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At least 145 records · Page 8

Enhancing Knowledge Capture and Management within a Knowledge-Driven Workforce [Capstone Project]

This project aimed to understand how the collective knowledge of a group of engineers or ‘knowledge-based workers’ can be baselined through use of qualitative questionnaires based on input from subject matter experts. The results of the questionnaires were then used to inform management and the group where to focus efforts on terms of training and mentoring. With use of re-administering the qualitative questionnaire to gauge progress over time. Additionally, the development a knowledge-based wiki was explored to help shape group culture from one where ideas and knowledge tend to be siloed, into one where information is traded freely across the group and with external customers and collaborators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Semantic Search with Sentence-BERT for Design Information Retrieval

Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval (IR): semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pre-trained sBERT model performs well out-of-the-box, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over a keyword search. Our use case throughout the paper is to use queries related to specific requirements from a NASA project. Fine tuning the sBERT model on LLIS data yields a mean average precision (MAP) of 0.807 on queries based on information needs from a real NASA project. Results indicate that applying state-of-the-art natural language processing techniques, especially when finetuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.

Hannah S. Walsh↗

A colalborative environment for information driven safeguards

For two decades, the IAEA has recognized the need for a comprehensive and strongly integrated Knowledge Management system to support its Information Driven Safeguards activities. In the past, plans for the development of such a system have progressed slowly due to concerns over costs and feasibility. In recent years, Los Alamos National Laboratory has developed a knowledge management system that could serve as the basis for an IAEA Collaborative Environment (ICE). The ICE derivative knowledge management system described in this paper addresses the challenge of living in an era of information overload coupled with certain knowledge shortfalls. The paper describes and defines a system that is flexible, yet ensures coordinated and focused collaboration, broad data evaluation capabilities, architected and organized work flows, and improved communications. The paper and demonstration of ICE will utilize a hypothetical scenario to highlight the functional features that facilitate collaboration amongst and between information analysts and inspectors. The scenario will place these two groups into a simulated planning exercise for a safeguards inspection drawing upon past data acquisitions, inspection reports, analyst conclusions, and a coordinated walk-through of a 3-D model of the facility. Subsequent to the conduct of the simulated facility inspection, the detection of an anomaly and pursuit of follow up activities will illustrate the event notification, information sharing, and collaborative capabilities of the system. The use of a collaborative environment such as ICE to fulfill the complicated knowledge management demands of the Agency and facilitate the completion of annual State Evaluation Reports will also be addressed.

97 MATHEMATICS AND COMPUTING↗

Knowledge Framework Implementation with Multiple Architectures - 13090

Multiple kinds of knowledge management systems are operational in public and private enterprises, large and small organizations with a variety of business models that make the design, implementation and operation of integrated knowledge systems very difficult. In recent days, there has been a sweeping advancement in the information technology area, leading to the development of sophisticated frameworks and architectures. These platforms need to be used for the development of integrated knowledge management systems which provides a common platform for sharing knowledge across the enterprise, thereby reducing the operational inefficiencies and delivering cost savings. This paper discusses the knowledge framework and architecture that can be used for the system development and its application to real life need of nuclear industry. A case study of deactivation and decommissioning (D and D) is discussed with the Knowledge Management Information Tool platform and framework. D and D work is a high priority activity across the Department of Energy (DOE) complex. Subject matter specialists (SMS) associated with DOE sites, the Energy Facility Contractors Group (EFCOG) and the D and D community have gained extensive knowledge and experience over the years in the cleanup of the legacy waste from the Manhattan Project. To prevent the D and D knowledge and expertise from being lost over time from the evolving and aging workforce, DOE and the Applied Research Center (ARC) at Florida International University (FIU) proposed to capture and maintain this valuable information in a universally available and easily usable system. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sustaining knowledge in the neutron generator community and benchmarking study. Phase II.

