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At least 127 records · Page 7

Readiness Evaluation for Sustained Operations

Readiness evaluation for sustained operations is a continuous function that progresses from overseeing establishment of five key programmatic elements during design and construction phases to monitoring the output of those elements performing during commissioning and operations. Continuously assessing readiness for sustained operations becomes an important business function for the U.S. Department of Energy’s Office of River Protection as competition for federal funds increases with increasing waste treatment operations throughout the Office of Environmental Management complex. The five key programmatic elements are as follows: Risk management – Risks and opportunities should prioritize continuous improvement initiatives and be informed by the design and technical authorities and stakeholder monitors. Continuous improvement – All levels of the project organization should exhibit commitment to continuous improvement and learning. Continuity of design and technical authorities – The authorities are responsible for managing knowledge for its effective use in the other elements. Stakeholder monitoring – Active and deliberate monitoring of stakeholder relationships. Sustained operations integrated business planning – Integrated business planning in a federal environment competitive for congressional funding.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Developing an Advanced Environment for Collaborative Computing

Knowledge management in general tries to organize and make available important know-how, whenever and where ever is needed. Today, organizations rely on decision-makers to produce "mission critical" decisions that am based on inputs from multiple domains. The ideal decision-maker has a profound understanding of specific domains that influence the decision-making process coupled with the experience that allows them to act quickly and decisively on the information. In addition, learning companies benefit by not repeating costly mistakes, and by reducing time-to-market in Research & Development projects. Group-decision making tools can help companies make better decisions by capturing the knowledge from groups of experts. Furthermore, companies that capture their customers preferences can improve their customer service, which translates to larger profits. Therefore collaborative computing provides a common communication space, improves sharing of knowledge, provides a mechanism for real-time feedback on the tasks being performed, helps to optimize processes, and results in a centralized knowledge warehouse. This paper presents the research directions. of a project which seeks to augment an advanced collaborative web-based environment called Postdoc, with workflow capabilities. Postdoc is a "government-off-the-shelf" document management software developed at NASA-Ames Research Center (ARC).

Becerra-Fernandez, Irma↗

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗

A Step Beyond Simple Keyword Searches: Services Enabled by a Full Content Digital Journal Archive

The problems of managing and searching large archives of scientific journal articles can potentially be addressed through data mining and statistical techniques matured primarily for quantitative scientific data analysis. A journal paper could be represented by a multivariate descriptor, e.g., the occurrence counts of a number key technical terms or phrases (keywords), perhaps derived from a controlled vocabulary ( e . g . , the American Meteorological Society's Glossary of Meteorology) or bootstrapped from the journal archive itself. With this technique, conventional statistical classification tools can be leveraged to address challenges faced by both scientists and professional societies in knowledge management. For example, cluster analyses can be used to find bundles of "most-related" papers, and address the issue of journal bifurcation (when is a new journal necessary, and what topics should it encompass). Similarly, neural networks can be trained to predict the optimal journal (within a society's collection) in which a newly submitted paper should be published. Comparable techniques could enable very powerful end-user tools for journal searches, all premised on the view of a paper as a data point in a multidimensional descriptor space, e.g.: "find papers most similar to the one I am reading", "build a personalized subscription service, based on the content of the papers I am interested in, rather than preselected keywords", "find suitable reviewers, based on the content of their own published works", etc. Such services may represent the next "quantum leap" beyond the rudimentary search interfaces currently provided to end-users, as well as a compelling value-added component needed to bridge the print-to-digital-medium gap, and help stabilize professional societies' revenue stream during the print-to-digital transition.

