vault backup: 2025-12-17 15:32:09

This commit is contained in:
Dane Sabo 2025-12-17 15:32:09 -05:00
parent 1f3afde500
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#!/bin/sh
PROMPT="$1"
TEMP_FILE="$OBSIDIAN_GIT_CREDENTIALS_INPUT"
cleanup() {
rm -f "$TEMP_FILE" "$TEMP_FILE.response"
}
trap cleanup EXIT
echo "$PROMPT" > "$TEMP_FILE"
while [ ! -e "$TEMP_FILE.response" ]; do
if [ ! -e "$TEMP_FILE" ]; then
echo "Trigger file got removed: Abort" >&2
exit 1
fi
sleep 0.1
done
RESPONSE=$(cat "$TEMP_FILE.response")
echo "$RESPONSE"

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# Use the command 'task show' to see all defaults and overrides
# Files
data.location=/home/danesabo/Documents/Dane's Vault/.task
data.location=~/Documents/Dane's Vault/.task
# To use the default location of the XDG directories,
# move this configuration file from ~/.taskrc to ~/.config/task/taskrc and uncomment below
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#include light-16.theme
#include light-256.theme
#include dark-16.theme
include dark-256.theme
include light-256.theme
#include dark-red-256.theme
#include dark-green-256.theme
#include dark-blue-256.theme
@ -40,4 +40,4 @@ include dark-256.theme
#include no-color.theme
urgency.user.project.zk.coefficient=1.0
news.version=2.6.0
news.version=3.4.2

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% GOAL PARAGRAPH
The goal of this research is to develop a methodology for creating autonomous
control systems with event-driven control laws that have guarantees of safe and
correct behavior.
% INTRODUCTORY PARAGRAPH Hook
Nuclear power relies on extensively trained operators who follow detailed
written procedures to manage reactor control. Based on these procedures and
operators' interpretation of plant conditions, operators make critical decisions
about when to switch between control objectives.
% Gap
But, reliance on human operators has created an economic challenge for
next-generation nuclear power plants. Small modular reactors face significantly
higher per-megawatt staffing costs than conventional plants. Autonomous control
systems are needed that can safely manage complex operational sequences with the
same assurance as human-operated systems, but without constant supervision.
% APPROACH PARAGRAPH Solution
To address this need, we will combine formal methods from computer science with
control theory to build hybrid control systems that are correct by construction.
% Rationale
Hybrid systems use discrete logic to switch between continuous control modes,
similar to how operators change control strategies. Existing formal methods
generate provably correct switching logic but cannot handle continuous dynamics
during transitions, while traditional control theory verifies continuous
behavior but lacks tools for proving discrete switching correctness.
% Hypothesis and Technical Approach
We will bridge this gap through a three-stage methodology. First, we will
translate written operating procedures into temporal logic specifications using
NASA's Formal Requirements Elicitation Tool (FRET), which structures
requirements into scope, condition, component, timing, and response elements.
This structured approach enables realizability checking to identify conflicts
and ambiguities in procedures before implementation. Second, we will synthesize
discrete mode switching logic using reactive synthesis
to generate deterministic automata that are provably
correct by construction. Third, we will develop continuous
controllers for each discrete mode using standard control theory and
reachability analysis. We will classify continuous modes based on their
transition objectives, and then employ assume-guarantee contracts and barrier
certificates to prove that mode transitions occur safely and as defined by the
deterministic automata. This compositional approach enables local verification
of continuous modes without requiring global trajectory analysis across the
entire hybrid system. We will demonstrate this on an Emerson Ovation control system.
% Pay-off
This approach will demonstrate autonomous control can be used for complex
nuclear power operations while maintaining safety guarantees.
% OUTCOMES PARAGRAPHS
If this research is successful, we will be able to do the following:
\begin{enumerate}
% OUTCOME 1 Title
\item \textit{Synthesize written procedures into verified control logic.}
% Strategy
We will develop a methodology for converting written operating procedures
into formal specifications. These specifications will be synthesized into
discrete control logic using reactive synthesis tools.
% Outcome
Control engineers will be able to generate mode-switching controllers from
regulatory procedures with little formal methods expertise, reducing
barriers to high-assurance control systems.
% OUTCOME 2 Title
\item \textit{Verify continuous control behavior across mode transitions. }
% Strategy
We will develop methods using reachability analysis to ensure continuous control modes
satisfy discrete transition requirements.
% Outcome
Engineers will be able to design continuous controllers using standard
practices while ensuring system correctness and proving mode transitions
occur safely at the right times.
% OUTCOME 3 Title
\item \textit{Demonstrate autonomous reactor startup control with safety
guarantees. }
% Strategy
We will implement this methodology on a small modular reactor simulation
using industry-standard control hardware. % Outcome
Control engineers will be able to implement high-assurance autonomous
controls on industrial platforms they already use, enabling users to
achieve autonomy without retraining costs or developing new equipment.
\end{enumerate}

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\section{Goals and Outcomes}
% GOAL PARAGRAPH
The goal of this research is to develop a methodology for creating autonomous
hybrid control systems with mathematical guarantees of safe and correct
behavior.
% INTRODUCTORY PARAGRAPH Hook
Nuclear power plants require the highest levels of control system reliability,
where failures can result in significant economic losses, service interruptions,
or radiological release.
% Known information
Currently, nuclear plant operations rely on extensively trained human operators
who follow detailed written procedures and strict regulatory requirements to
manage reactor control. These operators make critical decisions about when to
switch between different control modes based on their interpretation of plant
conditions and procedural guidance.
% Gap
This reliance on human operators prevents autonomous control capabilities and
creates a fundamental economic challenge for next-generation reactor designs.
Small modular reactors, in particular, face per-megawatt staffing costs far
exceeding those of conventional plants and threaten their economic viability.
% Critical Need
What is needed is a method to create autonomous control systems that safely
manage complex operational sequences with the same assurance as human-operated
systems, but without constant human supervision.
% APPROACH PARAGRAPH Solution
To address this need, we will combine formal methods with control theory to
build hybrid control systems that are correct by construction.
% Rationale
Hybrid systems use discrete logic to switch between continuous control modes,
mirroring how operators change control strategies. Existing formal methods can
generate provably correct switching logic from written requirements, but they
cannot handle the continuous dynamics that occur during transitions between
modes. Meanwhile, traditional control theory can verify continuous behavior but
lacks tools for proving correctness of discrete switching decisions.
% Hypothesis
By synthesizing discrete mode transitions directly from written operating
procedures and verifying continuous behavior between transitions, we can create
hybrid control systems with end-to-end correctness guarantees. If existing
procedures can be formalized into logical specifications and continuous dynamics
verified against transition requirements, then autonomous controllers can be
built that are provably free from design defects.
% Pay-off
This approach will enable autonomous control in nuclear power plants while
maintaining the high safety standards required by the industry.
% Qualifications
This work is conducted within the University of Pittsburgh Cyber Energy Center,
which provides access to industry collaboration and Emerson control hardware,
ensuring that developed solutions align with practical implementation
requirements.
% OUTCOMES PARAGRAPHS
If this research is successful, we will be able to do the following:
\begin{enumerate}
% OUTCOME 1 Title
\item \textbf{Translate written procedures into verified control logic.}
% Strategy
We will develop a methodology for converting existing written operating
procedures into formal specifications that can be automatically synthesized
into discrete control logic. This process will use structured intermediate
representations to bridge natural language procedures and mathematical
logic.
% Outcome
Control system engineers will generate verified mode-switching controllers
directly from regulatory procedures without formal methods expertise,
lowering the barrier to high-assurance control systems.
% OUTCOME 2 Title
\item \textbf{Verify continuous control behavior across mode transitions.}
% Strategy
We will establish methods for analyzing continuous control modes to ensure
they satisfy discrete transition requirements. Using classical control
theory for linear systems and reachability analysis for nonlinear dynamics,
we will verify that each continuous mode safely reaches its intended
transitions.
Engineers will design continuous controllers using standard practices while
iterating to ensure broader system correctness, proving that mode
transitions occur safely and at the correct times.
% OUTCOME 3 Title
\item \textbf{Demonstrate autonomous reactor startup control with safety
guarantees.}
% Strategy
We will apply this methodology to develop an autonomous controller for
nuclear reactor startup procedures, implementing it on a small modular
reactor simulation using industry-standard control hardware. This
demonstration will prove correctness across multiple coordinated control
modes from cold shutdown through criticality to power operation.
% Outcome
We will demonstrate that autonomous hybrid control can be realized in the
nuclear industry with current equipment, establishing a path toward reduced
operator staffing while maintaining safety.
\end{enumerate}
% IMPACT PARAGRAPH Innovation
The innovation in this work is unifying discrete synthesis with continuous
verification to enable end-to-end correctness guarantees for hybrid systems.
% Outcome Impact
If successful, control engineers will create autonomous controllers from
existing procedures with mathematical proof of correct behavior. High-assurance
autonomous control will become practical for safety-critical applications.
% Impact/Pay-off
This capability is essential for the economic viability of next-generation
nuclear power. Small modular reactors offer a promising solution to growing
energy demands, but their success depends on reducing per-megawatt operating
costs through increased autonomy. This research will provide the tools to
achieve that autonomy while maintaining the exceptional safety record the
nuclear industry requires.

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# Outline of State of the Art
## Writing is thinking, and this is like journaling
This research is really about using techniques that we
already have to make hybrid systems that from the jump are
provably adherent to requirements and in general that we can
say what they're gonna do fo sho. Does that make any sense?
The critical technologies to do this are as follows, in no
particular order: discrete system theory and reactive
synthesis, temporal logics, reachability for hybrid systems.
Things that are adjacent to what I'm doing but aren't what
I'm doing include stuff by Platzer and all the differential
dynamic logic stuff. His stuff looks like another way of
conquering this problem but adds a whole lot of complexity
and makes synthesis ambiguous. Great at checking, but what
does that mean for designing?
I feel like I should get more sources on designing hybrid
systems. I think there are some books out there about this
maybe.
----
**Outline**
----
## 1. Hybrid Control Systems Foundations
- **Classical hybrid systems theory** (Branicky, Liberzon,
Morse - switching systems)
- **Hybrid automata and modeling** (Henzinger, Alur, Dill)
- **Stability analysis for switching systems** (Shorten,
Narendra, Lin & Antsaklis)
**Key points to include:**
- Definition of hybrid systems and why they're needed for
complex control
- Challenges in stability analysis when switching between
controllers
- Gap between individual mode stability and overall system
stability
- Motivate why traditional control theory alone is
insufficient
## 2. Discrete Controller Synthesis
- **Reactive synthesis from temporal logic** (Pnueli, Bloem,
Ehlers)
- **Tools like Strix, TuLiP, SLUGS** - emphasize their
discrete-only assumptions
- **LTL/GR(1) synthesis** and why these assume instantaneous
transitions
**Key points to include:**
- Power of temporal logic for specifying complex behaviors
- Success of reactive synthesis in discrete domains
- Correctness-by-construction guarantees from synthesis
tools
- Critical limitation: assumption of instantaneous state
changes
- Why this breaks down for physical systems with continuous
dynamics
## 3. Continuous System Verification
- **Reachability analysis** (Girard, Le Guernic, Althoff -
especially for nonlinear systems)
- **Linear system verification** (Boyd, Dullerud - classical
control meets verification)
- **Set-based methods** (Mitchell, Tomlin for
Hamilton-Jacobi reachability)
**Key points to include:**
- Mature tools for analyzing continuous dynamics
- Reachability as the fundamental verification problem
- Computational challenges for nonlinear systems
- Gap: these are analysis tools, not synthesis tools
- They tell you if a controller works, but don't help design
it
## 4. Existing Hybrid Verification Approaches
- **Platzer's differential dynamic logic** (as you noted -
good for verification, unclear for synthesis)
- **SpaceEx, Flow*, dReach** - model checking tools that
don't synthesize
- **Contract-based design** (Benveniste,
Sangiovanni-Vincentelli)
**Key points to include:**
- Current approaches focus on verification after design
- Platzer's dL: powerful for proving correctness, but
synthesis unclear
- Model checking tools require pre-designed controllers
- Contract-based approaches: compositional but still
verification-focused
- Missing: unified synthesis framework that handles both
discrete and continuous
## 5. The Gap You're Filling
- **Why discrete synthesis + continuous verification hasn't
been unified**
- **Challenges with non-instantaneous transitions**
- **The synthesis vs. verification divide**
**Key points to include:**
- Fundamental mismatch: discrete synthesis assumes instant
transitions
- Physical reality: transitions take time and follow
continuous trajectories
- Current workflow: synthesize discrete, design continuous,
then verify
- Your contribution: unified framework for
correct-by-construction hybrid synthesis
- Nuclear startup as ideal testbed: well-defined continuous
dynamics + explicit procedural requirements
## Key Sources to Hunt Down
**Foundational hybrid systems:**
- Branicky's "Multiple Lyapunov functions and other analysis
tools"
- Liberzon's "Switching in Systems and Control"
- Antsaklis & Koutsoukos survey papers
**Reactive synthesis:**
- Ehlers & Topcu on GR(1) synthesis
- Recent Strix papers (Meyer, Sickert, Luttenberger)
- Wongpiromsarn's work on TuLiP
**Hybrid verification:**
- Althoff's reachability analysis work
- Girard's papers on abstraction-based verification
- Any recent survey on hybrid system verification tools
**Nuclear/critical systems control:**
- Look for papers on autonomous nuclear plant operation
- Regulatory papers on control system requirements (might be
more engineering sources)