This report documents the second phase of work under the Sustainable Knowledge Management (SKM) project for the Neutron Generator organization at Sandia National Laboratories. Previous work under this project is documented in SAND2008-1777, Sustaining Knowledge in the Neutron Generator Community and Benchmarking Study. Knowledge management (KM) systems are necessary to preserve critical knowledge within organizations. A successful KM program should focus on people and the process for sharing, capturing, and applying knowledge. The Neutron Generator organization is developing KM systems to ensure knowledge is not lost. A benchmarking study involving site visits to outside industry plus additional resource research was conducted during this phase of the SKM project. The findings presented in this report are recommendations for making an SKM program successful. The recommendations are activities that promote sharing, capturing, and applying knowledge. The benchmarking effort, including the site visits to Toyota and Halliburton, provided valuable information on how the SEA KM team could incorporate a KM solution for not just the neutron generators (NG) community but the entire laboratory. The laboratory needs a KM program that allows members of the workforce to access, share, analyze, manage, and apply knowledge. KM activities, such as communities of practice (COP) and sharing best practices, provide a solution towards creating an enabling environment for KM. As more and more people leave organizations through retirement and job transfer, the need to preserve knowledge is essential. Creating an environment for the effective use of knowledge is vital to achieving the laboratory's mission.

07 ISOTOPE AND RADIATION SOURCES↗

Learning from the Mars Rover Mission: Scientific Discovery, Learning and Memory

Purpose: Knowledge management for space exploration is part of a multi-generational effort. Each mission builds on knowledge from prior missions, and learning is the first step in knowledge production. This paper uses the Mars Exploration Rover mission as a site to explore this process. Approach: Observational study and analysis of the work of the MER science and engineering team during rover operations, to investigate how learning occurs, how it is recorded, and how these representations might be made available for subsequent missions. Findings: Learning occurred in many areas: planning science strategy, using instrumen?s within the constraints of the martian environment, the Deep Space Network, and the mission requirements; using software tools effectively; and running two teams on Mars time for three months. This learning is preserved in many ways. Primarily it resides in individual s memories. It is also encoded in stories, procedures, programming sequences, published reports, and lessons learned databases. Research implications: Shows the earliest stages of knowledge creation in a scientific mission, and demonstrates that knowledge management must begin with an understanding of knowledge creation. Practical implications: Shows that studying learning and knowledge creation suggests proactive ways to capture and use knowledge across multiple missions and generations. Value: This paper provides a unique analysis of the learning process of a scientific space mission, relevant for knowledge management researchers and designers, as well as demonstrating in detail how new learning occurs in a learning organization.

Linde, Charlotte↗

Deactivation and decommissioning web log analysis using big data technology - 15710

The D and D Knowledge Management Information Tool (D and D KM- IT) is a web-based knowledge management information tool built for the D and D user community. Big data is a massive volume of structured and unstructured datasets which is so large that it's difficult to process using traditional database techniques. Web logs are the repository of files which are generated automatically for any operation on the web site. Web log files generated from the D and D KM-IT will be processed using the Apache Hadoop Framework to extract meaningful data. Hadoop is an open-source software framework for storing and processing big data in a distributed environment on large clusters of commodity hardware. Hadoop framework consists of two main layers: Hadoop distributed file system (HDFS) and the Execution engine (MapReduce). Automatic parallelization and distribution; clean and simple programming abstraction. Implementation: Web log files from the D and D KM-IT server are fetched using Apache Flume and loaded into the Hadoop distributed file system. Using the Apache Hcatalog tool, the web log data is parsed and converted into a structured table format. A Pig program is developed to query the tables to retrieve and store the significant information onto the HDFS. The extracted data is fed to business visualization tools such as Microsoft Excel for analysis and reporting. Results The reports generated through the web log data processing will be analyzed to improve the usability and performance of the D and D KM-IT. Conclusion/Future Work: User keyword information can be explored to add new trending topics to the D and D KM-IT application. Statistics generated can be compared to analysis reports from existing analytical tools.

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'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elements of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.

Big Data↗

Sodium Fast Reactor Safety and Licensing Research Plan – Volume I

This report proposes potential research priorities for the Department of Energy (DOE) with the intent of improving the licensability of the Sodium Fast Reactor (SFR). In support of this project, five panels were tasked with identifying potential safety-related gaps in available information, data, and models needed to support the licensing of a SFR. The areas examined were sodium technology, accident sequences and initiators, source term characterization, codes and methods, and fuels and materials. It is the intent of this report to utilize a structured and transparent process that incorporates feedback from all interested stakeholders to suggest future funding priorities for the SFR research and development. While numerous gaps were identified, two cross-cutting gaps related to knowledge preservation were agreed upon by all panels and should be addressed in the near future. The first gap is a need to re-evaluate the current procedures for removing the Applied Technology designation from old documents. The second cross-cutting gap is the need for a robust Knowledge Management and Preservation system in all SFR research areas. Closure of these and the other identified gaps will require both a reprioritization of funding within DOE as well as a re-evaluation of existing bureaucratic procedures within the DOE associated with Applied Technology and Knowledge Management.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

