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

Annals of Nuclear Energy

Shoman, Nathan; Williams, Kyle; Balsara, Burzin; Ramakrishnan, Adithya; Kakish, Zahi; Coram, Jamie L.; Honnold, Philip; Rivas, Tania; Smartt, Heidi A.

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. 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.

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TYPE Journal Article YEAR 2024
DOIOSTIScopus

Inspecta Annual Technical Report

Smartt, Heidi A.; Coram, Jamie L.; Dorawa, Sydney; Foulk, James W.; Honnold, Philip; Kakish, Zahi; Pickett, Chris; Shoman, Nathan; Spence, Katherine

Sandia National Laboratories (SNL) is designing and developing an Artificial Intelligence (AI)-enabled smart digital assistant (SDA), Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant). The goal is to provide inspectors an in-field digital assistant that can perform tasks identified as tedious, challenging, or prone to human error. During 2021, we defined the requirements for Inspecta based on reviews of International Atomic Energy Agency (IAEA) publications and interviews with former IAEA inspectors. We then mapped the requirements to current commercial or open-source technical capabilities to provide a development path for an initial Inspecta prototype while highlighting potential research and development tasks. We selected a highimpact inspection task that could be performed by an early Inspecta prototype and are developing the initial architecture, including hardware platform. This paper describes the methodology for selecting an initial task scenario, the first set of Inspecta skills needed to assist with that task scenario and finally the design and development of Inspecta’s architecture and platform.

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TYPE SAND Report YEAR 2022
DOIOSTI

Applying Compression-Based Metrics to Seismic Data in Support of Global Nuclear Explosion Monitoring

Matzen, Laura E.; Ting, Christina; Field, Richard V.; Morrow, J.D.; Brogan, Ronald; Young, Christopher J.; Zhou, Angela; Trumbo, Michael C.S.; Coram, Jamie L.

The analysis of seismic data for evidence of possible nuclear explosion testing is a critical global security mission that relies heavily on human expertise to identify and mark seismic signals embedded in background noise. To assist analysts in making these determinations, we adapted two compression distance metrics for use with seismic data. First, we demonstrated that the Normalized Compression Distance (NCD) metric can be adapted for use with waveform data and can identify the arrival times of seismic signals. Then we tested an approximation for the NCD called Sliding Information Distance (SLID), which can be computed much faster than NCD. We assessed the accuracy of the SLID output by comparing it to both the Akaike Information Criterion (AIC) and the judgments of expert seismic analysts. Our results indicate that SLID effectively identifies arrival times and provides analysts with useful information that can aid their analysis process.

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TYPE SAND Report YEAR 2020
DOIOSTI

AstroTouch: A multi-touch digital desktop for astrodynamics

ITS 2013 - Proceedings of the 2013 ACM International Conference on Interactive Tabletops and Surfaces

Coram, Jamie L.; Iverson, John; Ackerman, Andrew

In this paper, we present the design, implementation, and preliminary evaluation of AstroTouch, a prototype desktop surface application to support analysis and visualization in the field of astrodynamics. We describe the fundamental characteristics of this complex scientific domain and discuss how these characteristics, combined with an assessment of current research surrounding multi-touch and the digital desktop, informed the design of our system. We detail the prototype implementation and present the results of an initial design critique conducted with domain experts. © 2013 ACM.

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TYPE Conference YEAR 2013
OSTIScopus
81 Results
81 Results