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\section{State of the Art and Limits of Current Practice}
The principal aim of this research is to create autonomous reactor control
systems that are tractably safe. To understand what is being automated, we must
first understand how nuclear reactors are operated today. This section examines
reactor operators and the operating procedures we aim to leverage, then
investigates limitations of human-based operation, and concludes with current
formal methods approaches to reactor control systems.
\subsection{Current Reactor Procedures and Operation}
Nuclear plant procedures exist in a hierarchy: normal operating procedures for
routine operations, abnormal operating procedures for off-normal conditions,
Emergency Operating Procedures (EOPs) for design-basis accidents, Severe
Accident Management Guidelines (SAMGs) for beyond-design-basis events, and
Extensive Damage Mitigation Guidelines (EDMGs) for catastrophic damage
scenarios. These procedures must comply with 10 CFR 50.34(b)(6)(ii) and are
developed using guidance from NUREG-0900~\cite{NUREG-0899, 10CFR50.34}, but their
development relies fundamentally on expert judgment and simulator validation
rather than formal verification. Procedures undergo technical evaluation,
simulator validation testing, and biennial review as part of operator
requalification under 10 CFR 55.59~\cite{10CFR55.59}. Despite this rigor,
procedures fundamentally lack formal verification of key safety properties. No
mathematical proof exists that procedures cover all possible plant states, that
required actions can be completed within available timeframes, or that
transitions between procedure sets maintain safety invariants.
\textbf{LIMITATION:} \textit{Procedures lack formal verification of correctness
and completeness.} Current procedure development relies on expert judgment and
simulator validation. No mathematical proof exists that procedures cover all
possible plant states, that required actions can be completed within available
timeframes, or that transitions between procedure sets maintain safety
invariants. Paper-based procedures cannot ensure correct application, and even
computer-based procedure systems lack the formal guarantees that automated
reasoning could provide.
Nuclear plants operate with multiple control modes: automatic control, where the
reactor control system maintains target parameters through continuous reactivity
adjustment; manual control, where operators directly manipulate the reactor; and
various intermediate modes. In typical pressurized water reactor operation, the
reactor control system automatically maintains a floating average temperature
and compensates for power demand changes through reactivity feedback loops
alone. Safety systems, by contrast, operate with implemented automation. Reactor
Protection Systems trip automatically on safety signals with millisecond
response times, and engineered safety features actuate automatically on accident
signals without operator action required.
The division between automated and human-controlled functions reveals the
fundamental challenge of hybrid control. Highly automated systems handle reactor
protection---automatic trips on safety parameters, emergency core cooling
actuation, containment isolation, and basic process
control~\cite{WRPS.Description, gentillon_westinghouse_1999}. Human operators,
however, retain control of strategic decision-making: power level changes,
startup/shutdown sequences, mode transitions, and procedure implementation.
\subsection{Human Factors in Nuclear Accidents}
Current-generation nuclear power plants employ over 3,600 active NRC-licensed
reactor operators in the United States~\cite{operator_statistics}. These
operators divide into Reactor Operators (ROs), who manipulate reactor controls,
and Senior Reactor Operators (SROs), who direct plant operations and serve as
shift supervisors~\cite{10CFR55}. Staffing typically requires at least two ROs
and one SRO for current-generation units~\cite{10CFR50.54}. Becoming a reactor
operator requires several years of training.
The persistent role of human error in nuclear safety incidents---despite decades
of improvements in training and procedures---provides the most compelling
motivation for formal automated control with mathematical safety guarantees.
Operators hold legal authority under 10 CFR Part 55 to make critical decisions,
including departing from normal regulations during emergencies. The Three Mile
Island (TMI) accident demonstrated how a combination of personnel error, design
deficiencies, and component failures led to partial meltdown when operators
misread confusing and contradictory readings and shut off the emergency water
system~\cite{Kemeny1979}. The President's Commission on TMI identified a
fundamental ambiguity: placing responsibility for safe power plant operations on
the licensee without formal verification that operators can fulfill this
responsibility does not guarantee safety. This tension between operational
flexibility and safety assurance remains unresolved: the person responsible for
reactor safety is often the root cause of failures.
Multiple independent analyses converge on a striking statistic: 70--80\% of
nuclear power plant events are attributed to human error, versus approximately
20\% to equipment failures~\cite{WNA2020}. More significantly, the root cause of
all severe accidents at nuclear power plants---Three Mile Island, Chernobyl, and
Fukushima Daiichi---has been identified as poor safety management and safety
culture: primarily human factors~\cite{hogberg_root_2013}. A detailed analysis
of 190 events at Chinese nuclear power plants from
2007--2020~\cite{zhang_analysis_2025} found that 53\% of events involved active
errors, while 92\% were associated with latent errors---organizational and
systemic weaknesses that create conditions for failure.
\textbf{LIMITATION:} \textit{Human factors impose fundamental reliability limits
that cannot be overcome through training alone.} The persistent human
error contribution despite four decades of improvements demonstrates that these
limitations are fundamental rather than a remediable part of human-driven control.
\subsection{HARDENS and Formal Methods}
The High Assurance Rigorous Digital Engineering for Nuclear Safety (HARDENS)
project represents the most advanced application of formal methods to nuclear
reactor control systems to date~\cite{Kiniry2024}.
HARDENS aimed to address a fundamental dilemma: existing U.S. nuclear control
rooms rely on analog technologies from the 1950s--60s. This technology is
obsolete compared to modern control systems and incurs significant risk and
cost. The NRC contracted Galois, a formal methods firm, to demonstrate that
Model-Based Systems Engineering and formal methods could design, verify, and
implement a complex protection system meeting regulatory criteria at a fraction
of typical cost. The project delivered a Reactor Trip System (RTS)
implementation with full traceability from NRC Request for Proposals and IEEE
standards through formal architecture specifications to verified software.
HARDENS employed formal methods tools and techniques across the verification
hierarchy. High-level specifications used Lando, SysMLv2, and FRET (NASA Formal
Requirements Elicitation Tool) to capture stakeholder requirements, domain
engineering, certification requirements, and safety requirements. Requirements
were analyzed for consistency, completeness, and realizability using SAT and SMT
solvers. Executable formal models used Cryptol to create a behavioral model of
the entire RTS, including all subsystems, components, and limited digital twin
models of sensors, actuators, and compute infrastructure. Automatic code
synthesis generated verifiable C implementations and SystemVerilog hardware
implementations directly from Cryptol models---eliminating the traditional gap
between specification and implementation where errors commonly arise.
Despite its accomplishments, HARDENS has a fundamental limitation directly
relevant to hybrid control synthesis: the project addressed only discrete
digital control logic without modeling or verifying continuous reactor dynamics.
The Reactor Trip System specification and verification covered discrete state
transitions (trip/no-trip decisions), digital sensor input processing through
discrete logic, and discrete actuation outputs (reactor trip commands). The
project did not address continuous dynamics of nuclear reactor physics. Real
reactor safety depends on the interaction between continuous
processes---temperature, pressure, neutron flux---evolving in response to
discrete control decisions. HARDENS verified the discrete controller in
isolation but not the closed-loop hybrid system behavior.
\textbf{LIMITATION:} \textit{HARDENS addressed discrete control logic without
continuous dynamics or hybrid system verification.} Verifying discrete control
logic alone provides no guarantee that the closed-loop system exhibits desired
continuous behavior such as stability, convergence to setpoints, or maintained
safety margins.
HARDENS produced a demonstrator system at Technology Readiness Level 2--3
(analytical proof of concept with laboratory breadboard validation) rather than
a deployment-ready system validated through extended operational testing. The
NRC Final Report explicitly notes~\cite{Kiniry2024} that all material is
considered in development, not a finalized product, and that ``The demonstration
of its technical soundness was to be at a level consistent with satisfaction of
the current regulatory criteria, although with no explicit demonstration of how
regulatory requirements are met.'' The project did not include deployment in
actual nuclear facilities, testing with real reactor systems under operational
conditions, side-by-side validation with operational analog RTS systems,
systematic failure mode testing (radiation effects, electromagnetic
interference, temperature extremes), NRC licensing review, or human factors
validation with licensed operators in realistic control room scenarios.
\textbf{LIMITATION:} \textit{HARDENS achieved TRL 2--3 without experimental
validation.} While formal verification provides mathematical correctness
guarantees for the implemented discrete logic, the gap between formal
verification and actual system deployment involves myriad practical
considerations: integration with legacy systems, long-term reliability
under harsh environments, human-system interaction in realistic
operational contexts, and regulatory acceptance of formal methods as
primary assurance evidence.

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Okay so here's how things will go:
Integrate V design into the workings here
1. Requirement identification and translation
1. Point towards hardens lando thing
2. we're going to do a nuclear start up sequence
2. Synthesize requirements into a discrete automata
1. this makes up our mode switching behavior
2. There's probably going to be a serious amount of
refinement required here
3. Figure out by the structure of the nodes what the
purpose of the mode is
1. Do all traces leave? Do any traces leave? What
does this mean for the FUNCTION of the node?
3. Build controllers that satisfy each mode requirement
1. Reachability to ensure valid input and output sets?
2. We can ensure zeno behavior won't happen by looking
at the interface between modes
3. We should also see based on reachability that a well
built controller ONLY can enter the modes as
specified by the discrete automata
4. Contract based methods?
4. Fuck it man, that's like your provability or whatever
man.
What are the critical needs?
1. We need a way to build some operating procedures into
controllers for autonomy
2. How the hell do we know what the goals of each mode are?
3. How do we know for sure the continuous dynamics will
actually get us there?