FJET Database Project: Extract, Transform, and Load

The Data Mining & Knowledge Management team at Kennedy Space Center is providing data management services to the Frangible Joint Empirical Test (FJET) project at Langley Research Center (LARC). FJET is a project under the NASA Engineering and Safety Center (NESC). The purpose of FJET is to conduct an assessment of mild detonating fuse (MDF) frangible joints (FJs) for human spacecraft separation tasks in support of the NASA Commercial Crew Program. The Data Mining & Knowledge Management team has been tasked with creating and managing a database for the efficient storage and retrieval of FJET test data. This paper details the Extract, Transform, and Load (ETL) process as it is related to gathering FJET test data into a Microsoft SQL relational database, and making that data available to the data users. Lessons learned, procedures implemented, and programming code samples are discussed to help detail the learning experienced as the Data Mining & Knowledge Management team adapted to changing requirements and new technology while maintaining flexibility of design in various aspects of the data management project.

excel vba↗

KM-IT Mobile Platform for D and D - 18300

Knowledge management (KM) is the practice or process responsible for gathering, analyzing, storing and sharing insights, experiences, knowledge, and information within an organization or community. The main focus of the Knowledge Management Information Tool (KM-IT) for the deactivation and decommissioning (D and D) community is to enhance safety through improved efficiencies (e.g., by reducing the need to rediscover the knowledge and experience gained over time and to promote the reuse of the existing knowledge). KM-IT serves as a centralized information repository and a common interface for D and D related activities. It facilitates the gathering, analysis, storage and sharing of knowledge and information within the D and D community. FIU has developed eight active modules as part of the web-based mobile application for the KM-IT, which can be accessed from m.dndkm.org: Vendor, Specialist Directory, Technology, Picture Library, Hotline, Lessons Learned, Best Practices and Fixatives. All of the mobile modules are scaled-down versions of the desktop module available at www.dndkm.org and publish data from the KM-IT database to the D and D community. FIU has recently developed a native mobile application for Android mobile devices for selecting D and D fixatives. This application runs natively on mobile devices and displays data through the fixative services which uses REST-based API for communication across mobile platforms. Xamarin Forms are used to develop the front-end application for the Android operating system (OS) and will be used for future platforms (iOS and Windows) as well. The native fixative application can be installed on mobile devices to search information related to fixatives, decontamination gels and strippable coatings applicable to D and D. The KM-IT platform includes a comprehensive database of commercially available fixatives and other contamination control products. Search functionality allows the user to filter and sort these products according to the search criteria or keyword. Three levels of refinement are available via a drill down menu for the criteria. (authors)

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LLM Generation of Online Courses from a Curated Set of Documents in the Nuclear Safeguards Domain

A multidisciplinary team at Argonne National Laboratory explores the application of advanced technologies to enhance knowledge transfer and retention within the nuclear safeguards domain. Specifically, it examines the feasibility of leveraging secure large language models (LLMs) to streamline the creation of e-learning modules for the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Safeguards (NA-241). The initiative addresses the critical need for preserving institutional memory and accelerating skill development amidst the imminent retirement of senior professionals in the field in addition to supporting good knowledge management practices. The project integrates instructional design theory with cutting-edge AI technologies to transform curated document sets from the Safeguards Knowledge Repository (SKR) into modular online courses. By automating the generation of learning objectives and instructional content, the effort aims to reduce manual effort while maintaining high-quality educational outcomes. A limited measure of human supervision, however, ensures accuracy, relevance, and alignment with NNSA’s strategic priorities. Key findings highlight the potential of AI-assisted course generation to support safeguards professionals by creating structured, interactive learning experiences. The report underscores the importance of SME validation to address limitations in AI-generated content, such as terminology errors and gaps in coverage. Recommendations include adopting a structured workflow combining LLM acceleration with expert oversight to ensure accuracy, usability, and alignment with learner needs. This work demonstrates Argonne’s commitment to advancing national security and scientific excellence through innovative knowledge management solutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Science and Engineering Team Repository Selection and Validation

The National Nuclear Security Administration’s Office of Nuclear Smuggling Detection and Deterrence (NSDD), Science and Engineering Team (SET) has engaged Brookhaven National Laboratory (BNL) in the selection, development and management of a knowledge management platform. This platform will serve as a repository for programmatic documents, data, and other relevant files. In support of this effort, BNL implemented a sixteen-month process to ensure the selection of the most relevant and user-friendly repository from among several commercially available and open source options.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Knowledge Capture and Management for Space Flight Systems

