where interchange of data and information is most needed. It sets guidelines for the continued development of SEDAC's directory of social science datasets and establishes priorities for efforts to make data held by SEDAC or accessible through SEDAC available to the user community. The Plan also describes the means by which the SEDAC user community can access information products specified by the SEDAC Data and Applications Development Plan (DADP). Among other major activities, SEDAC will continue to enhance and operate a directory capability, interoperable with the Global Change Master Directory, that provides the socioeconomic community with information about earth science products and the earth science research community with information about socioeconomic data. The Information Gateway also serves as a unique and powerful access pathway for a wide range of users and potential users of socioeconomic and earth science data, including especially remote sensing data.

Chen, Robert S.↗

NASA NTRS2002

General Aviation Pilots' Perceived Usage and Valuation of Aviation Weather Information Sources

Aviation suffers many accidents due to the lack of good weather information in flight. Existing aviation weather information is difficult to obtain when it is most needed and is not well formatted for in-flight use. Because it is generally presented aurally, aviation weather information is difficult to integrate with spatial flight information and retain for reference. Efforts, by NASA's Aviation Weather Information (AWIN) team and others, to improve weather information accessibility, usability and decision aiding will enhance General Aviation (GA) pilots' weather situation awareness and decision-making and therefore should improve the safety of GA flight. Consideration of pilots' economic concerns will ensure that in-flight weather information systems are financially accessible to GA pilots as well. The purpose of this survey was to describe how aviation operator communities gather and use weather information as well as how weather related decisions are made between flight crews and supporting personnel. Pilots of small GA aircraft experience the most weather-related accidents as well as the most fatal weather related accident. For this reason, the survey design and advertisement focused on encouraging participation from GA pilots. Perhaps as a result of this emphasis, most responses, 97 responses or 85% of the entire response set, were from GA pilots, This paper presents only analysis of these GA pilots' responses. The insights provided by this survey regarding GA pilots' perceived value and usage of current aviation weather information. services, and products provide a basis for technological approaches to improve GA safety. Results of this survey are discussed in the context of survey limitations and prior work, and serve as the foundation for a model of weather information value, guidance for the design of in-flight weather information systems, and definition of further research toward their development.

Latorella, Kara↗

NASA NTRS2003

Organizing Diverse, Distributed Project Information

SemanticOrganizer is a software application designed to organize and integrate information generated within a distributed organization or as part of a project that involves multiple, geographically dispersed collaborators. SemanticOrganizer incorporates the capabilities of database storage, document sharing, hypermedia navigation, and semantic-interlinking into a system that can be customized to satisfy the specific information-management needs of different user communities. The program provides a centralized repository of information that is both secure and accessible to project collaborators via the World Wide Web. SemanticOrganizer's repository can be used to collect diverse information (including forms, documents, notes, data, spreadsheets, images, and sounds) from computers at collaborators work sites. The program organizes the information using a unique network-structured conceptual framework, wherein each node represents a data record that contains not only the original information but also metadata (in effect, standardized data that characterize the information). Links among nodes express semantic relationships among the data records. The program features a Web interface through which users enter, interlink, and/or search for information in the repository. By use of this repository, the collaborators have immediate access to the most recent project information, as well as to archived information. A key advantage to SemanticOrganizer is its ability to interlink information together in a natural fashion using customized terminology and concepts that are familiar to a user community.

Keller, Richard M.↗

NASA NTRS2018

Information Theory Applied to Decision Making Structures

Decision making structures, such as control boards, process information on many topics as they select options for the system and project. The decisions are based on the information known to the board members and presenters (subject matter experts) and shared at the board during discussion. This information flow through this process can be modelled using information theory. Information theory provides a mathematical basis to understand the flow of information through the decision making process and the information needed for a particular decision. Information theory also provides the mathematical relationships on which to base the optimal decision making structure for a specific system development and organizational structure. Since decision making bodies provide control for the system or project, control theory can be used to construct a decision making model. This provides a starting point for adding cognitive science models. Information processing by each individual board participant can be represented through cognitive processes which are integrated across the board participants through information theory relationship. The set theory view of information theory provides a structure in which to look at the relationships between the participants in a decision making structure.

Watson, Michael D.↗

NASA NTRS2018

Information Theory Applied to Decision Making Structures

Watson, Michael D.↗

DOE OSTI2015

Rényi generalizations of the conditional quantum mutual information

The conditional quantum mutual information I(A; B|C) of a tripartite state ρ{sub ABC} is an information quantity which lies at the center of many problems in quantum information theory. Three of its main properties are that it is non-negative for any tripartite state, that it decreases under local operations applied to systems A and B, and that it obeys the duality relation I(A; B|C) = I(A; B|D) for a four-party pure state on systems ABCD. The conditional mutual information also underlies the squashed entanglement, an entanglement measure that satisfies all of the axioms desired for an entanglement measure. As such, it has been an open question to find Rényi generalizations of the conditional mutual information, that would allow for a deeper understanding of the original quantity and find applications beyond the traditional memoryless setting of quantum information theory. The present paper addresses this question, by defining different α-Rényi generalizations I{sub α}(A; B|C) of the conditional mutual information, some of which we can prove converge to the conditional mutual information in the limit α → 1. Furthermore, we prove that many of these generalizations satisfy non-negativity, duality, and monotonicity with respect to local operations on one of the systems A or B (with it being left as an open question to prove that monotonicity holds with respect to local operations on both systems). The quantities defined here should find applications in quantum information theory and perhaps even in other areas of physics, but we leave this for future work. We also state a conjecture regarding the monotonicity of the Rényi conditional mutual informations defined here with respect to the Rényi parameter α. We prove that this conjecture is true in some special cases and when α is in a neighborhood of one.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