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\section{Research Approach}
This research will overcome the limitations of current practice to build
high-assurance hybrid control systems for critical infrastructure. Building
these systems with formal correctness guarantees requires three main thrusts:
\begin{enumerate}
\item Translate operating procedures and requirements into temporal logic
formulae
\item Create the discrete half of a hybrid controller using reactive synthesis
\item Develop continuous controllers to operate between modes, and verify
their correctness
\end{enumerate}
Commercial nuclear power operations remain manually controlled by human
operators, yet the procedures they follow are highly prescriptive and
well-documented. This suggests that human operators may not be entirely
necessary given current technology. Written procedures and requirements are
sufficiently detailed that they may be translatable into logical formulae with
minimal effort. If successful, this approach enables automation of existing
procedures without system reengineering. To formalize these procedures, we will
use temporal logic, which captures system behaviors through temporal relations.
The most efficient path for this translation is NASA's Formal Requirements
Elicitation Tool (FRET). FRET employs a specialized requirements language called
FRETish that restricts requirements to easily understood components while
eliminating ambiguity~\cite{katis_capture_2022}. FRETish bridges natural language
and mathematical specifications through a structured English-like syntax
automatically translatable to temporal logic.
FRET enforces this structure by requiring all requirements to contain six
components: %CITE FRET MANUAL
\begin{enumerate}
\item Scope: \textit{What modes does this requirement apply to?}
\item Condition: \textit{Scope plus additional specificity}
\item Component: \textit{What system element does this requirement affect?}
\item Shall
\item Timing: \textit{When does the response occur?}
\item Response: \textit{What action should be taken?}
\end{enumerate}
FRET provides functionality to check system \textit{realizability}. Realizability
analysis determines whether written requirements are complete by examining the
six structural components. Complete requirements neither conflict with one
another nor leave any behavior undefined. Systems that are not realizable from
their procedure definitions and design requirements present problems beyond
autonomous control implementation. Such systems contain behavioral
inconsistencies---the physical equivalent of software bugs. Using FRET during
autonomous controller development allows systematic identification and
resolution of these errors.
The second category of realizability issues involves undefined behaviors
typically left to human judgment during operations. This ambiguity is
undesirable for high-assurance systems, since even well-trained humans remain
prone to errors. Addressing these specification gaps in FRET during development
yields controllers free from these vulnerabilities.
FRET exports requirements in temporal logic format compatible with reactive
synthesis tools. Linear Temporal Logic (LTL) builds upon modal logic's
foundational operators for necessity ($\Box$, ``box'') and possibility
($\Diamond$, ``diamond''), extending them to reason about temporal
behavior~\cite{baier_principles_2008}. The box operator $\Box$ expresses that a
property holds at all future times (necessarily always), while the diamond
operator $\Diamond$ expresses that a property holds at some future time
(possibly eventually). These are complemented by the next operator ($X$) for the
immediate successor state and the until operator ($U$) for expressing
persistence conditions.
Consider a nuclear reactor SCRAM requirement expressed in natural language:
\textit{``If a high temperature alarm triggers, control rods must immediately
insert and remain inserted until operator reset.''} This plain language
requirement can be translated into a rigorous logical specification:
\begin{equation}
\Box(HighTemp \rightarrow X(RodsInserted \wedge (\neg
RodsWithdrawn\ U\ OperatorReset)))
\end{equation}
This specification precisely captures the temporal relationship between the
alarm condition, the required response, and the persistence requirement. The
necessity operator $\Box$ ensures this safety property holds throughout all
possible future system executions, while the next operator $X$ enforces
immediate response. The until operator $U$ maintains the state constraint until
the reset condition occurs. No ambiguity exists in this scenario because all
decisions are represented by discrete variables. Formulating operating rules in
this logic enforces finite, correct operation.
Reactive synthesis is an active research field focused on generating discrete
controllers from temporal logic specifications. The term ``reactive'' indicates
that the system responds to environmental inputs to produce control outputs.
These synthesized systems are finite, with each node representing a unique
discrete state. The connections between nodes, called \textit{state
transitions}, specify the conditions under which the discrete controller moves
from state to state. This complete mapping of possible states and transitions
constitutes a \textit{discrete automaton}. Discrete automata can be represented
graphically as nodes (discrete states) with edges indicating transitions between
them. From the automaton graph, one can fully describe discrete system dynamics
and develop intuitive understanding of system behavior. Hybrid systems naturally
exhibit discrete behavior amenable to formal analysis through these finite state
representations.
We will employ state-of-the-art reactive synthesis tools, particularly Strix,
which has demonstrated superior performance in the Reactive Synthesis
Competition (SYNTCOMP) through efficient parity game solving
algorithms~\cite{meyer_strix_2018,jacobs_reactive_2024}. Strix translates linear
temporal logic specifications into deterministic automata automatically while
maximizing generated automata quality. Once constructed, the automaton can be
implemented using standard programming control flow constructs. The graphical
representation enables inspection and facilitates communication with controls
programmers who lack formal methods expertise.
We will use discrete automata to represent the switching behavior of our hybrid
system. This approach yields an important theoretical guarantee: because the
discrete automaton is synthesized entirely through automated tools from design
requirements and operating procedures, the automaton---and therefore our hybrid
switching behavior---is \textit{correct by construction}. Correctness of the
switching controller is paramount. Mode switching represents the primary
responsibility of human operators in control rooms today. Human operators
possess the advantage of real-time judgment: when mistakes occur, they can
correct them dynamically with capabilities extending beyond written procedures.
Autonomous control lacks this adaptive advantage. Instead, autonomous
controllers replacing human operators must not make switching errors between
continuous modes. Synthesizing controllers from logical specifications with
guaranteed correctness eliminates the possibility of switching errors.
While discrete system components will be synthesized with correctness
guarantees, they represent only half of the complete system. Autonomous
controllers like those we are developing exhibit continuous dynamics within
discrete states. These systems, called hybrid systems, combine continuous
dynamics (flows) with discrete transitions (jumps). These dynamics can be
formally expressed as~\cite{branicky_multiple_1998}:
\begin{equation}
\dot{x}(t) = f(x(t),q(t),u(t))
\end{equation}
\begin{equation}
q(k+1) = \nu(x(k),q(k),u(k))
\end{equation}
Here, $f(\cdot)$ defines the continuous dynamics while $\nu(\cdot)$ governs
discrete transitions. The continuous states $x$, discrete state $q$, and
control input $u$ interact to produce hybrid behavior. The discrete state $q$
defines which continuous dynamics mode is currently active. Our focus centers
on continuous autonomous hybrid systems, where continuous states remain
unchanged during jumps---a property naturally exhibited by physical systems. For
example, a nuclear reactor switching from warm-up to load-following control
cannot instantaneously change its temperature or control rod position, but can
instantaneously change control laws.
The approach described for producing discrete automata yields physics-agnostic
specifications representing only half of a complete hybrid autonomous
controller. These automata alone cannot define the full behavior of the control
systems we aim to construct. The continuous modes will be developed after
discrete automaton construction, leveraging the automaton structure and
transitions to design multiple smaller, specialized continuous controllers.
Notably, translation into linear temporal logic creates barriers between
different control modes. Switching from one mode to another becomes a discrete
boolean variable. \(RodsInserted\) or \(HighTemp\) in the temporal
specifications are booleans, but in the real system they represent physical
features in the state space. These features mark where continuous control modes
end and begin; their definition is critical for determining which control mode
is active at any given time. Information about where in the state space these
conditions exist will be preserved from the original requirements and included
in continuous control mode development, but will not appear as numeric values in
discrete mode switching synthesis.
The discrete automaton transitions are key to the supervisory behavior of the
autonomous controller. These transitions mark decision points for switching
between continuous control modes and define their strategic objectives. We
will classify three types of high-level continuous controller objectives based
on discrete mode transitions:
\begin{enumerate}
\item \textbf{Stabilizing:} A stabilizing control mode has one primary
objective: maintaining the hybrid system within its current discrete mode.
This corresponds to steady-state normal operating modes, such as a
full-power load-following controller in a nuclear power plant. Stabilizing
modes can be identified from discrete automata as nodes with only incoming
transitions.
\item \textbf{Transitory:} A transitory control mode has the primary goal of
transitioning the hybrid system from one discrete state to another. In
nuclear applications, this might represent a controlled warm-up procedure.
Transitory modes ultimately drive the system toward a stabilizing
steady-state mode. These modes may have secondary objectives within a
discrete state, such as maintaining specific temperature ramp rates before
reaching full-power operation.
\item \textbf{Expulsory:} An expulsory mode is a specialized transitory mode
with additional safety constraints. Expulsory modes ensure the system is
directed to a safe stabilizing mode during failure conditions. For example,
if a transitory mode fails to achieve its intended transition, the
expulsory mode activates to immediately and irreversibly guide the system
toward a globally safe state. A reactor SCRAM exemplifies an expulsory
continuous mode: when initiated, it must reliably terminate the nuclear
reaction and direct the reactor toward stabilizing decay heat removal.
\end{enumerate}
Building continuous modes after constructing discrete automata enables local
controller design focused on satisfying discrete transitions. The primary
challenge in hybrid system verification is ensuring global stability across
transitions~\cite{branicky_multiple_1998}. Current techniques struggle with this
problem because dynamic discontinuities complicate
verification~\cite{bansal_hamilton-jacobi_2017,guernic_reachability_2009}. This
work alleviates these problems by designing continuous controllers specifically
with transitions in mind. Decomposing continuous modes according to their
required behavior at transition points avoids solving trajectories through the
entire hybrid system. Instead, local behavior information at transition
boundaries suffices. To ensure continuous modes satisfy their requirements, we
employ three main techniques: reachability analysis, assume-guarantee contracts,
and barrier certificates.
Reachability analysis computes the reachable set of states for a given input
set. While trivial for linear continuous systems, recent advances have extended
reachability to complex nonlinear
systems~\cite{frehse_spaceex_2011,mitchell_time-dependent_2005}. We use
reachability to define continuous state ranges at discrete transition boundaries
and verify that requirements are satisfied within continuous modes.
Assume-guarantee contracts apply when continuous state boundaries are not
explicitly defined. For any given mode, the input range for reachability
analysis is defined by the output ranges of discrete modes that transition to
it. This compositional approach ensures each continuous controller is prepared
for its possible input range, enabling reachability analysis without global
system analysis. Finally, barrier certificates prove that mode transitions are
satisfied. Barrier certificates ensure that continuous modes on either side of a
transition behave appropriately by preventing system trajectories from crossing
a given barrier. Control barrier functions certify safety by establishing
differential inequality conditions that guarantee forward invariance of safe
sets~\cite{prajna_safety_2004}. For example, a barrier certificate can guarantee
that a transitory mode transferring control to a stabilizing mode will always
move away from the transition boundary, rather than destabilizing the target
stabilizing mode.
This compositional approach has several advantages. First, this approach breaks
down autonomous controller design into smaller pieces. For designers of future
autonomous control systems, the barrier to entry is low, and design milestones
are clear due to the procedural nature of this research plan. Second, measurable
design progress also enables measurement of regulatory adherence. Each step in
this development procedure generates an artifact that can be independently
evaluated as proof of safety and performance. Finally, the compositional nature
of this development plan enables incremental refinement between control system
layers. For example, difficulty developing a continuous mode may reflect a
discrete automaton that is too restrictive, prompting refinement of system
design requirements. This synthesis between levels promotes broader
understanding of the autonomous controller.
To demonstrate this methodology, we will develop an autonomous startup
controller for a Small Modular Advanced High Temperature Reactor (SmAHTR). We
have already developed a high-fidelity SmAHTR model in Simulink that captures
the thermal-hydraulic and neutron kinetics behavior essential for verifying
continuous controller performance under realistic plant dynamics. The
synthesized hybrid controller will be implemented on an Emerson Ovation control
system platform, representative of industry-standard control hardware deployed
in modern nuclear facilities. The Advanced Reactor Cyber Analysis and
Development Environment (ARCADE) suite will serve as the integration layer,
managing real-time communication between the Simulink simulation and the Ovation
controller. This hardware-in-the-loop configuration enables validation of the
controller implementation on actual industrial control equipment interfacing
with a realistic reactor simulation, assessing computational performance,
real-time execution constraints, and communication latency effects.
Demonstrating autonomous startup control on this representative platform will
establish both the theoretical validity and practical feasibility of the
synthesis methodology for deployment in actual small modular reactor systems.
This unified approach addresses a fundamental gap in hybrid system design by
bridging formal methods and control theory through a systematic, tool-supported
methodology. Translating existing nuclear procedures into temporal logic,
synthesizing provably correct discrete switching logic, and developing verified
continuous controllers creates a complete framework for autonomous hybrid
control with mathematical guarantees. The result is an autonomous controller
that not only replicates human operator decision-making but does so with formal
assurance that switching logic is correct by construction and continuous
behavior satisfies safety requirements. This methodology transforms nuclear
reactor control from a manually intensive operation requiring constant human
oversight into a fully autonomous system with higher reliability than
human-operated alternatives. More broadly, this approach establishes a
replicable framework for developing high-assurance autonomous controllers in any
domain where operating procedures are well-documented and safety is paramount.