Boccippio, Dennis J.↗

Space Station Module Power Management and Distribution System (SSM/PMAD)

This report provides an overview of the Space Station Module Power Management and Distribution (SSM/PMAD) testbed system and describes recent enhancements to that system. Four tasks made up the original contract: (1) common module power management and distribution system automation plan definition; (2) definition of hardware and software elements of automation; (3) design, implementation and delivery of the hardware and software making up the SSM/PMAD system; and (4) definition and development of the host breadboard computer environment. Additions and/or enhancements to the SSM/PMAD test bed that have occurred since July 1990 are reported. These include: (1) rehosting the MAESTRO scheduler; (2) reorganization of the automation software internals; (3) a more robust communications package; (4) the activity editor to the MAESTRO scheduler; (5) rehosting the LPLMS to execute under KNOMAD; implementation of intermediate levels of autonomy; (6) completion of the KNOMAD knowledge management facility; (7) significant improvement of the user interface; (8) soft and incipient fault handling design; (9) intermediate levels of autonomy, and (10) switch maintenance.

Miller, William↗

Product Lifecycle Management and the Quest for Sustainable Space Exploration Solutions

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Engineering Directorate at the National Aeronautics and Space Administration's (NASA's) Marshall Space Flight Center, total lifecycle costs are important variables for critical decisionmaking. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful tool to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This paper will demonstrate how the Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions. It has been 30 years since the United States fielded the Space Shuttle. The next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. The outcome is a better use of scarce resources, along with more focus on stakeholder and customer requirements, as a new portfolio of enabling tools becomes second nature to the workforce. This paper will use the design and manufacturing processes, which have transitioned to digital-based activities, to show how PLM supports the comprehensive systems engineering and integration function. It also will go through a launch countdown scenario where an anomaly is detected to show how the virtual vehicle created from paperless processes will help solve technical challenges and improve the likelihood of launching on schedule, with less hands-on labor needed for processing and troubleshooting. Sustainable space exploration solutions demand that all lifecycle phases be optimized. Adopting PLM, which has been used by the automotive industry for many years, for aerospace applications provides a foundation for strong, disciplined systems engineering and accountable return on investment by making lifecycle considerations variables in an iterative decision-making process. This paper combines the perspectives of the founding father of PLM, along with the experience of Engineering leaders who are implementing these processes and practices real-time. As the nation moves from an industrial-based society to one where information is a valued commodity, future NASA programs and projects will benefit from the experience being gained today for the exploration missions of tomorrow.

Caruso, Pamela W.↗

Product Lifecycle Management and the Quest for Sustainable Space Explorations

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Engineering Directorate at the National Aeronautics and Space Administration's (NASA's) Marshall Space Flight Center, total lifecycle costs are important variables for critical decision-making. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful concept to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This paper will demonstrate how the Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions. It has been 30 years since the United States fielded the Space Shuttle. The next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. The outcome is a better use of scarce resources, along with more focus on stakeholder and customer requirements, as a new portfolio of enabling tools becomes second nature to the workforce. This paper will use the design and manufacturing processes, which have transitioned to digital-based activities, to show how PLM supports the comprehensive systems engineering and integration function. It also will go through a launch countdown scenario where an anomaly is detected to show how the virtual vehicle created from paperless processes will help solve technical challenges and improve the likelihood of launching on schedule, with less hands-on labor needed for processing and troubleshooting.

Caruso, Pamela W.↗

Oxidation Chemistry of Bicarbonate and Peroxybicarbonate: Implications for Carbonate Management in Energy Storage

Carbonate formation presents a major challenge to energy storage applications based on low-temperature CO 2 electrolysis and recyclable metal–air batteries. While direct electrochemical oxidation of (bi)carbonate represents a straightforward route for carbonate management, knowledge of the feasibility and mechanisms of direct oxidation is presently lacking. Herein, we report the isolation and characterization of the bis(triphenylphosphine)iminium salts of bicarbonate and peroxybicarbonate, thus enabling the examination of their oxidation chemistry. Infrared spectroelectrochemistry combined with time-resolved infrared spectroscopy reveals that the photoinduced oxidation of HCO 3 – by an Ir(III) photoreagent results in the generation of the short-lived bicarbonate radical in less than 50 ns. The highly acidic bicarbonate radical undergoes proton transfer with HCO 3 – to furnish the carbonate radical anion and H 2 CO 3 , leading to the eventual release of CO 2 and H 2 O, thus accounting for the appearance of H 2 O and CO 2 in both electrochemical and photochemical oxidation experiments. Here, the back reaction of the carbonate radical subsequently oxidizes the Ir(II) photoreagent, leading to carbonate. In the absence of this back reaction, dimerization of the carbonate radical provides entry into peroxybicarbonate, which we show undergoes facile oxidation to O 2 and CO 2 . Together, the results reported identify tangible pathways for the design of catalysts for the management of carbonate in energy storage applications.

