\subsection{Broader Impacts}

Nuclear power presents both a compelling application domain and an urgent
economic challenge. Recent interest in powering artificial intelligence
infrastructure has renewed focus on small modular reactors (SMRs), particularly
for hyperscale datacenters requiring hundreds of megawatts of continuous power.
Deploying SMRs at datacenter sites would minimize transmission losses and
eliminate emissions from hydrocarbon-based alternatives. However, the economics
of nuclear power deployment at this scale demand careful attention to operating
costs.

According to the U.S. Energy Information Administration's Annual Energy Outlook
2022, advanced nuclear power entering service in 2027 is projected to cost
\$88.24 per megawatt-hour~\cite{eia_lcoe_2022}. Datacenter electricity demand is
projected to reach 1,050 terawatt-hours annually by
2030~\cite{eesi_datacenter_2024}. If this demand were supplied by nuclear power,
the total annual cost of power generation would exceed \$92 billion. Within this
figure, operations and maintenance represents a substantial component. The EIA
estimates that fixed O\&M costs alone account for \$16.15 per megawatt-hour,
with additional variable O\&M costs embedded in fuel and operating
expenses~\cite{eia_lcoe_2022}. Combined, O\&M-related costs represent
approximately 23-30\% of the total levelized cost of electricity, translating to
\$21-28 billion annually for projected datacenter demand.

This research directly addresses the multi-billion dollar O\&M cost challenge
through implementations of high-assurance autonomous control. Current nuclear
operations require full control room staffing for each reactor, whether large
conventional units or small modular designs. These staffing requirements drive
the high O\&M costs that make nuclear power economically challenging,
particularly for smaller reactor designs where the same staffing overhead must
be spread across lower power output. By synthesizing provably correct hybrid
controllers from formal specifications, we can automate routine operational
sequences that currently require constant human oversight. This enables a
fundamental shift from direct operator control to supervisory monitoring, where
operators can oversee multiple autonomous reactors rather than manually
controlling individual units.

The correct-by-construction methodology is critical for this transition.
Traditional automation approaches cannot provide sufficient safety guarantees
for nuclear applications, where regulatory requirements and public safety
concerns demand the highest levels of assurance. By formally verifying both the
discrete mode-switching logic and the continuous control behavior, this research
will produce controllers with mathematical proofs of correctness. These
guarantees enable automation to safely handle routine operations—such as startup
sequences, power level changes, and normal operational transitions—that
currently require human operators to follow written procedures. Operators will
remain in supervisory roles to handle off-normal conditions and provide
authorization for major operational changes, but the routine cognitive burden of
procedure execution shifts to provably correct automated systems that are much
cheaper to operate.

SMRs represent an ideal deployment target for this technology. Nuclear Regulatory
Commission certification requires extensive documentation of control procedures,
operational requirements, and safety analyses written in structured natural
language. As described in our approach, these regulatory documents can be
translated into temporal logic specifications using tools like FRET, then
synthesized into discrete switching logic using reactive synthesis tools, and
finally verified using reachability analysis and barrier certificates for the
continuous control modes. The infrastructure of requirements and specifications
is already complete as part of the licensing process, creating a direct pathway
from existing regulatory documentation to formally verified autonomous
controllers.

Beyond reducing operating costs for new reactors, this research will establish a
generalizable framework for autonomous control of safety-critical systems. The
methodology of translating operational procedures into formal specifications,
synthesizing discrete switching logic, and verifying continuous mode behavior
applies to any hybrid system with documented operational requirements. Potential
applications include chemical process control, aerospace systems, and autonomous
transportation, where similar economic and safety considerations favor increased
autonomy with provable correctness guarantees. By demonstrating this approach in
nuclear power—one of the most regulated and safety-critical domains—this
research will establish both the technical feasibility and regulatory pathway
for broader adoption across critical infrastructure.