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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Transparent application-layer/os deeper packet inspector

A computer-implemented method of deep packet inspection (DPI) in a network is provided. The method comprises collecting data packets comprising a number of traffic flows from a number of devices via a number of traffic taps and classifying each traffic flow according to data about network protocol layers of the packets comprising the traffic flow. Application layer metadata is extracted from the packets. Traffic flow classification data and the extracted metadata are ingested into a data cluster and normalized. The normalized classification data and extracted metadata is then correlated to other data sets.

Urias, Vincent↗
DOE OSTI2013

Use of InSpector{sup TM} 1 1000 Instrument with LaBr{sub 3} for Nuclear Criticality Safety (NCS) Applications at the Westinghouse Hematite Decommissioning Project (HDP) - 13132

The Westinghouse Hematite Decommissioning Project (HDP) is a former nuclear fuel cycle facility that is currently undergoing decommissioning. One aspect of the decommissioning scope is remediation of buried nuclear waste in unlined burial pits. The current Nuclear Criticality Safety program relies on application of criticality controls based on radiological setpoints from a 2 x 2 Sodium Iodide (NaI) detector. Because of the nature of the material buried (Low Enriched Uranium (LEU), depleted uranium, thorium, and radium) and the stringent threshold for application of criticality controls based on waste management (0.1 g {sup 235}U/L), a better method for {sup 235}U identification and quantification has been developed. This paper outlines the early stages of a quick, in-field nuclear material assay and {sup 235}U mass estimation process currently being deployed at HDP. Nuclear material initially classified such that NCS controls are necessary can be demonstrated not to require such controls and dispositioned as desired by project operations. Using Monte Carlo techniques and a high resolution Lanthanum Bromide (LaBr) detector with portable Multi-Channel Analyzer (MCA), a bounding {sup 235}U mass is assigned to basic geometries of nuclear material as it is excavated. The deployment of these methods and techniques has saved large amounts of time and money in the nuclear material remediation process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

NASA NDE Fracture Critical Detectable Flaw Sizes History and Methodology

NASA requires that NDE methods and inspectors demonstrate 90% Probability of Detection (POD) with 95% confidence for critical flaw sizes when inspecting fracture critical metallic components. NASA addresses the known variability of NDE inspector capability in two ways. The first, Special NDE, requires that every inspector demonstrate the required 90/95 POD, which is resource intensive. The second approach is Standard NDE for which conservative flaw sizes for different NDE methods are provided such that it is expected that most properly trained inspectors will exceed the 90/95 POD requirement. As such, individual POD demonstration testing is not required. The origin of NASA Standard NDE dates to the start of the Space Shuttle Program in the early 1970’s. In the first study to quantitatively assess NDE methods and inspectors, the performance of multiple inspectors was evaluated for different NDE methods using a large set of fatigue cracked specimens. A rudimentary POD analysis was performed to estimate the 90/95 POD flaw size for each inspector for each method. Additionally, the average and standard deviation of the 90/95 POD flaw size across the multiple inspectors was calculated to estimate the flaw size for which 95 percent of inspectors would provide the 90/95 POD capability. These estimated 90/95/95 POD flaw sizes evolved into the NASA Standard NDE flaw sizes still in use for structural analysis five decades later. The methodology for performing Standard NDE POD studies was never documented in NASA requirements. Furthermore, POD analysis methods have significantly evolved since this seminal study. Likewise, NDE methods have improved and there has been a push to reassess Standard NDE flaw sizes for existing methods, and to develop Standard NDE flaw sizes for new methods such as digital radiography. In this study, a Standard NDE POD methodology was developed and baselined using the historical data. This reanalysis of the historical data identified several deficiencies in the original test plan as well as an overall lack of conservatism in the estimated 90/95/95 POD flaw sizes. The results of this historical review and the new methodology are being incorporated into an update of NASA NDE POD requirements.

