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Several AESL students traveled to Washington DC in early November to present their research at the ANS Winter Meeting. PhD students Dan Watson and Hui Yu Hsieh presented progress on their research in the field of deep learning applications in reactor systems, and undergraduate Sydney Ballard attended her first conference to present her research on reactor siting criteria. Dr Thabit Abuqudaira, who graduated from the AESL group this August, also attended and presented his research on his System Dynamics Analysis Tool.

       

AESL student Tyler Gates represented Texas A&M University at the Nuclear Energy Agency’s NEST (Nuclear Education, Skills, and Technology) Award Ceremony in Paris. The event recognized NEA-sponsored research from all over the world, and included an exhibition from hundreds of vendors showing off their latest work.

AESL recently helped host a team of special visitors and provided a tour of Texas A&M’s Nuclear Engineering Department. Visitors included Jay Umholz from GSE Solutions, and Danny Bacot, Gary Bonewald, and David Amador from Wharton County Junior College.

AESL recently participated in the Texas A&M University Small Modular Reactor Workshop, which featured guest and presenters from across the university and the nation to discuss the latest research related to the development of small modular reactors. AESL provided 8 poster presentations, and Dr. Pavel Tsvetkov moderated a panel discussion in “Research Needs in SMR Thermal–Hydraulics”, and presented an overview of “AI-Enabled Nuclear System Design Engineering Capabilities”.

The American Nuclear Society hosted its annual conference in Chicago last week, and members of AESL presented recent research. Dr. Pavel Tsvetkov was one of the conference’s Keynote Speakers, and discussed “Reactor Physics Frontiers in the Age of Artificial Intelligence Breakthroughs”. Two PhD students also presented research; Hui-Yu Hsieh gave a presentation on “Intelligent Prediction and Uncertainty Quantification of Reactivity-Induced Power Excursions in Molten Salt Reactors”, and Michael Parnell gave a presentation titled “Use of System Dynamics Analysis Tool in Stability Analysis Applications for Flowing-Fuel Reactors”.

Last week, members of AESL presented their research work at Texas A&M’s Nuclear Engineering Spring BBQ and Poster Session to students, faculty, and the department’s advisory board. AESL presented 9 posters, and many were focused on applications of artificial intelligence and deep learning to solve various nuclear engineering problems.

         

A paper written by several AESL members was recently published by Nuclear Technology, and is now available (open access) at Taylor & Francis Online. Their paper is available here:  Fission Surface Power—A Conceptual 350-kW(thermal) Microreactor Designed for Lunar Power Around SpaceX Falcon Heavy Mass Constraints

Daniel Watson attended and presented at Defense Tech Connect Innovation Summit and Expo, on December 3 – 5, 2024, in Austin, TX. His poster, “Robust Remote Monitoring Capabilities via AI Integration”, had the following focus:

Large-scale surveillance missions require substantial resources and are susceptible to human error. To mitigate these challenges, autonomous methods—specifically anomaly detection and classification using artificial intelligence (AI)—have been employed to enhance human capabilities, enabling planet-scale surveillance. Under the Consortium for Enabling Technologies and Innovation (ETI), funded by the National Nuclear Security Administration (NNSA, NA20), a multi-modal remote surveillance platform utilizing CubeSats and AI for terrestrial anomaly detection has been developed.

This platform focuses on predictive, on-demand characterization of localized anomalies on Earth’s surface, subsurface, and atmosphere. By leveraging CubeSats equipped with advanced sensors/hardware and AI algorithms, the system enhances remote detection of nuclear activities via secondary optical signatures. The signature-based approach provides foundational architectures for facility monitoring.

Development efforts include generating specifications for CubeSat architectures and sensors informed by current technologies, creating surrogate datasets, and compiling a phenomena database for future surveillance applications. Initial results demonstrate successful anomaly detection using low-resolution satellite imagery with convolutional neural networks.

Future work aims to mature characterization methods and training libraries using real and high-fidelity surrogate datasets, expand phenomena characterization metrics for efficient orbital data processing, and produce a Front-End Engineering Design (FEED) report for the proposed CubeSat system.

AESL student Dan Watson represented Texas A&M’s Nuclear Engineering Department at the recent Global Cyber Research Institute Summit on campus, alongside representatives from the Center for Nuclear Security Science and Policy Initiatives (NSSPI). Nuclear and cyber security have substantial overlap, and this summit was an excellent opportunity for raising awareness and making connections between nuclear and cyber organizations.

Graduate student Tyler Gates represented Texas A&M at the Nuclear Innovator Cultivation Camp (NICC 2024) sponsored by the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT). It brought together 13 participants from 6 U.S. Universities (TAMU, NC State, Michigan, MIT, Wisconsin, Berkeley), 2 Japanese Universities (Tokyo Tech, Fukui Uni.), and 1 Industrial Partner (Hitachi-GE) to collaborate and discuss the future of nuclear energy post-Fukushima. It was hosted at Tokyo Tech by Dr. Toru Obara and Dr. Tatsuya Katabuchi and featured speakers from JAEC, IRID, and Advanced Float Co. Ltd. Tours were provided of the High Temperature Engineering Test Reactor (HTTR) and the Fukushima Daiichi nuclear power plant.