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At least 109 records · Page 6

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)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Semantic Property Graph for Scalable Knowledge Graph Analytics

Graphs are a natural and fundamental representation to describe entities, relationships, activities, and evolution of complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Resource Description Framework (RDF) and Labeled Property Graph (LPG) are two of the most used data models to encode information in a graph. Both models are similar in terms of using basic graph elements such as nodes and edges but differ in terms of the modeling approach, expressibility, serialization, and target applications. RDF is a flexible data exchange model for expressing information about entities but it tends to a have high memory footprint and inefficient storage, which does not make it a natural choice to perform scalable graph analytics. In contrast, LPG has gained traction as a reliable model to perform scalable graph analytic tasks such as sub-graph matching, network alignment, and real-time knowledge graph query. It provides efficient storage, fast traversal, and flexibility to model various real-world domains. At the same time, the LPG lacks the support of a formal knowledge representation such as an ontology to provide automated knowledge inference. We propose Semantic Property Graph (SPG) as a logical projection of reified RDF into the LPG model. SPG continues to use RDF ontology to define the type hierarchy of the projected graph and validate it against a given ontology. We present a framework to convert reified RDF graphs into SPG using two different computing environments. We also present cloud-based graph migration capabilities using Amazon Web Services.

Purohit, Sumit↗

Developing a digital twin framework for remotely monitoring nuclear reactor facilities

A digital twin must seek to represent all applicable functional components of the system of interest. Different expertise is required for understanding the physical system being modeled than the skills needed for transforming those models into a functional digital twin through physics modeling, machine learning analysis, and visualization. The diversity of knowledge requires a multi-disciplinary team to ensure all system details are captured. Team members also need a method to verify that the data they generate within their domain can be effectively communicated to professionals in other fields. To address this challenge, this work provides an approach for developing a digital twin framework to remotely monitoring nuclear facilities. Through this, general knowledge of the framework is presented along with two examples to solidify the process. The AGN-201 digital twin and microreactor digital twins provide varying levels of complexity in a potential nuclear facility, where common threads are identified and lessons learned are provided. The goal of this research is to aid future researchers by providing a formula for a successful digital twin and in turn reducing the development time of nuclear system digital twins, specifically for remote monitoring.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

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

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

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Using Digital Trace Data to Identify Regions and Cities

A greater understanding of human dynamics as they play out in both physical space and through inter-personal communication is vital for the design and development of intelligent and resilient cities. Physical context provides insight in to the space-time distribution of population and their activity patterns, while inter-personal communication can, for the first time, be measured at scale through virtual interactions. The confluence of these two enables spatial social network analysis in the built environment for edge computing, knowledge discovery, and artificial intelligence activities. In this work, we propose a novel method to discover such dynamics. We use a dataset of 72 million tweets to develop a spatially embedded network of communication, and then use community detection algorithms to explore regional and urban delineation in the United States. We find that the broad spatial delineation of communities and community sub-structure is consistent with major United States socio-cultural regions, states, and major metropolitan areas. We describe how these methods could be extended to generate a measure of socially cohesive regions that can be consistently applied anywhere there is a sufficiently rich data source. We hope the proposed methods will generate new perspectives on smart and resilient cities.

Brelsford, Christa↗

International Training to Promote Successful Environmental Remediation Projects - 18636