Nondestructive Evaluation↗
NASA NTRS2006

3D X-Ray Luggage-Screening System

A three-dimensional (3D) x-ray luggage- screening system has been proposed to reduce the fatigue experienced by human inspectors and increase their ability to detect weapons and other contraband. The system and variants thereof could supplant thousands of xray scanners now in use at hundreds of airports in the United States and other countries. The device would be applicable to any security checkpoint application where current two-dimensional scanners are in use. A conventional x-ray luggage scanner generates a single two-dimensional (2D) image that conveys no depth information. Therefore, a human inspector must scrutinize the image in an effort to understand ambiguous-appearing objects as they pass by at high speed on a conveyor belt. Such a high level of concentration can induce fatigue, causing the inspector to reduce concentration and vigilance. In addition, because of the lack of depth information, contraband objects could be made more difficult to detect by positioning them near other objects so as to create x-ray images that confuse inspectors. The proposed system would make it unnecessary for a human inspector to interpret 2D images, which show objects at different depths as superimposed. Instead, the system would take advantage of the natural human ability to infer 3D information from stereographic or stereoscopic images. The inspector would be able to perceive two objects at different depths, in a more nearly natural manner, as distinct 3D objects lying at different depths. Hence, the inspector could recognize objects with greater accuracy and less effort. The major components of the proposed system would be similar to those of x-ray luggage scanners now in use. As in a conventional x-ray scanner, there would be an x-ray source. Unlike in a conventional scanner, there would be two x-ray image sensors, denoted the left and right sensors, located at positions along the conveyor that are upstream and downstream, respectively (see figure). X-ray illumination may be provided by a single source or by two sources. The position of the conveyor would be detected to provide a means of matching the appropriate left- and right-eye images of an item under inspection. The appropriate right- and left-eye images of an item would be displayed simultaneously to the right and left eyes, respectively, of the human inspector, using commercially available stereo display screens. The human operator could adjust viewing parameters for maximum viewing comfort. The stereographic images thus generated would differ from true stereoscopic images by small distortions that are characteristic of radiographic images in general, but these distortions would not diminish the value of the images for identifying distinct objects at different depths.

Fernandez, Kenneth↗
DOE OSTI2021

Deep Learning Systems for Increased Safeguards Surveillance Review Productivity

Nuclear safeguards inspectors expend significant time and maintain intense focus in reviewing video surveillance for safeguards relevant events. To increase efficiency and reduce the time burden of safeguards inspectors performing surveillance data review, this paper presents a novel deep learning (DL) systems concept to integrate generalized DL models into the safeguards surveillance review workflow. The Agency is investigating several DL algorithms for object recognition, localization, tracking, and flagging relevant activities. The project team is working closely with nuclear safeguards inspectors to identify review use cases (based on specific safeguards objectives) and collect their associated requirements. We focused on CANDU and LWR Nuclear Power Plants (NPPs) and their associated dry storage areas as these present a particularly heavy burden on the inspector surveillance review process due to the number of these facilities under safeguards worldwide. Initial DL algorithm results on safeguards data are promising. Using a convolutional neural network, the team attained a mean average precision (mAP) of 92.9% identifying and localizing spent fuel (SF) casks from a 475 surveillance image dataset. Further, the team had initial success in training a recurrent neural network to identify reactor area activities in video clips, successfully indicating when SF casks enter or exit a pool. We discuss how such DL algorithms would be integrated into the Next Generation Surveillance Review (NGSR) software application. Another issue impacting review productivity is the long time inspectors may have to wait when running these algorithms in NGSR. We present a concept to pre-process remotely collected surveillance data with DL models as the data arrives to IAEA headquarters so that results are already available when starting a new review in NGSR. The proposed DL system concept shows a pathway and workflow for increasing an inspector’s surveillance review productivity by quickly and accurately identifying declared and undeclared safeguards relevant objects and activities in large quantities of surveillance imagery data.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Tamper-Indicating Enclosures with Visually Obvious Tamper Response

