Machine Learning in Safeguards at Pebble Bed Reactors
- Brookhaven National Lab. (BNL), Upton, NY (United States)
The goal of this project is to investigate and demonstrate the applicability of machine learning (ML) in safeguards at pebble bed reactors (PBRs). The detailed scope of work includes working with DOE-Nuclear Energy and other domain experts to examine current safeguards approaches at PBRs, defining ML tasks that can potentially strengthen the safeguards at PBRs, selecting ML task(s) for proof of concept based on safeguards needs and availability of testbeds and datasets, and developing ML algorithm(s) to demonstrate the feasibility of ML in PBR safeguards.
- Research Organization:
- Brookhaven National Laboratory (BNL), Upton, NY (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development (NA-22)
- DOE Contract Number:
- SC0012704
- OSTI ID:
- 1679954
- Report Number(s):
- BNL--219955-2020-FORE
- Country of Publication:
- United States
- Language:
- English
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