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\section{Metrics for Success}
This research will be measured by advancement through Technology Readiness
Levels, progressing from fundamental concepts to validated prototype
demonstration. This work begins at TRL 2--3 and aims to reach TRL 5, where
system components operate successfully in a relevant laboratory environment.
This section explains why TRL advancement provides the most appropriate success
metric and defines the specific criteria required to achieve TRL 5.
Technology Readiness Levels provide the ideal success metric because they
explicitly measure the gap between academic proof-of-concept and practical
deployment---precisely what this work aims to bridge. Academic metrics like
papers published or theorems proved cannot capture practical feasibility.
Empirical metrics like simulation accuracy or computational speed cannot
demonstrate theoretical rigor. TRLs measure both dimensions simultaneously.
Advancing from TRL 3 to TRL 5 requires maintaining theoretical rigor while
progressively demonstrating practical feasibility. Formal verification must
remain valid as the system moves from individual components to integrated
hardware testing.
The nuclear industry requires extremely high assurance before deploying new
control technologies. Demonstrating theoretical correctness alone is
insufficient for adoption; conversely, showing empirical performance without
formal guarantees fails to meet regulatory requirements. TRLs capture this dual
requirement naturally. Each level represents both increased practical maturity
and sustained theoretical validity. Furthermore, TRL assessment forces explicit
identification of remaining barriers to deployment. The nuclear industry already
uses TRLs for technology assessment, making this metric directly relevant to
potential adopters. Reaching TRL 5 provides a clear answer to industry questions
about feasibility and maturity that academic publications alone cannot.
Moving from current state to target requires achieving three intermediate
levels, each representing a distinct validation milestone:
\paragraph{TRL 3 \textit{Critical Function and Proof of Concept}}
For this research, TRL 3 means demonstrating that each component of the
methodology works in isolation. Startup procedures must be translated into
temporal logic specifications that pass realizability analysis. A discrete
automaton must be synthesized with interpretable structure. At least one
continuous controller must be designed with reachability analysis proving
transition requirements are satisfied. Independent review must confirm that
specifications match intended procedural behavior. This proves the fundamental
approach on a simplified startup sequence.
\paragraph{TRL 4 \textit{Laboratory Testing of Integrated Components}}
For this research, TRL 4 means demonstrating a complete integrated hybrid
controller in simulation. All startup procedures must be formalized with a
synthesized automaton covering all operational modes. Continuous controllers
must exist for all discrete modes. Verification must be complete for all mode
transitions using reachability analysis, barrier certificates, and
assume-guarantee contracts. The integrated controller must execute complete
startup sequences in software simulation with zero safety violations across
multiple consecutive runs. This proves that formal correctness guarantees can be
maintained throughout system integration.
\paragraph{TRL 5 \textit{Laboratory Testing in Relevant Environment}}
For this research, TRL 5 means demonstrating the verified controller on
industrial control hardware through hardware-in-the-loop testing. The discrete
automaton must be implemented on the Emerson Ovation control system and verified
to match synthesized specifications exactly. Continuous controllers must execute
at required rates. The ARCADE interface must establish stable real-time
communication between the Emerson Ovation hardware and SmAHTR simulation.
Complete autonomous startup sequences must execute via hardware-in-the-loop
across the full operational envelope. The controller must handle off-nominal
scenarios to validate that expulsory modes function correctly. For example,
simulated sensor failures must trigger appropriate fault detection and mode
transitions, and loss-of-cooling scenarios must activate SCRAM procedures as
specified. Graded responses to minor disturbances are outside this work's scope.
Formal verification results must remain valid, with discrete behavior matching
specifications and continuous trajectories remaining within verified bounds.
This proves that the methodology produces verified controllers implementable on
industrial hardware.
Progress will be assessed quarterly through collection of specific data
comparing actual results against TRL advancement criteria. Specification
development status indicates progress toward TRL 3. Synthesis results and
verification coverage indicate progress toward TRL 4. Simulation performance
metrics and hardware integration milestones indicate progress toward TRL 5. The
research plan will be revised only when new data invalidates fundamental
assumptions. This research succeeds if it achieves TRL 5 by demonstrating a
complete autonomous hybrid controller with formal correctness guarantees
operating on industrial control hardware through hardware-in-the-loop testing in
a relevant laboratory environment. This establishes both theoretical validity
and practical feasibility, proving that the methodology produces verified
controllers and that implementation is achievable with current technology.

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# Risk and Contingencies Assumptions Exercise
**The outcome I want to achieve is?**
- Turn written reqs into discrete controller
- Build continuous modes that ensure hybrid stability
- Implement on industrial controller with HIL simulation
**What can't anyone solve this today?**
- Nobody has tried to build system like this with stability
in mind from the ground up. NUCE is a specific domain this
is useful. Reliance on human operators for safety.
**The research approach I am using is?**
- Formal Methods + Control Theory
- FRET - Reachability
- Reactive Synthesis
**This research approach relies on these fundamental
principles?**
- Temporal logic precision
- automata
- differential and difference equations
- procedure writing
**The experiment that I will perform is?**
- trying to make an autonomous start up procedure for a
SmAHTR reactor
**The equipment I will use is?**
1. FRET
2. STRIX
3. Simulink
4. Reachability tools
5. Ovation
**I will analyze the results using?**
1. Prose. How hard was this to do, what MacGuyvering needed
done? What TRL?
**The expected outcome of this experiment is?**
1. A working autonomous start up controller can take a
simulation from cold to critical without needing a human
operator to intervene.
**What happens if this experiment does not work?**
1. We'll shift to a smaller, simpler problem where we can
overcome the limits.
**What happens if the hypothesis or prediction is false?**
1. We'll show the gap between current procedure writing and
where we need to be to actually do synthesis.
**What assumptions do I have that, if proven wrong, would
derail this project?**
1. Temporal logic from FRET is easy to synthesize with STRIX
2. I'm not going to have state-space explosion happen
3. Writing a start-up procedure for SmAHTR isn't that hard
4. People give a crap about molten salt reactors
5. This whole discrete boundary thing is not going to be
really hard to implement. The idea is conditions for the
transitions between modes to be boolean variables for
the temporal lgoic, but that they correspond to some surface
in the continuous state space. How am I going to keep track
of that?
6. Computational cost. Center for Research Computing is the
answer.

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\section{Risks and Contingencies}
This research relies on several critical assumptions that, if invalidated, would
require scope adjustment or methodological revision. The primary risks to
successful completion fall into four categories: computational tractability of
synthesis and verification, complexity of the discrete-continuous interface,
completeness of procedure formalization, and hardware-in-the-loop integration
challenges. Each risk has associated indicators for early detection and
contingency plans that preserve research value even if core assumptions prove
false. The staged project structure ensures that partial success yields
publishable results and clear identification of remaining barriers to
deployment.
\subsection{Computational Tractability of Synthesis}
The first major assumption is that formalized startup procedures will yield
automata small enough for efficient synthesis and verification. Reactive
synthesis scales exponentially with specification complexity, creating risk that
temporal logic specifications derived from complete startup procedures may
produce automata with thousands of states. Such large automata would require
synthesis times exceeding days or weeks, preventing demonstration of the
complete methodology within project timelines. Reachability analysis for
continuous modes with high-dimensional state spaces may similarly prove
computationally intractable. Either barrier would constitute a fundamental
obstacle to achieving the research objectives.
Several indicators would provide early warning of computational tractability
problems. Synthesis times exceeding 24 hours for simplified procedure subsets
would suggest complete procedures are intractable. Generated automata containing
more than 1,000 discrete states would indicate the discrete state space is too
large for efficient verification. Specifications flagged as unrealizable by FRET
or Strix would reveal fundamental conflicts in the formalized procedures.
Reachability analysis failing to converge within reasonable time bounds would
show that continuous mode verification cannot be completed with available
computational resources.
The contingency plan for computational intractability is to reduce scope to a
minimal viable startup sequence. This reduced sequence would cover only cold
shutdown to criticality to low-power hold, omitting power ascension and other
operational phases. The subset would still demonstrate the complete methodology
while reducing computational burden. The research contribution would remain
valid even with reduced scope, proving that formal hybrid control synthesis is
achievable for safety-critical nuclear applications. The limitation to
simplified operational sequences would be explicitly documented as a constraint
rather than a failure.
\subsection{Discrete-Continuous Interface Formalization}
The second critical assumption concerns the mapping between boolean guard
conditions in temporal logic and continuous state boundaries required for mode
transitions. This interface represents the fundamental challenge of hybrid
systems: relating discrete switching logic to continuous dynamics. Temporal
logic operates on boolean predicates, while continuous control requires
reasoning about differential equations and reachable sets. Guard conditions
requiring complex nonlinear predicates may resist boolean abstraction, making
synthesis intractable. Continuous safety regions that cannot be expressed as
conjunctions of verifiable constraints would similarly create insurmountable
verification challenges. The risk extends beyond static interface definition to
dynamic behavior across transitions: barrier certificates may fail to exist for
proposed transitions, or continuous modes may be unable to guarantee convergence
to discrete transition boundaries.
Early indicators of interface formalization problems would appear during both
synthesis and verification phases. Guard conditions requiring complex nonlinear
predicates that resist boolean abstraction would suggest fundamental misalignment
between discrete specifications and continuous realities. Continuous safety
regions that cannot be expressed as conjunctions of half-spaces or polynomial
inequalities would indicate the interface between discrete guards and continuous
invariants is too complex. Failure to construct barrier certificates proving
safety across mode transitions would reveal that continuous dynamics cannot be
formally related to discrete switching logic. Reachability analysis showing that
continuous modes cannot reach intended transition boundaries from all possible
initial conditions would demonstrate the synthesized discrete controller is
incompatible with achievable continuous behavior.
The primary contingency for interface complexity is restricting continuous modes
to operate within polytopic invariants. Polytopes are state regions defined as
intersections of linear half-spaces, which map directly to boolean predicates
through linear inequality checks. This restriction ensures tractable synthesis
while maintaining theoretical rigor, though at the cost of limiting
expressiveness compared to arbitrary nonlinear regions. The discrete-continuous
interface remains well-defined and verifiable with polytopic restrictions,
providing a clear fallback position that preserves the core methodology.
Conservative over-approximations offer an alternative approach: a nonlinear safe
region can be inner-approximated by a polytope, sacrificing operational
flexibility to maintain formal guarantees. The three-mode classification already
structures the problem to minimize complex transitions, with critical safety
properties concentrated in expulsory modes that can receive additional design
attention.
Mitigation strategies focus on designing continuous controllers with discrete
transitions as primary objectives from the outset. Rather than designing
continuous control laws independently and verifying transitions post-hoc, the
approach uses transition requirements as design constraints. Control barrier
functions provide a systematic method to synthesize controllers that guarantee
forward invariance of safe sets and convergence to transition boundaries. This
design-for-verification approach reduces the likelihood that interface
complexity becomes insurmountable. Focusing verification effort on expulsory
modes---where safety is most critical---allows more complex analysis to be
applied selectively rather than uniformly across all modes, concentrating
computational resources where they matter most for safety assurance.
\subsection{Procedure Formalization Completeness}
The third assumption is that existing startup procedures contain sufficient
detail and clarity for translation into temporal logic specifications. Nuclear
operating procedures, while extensively detailed, were written for human
operators who bring contextual understanding and adaptive reasoning to their
interpretation. Procedures may contain implicit knowledge, ambiguous directives,
or references to operator judgment that resist formalization in current
specification languages. Underspecified timing constraints, ambiguous condition
definitions, or gaps in operational coverage would cause synthesis to fail or
produce incorrect automata. The risk is not merely that formalization is
difficult, but that current procedures fundamentally lack the precision required
for autonomous control, revealing a gap between human-oriented documentation and
machine-executable specifications.
Several indicators would reveal formalization completeness problems early in the
project. FRET realizability checks failing due to underspecified behaviors or
conflicting requirements would indicate procedures do not form a complete
specification. Multiple valid interpretations of procedural steps with no clear
resolution would demonstrate procedure language is insufficiently precise for
automated synthesis. Procedures referencing ``operator judgment,'' ``as
appropriate,'' or similar discretionary language for critical decisions would
explicitly identify points where human reasoning cannot be directly formalized.
Domain experts unable to provide crisp answers to specification questions about
edge cases would suggest the procedures themselves do not fully define system
behavior, relying instead on operator training and experience to fill gaps.
The contingency plan treats inadequate specification as itself a research
contribution rather than a project failure. Documenting specific ambiguities
encountered would create a taxonomy of formalization barriers: timing
underspecification, missing preconditions, discretionary actions, and undefined
failure modes. Each category would be analyzed to understand why current
procedure-writing practices produce these gaps and what specification languages
would need to address them. Proposed extensions to FRETish or similar
specification languages would demonstrate how to bridge the gap between current
procedures and the precision needed for autonomous control. The research output
would shift from ``here is a complete autonomous controller'' to ``here is what
formal autonomous control requires that current procedures do not provide, and
here are language extensions to bridge that gap.'' This contribution remains
valuable to both the nuclear industry and formal methods community, establishing
clear requirements for next-generation procedure development and autonomous
control specification languages.
Early-stage procedure analysis with domain experts provides the primary
mitigation strategy. Collaboration through the University of Pittsburgh Cyber
Energy Center enables identification and resolution of ambiguities before
synthesis attempts, rather than discovering them during failed synthesis runs.
Iterative refinement with reactor operators and control engineers can clarify
procedural intent before formalization begins, reducing the risk of discovering
insurmountable specification gaps late in the project. Comparison with
procedures from multiple reactor designs---pressurized water reactors, boiling
water reactors, and advanced designs---may reveal common patterns and standard
ambiguities amenable to systematic resolution. This cross-design analysis would
strengthen the generalizability of any proposed specification language
extensions, ensuring they address industry-wide practices rather than specific
quirks.