The International Atomic Energy Agency (IAEA) supports the efforts of its Member States to manage their nuclear and radiological liabilities, including radioactive waste management, decommissioning of facilities, and remediation of contaminated sites. As part of a project addressing Constraints in Decommissioning and Environmental Remediation (the CIDER Project), the IAEA is developing initiatives to further support capacity development specifically to promote implementation of safe, appropriate, and cost-effective environmental remediation (ER) projects. The IAEA sponsors numerous initiatives to provide its Member States training on important topics related to ER. It has become clear in recent years, however, that the existing training should be augmented with more in-depth training to provide for the development of the critical expertise needed to address significant ER challenges. ER projects typically are very complex, requiring the integration of numerous scientific and engineering disciplines, along with effective project planning and management. There are many examples of ER projects where considerable work has been completed, qualified technical staff are available, and adequate funding has been obtained, yet actual progress towards a final solution has been limited. In such cases, it appears that a key barrier is the lack of capacity to develop strategies, make fully informed decisions, plan for and manage activities, and implement successful ER actions. In light of the above, the IAEA has placed a priority on capacity development across the broad spectrum of ER project implementation. Efforts are underway to develop a new training program to develop capacity at the institutional and individual levels to equip course graduates to effectively integrate all areas of expertise in the planning and execution of ER projects. The target audience includes decision-makers; project managers, planners, and implementers; and academics. The core capabilities to be developed via this program include knowledge and skills related to: (1) radiation issues and radionuclide behavior; (2) health and safety protection principles and requirements; (3) identification, evaluation, and selection of ER technologies and approaches; (4) ongoing, constructive dialogue with stakeholders; (5) project planning, management, and communication; (6) cost estimation and funding development; and (7) implementation of appropriate site monitoring activities. The IAEA is collaborating with multiple organizations to develop and implement this training program, to leverage existing training programs and materials, and to coordinate on the development of sustainable training solutions. This paper will present the status of this initiative and work accomplished thus far. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Diffusion of Innovations: Interplay of Social, Economic, Technological, and Policy Drivers in the Solar Industry. Summary of UT Austin Student Capstone Research Projects

The University of Texas at Austin’s Policy Research Project (PRP), a nine-month (two semesters) capstone, is a keystone of the core curriculum at the LBJ School of Public Affairs. In PRPs, small groups of students, under the mentorship of a faculty director, take on real-world problems that require special knowledge and skill sets. PRPs expose students to challenges in formulating and executing research, and in communicating academic research and related complex data to broader stakeholder communities and decision makers. The PRP structure is an innovative and effective approach for integrating research within the teaching and training of graduate students who are preparing themselves to address important real-world problems at the intersection of society, economics, technology, and policy. The project summaries below describe seven papers developed during September 2017 – May 2018 as part of a PRP on “Diffusion of Innovations: Interplay of Social, Economic, Technological, and Policy Drivers in the Solar Industry.” Twenty graduate students, drawn from the LBJ School’s Masters in Public Affairs and Masters in Global Policy Studies programs and the Jackson School Geoscience’s Energy and Earth Resources program, participated in this PRP. Dr. Varun Rai, Associate Professor and Associate Dean for Research at the LBJ School, directed the PRP, with support from his research team including: Dr. Ariane Beck, Dr. Ashok Sekar, D. Cale Reeves, and Erik Funkhouser. Clients for the project included the U.S. Department of Energy (Casey Canfield), Lawrence Berkeley National Laboratory (Ben Hoen, Galen Barbose Joachim Seel, Naïm Darghouth, Ryan Wiser), and National Renewable Energy Laboratory (Benjamin Sigrin, Eric O’Shaughnessy). The seven projects separately addressed one of the following topics: (1) low- and middle-income PV adoption, (2) modeling economic and information intervention design, (3) evaluation of DOE’s Solar in Your Community Challenge, (4) property value impacts near large-scale solar facilities, (5) solar market maturity and evolution of business models, (6) social media data for predicting PV adoption, and (7) individual-level variation in adoption of innovations. Many of the papers relied on data collected and curated by Lawrence Berkeley National Laboratory, including data embedded within the annual Tracking the Sun and Utility-Scale Solar reports. Each of the seven teams in the PRP prepared a research paper. The PRP culminated with a full-day conference at UT Austin in May 2018 to present findings from the seven projects in this PRP to a broad audience of about 75 experts from academia, national labs, industry, and government from across the country.

