\section{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, nuclear power economics at this scale demand careful
attention to operating costs.

\oldt{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.}
\newt{[DANE: Verify these figures are current. Check EIA Annual Energy
Outlook 2024/2025 for updated LCOE projections. The \$88.24/MWh,
\$16.15/MWh O\&M, and datacenter demand projections may have newer
sources.]}\dasinline{Check all of this math and update if newer sources
exist.}

This research directly addresses the multi-billion-dollar O\&M cost challenge
through 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. Synthesizing provably correct hybrid controllers
from formal specifications 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
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. 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---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 already exists 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. Demonstrating this approach in nuclear power---one of
the most regulated and safety-critical
domains\splitnote{``If it works here, it works anywhere — strong closing
argument.}---will establish both the technical feasibility and regulatory
pathway for broader adoption across critical infrastructure.