25 ENERGY STORAGE↗

Product Lifecycle Management and the Quest for Sustainable Space Exploration Solutions

Product Lifecycle Management (PLM) is an outcome of lean thinking to eliminate waste and increase productivity. PLM is inextricably tied to the systems engineering business philosophy, coupled with a methodology by which personnel, processes and practices, and information technology combine to form an architecture platform for product design, development, manufacturing, operations, and decommissioning. In this model, which is being implemented by the Marshall Space Flight Center (MSFC) Engineering Directorate, total lifecycle costs are important variables for critical decision-making. With the ultimate goal to deliver quality products that meet or exceed requirements on time and within budget, PLM is a powerful concept to shape everything from engineering trade studies and testing goals, to integrated vehicle operations and retirement scenarios. This briefing will demonstrate how the MSFC Engineering Directorate is implementing PLM as part of an overall strategy to deliver safe, reliable, and affordable space exploration solutions and how that strategy aligns with the Agency and Center systems engineering policies and processes. Sustainable space exploration solutions demand that all lifecycle phases be optimized, and engineering the next generation space transportation system requires a paradigm shift such that digital tools and knowledge management, which are central elements of PLM, are used consistently to maximum effect. Adopting PLM, which has been used by the aerospace and automotive industry for many years, for spacecraft applications provides a foundation for strong, disciplined systems engineering and accountable return on investment. PLM enables better solutions using fewer resources by making lifecycle considerations in an integrative decision-making process.

Caruso, Pamela W.↗

Gen IV Education and Training Working Group Webinars’ Initiative

Collaboration and support among national laboratories, industry, universities, and research and development organizations are vital to not only maintain a skilled and competent nuclear workforce but also to avert the risk of human resource shortages. As stated in a recent IAEA paper [1], the world nuclear electrical generating capacity is projected to increase to 554 GW(e) by 2030 and up to 874 GW(e) by 2050 (Fig. 1). This represents a 42% increase over current levels by 2030 and a doubling of the current capacity by 2050. To promote Education and Training (E&T) on Gen IV reactor systems and other nuclear related topics of interest, the Gen IV Education and Training Working Group (ETWG) identifies and advertises training courses; engages collaboration with other international education and training organizations; delivers webinars dedicated to Gen IV systems; and maintains a modern social medium platform to exchange information and ideas on Gen IV R&D topics, as well as on related GIF education and training activities. At the end of June 2020, the GIF ETWG has produced, podcasted and posted forty-one webinars covering the six Gen IV systems and various subjects addressing e.g. the economics of the nuclear fuel cycle, sustainability aspects of Gen IV systems, nuclear fuels and materials challenges, the thorium fuel cycle, energy conversion systems, and lessons learned for knowledge management and preservation. This paper describes the development of these webinars from the initial concept to its full realization, with future webinars planned in 2021, addressing topics such as materials and fuels performance for advanced reactors, small modular reactor.

Paviet, Patricia D.↗

eLog analysis for accelerators: status and future outlook

This work demonstrates electronic logbook (eLog) systems leveraging modern AI-driven information retrieval capabilities at the accelerator facilities of Fermilab, Jefferson Lab, Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory. We evaluate contemporary tools and methodologies for information retrieval with Retrieval Augmented Generation (RAGs), focusing on operational insights and integration with existing accelerator control systems. The study addresses challenges and proposes solutions for state-of-the-art eLog analysis through practical implementations, demonstrating applications and limitations. We present a framework for enhancing accelerator facility operations through improved information accessibility and knowledge management, which could potentially lead to more efficient operations.

