Explores closed-loop control in a reactor surrogate, indicating advancements in reactor safety and performance.
ViBRANT (Visual Benign Reactor as Analog for Nuclear Testing) is a testing platform configured as a physical surrogate of the Microreactor Applications Research Validation and Evaluation (MARVEL) reactor for this paper. In this MARVEL configuration, ViBRANT is intended to wholistically represent primary reactor behaviors through an accessible light emitting diode (LED)–driven reactor core, photodiodes, thermocouples, and high-performance software interfaces. While the presented items are scaled or are alternative physics replacements of actual reactor aspects, this paper shows how they can be used to directly investigate and mature key system aspects, resulting in the development of an actual reactor’s entire instrumentation and control system to the necessary paramount safety standards while optimizing performance prior to deployment in an actual reactor.Like MARVEL, ViBRANT is equipped with four control drum systems enabled with all the required reactivity control system capabilities, two LED-populated surrogate core configurations (a barrel and a 36-pin configuration) to represent matched reactor physics phenomena, and a distributed set of photodiode and thermocouple sensors to capture the analog response in the surrogate cores. The controller compiled these inputs and outputs to demonstrate effective closed-loop control. Although some nonlinear digital interjections are required to match the nuclear physics with light physics, the system’s geometric form has shown good, scaled approximations of both the flux and thermal profiles found in nuclear reactors.Compounding the value of this study’s results is the fact that all this has been done with basic homogeneous inputs, which have merely scratched the surface of what direct control of 60 000 effectively distributed light and thermal physics–inducing LEDs could provide. This characteristic provides ViBRANT with great digital tuning potential to create accurate scaled physical manifestations of a wide variety of reactors; thus providing nearly all reactor developers with a common, powerful, yet accessible and intuitive resource. The result yielded a more rapid, higher-quality, and powerful development with relevance to the implementation of automation and advanced artificial intelligence algorithms in nuclear reactors such as MARVEL.
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Anthony L. Crawford (2026) studied this question.
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