The Efficient Utilization of Open Source Information

These are a set of slides on the efficient utilization of open source information. Open source information consists of a vast set of information from a variety of sources. Not only does the quantity of open source information pose a problem, the quality of such information can hinder efforts. To show this, two case studies are mentioned: Iran and North Korea, in order to see how open source information can be utilized. The huge breadth and depth of open source information can complicate an analysis, especially because open information has no guarantee of accuracy. Open source information can provide key insights either directly or indirectly: looking at supporting factors (flow of scientists, products and waste from mines, government budgets, etc.); direct factors (statements, tests, deployments). Fundamentally, it is the independent verification of information that allows for a more complete picture to be formed. Overlapping sources allow for more precise bounds on times, weights, temperatures, yields or other issues of interest in order to determine capability. Ultimately, a "good" answer almost never comes from an individual, but rather requires the utilization of a wide range of skill sets held by a team of people.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2015

Modelling informally collected quantities of bulky waste and reusable items in Austria

Highlights: • Informal collectors from Hungary collect bulky waste and reusable items in Austria. • Two methodologies were applied to estimate the informally collected quantities. • Both approaches lead to an estimation of roughly 100,000 t p.a. informally collected. • The formal Austrian system collects 72 kg/cap/yr of bulky waste, WEE & scrap metal. • Informal collection amounts to approx. 12 kg/cap/yr. - Abstract: Disparities in earnings between Western and Eastern European countries are the reason for a well-established informal sector actively involved in collection and transboundary shipment activities from Austria to Hungary. The preferred objects are reusable items and wastes within the categories bulky waste, WEEE and metals, intended to be sold on flea markets. Despite leading to a loss of recyclable resources for Austrian waste management, these informal activities may contribute to the extension of the lifetime of certain goods when they are reused in Hungary; nevertheless they are discussed rather controversially. The aim of this paper is to provide objective data on the quantities informally collected and transhipped. The unique activities of informal collectors required the development and implementation of a new set of methodologies. The concept of triangulation was used to verify results obtained by field visits, interviews and a traffic counting campaign. Both approaches lead to an estimation of approx. 100,000 t per year of reusable items informally collected in Austria. This means that in addition to the approx. 72 kg/cap/yr formally collected bulky waste, bulky waste wood, household scrap (excluding packaging) and WEEE, up to a further 12 kg/cap/yr might, in the case that informal collection is abandoned, end up as waste or in the second-hand sector.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Consolidating WLCG topology and configuration in the Computing Resource Information Catalogue

Here, the Worldwide LHC Computing Grid infrastructure links about 200 participating computing centres affiliated with several partner projects. It is built by integrating heterogeneous computer and storage resources in diverse data centres all over the world and provides CPU and storage capacity to the LHC experiments to perform data processing and physics analysis. In order to be used by the experiments, these distributed resources should be well described, which implies easy service discovery and detailed description of service configuration. Currently this information is scattered over multiple generic information sources like GOCDB, OIM, BDII and experiment-specific information systems. Such a model does not allow to validate topology and configuration information easily. Moreover, information in various sources is not always consistent. Finally, the evolution of computing technologies introduces new challenges. Experiments are more and more relying on opportunistic resources, which by their nature are more dynamic and should also be well described in the WLCG information system. This contribution describes the new WLCG configuration service CRIC (Computing Resource Information Catalogue) which collects information from various information providers, performs validation and provides a consistent set of UIs and APIs to the LHC VOs for service discovery and usage configuration. The main requirements for CRIC are simplicity, agility and robustness. CRIC should be able to be quickly adapted to new types of computing resources, new information sources, and allow for new data structures to be implemented easily following the evolution of the computing models and operations of the experiments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A study on the statistical significance of mutual information between morphology of a galaxy and its large-scale environment

ABSTRACT A non-zero mutual information between morphology of a galaxy and its large-scale environment is known to exist in Sloan Digital Sky Survey (SDSS) upto a few tens of Mpc. It is important to test the statistical significance of these mutual information if any. We propose three different methods to test the statistical significance of these non-zero mutual information and apply them to SDSS and Millennium run simulation. We randomize the morphological information of SDSS galaxies without affecting their spatial distribution and compare the mutual information in the original and randomized data sets. We also divide the galaxy distribution into smaller subcubes and randomly shuffle them many times keeping the morphological information of galaxies intact. We compare the mutual information in the original SDSS data and its shuffled realizations for different shuffling lengths. Using a t-test, we find that a small but statistically significant (at $99.9{{\ \rm per\ cent}}$ confidence level) mutual information between morphology and environment exists upto the entire length-scale probed. We also conduct another experiment using mock data sets from a semi-analytic galaxy catalogue where we assign morphology to galaxies in a controlled manner based on the density at their locations. The experiment clearly demonstrates that mutual information can effectively capture the physical correlations between morphology and environment. Our analysis suggests that physical association between morphology and environment may extend to much larger length-scales than currently believed, and the information theoretic framework presented here can serve as a sensitive and useful probe of the assembly bias and large-scale environmental dependence of galaxy properties.