Accelerator Physics↗

FAIRmaterials: Ontology Tools with Data FAIRification in Development

The bilingual FAIRmaterials package simplifies the creation and visualization of materials and data science ontologies. FAIRmaterials, available in the Python and R languages, addresses the complexities associated with traditional ontology editors based on manual user input such as Protege with an intuitive workflow and easy-to-use templates, making it accessible to users both experienced and inexperienced with ontologies. The FAIRmaterials package is its ability to programatically convert simple and structured CSV inputs into rich, well-defined ontologies. This capability is designed to support the findability, accessibility, interoperability, and reusability (FAIR) of research data and serve as a tool in the process of data FAIRification. Its additional features, such as automated ontology merging, static visualizations, and comprehensive documentation for outputs extend its utility, making it a valuable tool for any researcher engaged in knowledge management.

Bradley, Alexander Harding [Case Western Reserve U↗

A Systems Engineering Approach to Accident Response Planning

This paper explores the Systems Engineering structure, strategies and tools for real world scenarios involving work with accident response groups. A systems engineering approach must be taken by the technical teams to prepare for a successful response and design the technical systems in support of the operations. The scope of this project is focused on laying out the foundation of the systems engineering approach taken to help the teams develop an accident response strategy and identify new engineering designs in support of these operations for the black box systems. This Master’s project involves several interdisciplinary teams & stakeholders across different areas. Identifying the proper tools to use is key to addressing the big picture needs of the multiple stakeholders. This project explores some of the key tools used by the integrated team. The integrated project work will primarily take place over the course of 8 weeks via integrated team meetings. Other work in support of this project will take place off-line as needed by the project lead. Details on the prospective timeline, milestones, key dates and work scope can be referenced in other sections of this paper. Key systems engineering methodologies and tools used thus far in support of this project includes: 1) Market Surveys and Interviews, 2) Project Charter, 3) Feasibility Study, 4) Swim Lane Diagram, and 5) Knowledge Management Plan.

42 ENGINEERING↗

A Systems Engineering Approach to Accident Response Planning.

This paper explores the Systems Engineering structure, strategies and tools for real world scenarios involving work with accident response planning. A systems engineering approach must be taken by the technical teams to prepare for a successful response and design the technical systems in support of the operations. The scope of this project is focused on laying out the foundation of the systems engineering approach taken to help the teams develop an accident response strategy and identify new engineering designs in support of these operations for the black box systems. This Masters project involved several interdisciplinary teams & stakeholders. Identifying the proper tools to use was key to addressing the big picture needs of the multiple stakeholders. The integrated project work primarily took place over the course of eight weeks via integrated team meetings. Other work in support of this project was conducted off-line as needed by the project lead. Details on the prospective timeline, milestones, key dates and work scope can be referenced in this paper. Key systems engineering methodologies and tools used in support of this project included but is not limited to: Market Surveys and Interviews Project Charter Feasibility Study Swim Lane Diagram Knowledge Management Plan. A full suite of tools and the details regarding the application of these tools and results of this study is provided in this report.

42 ENGINEERING↗

Project Management, Including Data Management Best Practices Framework (Best Management Practice; Work Product 12.3.b)

The Project Management documentation includes: (1) background on the RCSP Initiative and its best practices development process; (2) a historical perspective of best practices for project management; (3) a comparison of the roles of project managers, functional managers, and operations managers; (4) an overview of project management practices for field activities; and discussions of (5) managing change, (6) managing data, and (7) managing knowledge and information.