14 SOLAR ENERGY↗

A section 110 evaluation of the huron king test chamber, area 3, nevada national security site, nye county, nevada

The U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office tasked Desert Research Institute (DRI) with the identification and evaluation of the Huron King Test Chamber as part of their cultural resources program obligations under Section 110 of the National Historic Preservation Act. The Huron King nuclear test was a vertical line-of-sight weapons effects test that took place in Area 3 on June 24, 1980. Unique to this event was a specially designed aboveground test chamber that held a model defense communications satellite in a vacuum tank meant to replicate the space environment. Sponsored by the Defense Nuclear Agency, the purpose of the experiment was to understand the response of the satellite and its materials and equipment to an electromagnetic pulse and attendant radiation. Between July and August 2022, DRI conducted an archival review on the Huron King experiment and its associated test chamber. Subsequently, pedestrian fieldwork was undertaken at the Huron King Test Chamber by DRI on September 29, 2022. During fieldwork, the outside of the test chamber was documented using a Nevada State Historic Preservation Office Architectural Resource Assessment form. This effort included verifying the substructures that compose the test chamber as determined by the archival review, as well as obtaining a detailed photographic recordation of the exterior and assessing its current condition. Notably, the site where the Huron King test took place has been abandoned and almost entirely naturalized. All of the portable instrumentation trailers, communications and data cabling, and winch systems used to retract the test chamber following the detonation were removed after completion of the experiment in 1980. Only the subsidence crater and the test chamber remain as physical evidence of this experiment. Based on these findings, DRI recommends that the Huron King Test Chamber is eligible for listing in the National Register of Historic Places (NRHP) at the local level under Significance Criteria A and C and that it meets Criteria Consideration G for properties less than 50 years old.

54 ENVIRONMENTAL SCIENCES↗

Dynamic defense and network randomization for computer systems

The various technologies presented herein relate to determining a network attack is taking place, and further to adjust one or more network parameters such that the network becomes dynamically configured. A plurality of machine learning algorithms are configured to recognize an active attack pattern. Notification of the attack can be generated, and knowledge gained from the detected attack pattern can be utilized to improve the knowledge of the algorithms to detect a subsequent attack vector(s). Further, network settings and application communications can be dynamically randomized, wherein artificial diversity converts control systems into moving targets that help mitigate the early reconnaissance stages of an attack. An attack(s) based upon a known static address(es) of a critical infrastructure network device(s) can be mitigated by the dynamic randomization. Network parameters that can be randomized include IP addresses, application port numbers, paths data packets navigate through the network, application randomization, etc.

97 MATHEMATICS AND COMPUTING↗

Multimodal communication system

A multimodal communication system includes a vehicle controller that controls one or more systems or subsystems of an unmanned vehicle. The communication controller manages communication and logical access to the unmanned vehicle. One or more sensors in communication with the communication controller detects and measures physical properties in proximity to the unmanned vehicle. Transceivers receive the unmanned vehicle commands that are transmitted simultaneously or concurrently and a monotonic generator generates a monotonic object each time the unmanned vehicle's operating state changes. The communication controller executes the first unmanned vehicle command received that has the correct cryptographic hash validating knowledge of the unmanned vehicle's current operating state.

Duncan, Andrew M.↗

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)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Test your Trinity knowledge, print a 75th anniversary poster

To commemorate the 75th anniversary of the Trinity test, award-winning artist and graphic designer Paul Ziomek (Communication Arts and Services, CPA-CAS), illustrated an original poster. This one-of-a-kind work of art features Los Alamos Physicist Enrico Fermi witnessing the world’s first detonation of a nuclear device, the Gadget, on July, 16, 1945. This moment marked one of the greatest scientific achievements of all time and the dawn of the nuclear age. The work of those Los Alamos scientists – documented in their notebooks, photos, films, engineering drawings, and memos to each other – is part of the collections in the National Security Research Center, the Lab’s classified library located in the National Security Sciences Building.