Sandia National Laboratories is developing a way to visualize molecular changes that indicate penetration of a tamper-indicating enclosure (TIE). Such "bleeding" materials (analogous to visually obvious, colorful bruised skin that doesn't heal) allows inspectors to use simple visual observation to readily recognize that penetration into a material used as a TIE has been attempted, without providing adversaries the ability to repair damage. Such a material can significantly enhance the current capability for TIEs, used to support treaty verification regimes. Current approaches rely on time-consuming and subjective visual assessment by an inspector, external equipment, such as eddy current or camera devices, or active approaches that may be limited due to application environment. The complexity of securing whole volumes includes: (1) enclosures that are non-standard in size/shape; (2) enclosures that may be inspectorate- or facility-owned; (3) tamper attempts that are detectable but difficult or timely for an inspector to locate; (4) the requirement for solutions that are robust regarding reliability and environment (including facility handling); and (5) the need for solutions that prevent adversaries from repairing penetrations. The approach is based on a transition metal ion solution within a microsphere changing color irreversibly when the microsphere is ruptured. Investigators examine 3D printing of the microspheres as well as the spray coating formulation. The anticipated benefits of this work are passive, flexible, scalable, cost-effective TIEs with obvious and robust responses to tamper attempts. This results in more efficient and effective monitoring, as inspectors will require little or no additional equipment and will be able to detect tamper without extensive time-consuming visual examination. Applications can include custom TIEs (cabinets or equipment enclosures), spray-coating onto facility-owned items, spray-coating of walls or structures, spray-coatings of circuit boards, and 3D-printed seal bodies. The paper describes research to-date on the sensor compounds and microspheres.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Tamper-Indicating Enclosures with Visually Obvious Tamper Response (Final Project Report)

Sandia National Laboratories is developing a new method for detecting penetration of tamper - indicating enclosures (TIEs). This method incorporates the use of "bleeding" materials (analogous to visually obvious, colorful bruised skin that doesn't heal) into the design of TIEs. As designed, it will allow inspectors to use simple visual observation to detect attempts to penetrate the external surfaces of a TIE, without providing adversaries the ability to repair damage. A material of this type can enhance tamper indication of current TIEs used to support treaty verification regimes. Current TIE inspections are time - consuming and rely on subjective visual assessment by an inspector, equipment such as eddy current or camera devices, or involve approaches that may be limited due to application environment. The complexities and requirements that volumetric sealing methods (or TIEs) must address are: (1) enclosures that are non - standard in size/shape; (2) enclosures that may be inspectorate - or facility - owned; (3) finding tamper attempts that are difficult and time consuming for an inspector to locate; (4) enclosures that are reliable and durable enough to survive the conditions that exist in the operating environment (including facility handling); and (5) methods that prevent adversaries from repairing penetrations. Early project R&D [1] focused on encapsulated transition metals. Due to the challenges associated with the transition metal - based approach, a mitigation approach was investigated resulting in two separate research paths — one that involves fabricating custom TIE molds that meet the specific (size and shape) needs of safeguards equipment a nd one that can be deployed as a sprayed on or painted coating to an existing TIE or surface. The "custom mold" approach is based on creating thin layers of materials that , when penetrated, expose an inner material to O 2 which causes an irreversible color change. The "in-situ coating" approach is based on applying a sensor solution containing color changing microcapsules that bleed when the microcapsule is ruptured. The anticipated benefits of this work are passive, flexible, scalable, robust , cost-effective TIEs with visually obvious responses to tamper attempts. This provides more efficient and effective monitoring , as inspectors will require little or no additional equipment and will be able to detect tamper without extensive time - consuming visual examination. Applications include custom TIEs (cabinets , equipment enclosures or seal bodies ), or spray-coating/painting onto facility-owned items, walls or structures, or circuit boards. The paper describes research and testing completed to-date on the method and integration of select system components.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Laboratory and Field Testing of Commercially Available Detectors for the Identification of Chemicals of Interest in the Nuclear Fuel Cycle for the Detection of Undeclared Activities