Sarkar, Suman↗

DOE OSTI2015

Design Concepts for an Outage Control Center Information Dashboard

The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis. In the last two decades, the steady improvement of data storage devices and means to create and collect data along the way influenced the manner in which we deal with information. Most data is still stored without filtering and refinement for later use. Many functions at a nuclear power plant generate vast amounts of data, with scheduled and unscheduled outages being a prime example of a source of some of the most complex data sets at the plant. To make matters worse, modern information and communications technology is making it possible to collect and store data faster than our ability to use it for making decisions. However, in most applications, especially outages, raw data has no value in itself; instead, managers, engineers and other specialists want to extract the information contained in it. The complexity and sheer volume of data could lead to information overload, resulting in getting lost in data that may be irrelevant to the task at hand, processed in an inappropriate way, or presented in an ineffective way. To prevent information overload, many data sources are ignored so production opportunities are lost because utilities lack the ability to deal with the enormous data volumes properly. Decision-makers are often confronted with large amounts of disparate, conflicting and dynamic information, which are available from multiple heterogeneous sources. Information and communication technologies alone will not solve this problem. Utilities need effective methods to exploit and use the hidden opportunities and knowledge residing in unexplored data resources. Superior performance before, during and after outages depends upon the right information being available at the right time to the right people. Acquisition of raw data is the easy part; instead, it is the ability to use advanced analytical, data processing and data visualization methods to turn the data into reliable information and comprehensible, actionable information. Techniques like data mining, filtering and analysis only work reliably for well-defined and well-understood problems. The path from data to decision is more complex. The ability to communicate knowledge during outages and emergent issues is crucial. This paper presents an approach to turn the unused data into an opportunity: applying principles from semiotics, human factors and visual analytics to transform the traditional way of processing outage data into media that will improve the collective situation awareness, knowledge, decisions, actions and overall performance of the entire outage team, and also support the reliability, quality and overall effectiveness of maintenance work. The application of the proposed visualization methods will become the medium of a semi-automated analytical process where humans and machines cooperate using their respective, distinct capabilities for the most effective results.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

U.S. Effort Support to Examinations at Fukushima - Meeting Notes with Updated Information Requests (FY2020)

Much is still not known about the end-state of core materials in each unit that was operating on March 11, 2011 at the Fukushima Daiichi Nuclear Power Station (Daiichi). Information obtained from Daiichi is required to inform Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This document, which has been updated to include Fiscal Year 2020 (FY2020) information, summarizes results from a U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy (DOE-NE), is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Since its inception, comprehensive annual reports were issued that document significant safety insights being obtained in areas of special emphasis: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. For FY2020, it was decided that the program would gain more benefit from a more concise report that emphasizes new information and insights that affect prior findings and recommendations from the U.S. experts participating in this effort. A key aspect of prior U.S. efforts, the updated list of information requests, is included in this letter report to ensure that they are transmitted to organizations within Japan. In addition, findings and associated recommendations are provided regarding information presented by TEPCO Holdings, Nuclear Damage Compensation and Decommissioning Facilitation Corporation (NDF), and the Japan Atomic Energy Agency (JAEA). This letter report also continues to emphasize how information obtained from the affected reactors at Daiichi has been and will continue to be used to update severe accident management strategies, improve maintenance activities (especially in areas of radiation protection) and reduce uncertainties in systems analysis code models. In addition, recommendations are included that would expand the use of this information to provide insights regarding maintenance, radiation protection, design, and siting activities of existing and new reactors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

U.S. Efforts in Support of Examinations at Fukushima Daiichi (November 2021 Meeting Notes with Updated Information Requests)

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2022 (FY2022) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during forensics meetings benefit operating, new, and advanced reactors. Significant safety insights are being obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. As discussed in this document, revised operator guidance was successfully used to improve operator response during a loss of off-site power event at the Duane Arnold Energy Center plant. Reduced uncertainties in modeling the events at Daiichi improve the realism of reactor safety evaluations that inform future D&D activities. U.S. evaluations of information from Fukushima and input regarding future examinations are of interest to several organizations within Japan. Meeting presentations by Japan describe how comments and recommendations documented in prior U.S. forensics effort reports, including consensus information requests developed by forensics effort participants, are considered in future Fukushima D&D activities. As discussed in this report, TEPCO Holdings considered these information requests in their D&D planning activities. An updated list of consensus information requests is included in this FY2022 report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of interinstitutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action— particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