99 GENERAL AND MISCELLANEOUS↗

Characterization and identification of HPC applications at leadership computing facility

High Performance Computing (HPC) is an important method for scientific discovery via large-scale simulation, data analysis, or artificial intelligence. Leadership-class supercomputers are expensive, but essential to run large HPC applications. The Petascale era of supercomputers began in 2008, with the first machines achieving performance in excess of one petaflops, and with the advent of new supercomputers in 2021 (e.g., Aurora, Frontier), the Exascale era will soon begin. However, the high theoretical computing capability (i.e., peak FLOPS) of a machine is not the only meaningful target when designing a supercomputer, as the resources demand of applications varies. A deep understanding of the characterization of applications that run on a leadership supercomputer is one of the most important ways for planning its design, development and operation. In order to improve our understanding of HPC applications, user demands and resource usage characteristics, we perform correlative analysis of various logs for different subsystems of a leadership supercomputer. This analysis reveals surprising, sometimes counter-intuitive patterns, which, in some cases, conflicts with existing assumptions, and have important implications for future system designs as well as supercomputer operations. For example, our analysis shows that while the applications spend significant time on MPI, most applications spend very little time on file I/O. Combined analysis of hardware event logs and task failure logs show that the probability of a hardware FATAL event causing task failure is low. Combined analysis of control system logs and file I/O logs reveals that pure POSIX I/O is used more widely than higher level parallel I/O. Based on holistic insights of the application gained through combined and co-analysis of multiple logs from different perspectives and general intuition, we engineer features to "fingerprint" HPC applications. We use t-SNE (a machine learning technique for dimensionality reduction) to validate the explainability of our features and finally train machine learning models to identify HPC applications or group those with similar characteristic. To the best of our knowledge, this is the first work that combines logs on file I/O, computing, and inter-node communication for insightful analysis of HPC applications in production.

Liu, Zhengchun↗

Detecting Unclassified Electromagnetic Signals for Secure Wireless Communication Using Open Set Recognition

We developed multiple machine learning methods for the detection and classification of new wireless communication waveforms, which is critical for targeted attacks in wireless networks and electronic warfare. Our machine learning models are capable of dynamically detecting security threats in near real time through our advanced open set recognition (OSR) approach. This model has demonstrated significant improvements in the detection of unknown waveforms, thereby enhancing the security and reliability of mission critical communications. Our approach to detecting uncertain security threats is novel; we advanced OSR techniques by incorporating domain knowledge of wireless signals. Specifically, we combined time and frequency domain model features to enhance the model’s performance. Utilizing an OSR approach eliminates the need for training data to be distributed similarly to the deployment environment and removes the requirement for the training set to contains all possible threat classes. This is crucial because it is often infeasible to determine and characterize all potential security threats in advance. Our model were trained on simulated data, generated in partnership with the University at Albany, State of New York. The data set contained a diverse array of wireless signals, including those with additive white Gaussian noise and multipath signals, with and without line of sight. This comprehensive training set allowed us to optimize our models to detect unknown waveforms under various challenging scenarios, such as low signal-to-noise ratios. By training on various waveforms, varying signal-to-noise ratio, and different sample sizes under normal conditions, our models were fine tuned to perform effectively in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗

Abstract for CRADA between VariGrid Explorations Inc. and NETL (AGMT-0863)

As the energy industry continues to invest in data, big data, and advanced analytics to improve production, reduce operation and maintenance costs, improve safety, and reduce risks, uncertainty will serve as a limiting factor in the success of these operations. Intuitive communication of uncertainty can provide more transparency in the decision-making process; offering the ability to more accurately evaluate the risk and impact of decisions, identify data and knowledge gaps, and evaluate trade-offs. The issue of uncertainty will thus play a large role in the success of investments that rely on big data and data analytics. However, no robust method for representation of uncertainty in spatial data visuals currently exists. As such, uncertainty is, at best, communicated using multiple independent visuals and aggregated in final displays, or frequently omitted altogether. Failure to accurately and effectively quantify and communicate uncertainty poses a barrier, limiting critical information that would better allow businesses to make more accurate and intelligent decisions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Experimenting in the cloud: The digital divide's impact on innovation

This paper builds on a recent National Science Foundation working paper that identified a strong association between cloud use and various types of innovation but did not consider whether 1) cloud adoption is a reliable indicator of the innovation orientation of a firm, or 2) cloud adoption enables various types of innovation. We estimate propensity score matching and endogenous treatment effect models to control for innovation orientation, producing evidence to test the second explanation. Here, findings support an enabling effect of the cloud on innovation providing concrete evidence of the adverse impact of the digital divide.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Feedback Power Cost Optimization in Power Distribution Networks with Prosumers

