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M .task/backlog.data M .task/completed.data M .task/pending.data M .task/undo.data M Writing/ERLM/broader-impacts/v1.tex M Writing/ERLM/main.aux M Writing/ERLM/main.bbl M Writing/ERLM/main.blg
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time 1758732224
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---
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time 1759156527
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---
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time 1759156557
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---
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time 1759156557
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---
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time 1759156563
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---
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time 1759161466
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---
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@ -1,2 +1,74 @@
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\subsection{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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@ -4,22 +4,25 @@
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\@writefile{toc}{\contentsline {section}{\numberline {1}Goals and Outcomes}{1}{}\protected@file@percent }
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\citation{geromel2006stability}
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\citation{yang2024learning}
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\citation{alur1993hybrid}
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\citation{eia_lcoe_2022}
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\citation{eesi_datacenter_2024}
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\citation{eia_lcoe_2022}
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\@writefile{toc}{\contentsline {subsection}{\numberline {3.4}Broader Impacts}{8}{}\protected@file@percent }
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\bibdata{references}
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\bibcite{geromel2006stability}{1}
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\bibcite{branicky1998multiple}{2}
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@ -34,5 +37,7 @@
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\bibcite{platzer2008differential}{11}
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\bibcite{platzer2017complete}{12}
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\bibcite{fulton2015keymaera}{13}
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\bibcite{eia_lcoe_2022}{14}
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\bibcite{eesi_datacenter_2024}{15}
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\gdef \@abspage@last{12}
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@ -65,4 +65,16 @@ Nathan Fulton, Stefan Mitsch, Jan-David Quesel, Marcus V{\"o}lp, and Andr{\'e} P
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\newblock Keymaera x: An axiomatic tactical theorem prover for hybrid systems.
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\newblock In {\em International Conference on Automated Deduction}, pages 527--538. Springer, 2015.
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\bibitem{eia_lcoe_2022}
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{U.S. Energy Information Administration}.
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\newblock Levelized costs of new generation resources in the annual energy outlook 2022.
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\newblock Report, U.S. Energy Information Administration, March 2022.
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\newblock See Table 1b, page 9.
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\bibitem{eesi_datacenter_2024}
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{Environmental and Energy Study Institute}.
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||||
\newblock Data center energy needs are upending power grids and threatening the climate.
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\newblock Web article, 2024.
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||||
\newblock Accessed: 2025-09-29.
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\end{thebibliography}
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@ -3,44 +3,44 @@ Capacity: max_strings=200000, hash_size=200000, hash_prime=170003
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The top-level auxiliary file: main.aux
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The style file: unsrt.bst
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Database file #1: references.bib
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This is pdfTeX, Version 3.141592653-2.6-1.40.25 (TeX Live 2023/Debian) (preloaded format=pdflatex 2024.9.10) 24 SEP 2025 11:52
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This is pdfTeX, Version 3.141592653-2.6-1.40.25 (TeX Live 2023/Debian) (preloaded format=pdflatex 2024.9.11) 29 SEP 2025 11:55
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entering extended mode
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restricted \write18 enabled.
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file:line:error style messages enabled.
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(Font) Font shape `OT1/ptm/b/n' tried instead on input line 5.
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[1
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[3] [4]
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File: ts1ptm.fd 2001/06/04 font definitions for TS1/ptm.
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[]
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[5] [6]) (./broader-impacts/v1.tex [7] [8]) [9] (./main.bbl [10]) [11] (./main.aux)
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LaTeX2e <2023-11-01> patch level 1
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L3 programming layer <2024-01-22>
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***********
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Output written on main.pdf (12 pages, 124363 bytes).
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@ -4,11 +4,8 @@
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\maketitle
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||||
\input{goals-and-outcomes/v4}
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\newpage
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\input{state-of-the-art/v2}
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\newpage
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\input{broader-impacts/v1}
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\newpage
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@ -308,3 +308,24 @@
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year={2021},
|
||||
publisher={IEEE}
|
||||
}
|
||||
|
||||
%broader impacts
|
||||
@techreport{eia_lcoe_2022,
|
||||
author = {{U.S. Energy Information Administration}},
|
||||
title = {Levelized Costs of New Generation Resources in the Annual Energy Outlook 2022},
|
||||
institution = {U.S. Energy Information Administration},
|
||||
year = {2022},
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||||
month = {March},
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||||
type = {Report},
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||||
url = {https://www.eia.gov/outlooks/aeo/pdf/electricity_generation.pdf},
|
||||
note = {See Table 1b, page 9}
|
||||
}
|
||||
|
||||
@misc{eesi_datacenter_2024,
|
||||
author = {{Environmental and Energy Study Institute}},
|
||||
title = {Data Center Energy Needs Are Upending Power Grids and Threatening the Climate},
|
||||
howpublished = {Web article},
|
||||
year = {2024},
|
||||
url = {https://www.eesi.org/articles/view/data-center-energy-needs-are-upending-power-grids-and-threatening-the-climate},
|
||||
note = {Accessed: 2025-09-29}
|
||||
}
|
||||
|
||||
BIN
Writing/ERLM/sabo_broader_impacts.pdf
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Writing/ERLM/sabo_broader_impacts.pdf
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