Dane Sabo
59e3923cd2
M .task/backlog.data M .task/pending.data M .task/undo.data A Writing/ERLM/SaboRisksAndContingencies.pdf M Writing/ERLM/broader-impacts/v1.tex M Writing/ERLM/main.aux M Writing/ERLM/main.fdb_latexmk M Writing/ERLM/main.fls
75 lines
4.8 KiB
TeX
75 lines
4.8 KiB
TeX
\section{Broader Impacts}
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Nuclear power presents both a compelling application domain and an urgent
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economic challenge. Recent interest in powering artificial intelligence
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infrastructure has renewed focus on small modular reactors (SMRs), particularly
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for hyperscale datacenters requiring hundreds of megawatts of continuous power.
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Deploying SMRs at datacenter sites would minimize transmission losses and
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eliminate emissions from hydrocarbon-based alternatives. However, the economics
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of nuclear power deployment at this scale demand careful attention to operating
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costs.
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According to the U.S. Energy Information Administration's Annual Energy Outlook
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2022, advanced nuclear power entering service in 2027 is projected to cost
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\$88.24 per megawatt-hour~\cite{eia_lcoe_2022}. Datacenter electricity demand is
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projected to reach 1,050 terawatt-hours annually by
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2030~\cite{eesi_datacenter_2024}. If this demand were supplied by nuclear power,
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the total annual cost of power generation would exceed \$92 billion. Within this
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figure, operations and maintenance represents a substantial component. The EIA
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estimates that fixed O\&M costs alone account for \$16.15 per megawatt-hour,
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with additional variable O\&M costs embedded in fuel and operating
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expenses~\cite{eia_lcoe_2022}. Combined, O\&M-related costs represent
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approximately 23-30\% of the total levelized cost of electricity, translating to
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\$21-28 billion annually for projected datacenter demand.
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This research directly addresses the multi-billion dollar O\&M cost challenge
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through implementations of high-assurance autonomous control. Current nuclear
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operations require full control room staffing for each reactor, whether large
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conventional units or small modular designs. These staffing requirements drive
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the high O\&M costs that make nuclear power economically challenging,
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particularly for smaller reactor designs where the same staffing overhead must
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be spread across lower power output. By synthesizing provably correct hybrid
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controllers from formal specifications, we can automate routine operational
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sequences that currently require constant human oversight. This enables a
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fundamental shift from direct operator control to supervisory monitoring, where
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operators can oversee multiple autonomous reactors rather than manually
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controlling individual units.
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The correct-by-construction methodology is critical for this transition.
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Traditional automation approaches cannot provide sufficient safety guarantees
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for nuclear applications, where regulatory requirements and public safety
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concerns demand the highest levels of assurance. By formally verifying both the
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discrete mode-switching logic and the continuous control behavior, this research
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will produce controllers with mathematical proofs of correctness. These
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guarantees enable automation to safely handle routine operations—such as startup
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sequences, power level changes, and normal operational transitions—that
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currently require human operators to follow written procedures. Operators will
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remain in supervisory roles to handle off-normal conditions and provide
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authorization for major operational changes, but the routine cognitive burden of
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procedure execution shifts to provably correct automated systems that are much
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cheaper to operate.
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SMRs represent an ideal deployment target for this technology. Nuclear Regulatory
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Commission certification requires extensive documentation of control procedures,
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operational requirements, and safety analyses written in structured natural
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language. As described in our approach, these regulatory documents can be
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translated into temporal logic specifications using tools like FRET, then
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synthesized into discrete switching logic using reactive synthesis tools, and
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finally verified using reachability analysis and barrier certificates for the
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continuous control modes. The infrastructure of requirements and specifications
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is already complete as part of the licensing process, creating a direct pathway
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from existing regulatory documentation to formally verified autonomous
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controllers.
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Beyond reducing operating costs for new reactors, this research will establish a
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generalizable framework for autonomous control of safety-critical systems. The
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methodology of translating operational procedures into formal specifications,
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synthesizing discrete switching logic, and verifying continuous mode behavior
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applies to any hybrid system with documented operational requirements. Potential
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applications include chemical process control, aerospace systems, and autonomous
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transportation, where similar economic and safety considerations favor increased
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autonomy with provable correctness guarantees. By demonstrating this approach in
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nuclear power—one of the most regulated and safety-critical domains—this
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research will establish both the technical feasibility and regulatory pathway
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for broader adoption across critical infrastructure.
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