TRIPWIRE: Muti-Modal Distributed Sensing for Repository Verification [Slides]
The slides give an overview of the progress to date on project Tripwire.
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The slides give an overview of the progress to date on project Tripwire.
This presentation contains a review of the work conducted to date on project TRIPWIRE.
This report summarizes the research outcomes for the work performed in fiscal year 2020. The report is divided into two main sections addressing the radiation and electromagnetic sensing components. Both sections present an introduction with theory to lay the foundation of how the systems work. The report is the key deliverable for Task 1: Radiation and Electromagnetic Detector Development - Laboratory Work. This task involves all work related to initial laboratory research associated with the radiation and electromagnetic detector development to reach TRL-3.
TRIPWIRE is a multi-modal system for containment verification in inaccessible radiological and nuclear waste repositories. The sensing modes are focused on radiation, electromagnetic and vibration. The radiation detection component has been developed over the last three years at Idaho National Laboratory (INL). This development has focused on the fabrication, characterization, and testing of long-length (greater than 10-m) plastic scintillating fibers. This fiscal year, the focus of TRIPWIRE has been on field testing and demonstration of the radiation sensing component in a relevant environment. After reviewing the static storage facilities at INL, the Radioactive Scrap Waste Facility (RSWF) south storage area outside the Materials and Fuels Complex (MFC) was selected due to its periodic changes in configuration and inventory. This report summarizes the research outcomes for the work performed in fiscal year (FY) 2023.
The acoustic data of explosions and noise collected on smartphones were fed to the YAMNet model to obtain the scores of each class. The data was split 60/20/20 for training, validation, and testing. A single-layered neural network was trained using the computed scores to predict if the data was an explosion or noise. The trained model was then combined with the YAMNet model. The combined model was tested with the ESC-50 dataset to investigate overall accuracy and class based false positive rates.
This is a presentation for the Nuclear Security Applications Research and Development Program Review Meeting.
These slides contain the details of the central alarm station concept for the Tripwire project. The slides go over each detail of the graphic user interface.
This presentation documents the work done for Tripwire's alarm approaches.
Idaho National Laboratory (INL) recently conducted a workshop endorsed by the National Nuclear Security Administration (NNSA) under the auspices of the Defense Nuclear Nonproliferation R&D (DNN R&D) Office's Safeguards Portfolio. The workshop's primary objective was to foster an engaging dialogue among researchers, with a specialized emphasis on the safeguards pertaining to molten salt reactors. At INL, the installation of the state-of-the-art Molten Salt Thermophysical Examination Capability (MSTEC) is underway. This shielded argon glovebox facility, designed for both irradiated and non-irradiated actinide materials, represents the cutting edge of research infrastructure. MSTEC is poised to serve as a pivotal research platform in the realm of molten salt technology, with significant implications for safeguards applications. Participants of the workshop had the opportunity to tour the facilities, including the site where MSTEC is being installed, as well as to observe the INL's molten salt and pyroprocessing research hot cells. The event featured insightful presentations delving into molten salt chemistry and the MSTEC project. Each participating laboratory contributed to the discourse with presentations on their respective research efforts addressing safeguards in relation to molten salt reactors. The workshop culminated with a generative brainstorming session, where participants shared their thoughts on strategic integration with partner agencies, aiming to synergize efforts in advancing the field of nuclear safeguards.
This report summarizes a technology-inclusive and performance-based method to determine the physical security licensing basis for a commercial nuclear reactor under the proposed 10 CFR 73.100 for Part 53 licensees. The method focuses on the identification of security functions, the contributing security systems and programs to meet those functions, the identification of security events that will provide the foundation for the security licensing basis and includes a risk-informed performance-based defense in depth adequacy method. The method can also be employed to justify performance-based alternative measures to traditional security requirements found in 10 CFR 73.55.
The Nuclear Forensics International Technical Working Group (ITWG), in an evidentiary sense, has Dr. Klaus Mayer’s fingerprints all over it. His contributions to the working group and the broader international nuclear forensics community have been profound. As Klaus retires from the European Commission’s Joint Research Centre in Karlsruhe, Germany (JRC-Karlsruhe), it is only fitting to reflect on his dedication and lasting impact on nuclear forensics—guiding its evolution from its early days to its establishment as a vital tool for competent authorities in preventing and responding to the serious threat of nuclear and other radioactive materials out of regulatory control.