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\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.
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 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---will
establish both the technical feasibility and regulatory pathway for broader
adoption across critical infrastructure.

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\section{Schedule, Milestones, and Deliverables}
This research will be conducted over six trimesters (24 months) of full-time
effort following the proposal defense in Spring 2026. The work progresses
sequentially through three main research thrusts before culminating in
integrated demonstration and validation.
The first semester (Spring 2026) focuses on Thrust 1, translating startup
procedures into formal temporal logic specifications using FRET. This
establishes the foundation for automated synthesis by converting natural
language procedures into machine-readable requirements. The second semester
(Summer 2026) addresses Thrust 2, using Strix to synthesize the discrete
automaton that defines mode-switching behavior. With the discrete structure
established, the third semester (Fall 2026) develops the continuous controllers
for each operational mode through Thrust 3, employing reachability analysis and
barrier certificates to verify that each mode satisfies its transition
requirements. Integration and validation occupy the remaining three semesters.
Figure \ref{fig:gantt} shows the complete project schedule including research thrusts, major milestones, and planned publications.
\begin{figure}[htbp]
\centering
\begin{ganttchart}[
hgrid,
vgrid={*{4}{draw=none}, dotted},
x unit=0.4cm,
y unit title=0.6cm,
y unit chart=0.4cm,
title/.append style={fill=gray!30},
title height=1,
bar/.append style={fill=blue!50},
bar height=0.5,
bar label font=\small,
milestone/.append style={fill=red, shape=diamond},
milestone height=0.5
]{1}{24}
% Timeline headers
\gantttitle{2026}{12}
\gantttitle{2027}{12} \\
\gantttitle{Spring}{4}
\gantttitle{Summer}{4}
\gantttitle{Fall}{4}
\gantttitle{Spring}{4}
\gantttitle{Summer}{4}
\gantttitle{Fall}{4} \\
% Major thrusts
\ganttbar{Thrust 1: Procedure Translation}{1}{5} \\
\ganttbar{Thrust 2: Discrete Synthesis}{4}{10} \\
\ganttbar{Thrust 3: Continuous Control}{9}{15} \\
\ganttbar{Integration \& Simulation (TRL 4)}{13}{17} \\
\ganttbar{Hardware-in-Loop Testing (TRL 5)}{16}{21} \\
\ganttbar{Dissertation Writing}{18}{24} \\[grid]
% Milestones row
\ganttbar[bar/.append style={fill=orange!50}]{Milestones}{1}{24}
\ganttmilestone{}{4}
\ganttmilestone{}{8}
\ganttmilestone{}{12}
\ganttmilestone{}{16}
\ganttmilestone{}{20}
\ganttmilestone{}{24} \\
% Publications row
\ganttbar[bar/.append style={fill=green!50}]{Publications}{1}{24}
\ganttmilestone{}{8}
\ganttmilestone{}{16}
\ganttmilestone{}{20}
\end{ganttchart}
\caption{Project schedule showing major research thrusts, milestones (orange row), and publications (green row). Red diamonds indicate completion points. Overlapping bars indicate parallel work where appropriate.}
\label{fig:gantt}
\end{figure}
\subsection{Milestones and Deliverables}
Six major milestones mark critical validation points throughout the research. M1
(Month 4) confirms that startup procedures have been successfully translated to
temporal logic using FRET with realizability analysis demonstrating consistent
and complete specifications. M2 (Month 8) validates computational tractability
by demonstrating that Strix can synthesize a complete discrete automaton from
the formalized specifications. This milestone delivers a conference paper
submission to NPIC\&HMIT documenting the procedure-to-specification translation
methodology. M3 (Month 12) achieves TRL 3 by proving that continuous controllers
can be designed and verified to satisfy discrete transition requirements. This
milestone delivers an internal technical report demonstrating component-level
verification. M4 (Month 16) achieves TRL 4 through integrated simulation
demonstrating that component-level correctness composes to system-level
correctness. This milestone delivers a journal paper submission to IEEE
Transactions on Automatic Control presenting the complete hybrid synthesis
methodology. M5 (Month 20) achieves TRL 5 by demonstrating practical
implementability on industrial hardware. This milestone delivers a conference
paper submission to NPIC\&HMIT or CDC documenting hardware implementation and
experimental validation. M6 (Month 24) completes the dissertation documenting
the entire methodology, experimental results, and research contributions.