01 COAL, LIGNITE, AND PEAT↗

eLog Analysis for Accelerators: Status and Future Outlook

This work demonstrates electronic logbook (eLog) systems leveraging modern AI-driven information retrieval capabilities at the accelerator facilities of Fermilab, Jefferson Lab, Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory. We evaluate contemporary tools and methodologies for information retrieval with Retrieval Augmented Generation (RAGs), focusing on operational insights and integration with existing accelerator control systems. The study addresses challenges and proposes solutions for state-of-the-art eLog analysis through practical implementations, demonstrating applications and limitations. We present a framework for enhancing accelerator facility operations through improved information accessibility and knowledge management, which could potentially lead to more efficient operations.

Hellert, Thorsten [LBNL, ALS]↗

Artificial Intelligence in Nuclear Safeguards; Evaluating Safeguards and Security Risks and Benefits for Advanced and Small Modular Reactor Deployments

Rapidly growing interest in advanced and small modular reactor (A/SMR) technologies presents challenges as well as opportunities for implementing international safeguards and security. A/SMR deployments are expected to be more numerous, more geographically dispersed, and more varied in their designs, placing new demands on the data systems and analytical tools used to support oversight (Alberti et al., 2023; Canadian Nuclear Safety Commission et al., 2024). Because of this variability, the importance and reliance on data systems for A/SMR deployments is expected to be higher than for previous reactor generations. Artificial Intelligence and Machine Learning (AI/ML) offer potential capabilities to address the high variability inherent in A/SMR technology. The beneficiaries of AI-assisted tools include facility operators, government regulators, IAEA inspectors, and A/SMR vendors. This report analyzes how AI/ML-assisted technologies can strengthen the implementation of IAEA safeguards and security measures. It also identifies AI-assisted tools to strengthen operator, facility, and regulator knowledge management practices and examines the potential risks AI/ML-based tools may introduce to IAEA safeguards and security efforts. It concludes with a set of hypothetical, standards-style requirements for AI/ML systems used in safeguards contexts, grounded in an inspector-centric view of system verification. Despite the potential benefits of AI/ML systems, understanding potential intentional and unintentional failure modes is critical for ensuring adequate protection of nuclear materials and facilities. Unique features of A/SMRs including sealed cores, remote and novel paradigms of operation, off-site reactor fabrication, novel fuel forms, and varied refueling requirements, introduce challenges for traditional safeguards technological approaches (Pensado et al., 2024; Federation of American Scientists, 2025). AI/ML systems deployed to address these challenges may introduce new risks requiring systematic evaluation rooted in both AI-specific risk frameworks, such as the NIST AI Risk Management Framework (NIST AI RMF), and established cyber risk management standards such as NIST SP 800-30 (National Institute of Standards and Technology [NIST], 2023; NIST, 2012).

97 MATHEMATICS AND COMPUTING↗

Grid Architecture Mapping to Understand Transformation (GAMUT): Methods and Framework Architecture

Grid architecture (GA) is a concept that was developed to address the need for a comprehensive view of power grid challenges. GA can be viewed as a relatively consistent and fixed high-level approach; however, for any instantiation of grid structures, a combinatorial explosion results from each lower-layer expansion. This constitutes the main challenge with GA—it is a grid architect’s view of the system, which might not be very informative at the implementation level. Grid Architecture Mapping to Understand Transformation (GAMUT project) seeks to bridge that gap by integrating subject matter expertise across GA structures, providing users who lack expertise in GA approaches with valuable insights and informational materials. GAMUT seeks to answer feasibility questions for the approach. System-level expectations are that a GA baseline needs to be established in order for GA to be the common framework to which any lower layer approach is tied. This report explores a potential information ingestion and documentation framework to support GAMUT. The main concepts that enable the solution domain of GAMUT are discussed, and examples are provided. The solution domain leverages already-existing technology and concepts related to GA, knowledge management, and other relevant areas. To assess GAMUT building blocks and the overall approach, a feasibility assessment is proposed, rooted in systems engineering and GA architecture evaluation concepts.

24 POWER TRANSMISSION AND DISTRIBUTION↗