Traditionally, IAEA inspectors have focused on the detection of nuclear indicators as part of infield inspection activities. The ability to rapidly detect and identify chemical as well as nuclear signatures can increase the ability of IAEA inspectors to detect undeclared activities at a site. Identification of chemical indicators have been limited to use in the analysis of environmental samples. Although IAEA analytical laboratories are highly effective, environmental sample processing does not allow for immediate or real-time results to an IAEA inspector at a facility. During a complementary access inspection, under the Additional Protocol, the use of fieldable technologies that can quickly provide accurate information on chemicals that may be indicative of undeclared activities can increase the ability of IAEA to effectively and efficiently complete their mission. The Complementary Access Working Group (CAWG) is a multi-laboratory team with members from Brookhaven National Laboratory, Idaho National Laboratory, Los Alamos National Laboratory, and Sandia National Laboratory. The team identified chemicals at each stage of the nuclear fuel cycle that may provide IAEA inspectors with indications that proliferation activities may be occurring. The group eliminated all indicators related to equipment, technology and training, developing a list of by-products/effluents, non-nuclear materials, nuclear materials, and other observables. These proliferation indicators were prioritized based on detectability from a conduct of operations (CONOPS) perspective of a CA inspection (for example, whether an inspector actually can access the S&O or whether it is in process with no physical access), and the IAEA’s interest in the detection technology in conjunction with radiation detectors. The list was consolidated to general categories (nuclear materials from a chemical detection technique, inorganic chemicals, organic chemicals, halogens, and miscellaneous materials). The team then identified commercial off the shelf (COTS) chemical detectors that may detect the chemicals of interest. Three chemical detectors were selected and tested both in laboratory settings and in field operations settings at Idaho National Laboratory. The instruments selected are: Thermo Scientific TruDefender FT (FTIR), Thermo Scientific FirstDefender RM (Raman), and Bruker Tracer III SD (XRF). Functional specifications, operability, and chemical detectability, selectivity, and limits of detection were determined. Results from the laboratory and field tests will be presented. This work is supported by the Next Generation Safeguards Initiative, Office of Nonproliferation and International Security, National Nuclear Security Administration.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Machine learning at the edge to improve in-field safeguards inspections

Artificial intelligence (AI) and machine learning (ML) are near-ubiquitous in day-to-day life; from cars with automated driver-assistance, recommender systems, generative content platforms, and large language chatbots. Implementing AI as a tool for international safeguards could significantly decrease the burden on safeguards inspectors and nuclear facility operators. The use of AI would allow inspectors to complete their in-field activities quicker, while identifying patterns and anomalies and freeing inspectors to focus on the uniquely human component of inspections. Sandia National Laboratories has spent the past two and a half years developing on-device machine learning to develop both a digital and robotic assistant. This combined platform, which we term inspecta, has numerous on-device machine learning capabilities that have been demonstrated at the laboratory scale. Here this work describes early successes implementing AI/ML capabilities to reduce the burden of tedious inspector tasks such as seal examination, information recall, note taking, and more.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2014

Ultrafast dark-field surface inspection with hybrid-dispersion laser scanning

High-speed surface inspection plays an important role in industrial manufacturing, safety monitoring, and quality control. It is desirable to go beyond the speed limitation of current technologies for reducing manufacturing costs and opening a new window onto a class of applications that require high-throughput sensing. Here, we report a high-speed dark-field surface inspector for detection of micrometer-sized surface defects that can travel at a record high speed as high as a few kilometers per second. This method is based on a modified time-stretch microscope that illuminates temporally and spatially dispersed laser pulses on the surface of a fast-moving object and detects scattered light from defects on the surface with a sensitive photodetector in a dark-field configuration. The inspector's ability to perform ultrafast dark-field surface inspection enables real-time identification of difficult-to-detect features on weakly reflecting surfaces and hence renders the method much more practical than in the previously demonstrated bright-field configuration. Consequently, our inspector provides nearly 1000 times higher scanning speed than conventional inspectors. To show our method's broad utility, we demonstrate real-time inspection of the surface of various objects (a non-reflective black film, transparent flexible film, and reflective hard disk) for detection of 10 μm or smaller defects on a moving target at 20 m/s within a scan width of 25 mm at a scan rate of 90.9 MHz. Our method holds promise for improving the cost and performance of organic light-emitting diode displays for next-generation smart phones, lithium-ion batteries for green electronics, and high-efficiency solar cells.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Enabling human–infrastructure interfaces for inspection using augmented reality

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.