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# ERLM Proposal Writing Review - Executive Summary
**Date**: December 2, 2025 **Reviewer**: Claude Code
**Framework**: Gopen's Sense of Structure
---
## Overview
This proposal demonstrates strong technical content, clear
methodology, and comprehensive coverage of all required
elements. The research approach is well-conceived, and the
progression from problem statement through solution is
logical. The writing is generally clear and professional.
**Key Strengths:**
- Excellent technical depth and specificity
- Strong motivation established through human factors
statistics
- Clear three-thrust research structure
- Comprehensive risk analysis with concrete contingencies
- Good use of specific examples (TMI accident, HARDENS
project)
**Priority Areas for Revision:**
- Sentence-level: Strengthen stress positions to emphasize
key claims
- Paragraph-level: Sharpen point-issue structure in some
sections
- Section-level: Tighten organization in State of the Art
section
- Big picture: Strengthen "so what" connections throughout
---
## Priority Issues (Top 10)
### 1. **SOTA Section Length and Organization**
[SECTION-LEVEL] **Location**: State of the Art section (358
lines) **Issue**: The SOTA section is the longest in the
proposal and covers multiple distinct topics (current
procedures, human factors, HARDENS). While comprehensive, it
risks overwhelming readers and obscuring your key
contributions. **Impact**: HIGH - Reviewers may lose track
of your argument in the density **Recommendation**:
Consider restructuring with clearer signposting. Each
subsection should explicitly connect back to what gap
you're filling. The current "\textbf{LIMITATION:}" callouts
are excellent—ensure every major subsection has one.
### 2. **Weak Stress Positions Throughout** [SENTENCE-LEVEL]
**Location**: All sections, especially Goals and State of
the Art **Issue**: Many sentences place old/known
information in stress position (sentence-final), missing
opportunities to emphasize new claims **Impact**:
MEDIUM-HIGH - Reduces rhetorical impact of key claims **See
Pattern**: "Stress Position Weakness" below for examples and
fixes
### 3. **Missing "So What" Connections** [BIG PICTURE]
**Location**: Transitions between major sections **Issue**:
The proposal moves from problem → approach → metrics without
always explicitly stating "this matters because..." at
transition points **Impact**: MEDIUM-HIGH - Reviewers may
not fully grasp significance **Recommendation**: Add
explicit "if successful, this enables..." statements at the
end of Goals section and beginning of Metrics section
### 4. **Passive Voice Obscuring Agency** [SENTENCE-LEVEL]
**Location**: Research Approach, especially subsection
introductions **Issue**: Passive constructions like "will be
employed" and "will be used" hide who does what and reduce
directness **Impact**: MEDIUM - Reduces clarity and makes
writing feel less confident **See Pattern**: "Passive Voice"
below
### 5. **Point-Issue Structure in Paragraphs**
[PARAGRAPH-LEVEL] **Location**: State of the Art, Risk
sections **Issue**: Some paragraphs present information
without first establishing why readers should care (the
"issue") **Impact**: MEDIUM - Readers may wonder "why are
you telling me this?" **See Pattern**: "Point-Issue
Structure" below
### 6. **Topic String Breaks** [PARAGRAPH-LEVEL]
**Location**: Research Approach, subsection transitions
**Issue**: Topic position doesn't always establish clear
continuity from previous sentence, forcing readers to
reconstruct connections **Impact**: MEDIUM - Increases
cognitive load **See Pattern**: "Topic Position &
Continuity" below
### 7. **Nominalization Hiding Action** [SENTENCE-LEVEL]
**Location**: Throughout, especially Research Approach
**Issue**: Action buried in nouns (e.g., "implementation"
instead of "implement", "verification" instead of "verify")
**Impact**: MEDIUM - Makes writing feel static rather than
dynamic **Recommendation**: Convert nominalizations to
active verbs where possible
### 8. **Long Complex Sentences** [SENTENCE-LEVEL]
**Location**: State of the Art (lines 45-51), Risks (lines
72-79) **Issue**: Some sentences exceed 40-50 words with
multiple subordinate clauses, challenging comprehension
**Impact**: MEDIUM - Reviewers may have to re-read
**Recommendation**: Break into 2-3 shorter sentences with
clear logical flow
### 9. **Subsection Balance in Risks Section**
[SECTION-LEVEL] **Location**: Risks and Contingencies
section **Issue**: Four subsections of vastly different
lengths (computational tractability gets more space than
discrete-continuous interface, despite latter being more
fundamental) **Impact**: LOW-MEDIUM - May suggest misaligned
priorities **Recommendation**: Consider whether space
allocation reflects actual risk magnitude
### 10. **Broader Impacts Underutilized** [BIG PICTURE]
**Location**: Broader Impacts section (75 lines vs 358 for
SOTA) **Issue**: This section is relatively brief given that
economic impact is a major motivation for SMRs **Impact**:
LOW-MEDIUM - Missing opportunity to strengthen value
proposition **Recommendation**: Consider expanding economic
analysis or adding brief discussion of workforce/educational
impacts
---
## Key Patterns Identified
### Pattern 1: Stress Position Weakness
**Principle** (Gopen): The stress position (end of sentence)
should contain the most important new information. Readers
expect climax at sentence-end and are disappointed when they
find old information or weak phrases there.
**Example 1** (Goals and Outcomes, lines 13-17): ```
Current: "Currently, nuclear plant operations rely on
extensively trained human operators who follow detailed
written procedures and strict regulatory requirements to
manage reactor control." ```
- **Issue**: Sentence ends with "manage reactor control"—a
restatement of the opening. The key claim is buried
mid-sentence: "extensively trained...detailed
procedures...strict requirements"
- **Fixed**: "Currently, nuclear plant operations require
extensively trained human operators following detailed
written procedures under strict regulatory requirements."
**Example 2** (State of the Art, lines 53-54): ``` Current:
"Procedures lack formal verification of correctness and
completeness." ```
- **Issue**: Ends weakly with "completeness" which is minor
compared to the bigger issue
- **Fixed**: "Procedures lack formal verification, leaving
correctness and completeness unproven."
**Example 3** (Research Approach, lines 41-42): ``` Current:
"The following sections discuss how these thrusts will be
accomplished." ```
- **Issue**: Pure metadiscourse in stress position, provides
no new information
- **Fixed**: Delete this sentence—the enumeration provides
sufficient transition, or combine with previous sentence:
"...through three main thrusts, each detailed below."
**Similar instances**:
- Goals lines 29-32: "...we will combine formal methods..."
- State of the Art lines 81-85: "...no application of hybrid
control theory exists..."
- Research Approach lines 115-116: "...enable progression to
the next step..."
- Metrics lines 29-31: "...makes this metric directly
relevant..."
- Risks lines 12-13: "...identification of remaining
barriers to deployment"
**How to fix**: Identify the most important new claim in
each sentence and move it to the end. Often this means
converting from "X does Y to achieve Z" to "X achieves Z by
doing Y."
---
### Pattern 2: Passive Voice Obscuring Agency
**Principle** (Gopen): Passive voice obscures who does what
and reduces directness. In proposal writing, active voice
demonstrates confidence and control. Use passive only when
the agent is truly unimportant or unknown.
**Example 1** (Research Approach, line 118): ``` Current:
"We will employ state-of-the-art reactive synthesis
tools..." ```
- **Issue**: "Employ" is weak; you're not hiring the tools,
you're using them
- **Better**: "We will use Strix, a state-of-the-art
reactive synthesis tool..."
- **Best**: "Strix will translate our temporal logic
specifications into deterministic automata..." (Shows what
the tool *does*, not just that you'll use it)
**Example 2** (Research Approach, line 207): ``` Current:
"Control barrier functions will be employed when..." ```
- **Issue**: Passive—who employs them? And "employed" sounds
formal/stuffy
- **Fixed**: "We will use control barrier functions to
verify..." or better "Control barrier functions verify..."
**Example 3** (Metrics, line 67): ``` Current: "This
milestone delivers an internal technical report..." ```
- **Issue**: Milestones don't deliver, people do
- **Fixed**: "We will deliver an internal technical report
documenting..."
**Similar instances**:
- Research Approach lines 161, 175, 206, 220: "will be
employed", "will be developed", "will be used"
- Metrics lines 69, 73, 79, 84: "...delivers a [document]"
- Risks lines 57, 109, 163: various passives
**How to fix**:
1. Identify the real agent (usually "we")
2. Make agent the subject: "We will X" or "X will Y"
3. Choose strong active verbs: use/apply/develop/verify (not
employ/utilize)
---
### Pattern 3: Point-Issue Structure Weakness
**Principle** (Gopen): Paragraphs should begin by
establishing (1) the point/claim being made and (2) why it
matters (the issue). Discussion then supports that point.
Readers need context before details.
**Example 1** (State of the Art, lines 88-107): ``` Current
paragraph begins: "The persistent role of human error in
nuclear safety incidents, despite decades of
improvements..." ```
- **Analysis**: This paragraph immediately dives into the
"persistent role" without first establishing why we're
discussing human factors at all. Reader thinks: "Wait,
weren't we just talking about procedures?"
- **Fixed**: Add issue statement first: "Human factors
provide the most compelling motivation for formal automated
control. Despite decades of improvements in training and
procedures, human error persists in 70-80% of nuclear
incidents—suggesting that operator-based control faces
fundamental, not remediable, limitations."
**Example 2** (Risks, first paragraph): ``` Current: "This
research relies on several critical assumptions that, if
invalidated, would require scope adjustment..." ```
- **Analysis**: Good—this establishes both point (critical
assumptions exist) and issue (invalidity requires
adjustment) immediately. The paragraph then delivers on this
promise. This is a good model!
**Example 3** (Research Approach, lines 166-169): ```
Current: "While discrete system components will be
synthesized with correctness guarantees, they represent only
half of the complete system." ```
- **Analysis**: Good issue statement (discrete alone
insufficient), but could be sharper about the point. What
will this section show?
- **Fixed**: "While discrete system components will be
synthesized with correctness guarantees, they represent only
half of the complete system. This section describes how we
will develop continuous control modes, verify their
correctness, and address the unique verification challenges
at the discrete-continuous interface."
**Similar instances**:
- State of the Art lines 13-34: long paragraph with delayed
point
- Goals lines 103-119: impact paragraph could be tighter
- Approach lines 178-208: three-mode classification needs
clearer framing
**How to fix**:
1. First sentence should state the paragraph's point
2. Second sentence (or same sentence) should state why this
matters
3. Remaining sentences provide supporting detail
---
### Pattern 4: Topic Position & Continuity
**Principle** (Gopen): The topic position (beginning of
sentence) should contain old/familiar information that links
to what came before. This creates flow and coherence. Abrupt
topic shifts disorient readers.
**Example 1** (Goals, lines 18-23): ``` Sentence 1: "...this
reliance on human operators prevents the introduction of
autonomous control capabilities..."
Sentence 2: "Emerging technologies like small modular
reactors face significantly higher per-megawatt staffing
costs..." ```
- **Issue**: Topic shifts abruptly from "reliance on
operators" to "emerging technologies". Connection exists
(both about staffing challenges) but isn't explicit
- **Fixed**: "...prevents autonomous control capabilities.
This limitation creates particular challenges for emerging
technologies like small modular reactors, which face
significantly higher per-megawatt staffing costs..."
**Example 2** (State of the Art, lines 234-243): ```
Sentence about what HARDENS addressed: "...discrete digital
control logic..."
Next sentence: "However, the project did not address
continuous dynamics..." ```
- **Analysis**: Good use of "however, the project" in topic
position—maintains focus on HARDENS while pivoting to
limitation. This is a good model!
**Example 3** (Research Approach, lines 56-58): ``` Sentence
1: "...we may be able to translate them into logical
formulae..."
Sentence 2: "Linear Temporal Logic (LTL) provides four
fundamental operators..." ```
- **Issue**: Abrupt topic shift from "translating
procedures" to "LTL provides". Missing: why LTL? Why now?
- **Fixed**: "...translate them into logical formulae. To
formalize these procedures, we will use Linear Temporal
Logic (LTL), which provides four fundamental operators..."
**Similar instances**:
- Goals lines 23-27: "emerging technologies" → "what is
needed"
- State of the Art lines 72-74: control modes → division
between automated/human
- Approach lines 183-185: stabilizing mode example →
transitory mode definition
**How to fix**:
1. Identify the topic of the previous sentence
2. Begin next sentence with something related to that topic
3. Use transitional phrases when shifting topics: "This
[previous thing] leads to [new thing]"
---
### Pattern 5: Long Complex Sentences
**Principle**: Sentences with multiple subordinate clauses
(especially over 35-40 words) tax reader working memory.
Breaking into multiple sentences often improves clarity
without losing sophistication.
**Example 1** (State of the Art, lines 48-51): ``` Current
(51 words): "Procedures undergo technical evaluation,
simulator validation testing, and biennial review as part of
operator requalification under 10 CFR 55.59, but despite
these rigorous development processes, procedures
fundamentally lack formal verification of key safety
properties." ```
- **Issue**: Long sentence with list, subordinate clause,
and contrast—hard to parse
- **Fixed (2 sentences)**: "Procedures undergo technical
evaluation, simulator validation testing, and biennial
review as part of operator requalification under 10 CFR
55.59. Despite these rigorous development processes,
procedures fundamentally lack formal verification of key
safety properties."
**Example 2** (Risks, lines 72-78): ``` Current (57 words):
"Temporal logic operates on boolean predicates, while
continuous control requires reasoning about differential
equations and reachable sets, and guard conditions that
require complex nonlinear predicates may resist boolean
abstraction, making synthesis intractable." ```
- **Issue**: Run-on with multiple clauses strung together
with commas
- **Fixed (3 sentences)**: "Temporal logic operates on
boolean predicates, while continuous control requires
reasoning about differential equations and reachable sets.
Guard conditions requiring complex nonlinear predicates may
resist boolean abstraction. This mismatch could make
synthesis intractable."
**Similar instances**:
- State of the Art lines 44-51: procedure development
description
- Research Approach lines 40-45: hybrid system description
- Risks lines 17-24: computational tractability discussion
- Broader Impacts lines 13-23: economic analysis
**How to fix**:
1. Identify natural breakpoints (usually where you have
"and" or "but")
2. Create new sentences at these breaks
3. Ensure each new sentence has clear topic position
4. May need to repeat/reference previous sentence's subject
for clarity
---
## Section-Level Issues
### Goals and Outcomes Section **Strengths**: Excellent
structure with clear goal → problem → approach → outcomes →
impact progression. The four-paragraph opening is very
strong.
**Issues**:
- Lines 29-53 (Approach paragraph): This is dense and tries
to cover too much. Consider breaking into two paragraphs:
one on the approach concept, one on the hypothesis and
rationale.
- Outcomes enumeration: Very clear, but could strengthen the
transition from strategy to outcome in each item. Currently
reads as "we'll do X. [new sentence] This enables Y."
Consider: "We'll do X, enabling Y."
### State of the Art Section **Strengths**: Comprehensive,
well-researched, excellent use of the HARDENS case study as
both positive example and gap identifier.
**Issues**:
- **Length**: At 358 lines, this risks losing readers. Most
concerning: readers may forget your framing by the time they
reach your contribution.
- **Organization**: Four major subsections (procedures,
human factors, HARDENS, research imperative) would benefit
from a roadmap sentence at the beginning: "To understand the
need for hybrid control synthesis, we first examine..."
- **Balance**: HARDENS subsection is 89 lines—nearly 25% of
SOTA. While impressive, consider whether this should be a
separate section or whether some detail could move to an
appendix.
- **Transition to Approach**: The "Research Imperative"
subsection is excellent but feels like it belongs at the
start of Research Approach rather than end of SOTA.
### Research Approach Section **Strengths**: Clear
three-thrust structure, good use of equations and examples,
strong technical detail.
**Issues**:
- **Subsection transitions**: The transitions between the
three main subsections (Procedures→Temporal,
Temporal→Discrete, Discrete→Continuous) could be smoother.
Each starts somewhat abruptly.
- **SmAHTR introduction**: The SmAHTR demonstration case is
introduced suddenly at line 253. Consider introducing it
earlier (perhaps in Goals section or at start of Approach)
so readers know it's coming.
- **Three-mode classification**: Lines 178-208 present the
stabilizing/transitory/expulsory framework, which is
innovative. This deserves more prominence—consider
highlighting it as a key contribution.
### Metrics of Success Section **Strengths**: TRL framework
is well-justified, progression through levels is clear.
**Issues**:
- **Defensive tone**: Lines 11-30 spend considerable space
justifying why TRL is appropriate. This is good but could be
more concise. Consider: one paragraph on why TRLs (lines
10-19) rather than two.
- **Grading criteria**: The TRL definitions (3, 4, 5) are
excellent. Very concrete and measurable.
### Risks and Contingencies Section **Strengths**:
Comprehensive, each risk has indicators and contingencies,
well-organized.
**Issues**:
- **Subsection balance**: Four subsections range from 41
lines (computational) to 65 lines (discrete-continuous).
Ensure space reflects actual risk level.
- **Mitigation vs. contingency**: Some subsections blur
"mitigation" (preventing problems) and "contingency"
(response if they occur). Consider clarifying this
structure.
### Broader Impacts Section **Strengths**: Clear economic
motivation, good connection to SMRs and datacenter
application.
**Issues**:
- **Brevity**: At 75 lines, this is the shortest technical
section. Given that economic viability is a key motivation,
consider expanding.
- **Missed opportunities**: Could briefly mention
workforce/educational impacts (training future engineers in
formal methods), equity (providing reliable clean energy to
underserved areas), broader applicability beyond nuclear.
### Budget Section **Brief review**: Budget is
comprehensive, well-justified, appropriate. Minor note:
Consider whether the high-performance workstation (Year 1)
might need upgrades in Year 2-3 as synthesis scales up.
### Schedule Section **Brief review**: Schedule is ambitious
but realistic. Six trimesters for dissertation research is
reasonable. Publication strategy is smart (nuclear community
first, then broader control theory community). Minor note:
Line 73 has a space issue ("t ranslation").
---
## Big Picture Observations
### Narrative and Argument Structure
**Strengths**:
- Clear problem-solution arc: operators make errors →
procedures lack formal guarantees → hybrid control synthesis
provides guarantees
- Good use of motivating examples (TMI, human error
statistics, HARDENS)
- Technical progression is logical: discrete synthesis →
continuous verification → integrated system
**Opportunities**:
1. **Strengthen "so what" transitions**: The proposal
sometimes presents information without explicitly stating
significance. Add more "This matters because..." statements.
2. **Emphasize novelty earlier**: The three-mode
classification and discrete-continuous interface
verification are novel contributions. Signal this earlier
and more explicitly.
3. **Create more callbacks**: When describing Research
Approach, refer back to specific limitations identified in
State of the Art. Currently these connections are implicit.
### Rhetorical Effectiveness
**Credibility established through**:
- Comprehensive literature review
- Specific technical detail
- Access to industry hardware (Emerson partnership)
- Prior conference recognition (best student paper)
**Value proposition**:
- Clear economic impact (O&M cost reduction)
- Safety improvement (mathematical guarantees vs. human
operators)
- Broader applicability (methodology generalizes)
**Could strengthen**:
- More explicit statements of what's novel vs. what's
established practice
- Stronger emphasis on the unique combination of discrete
synthesis + continuous verification (others do one or the
other, not both)
### Content Gaps and Consistency
**Terminology**:
- Generally consistent
- Good introduction of technical terms (hybrid automata,
temporal logic, reachability analysis)
- Minor: "correct by construction" vs. "provably
correct"—used interchangeably, which is fine, but could note
they're synonymous
**Scope consistency**:
- Excellent—stays focused on startup procedures for SmAHTR
- Appropriately acknowledges limitations (TRL 5, not
deployment-ready)
- Risk section addresses what happens if scope must narrow
**Potential gaps**:
1. **Cybersecurity**: Not mentioned. For autonomous nuclear
control, shouldn't there be at least a paragraph on security
verification?
2. **Regulatory path**: You mention "regulatory
requirements" but don't detail what NRC approval process
would look like. Even a paragraph would strengthen
credibility.
3. **Comparison with alternatives**: What about machine
learning approaches to autonomous control? Worth a paragraph
explaining why formal methods are superior for
safety-critical systems.
---
## Gopen Framework Quick Reference
**Stress Position**: End of sentence should contain most
important new information. Readers expect climax there.
**Topic Position**: Beginning of sentence should contain
familiar information that links to previous sentence.
Creates flow.
**Point-Issue Structure**: Paragraphs should open by stating
(1) the point/claim and (2) why it matters, before providing
supporting detail.
**Topic String**: The chain of topics across sentences in a
paragraph. Strong topic strings create coherence; broken
ones confuse readers.
**Old→New Information Flow**: Information should flow from
familiar (old) to unfamiliar (new) within sentences and
paragraphs.
---
## Next Steps
1. **Start with Priority Issues 1-3**: These have the
highest impact
2. **Apply Patterns**: Use the pattern examples to fix
similar instances throughout
3. **Consult Detailed Document**: For comprehensive
checkbox-by-checkbox revisions
4. **Section-by-section revision**: Work through one section
at a time, applying patterns
5. **Final pass for consistency**: Ensure changes maintain
consistent terminology and tone
This proposal has strong technical content and a solid
structure. The revisions suggested here will strengthen
clarity, emphasize key contributions, and make the argument
even more compelling for reviewers. Good luck with your
revisions!