Next-generation advanced reactors (ARs) incorporate enhanced safety systems, have smaller source terms, and feature compact modular designs, which should lessen their collective risk profiles. However, to fully evaluate risk, security needs to be a part of the equation. Without taking security into consideration, safety systems and components in the new ARs may be vulnerable to sabotage. These base attributes, coupled with enhanced security features specific to AR design through sound engineering and security-by-design (SeBD), should provide developers and operators with lower inherent security risk profiles. Building security early into the AR design may remove or passively secure potential critical targets from an adversary’s reach , thereby increasing overall safety and security. An integrated approach and diverse design team that includes engineering, operations, and security experts are fundamental to building security into the design without sacrificing fundamental operational efficiencies and principles. The objective of this project was to evaluate the security and safety interfaces for five classes of reactors, identify potential security vulnerabilities of structures, systems, and components (SSC), and underscore the need to consider security alongside safety in the design o f these concepts. The five reactor classes evaluated in this project and presented in this report are molten-salt reactors (MSR), high temperature gas reactors (HTGR), sodium-fast reactors (SFR), advanced light-water reactors (ALWR), and microreactors. These designs were selected because they reflect the concepts that are closest to market deployment and have received significant resource investments from the public and private sector. This project assesses the inherent security risks posed by common classes of ARs, provides a methodology and framework to assess security along with safety, and offers an analysis of potential mitigation strategies that could be incorporated. For each AR technology, the SSCs that relate to radionuclide source safety functions are discussed to understand the SSC contribution to safety and relative importance in the protective strategy for the design. The assumptions that went into evaluating each reactor concept originated from generic publicly available nonproprietary information and should not directly be used to qualify an absolute risk profile nor to rank specific AR designs. Instead, the purpose of the analysis is to understand and compare the generic inherent security risks of different AR technologies.
Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. In general, uncertainty quantification techniques ignore correlations between experiments and shared parts. Experiments, such as the TEX (Thermal/Epithermal eXperiments) campaigns, consist of many shared parts, such as the ‘Jemima’ HEU fuel plates, which create a strong correlation in their uncertainties. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes an intuitive method of determining the covariance for each of the experimental components, providing a correlation for each family of parts across the multiple cases examined within a benchmark. A proof-of-principle study using the TEX-HEU experimental campaign was performed and verified that the correlations can be calculated with information commonly found in the ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. This study showed that the introduction of model and experimental covariances reduces the χ 2 per degree of freedom from 2.203 to 1.179, indicating that the omission causes overly pessimistic bias quantifications. This technique can be seamlessly integrated to current benchmark evaluations as well as reevaluations of legacy benchmarks.
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Understanding techniques to strengthen the nuclear safeguards regime is crucial in preventing nuclear proliferation due to recent advancements in the nuclear energy industry such as Generation IV reactors and microreactors. Prior to the construction of a nuclear power plant, it is necessary to understand the proliferation potential of the plant's reactor. Digital twins serve as a unique solution to recognizing reactor behavior indicative of nuclear proliferation. A digital twin is defined as a virtual model that works in unison to represent a physical asset, with a transference of data between the virtual and physical assets [1]. This work serves as validation for training a digital twin on synthetic data fabricated via means of Serpent reactor physics and point kinetics equations simulations. In this case this work is based on parameters of Idaho State University's AGN-201 reactor. The synthetic data can then be utilized to train machine learning models in the future to further investigate the utility of these methods. The accuracy of the predicted data is measured against real operational data to verify the reliability of the synthetic data creation methods and decide whether these methods should be used in the future to inform inspectors of a reactor's proliferation potential.
Abstract not provided.
The requirements for U.S. nuclear power plants to maintain a large on-site physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an update on the progress in applying a dynamic computational framework that links results from a commercially available force-on-force simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework or MASS-DEF. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report does not contain any plant's sensitive information and/or Safeguards Information. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.
The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.