Maharjan, D.↗
DOE OSTI2017

FPGA Authentication Methods.

One of the greatest challenges facing designers of equipment to be used in a nuclear arms control treaty is how to convince the other party in the treaty to trust its results and functionality. Whether the host provides equipment meant to prove treaty obligations and the inspector needs to gain that trust (commonly referred to as authentication), or the inspector provides this equipment and the host needs to gain this trust (commonly considered to be included in certification), one party generally has higher confidence in the equipment at the start of a treaty regime and the other party needs to gain that confidence prior to use. While we focus on authentication in this document—that is, the inspector gaining confidence in host-provided equipment—our conclusions will likely apply to host certification of inspector-provided equipment.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Eyes On the Ground: Path Forward Analysis.

A previous report assesses our progress to date on the Eyes On the Ground project, and reviews lessons learned. In this report, we address the implications of those lessons in defining the most productive path forward for the remainder of the project. We propose two main concepts: Interactive Diagnosis and Model-Driven Assistance. Among these, the Model-Driven Assistance concept appears the most promising. The Model-Driven Assistance concept is based on an approximate but useful model of a facility, which provides a unified representation for storing, viewing, and analyzing data that is known about the facility. This representation provides value to both inspectors and IAEA headquarters, and facilitates communication between the two. The concept further includes a lightweight, portable field tool to aid the inspector in executing a variety of inspection tasks, including capture of images and 3-d scan data. We develop a detailed description of this concept, including its system components, functionality, and example use cases. The envisioned tool would provide value by reducing inspector cognitive load, streamlining inspection tasks, and facilitating communication between the inspector and teams at IAEA headquarters. We conclude by enumerating the top implementation priorities to pursue in the remaining limited time of the project. Approved for public release; further dissemination unlimited.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Brain Science and International Nuclear Safeguards: Implications from Cognitive Science and Human Factors Research on the Provision and Use of Safeguards-Relevant Information in the Field

Today’s international nuclear safeguards inspectors have access to an increasing volume of supplemental information about the facilities under their purview, including commercial satellite imagery, nuclear trade data, open source information, and results from previous safeguards activities. In addition to completing traditional in-field safeguards activities, inspectors are now responsible for being able to act upon this growing corpus of supplemental safeguards-relevant data and for maintaining situational awareness of unusual activities taking place in their environment. However, cognitive science research suggests that maintaining too much information can be detrimental to a user’s understanding, and externalizing information (for example, to a mobile device) to reduce cognitive burden can decrease cognitive function related to memory, navigation, and attention. Given this dichotomy, how can international nuclear safeguards inspectors better synthesize information to enhance situational awareness, decision making, and performance in the field? This paper examines literature from the fields of cognitive science and human factors in the areas of wayfinding, situational awareness, equipment and technical assistance, and knowledge transfer, and describes the implications for the provision of, and interaction with, safeguards-relevant information for international nuclear safeguards inspectors working in the field.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2018

Using Deep Machine Learning to Conduct Object-Based Identification and Motion Detection on Safeguards Video Surveillance

Video surveillance is one of the core monitoring technologies used by the International Atomic Energy Agency (IAEA) Department of Safeguards at safeguarded nuclear facilities worldwide. Current IAEA image-review software has functions for scene-change detection, black image detection and missing scene analysis, but their capabilities are not optimum. The current workflow for the detection of safeguards relevant events heavily depends on inspectors’ laborious visual examination of surveillance videos, which is a time-consuming process and prone to errors. To improve the accuracy of the process and reduce inspectors’ burden, the paper proposes using deep machine learning to detect objects of interest in video streams and to conduct object-based motion detection. The hypothesis of this work is that deep machine learning will reduce the burden on inspectors and reduce errors by automatically locating and identifying objects of interest in video streams. Objects of interest include casks and fuel assemblies that are typically monitored by inspectors. The algorithm being developed in this work is based on a computationally efficient deep machine learning algorithm – You Only Look Once (YOLO) – but is further devised to address specific challenges related to the operation of nuclear facilities. The developed model (which is called YOLO-NSG – YOLO for Nuclear Safeguards) is evaluated with data sets collected at the test facilities at Brookhaven National Laboratory (BNL) and Sandia National Laboratories (SNL). The initial focus of the research is for application at safeguarded nuclear reactors, such as pressurized heavy-water reactors, where video surveillance is broadly deployed, but can be extended to other use cases of nuclear safeguards. The detailed structure of YOLO-NSG model is introduced and the test results are reported in the paper.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Defending Weapons Inspections from the Effects of Disinformation