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\bibcite{zhang_analysis_2025}{12}
\bibcite{Kiniry2024}{13}
\bibcite{katis_capture_2022}{14}
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\begin{thebibliography}{10}
\bibitem{NUREG-0899}
{U.S. Nuclear Regulatory Commission}, ``Guidelines for the preparation of emergency operating procedures,'' Tech. Rep. NUREG-0899, U.S. Nuclear Regulatory Commission, 1982.
\bibitem{10CFR50.34}
{U.S. Nuclear Regulatory Commission}, ``{10 CFR Part 50.34}.'' Code of Federal Regulations.
\bibitem{10CFR55.59}
{U.S. Nuclear Regulatory Commission}, ``{10 CFR Part 55.59}.'' Code of Federal Regulations.
\bibitem{WRPS.Description}
``{Westinghouse RPS System Description},'' tech. rep., Westinghouse Electric Corporation.
\bibitem{gentillon_westinghouse_1999}
C.~D. Gentillon, D.~Marksberry, D.~Rasmuson, M.~B. Calley, S.~A. Eide, and T.~Wierman, ``Westinghouse reactor protection system unavailability, 1984-1995.''
\newblock Number: {INEEL}/{CON}-99-00374 Publisher: Idaho National Engineering and Environmental Laboratory.
\bibitem{operator_statistics}
{U.S. Nuclear Regulatory Commission}, ``{Operator Licensing}.'' \url{https://www.nrc.gov/reactors/operator-licensing}.
\bibitem{10CFR55}
{U.S. Nuclear Regulatory Commission}, ``{Part 55—Operators' Licenses}.'' \url{https://www.nrc.gov/reading-rm/doc-collections/cfr/part055/full-text}.
\bibitem{10CFR50.54}
{U.S. Nuclear Regulatory Commission}, ``{§ 50.54 Conditions of Licenses}.'' \url{https://www.nrc.gov/reading-rm/doc-collections/cfr/part050/part050-0054}.
\bibitem{Kemeny1979}
J.~G. Kemeny {\em et~al.}, ``Report of the president's commission on the accident at three mile island,'' tech. rep., President's Commission on the Accident at Three Mile Island, October 1979.
\bibitem{WNA2020}
{World Nuclear Association}, ``Safety of nuclear power reactors.'' \url{https://www.world-nuclear.org/information-library/safety-and-security/safety-of-plants/safety-of-nuclear-power-reactors.aspx}, 2020.
\bibitem{hogberg_root_2013}
L.~Högberg, ``Root causes and impacts of severe accidents at large nuclear power plants,'' vol.~42, no.~3, pp.~267--284.
\bibitem{zhang_analysis_2025}
M.~Zhang, L.~Dai, W.~Chen, and E.~Pang, ``Analysis of human errors in nuclear power plant event reports,'' vol.~57, no.~10, p.~103687.
\bibitem{Kiniry2024}
J.~Kiniry, A.~Bakst, S.~Hansen, M.~Podhradsky, and A.~Bivin, ``High assurance rigorous digital engineering for nuclear safety (hardens) final technical report,'' Tech. Rep. TLR-RES-RES/DE-2024-005, Galois, Inc. / U.S. Nuclear Regulatory Commission, 2024.
\newblock NRC Contract 31310021C0014.
\bibitem{katis_capture_2022}
A.~Katis, A.~Mavridou, D.~Giannakopoulou, T.~Pressburger, and J.~Schumann, ``Capture, analyze, diagnose: Realizability checking of requirements in {FRET},'' in {\em Computer Aided Verification} (S.~Shoham and Y.~Vizel, eds.), pp.~490--504, Springer International Publishing.
\bibitem{baier_principles_2008}
C.~Baier and J.-P. Katoen, {\em Principles of Model Checking}.
\newblock {MIT} Press.
\bibitem{meyer_strix_2018}
P.~J. Meyer, S.~Sickert, and M.~Luttenberger, ``Strix: Explicit reactive synthesis strikes back!,'' in {\em Computer Aided Verification} (H.~Chockler and G.~Weissenbacher, eds.), pp.~578--586, Springer International Publishing.
\bibitem{jacobs_reactive_2024}
S.~Jacobs {\em et~al.}, ``The reactive synthesis competition ({SYNTCOMP}): 2018-2021.''
\bibitem{branicky_multiple_1998}
M.~Branicky, ``Multiple lyapunov functions and other analysis tools for switched and hybrid systems,'' vol.~43, no.~4, pp.~475--482.
\bibitem{bansal_hamilton-jacobi_2017}
S.~Bansal, M.~Chen, S.~Herbert, and C.~J. Tomlin, ``Hamilton-jacobi reachability: A brief overview and recent advances,'' in {\em 2017 {IEEE} 56th Annual Conference on Decision and Control ({CDC})}, pp.~2242--2253.
\bibitem{guernic_reachability_2009}
C.~L. Guernic, ``Reachability analysis of hybrid systems with linear continuous dynamics.''
\bibitem{frehse_spaceex_2011}
G.~Frehse, C.~Le~Guernic, A.~Donzé, S.~Cotton, R.~Ray, O.~Lebeltel, R.~Ripado, A.~Girard, T.~Dang, and O.~Maler, ``{SpaceEx}: Scalable verification of hybrid systems,'' in {\em Computer Aided Verification} (G.~Gopalakrishnan and S.~Qadeer, eds.), pp.~379--395, Springer.
\bibitem{mitchell_time-dependent_2005}
I.~Mitchell, A.~Bayen, and C.~Tomlin, ``A time-dependent hamilton-jacobi formulation of reachable sets for continuous dynamic games,'' vol.~50, no.~7, pp.~947--957.
\bibitem{prajna_safety_2004}
S.~Prajna and A.~Jadbabaie, ``Safety verification of hybrid systems using barrier certificates,'' in {\em Hybrid Systems: Computation and Control} (R.~Alur and G.~J. Pappas, eds.), pp.~477--492, Springer.
\bibitem{eia_lcoe_2022}
{U.S. Energy Information Administration}, ``Levelized costs of new generation resources in the annual energy outlook 2022,'' report, U.S. Energy Information Administration, March 2022.
\newblock See Table 1b, page 9.
\bibitem{eesi_datacenter_2024}
{Environmental and Energy Study Institute}, ``Data center energy needs are upending power grids and threatening the climate.'' Web article, 2024.
\newblock Accessed: 2025-09-29.
\end{thebibliography}

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\documentclass{dane_proposal_format}
\usepackage{booktabs} % For professional tables
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\usepackage{multirow} % For multi-row cells
\usepackage{array} % Enhanced table formatting
\usepackage[table]{xcolor} % For colored tables (optional)
\usepackage{pgfgantt}
\usepackage{pdfpages} % For including PDF files
\begin{document}
\pagenumbering{roman}
\maketitle
\input{1-goals-and-outcomes/research_statement_v1.tex}
\newpage
\tableofcontents
\newpage
\pagenumbering{arabic}
\input{1-goals-and-outcomes/v1}
\input{2-state-of-the-art/v1}
\input{3-research-approach/v1}
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\input{5-risks-and-contingencies/v1}
\input{6-broader-impacts/v1}
\input{8-schedule/v1}
\newpage
\bibliographystyle{ieeetr}
\bibliography{references}
% White Paper (optional)
% \input{whitepaper/v1}
\end{document}