Here, we propose a feedback control approach for solving optimal power flow (OPF) problems in power distribution networks (DNs) based on a projected gradient scheme, where the cost is given by the sum of functions of local power injections. This approach does not require detailed knowledge of the grid model and enables real-time tracking of the optimal generation configuration. Moreover, the communication burden is minimal: only a broadcast from a central entity, called the Network Supervisor (NS), to the agents in the network is needed. Hence, agents do not have to share local information that can be sensitive, e.g., their power injections or the value of the local costs. Our approach is then used to solve a particular OPF problem targeting DNs with high penetration of distributed energy resources (DERs) in which the energy cost is given by the remuneration that the DERs owners receive for the service they provide.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Regulatory and Licensing Strategy for Microreactor Technology

With electricity demand on the rise, an increase in the use of nuclear energy is needed in order to meet future energy demands. The use of nuclear energy will not only begin to positively address this demand, but will also mitigate the negative impacts of carbon-induced climate change and provide energy security to the United States. An appropriate option to address the increasing energy demand is the use of advanced reactor systems like microreactors. Microreactors, often referred to as special-purpose reactors or vSMRs, are neutronically simple, factory manufacturable, easily transportable, and designed to produce less than 20 MWt (for classification as Hazard Category 2 per 10 CFR 830, DOE STD 1027). These reactors are decentralized energy sources that have the ability to provide sustainable and affordable power to remote communities and to industrial users, while having self-contained geometry that requires very low maintenance care. In order for microreactors to be approved for operation, they must abide by and successfully complete a rigorous regulatory and licensing process monitored by the Nuclear Regulatory Commission (NRC), the Department of Energy (DOE), or the Department of Defense (DoD). Because microreactors are a relatively new and disruptive technology, there is no clear licensing path for them to follow. Current licensing frameworks are tailored specifically to large, traditional light water reactors (LWRs) that have been developed and understood by the nuclear industry for many years. Unlike LWRs, microreactors have major design differences, specifically in the materials, coolant, reflectors and potential technology applications used. They also have higher in-core operating temperatures, which have the potential to push the materials used past their allowable limits. Because they are much smaller, safety margins, the amount of space required for assembly, and the distances required to meet dose-based regulatory criteria can technically be altered to better fit their new size. The following strategies and recommendations are intended to assure that key licensing issues do not influence the path to microreactor development, demonstration, and commercialization: Nuclear Regulatory Commission • The NRC should address the lack of knowledge and support of risk informed decision-making concepts from staff members and continue to advance and communicate risk initiatives using their Risk Informed Steering Committee • More research should be done into whether or not microreactors, which are small Class 103 facilities, can be licensed using Class 104-type guidance (e.g., NUREG 1537) • The NRC should use frequency-consequence curves to incrementally reduce regulatory uncertainty and risk to facilitate future construction and operation of advanced reactor designs Department of Energy • The DOE should continue to implement their multi-step Phenomena Identification and Ranking Table process in order to help detect and recommend the major design and technology work needed for licensing future reactor systems • The DOE should consider a joint licensing approach with the NRC where microreactors first go through the DOE process, then finish with the NRC process, providing an advantage for both applicants and NRC staff Department of Defense • The DoD should invest in personnel with sufficient expertise, incorporate their military reactors into tactical power systems, and self-regulate using Section 91b of the Atomic Energy Act Transportation • Licensees should convert enriched uranium hexafluoride into metal or oxide at an enrichment facility and then transport them to a fabrication facility • To avoid transportation issues altogether, licensees should consider positioning the enrichment and fabrication facilities on the same site • The DOE should provide their support in developing new shipping packages for safe transport, criticality benchmark data needed to license high-assay low-enriched uranium fuel facilities and transport packages, and provide financial and technical help to the Department of Transportation; and, • The NRC should help transportation efforts by finalizing and developing guidance for implementing 10 CFR 73 and 10 CFR 74 specifically for Category 2 Special Nuclear Material.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