The intentional spread of disinformation is not a new challenge for the scientific world. We have seen it perpetuate the idea of a flat earth, convince communities that vaccines are more dangerous than helpful, and even suggest a connection between the “5G” communication infrastructure and COVID-19. Nor is disinformation a new phenomenon in the weapons inspection arena. Weapons inspectors themselves are often forced to sift through alternative narratives of events and inconsistent reporting, and they regularly see their credibility and conclusions questioned in the face of government politics or public biases. But certain recent disinformation campaigns have become so overwhelmingly comprehensive and effective that they constitute a new kind of threat. By preventing accountability for clear violations of international law, these campaigns have created a challenge to the survival of arms control treaties themselves. If weapons inspectors cannot regain the trust of the international community in the face of this challenge, it will be increasingly difficult to ensure compliance with arms control and disarmament treaties going forward. In this essay, I will briefly discuss one of the most comprehensive disinformation efforts of the past decade: the disinformation campaign used to prevent accountability for Syria's repeated use of chemical weapons. After this discussion, I will propose one possible approach to help protect the credibility of disarmament experts and weapons inspectors in the face of pervasive disinformation. This approach will require a concerted effort to connect and support compliance experts and to understand and explain their expertise across cultural, political, national, economic, and religious divides.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2014

CTBT on-site inspections

On-site inspection (OSI) is a critical part of the verification regime for the Comprehensive Nuclear-Test-Ban Treaty (CTBT). The OSI verification regime provides for international inspectors to make a suite of measurements and observations on site at the location of an event of interest. The other critical component of the verification regime is the International Monitoring System (IMS), which is a globally distributed network of monitoring stations. The IMS along with technical monitoring data from CTBT member countries, as appropriate, will be used to trigger an OSI. After the decision is made to carry out an OSI, it is important for the inspectors to deploy to the field site rapidly to be able to detect short-lived phenomena such as the aftershocks that may be observable after an underground nuclear explosion. The inspectors will be on site from weeks to months and will be working with many tens of tons of equipment. Parts of the OSI regime will be tested in a field exercise in the country of Jordan late in 2014. The build-up of the OSI regime has been proceeding steadily since the CTBT was signed in 1996 and is on track to becoming a deterrent to someone considering conducting a nuclear explosion in violation of the Treaty.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Utilizing a Virtual Sodium-Cooled Fast Reactor Digital Twin to Aid in Diversion Pathway Analysis for International Safeguards Applications

We report digital twin technology has the potential to improve the effectiveness of international safeguards inspectors by providing a tool which can: first, perform an accurate diversion path analysis, identify their indicators, and required sensors to detect them; and second, monitor facilities in real-time using critical data streams that benefit from this safeguards-by-design approach. Safeguards inspectors are required to visit facilities and verify the nuclear material to ensure no diversion has taken place and detect misuse of the facility; however, this analysis and verification effort is time consuming, and with limited funding it is imperative that time spent at a nuclear facility is focused on key areas. A virtual digital twin of three prototypic sodium fast reactors was developed, where diversion and misuse scenarios were explored to determine how a digital twin could provide inspectors with an understanding of how proliferation may occur and where the most likely areas for proliferation would be. For each of the three reactors, an optimization algorithm was able to find core designs which would be difficult to detect via sensors alone; however, the use of a machine learning adapter provided by the digital twin was able to show general trends in where proliferation as likely to take place.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