Lauren Fortier: Automating Nuclear Plant Operations for Clean Energy Viability

Lauren Fortier, a doctoral student in the Department of Nuclear Science and Engineering (NSE) at MIT, is developing systems to facilitate the remote operation and autonomous control of nuclear power plants. The research aims to make nuclear energy more economically viable by reducing the costs associated with production and operations.

The drive toward automation is particularly critical for the economic viability of small and microreactors. According to research conducted by Fortier, reducing energy generation costs depends heavily on lowering operations and maintenance expenses, which can be achieved through the implementation of autonomous reactor control systems.

From Naval Operations to Academic Research

Fortier’s transition into nuclear automation was informed by her practical experience as a naval nuclear operator. After earning an undergraduate degree in materials science and engineering from Northwestern University via an ROTC scholarship, she supervised nuclear plant operations on a U.S. Aircraft carrier in the South China Sea.

During her time in the Navy, Fortier observed that many plant operations were extremely manually intensive and began investigating whether these processes could be streamlined. This operational background led her to pursue a master’s degree in nuclear engineering at MIT to move from the operations realm into academia.

Technical Framework for Autonomous Control

As part of her master’s research, Fortier developed a supervisory control system (SCS) designed as a transition technology toward fully autonomous reactor plant operations. This work utilized a simulator with a strong thermal hydraulic response to test the system’s efficacy.

The technical foundation of this system relies on Finite State Automata (FSA), a mathematical tool used for modeling discrete event systems (DES). Using FSA allows for the engineering of supervisory controllers that are fully verifiable and validatable.

The architecture employs a graded functionalization approach, similar to the systems used in self-driving vehicles. In this hierarchical structure:

• Feedback controllers regulate low-level actuation functions.
• A supervisory controller governs high-level plant state transitions.

By utilizing mathematical proofs within the scope of regular languages, properties such as controllability and nonblocking can be formally demonstrated. This framework is designed to lessen operator dependence and build trust in automated systems, creating a foundation for the eventual transition to fully autonomous control.

Industry Application and Human Factors

The research extends beyond theoretical modeling into practical application and user experience. Fortier has worked on a nuclear power plant operation automation program specifically designed to boost reliability and maintain low energy costs.

To ensure these technological shifts remain practical for human operators, Fortier collaborated with the human factors department at the Idaho National Laboratory (INL). This collaboration focused on ensuring that programmatic changes within the control room setting remained user-friendly.

Current professional activities indicate that Fortier continues to support advanced reactor operations at Westinghouse while pursuing her PhD in Nuclear Science and Engineering at MIT.

The integration of autonomous controllers is further supported by advanced reactor designs that feature digital instrumentation and control systems, reduced source terms and enhanced passive safety features, all of which reduce the inherent need for constant human intervention.