Microreactor AGile Non-nuclear Experimental Testbed (MAGNET)
MAGNET provides an integrated thermal testing capability to enable microreactors. It provides a facility for researchers and technology developers to test new microreactor concepts in a relevant environment to advance technical maturityDigital Twin Demo: Microreactor AGile Non-nuclear Experimental Testbed (MAGNET)
EXTERNAL REFERENCES TO THE MAGNET DIGITAL TWIN
11 BIG WINS FOR NUCLEAR ENERGY IN 2022
2022 was a year of mega milestones for nuclear energy.
From the historic signing of the Inflation Reduction Act (IRA) to loading fuel in the nation’s next new reactor, momentum is definitely building for our largest source of clean power.
Here are 11 BIG wins for nuclear energy that are setting the stage for what is shaping up to be another fruitful year in 2023.
IDAHO NATIONAL LABORATORY DEMONSTRATES FIRST DIGITAL TWIN OF A SIMULATED MICROREACTOR
Researchers at Idaho National Laboratory (INL) recently performed their first digital twin test of a simulated microreactor. The successful demonstration builds on advancements in remote monitoring, autonomous control, and predictive capabilities that can help lower operating costs of microreactor technologies and enhance their safety.
MICROREACTOR AGILE NON-NUCLEAR EXPERIMENTAL TESTBED (MAGNET)
The Microreactor AGile Non-nuclear Experimental Testbed (MAGNET) is aiding in the development, testing, and validation of various microreactor technologies. Some of these technologies to be tested include various heat pipe test articles and configurations. For microreactors to be economically competitive, they should be self-adjusting, or able to operate with minimal oversight. The MAGNET Digital Twin is being created to run in conjunction with the heat pipe tests and prove how self-adjusting microreactors can be achieved through the application of digital twins.
A digital twin is defined as the virtual representation of some physical asset or process. The twin may exist in various levels of maturity. These range from isolated physics or 3D representations of the physical asset or process, to a twin that can receive real time sensor data and use that data to update predictive models and apply asset control accordingly. At this highest level of maturity, the digital twin autonomously controls the asset without requiring any human intervention. The benefits of such a twin include reduced operations cost, predictive maintenance, optimized performance and real-time alerting, intelligent forecasting of potential problems or anomalies, new insights into performance, remote monitoring, and more.
The MAGNET Digital Twin is proving these capabilities and benefits through application to the heat pipe experiments within MAGNET. Created through Digital Engineering techniques and using the DeepLynx data warehouse and MOOSE multiphysics framework, the digital twin combines sensor data gathering, multiphysics simulation, machine learning forecasting, and asset control via integration to the MAGNET Data Acquisition System (DAQ). Users can view the status of MAGNET, the twin, generated predictions, and asset control via a user dashboard. Validated within a non-nuclear environment, this digital twin framework establishes a foundation that can be enhanced for the application of digital twins to nuclear microreactor environments.