The incorporation of knowledge capture and knowledge management strategies early in the development phase of an exploration program is necessary for safe and successful missions of human and robotic exploration vehicles over the life of a program. Following the transition from the development to the flight phase, loss of underlying theory and rationale governing design and requirements occur through a number of mechanisms. This degrades the quality of engineering work resulting in increased life cycle costs and risk to mission success and safety of flight. Due to budget constraints, concerned personnel in legacy programs often have to improvise methods for knowledge capture and management using existing, but often sub-optimal, information technology and archival resources. Application of advanced information technology to perform knowledge capture and management would be most effective if program wide requirements are defined at the beginning of a program.

Goodman, John L.↗

Project Management Meets Change Management - A Success Story. Focus Area: Tech Perspectives TI012SN

Utilizing the concepts and terminology from Project Management, the process of planning and executing a Change Management (CM) Infrastructure improvement project is described. The primary audience for this presentation includes both experienced and relatively new CM administrators and their managers. It also includes anyone with an interest in the application of project management knowledge to CM administration. There are several benefits: the complexity of the CM tool technology is more manageable, CM administrators get to use project management knowledge to complete a project (not "firefighting"), improve relations with your customers (that means developers and managers), and get the opportunity to do it again.

Hall, Wayne↗

Panel Session 24B: Records, Knowledge, and Memory for Radioactive Waste Repositories: Generational Equity Focus

This panel focused on the latest thoughts, ideas, and methodologies being explored throughout the world on how to communicate with future generations regarding nuclear waste disposal. Scientists determined many years ago that geological disposal in a repository was the preferred solution for nuclear waste disposal given the longevity concerns of the waste(s). Future generations must be informed through records, memory keeping and permanent markers to ensure they are aware of, and knowledgeable of, the dangers associated with nuclear waste isolated from the biosphere. Panelists with presentations: You Want to Drill Where? Human Intrusion Messaging Considerations (Thomas Peake, Jonathan Major); Ethical Reflections on the Basic Reasons for RK and M Measures (Carl-Reinhold Brakenhielm); NEA Activities on Information, Data and Knowledge Management (Rebecca Tadesse); Records, Knowledge and Memory (RK and M) Across Generations: Recent Activities and Progress in Sweden (Claudio Pescatore)

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Planning Mars Memory: Learning from the Mer Mission

Knowledge management for space exploration is part of a multi-generational effort at recognizing, preserving and transmitting learning. Each mission should be built on the learning, of both successes and failures, derived from previous missions. Knowledge management begins with learning, and the recognition that this learning has produced knowledge. The Mars Exploration Rover mission provides us with an opportunity to track how learning occurs, how it is recorded, and whether the representations of this learning will be optimally useful for subsequent missions. This paper focuses on the MER science and engineering teams during Rover operations. A NASA team conducted an observational study of the ongoing work and learning of the these teams. Learning occurred in a wide variety of areas: how to run two teams on Mars time for three months; how to use the instruments within the constraints of the martian environment, the deep space network and the mission requirements; how to plan science strategy; how best to use the available software tools. This learning is preserved in many ways. Primarily it resides in peoples memories, to be carried on to the next mission. It is also encoded in stones, in programming sequences, in published reports, and in lessons learned activities, Studying learning and knowledge development as it happens allows us to suggest proactive ways of capturing and using it across multiple missions and generations.

Linde, Charlotte↗

Brahman

The Adversary & Interdiction Methods (AIM) program provides training and capability assessment services to government agencies around the country. Interdisciplinary teams equipped with gear and radioactive sources are repeatedly fielded to offsite events to collaborate with law enforcement agencies at all levels of government. AIM has grown rapidly over the past three years. A knowledge management system as evolved along with the program but it has failed to keep pace. A new system is needed. The new system must comply with cybersecurity and information technology solutions already in place at an institutional level. The offsite nature of AIM activities must also be accommodated. Cost and schedule preclude the commissioning of new software and the procurement of expensive hardware. The new system must exploit in-house capabilities and be established quickly. A novel system is proposed. This solution centers on a recently introduced institutional file sharing capability called Syncplicity. AIM-authored software will be combined with a dedicated institutional account to vastly extend the capability of this resource. The new knowledge management system will reduce error and increase efficiency through automation and be accessible offsite via mobile devices.

42 ENGINEERING↗