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\contentsline {section}{Contents}{ii}{}%
\contentsline {section}{\numberline {1}Goals and Outcomes}{1}{}%
\contentsline {section}{\numberline {2}State of the Art and Limits of Current Practice}{2}{}%
\contentsline {subsection}{\numberline {2.1}Current Reactor Procedures and Operation}{2}{}%
\contentsline {subsection}{\numberline {2.2}Human Factors in Nuclear Accidents}{3}{}%
\contentsline {subsection}{\numberline {2.3}HARDENS and Formal Methods}{4}{}%
\contentsline {section}{\numberline {3}Research Approach}{5}{}%
\contentsline {section}{\numberline {4}Metrics for Success}{9}{}%
\contentsline {paragraph}{TRL 3 \textit {Critical Function and Proof of Concept}}{10}{}%
\contentsline {paragraph}{TRL 4 \textit {Laboratory Testing of Integrated Components}}{10}{}%
\contentsline {paragraph}{TRL 5 \textit {Laboratory Testing in Relevant Environment}}{10}{}%
\contentsline {section}{\numberline {5}Risks and Contingencies}{11}{}%
\contentsline {subsection}{\numberline {5.1}Computational Tractability of Synthesis}{11}{}%
\contentsline {subsection}{\numberline {5.2}Discrete-Continuous Interface Formalization}{11}{}%
\contentsline {subsection}{\numberline {5.3}Procedure Formalization Completeness}{12}{}%
\contentsline {section}{\numberline {6}Broader Impacts}{13}{}%
\contentsline {section}{\numberline {7}Schedule, Milestones, and Deliverables}{14}{}%
\contentsline {subsection}{\numberline {7.1}Milestones and Deliverables}{15}{}%
\contentsline {section}{References}{16}{}%
\contentsline {section}{\numberline {8}Budget and Budget Justification}{I}{}%
\contentsline {subsection}{\numberline {8.1}Budget Summary}{I}{}%
\contentsline {subsection}{\numberline {8.2}Budget Justification}{II}{}%
\contentsline {subsubsection}{\numberline {8.2.1}Senior Personnel}{II}{}%
\contentsline {paragraph}{Faculty Advisor}{II}{}%
\contentsline {subsubsection}{\numberline {8.2.2}Other Personnel}{II}{}%
\contentsline {paragraph}{Graduate Research Assistant (Principal Investigator)}{II}{}%
\contentsline {subsubsection}{\numberline {8.2.3}Fringe Benefits}{II}{}%
\contentsline {paragraph}{Faculty Fringe Benefits}{II}{}%
\contentsline {paragraph}{Graduate Research Assistant Fringe Benefits}{II}{}%
\contentsline {subsubsection}{\numberline {8.2.4}Travel}{II}{}%
\contentsline {paragraph}{Conference Travel (\$4,000 per year)}{II}{}%
\contentsline {paragraph}{Industry Collaboration Visits (\$1,500 per year)}{II}{}%
\contentsline {subsubsection}{\numberline {8.2.5}Other Direct Costs}{II}{}%
\contentsline {paragraph}{Materials and Supplies}{II}{}%
\contentsline {paragraph}{Publication Costs}{II}{}%
\contentsline {paragraph}{Computing and Cloud Services}{III}{}%
\contentsline {subsubsection}{\numberline {8.2.6}H. Indirect Costs (Facilities \& Administrative)}{III}{}%
\contentsline {section}{\numberline {9}Supplemental Sections}{III}{}%
\contentsline {subsection}{\numberline {9.1}Biosketch}{III}{}%
\contentsline {subsection}{\numberline {9.2}Data Management Plan}{VI}{}%
\contentsline {subsection}{\numberline {9.3}Facilities}{X}{}%

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@techreport{NUREG-0899,
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@misc{10CFR50.34,
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}
@misc{10CFR55.59,
title = {{10 CFR Part 55.59}},
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@misc{10CFR55,
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@online{10CFR50.54,
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@misc{WNA2020,
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@techreport{Kiniry2024,
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}
@techreport{eia_lcoe_2022,
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@misc{eesi_datacenter_2024,
author = {{Environmental and Energy Study Institute}},
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@book{baier_principles_2008,
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@thesis{guernic_reachability_2009,
title = {Reachability Analysis of Hybrid Systems with Linear Continuous Dynamics},
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date = {2009-10-28},
langid = {english},
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@inproceedings{alur_hybrid_1993,
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booktitle = {Hybrid Systems},
publisher = {Springer},
author = {Alur, Rajeev and Courcoubetis, Costas and Henzinger, Thomas A. and Ho, Pei -Hsin},
editor = {Grossman, Robert L. and Nerode, Anil and Ravn, Anders P. and Rischel, Hans},
date = {1993},
langid = {english},
keywords = {Acceptance Condition, Hybrid Automaton, Hybrid System, Mutual Exclusion, Reachability Problem},
file = {Full Text PDF:/home/danesabo/Zotero/storage/WBXYUC86/Alur et al. - 1993 - Hybrid automata An algorithmic approach to the specification and verification of hybrid systems.pdf:application/pdf},
}
@article{mitchell_time-dependent_2005,
title = {A time-dependent Hamilton-Jacobi formulation of reachable sets for continuous dynamic games},
volume = {50},
issn = {1558-2523},
url = {https://ieeexplore.ieee.org/abstract/document/1463302},
doi = {10.1109/TAC.2005.851439},
pages = {947--957},
number = {7},
journaltitle = {{IEEE} Transactions on Automatic Control},
author = {Mitchell, I.M. and Bayen, A.M. and Tomlin, C.J.},
urldate = {2025-09-15},
date = {2005-07},
keywords = {Aircraft, Collaborative software, Collision avoidance, Computational modeling, Differential games, HamiltonJacobi equations, Nonlinear equations, Nonlinear systems, Partial differential equations, reachability, Trajectory, Vehicle dynamics, verification, Viscosity},
file = {Snapshot:/home/danesabo/Zotero/storage/SLKV9PEI/1463302.html:text/html;Submitted Version:/home/danesabo/Zotero/storage/9YWL2UDH/Mitchell et al. - 2005 - A time-dependent Hamilton-Jacobi formulation of reachable sets for continuous dynamic games.pdf:application/pdf},
}
@inproceedings{frehse_spaceex_2011,
location = {Berlin, Heidelberg},
title = {{SpaceEx}: Scalable Verification of Hybrid Systems},
isbn = {978-3-642-22110-1},
doi = {10.1007/978-3-642-22110-1_30},
shorttitle = {{SpaceEx}},
pages = {379--395},
booktitle = {Computer Aided Verification},
publisher = {Springer},
author = {Frehse, Goran and Le Guernic, Colas and Donzé, Alexandre and Cotton, Scott and Ray, Rajarshi and Lebeltel, Olivier and Ripado, Rodolfo and Girard, Antoine and Dang, Thao and Maler, Oded},
editor = {Gopalakrishnan, Ganesh and Qadeer, Shaz},
date = {2011},
langid = {english},
keywords = {Hybrid Automaton, Hybrid System, Reachability Analysis, Reachable State, Support Function},
file = {Full Text PDF:/home/danesabo/Zotero/storage/LPQK8GY2/Frehse et al. - 2011 - SpaceEx Scalable Verification of Hybrid Systems.pdf:application/pdf},
}
@inproceedings{bansal_hamilton-jacobi_2017,
title = {Hamilton-Jacobi reachability: A brief overview and recent advances},
url = {https://ieeexplore.ieee.org/abstract/document/8263977},
doi = {10.1109/CDC.2017.8263977},
shorttitle = {Hamilton-Jacobi reachability},
eventtitle = {2017 {IEEE} 56th Annual Conference on Decision and Control ({CDC})},
pages = {2242--2253},
booktitle = {2017 {IEEE} 56th Annual Conference on Decision and Control ({CDC})},
author = {Bansal, Somil and Chen, Mo and Herbert, Sylvia and Tomlin, Claire J.},
urldate = {2025-09-15},
date = {2017-12},
keywords = {Aircraft, Games, Level set, Safety, Tools, Trajectory, Tutorials},
file = {Snapshot:/home/danesabo/Zotero/storage/EEK5IE93/8263977.html:text/html;Submitted Version:/home/danesabo/Zotero/storage/BMNLZ9DW/Bansal et al. - 2017 - Hamilton-Jacobi reachability A brief overview and recent advances.pdf:application/pdf},
}
@inproceedings{prajna_safety_2004,
location = {Berlin, Heidelberg},
title = {Safety Verification of Hybrid Systems Using Barrier Certificates},
isbn = {978-3-540-24743-2},
doi = {10.1007/978-3-540-24743-2_32},
pages = {477--492},
booktitle = {Hybrid Systems: Computation and Control},
publisher = {Springer},
author = {Prajna, Stephen and Jadbabaie, Ali},
editor = {Alur, Rajeev and Pappas, George J.},
date = {2004},
langid = {english},
keywords = {Continuous State, Discrete Transition, Hybrid System, Integral Constraint, Reachability Analysis},
}

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@ -0,0 +1,547 @@
% Foundational Papers
@article{alur1995algorithmic,
title={The algorithmic analysis of hybrid systems},
author={Alur, Rajeev and Courcoubetis, Costas and Halbwachs, Nicolas and Henzinger, Thomas A and Ho, Pei-Hsin and Nicollin, Xavier and Olivero, Alfredo and Sifakis, Joseph and Yovine, Sergio},
journal={Theoretical Computer Science},
volume={138},
number={1},
pages={3--34},
year={1995},
publisher={Elsevier}
}
@inproceedings{alur1993hybrid,
title={Hybrid automata: An algorithmic approach to the specification and verification of hybrid systems},
author={Alur, Rajeev and Courcoubetis, Costas and Henzinger, Thomas A and Ho, Pei-Hsin},
booktitle={Hybrid Systems},
pages={209--229},
year={1993},
publisher={Springer}
}
@article{mitchell2005time,
title={A time-dependent Hamilton-Jacobi formulation of reachable sets for continuous dynamic games},
author={Mitchell, Ian M and Bayen, Alexandre M and Tomlin, Claire J},
journal={IEEE Transactions on Automatic Control},
volume={50},
number={7},
pages={947--957},
year={2005},
publisher={IEEE}
}
@article{platzer2008differential,
title={Differential dynamic logic for hybrid systems},
author={Platzer, Andr{\'e}},
journal={Journal of Automated Reasoning},
volume={41},
number={2},
pages={143--189},
year={2008},
publisher={Springer}
}
@article{platzer2017complete,
title={A complete uniform substitution calculus for differential dynamic logic},
author={Platzer, Andr{\'e}},
journal={Journal of Automated Reasoning},
volume={59},
number={2},
pages={219--265},
year={2017},
publisher={Springer}
}
@inproceedings{donze2010robust,
title={Robust satisfaction of temporal logic over real-valued signals},
author={Donz{\'e}, Alexandre and Maler, Oded},
booktitle={International Conference on Formal Modeling and Analysis of Timed Systems},
pages={92--106},
year={2010},
publisher={Springer}
}
% Control Theory and Stability
@article{geromel2006stability,
title={Stability and stabilization of continuous-time switched linear systems},
author={Geromel, Jos{\'e} C and Colaneri, Patrizio},
journal={SIAM Journal on Control and Optimization},
volume={45},
number={5},
pages={1915--1930},
year={2006},
publisher={SIAM}
}
@book{liberzon2003switching,
title={Switching in systems and control},
author={Liberzon, Daniel},
year={2003},
publisher={Birkh{\"a}user Boston}
}
@article{branicky1998multiple,
title={Multiple Lyapunov functions and other analysis tools for switched and hybrid systems},
author={Branicky, Michael S},
journal={IEEE Transactions on Automatic Control},
volume={43},
number={4},
pages={475--482},
year={1998},
publisher={IEEE}
}
% Recent Advances (2020-2025)
@article{yang2024learning,
title={Learning Local Control Barrier Functions for Hybrid Systems},
author={Yang, Shuo and Chen, Yiwei and Yin, Xiang and Mangharam, Rahul},
journal={arXiv preprint arXiv:2401.14907},
year={2024}
}
@inproceedings{su2024switching,
title={Switching Controller Synthesis for Hybrid Systems Against STL Formulas},
author={Su, Mingyu and Vizel, Yakir and Vardi, Moshe Y},
booktitle={International Symposium on Formal Methods},
pages={231--248},
year={2024},
publisher={Springer}
}
@article{yao2024model,
title={Model predictive control of stochastic hybrid systems with signal temporal logic constraints},
author={Yao, Li and Wang, Yiming and Chen, Xiang},
journal={Automatica},
volume={159},
pages={111037},
year={2024},
publisher={Elsevier}
}
@article{yu2024online,
title={Online control synthesis for uncertain systems under signal temporal logic specifications},
author={Yu, Pian and Gao, Yulong and Jiang, Frank J and Johansson, Karl H and Dimarogonas, Dimos V},
journal={The International Journal of Robotics Research},
volume={43},
number={3},
pages={284--307},
year={2024},
publisher={SAGE}
}
% Tools and Frameworks
@inproceedings{meyer2018strix,
title={Strix: Explicit reactive synthesis strikes back!},
author={Meyer, Philipp J and Luttenberger, Michael},
booktitle={International Conference on Computer Aided Verification},
pages={578--586},
year={2018},
publisher={Springer}
}
@techreport{giannakopoulou2022fret,
title={Capturing and Analyzing Requirements with FRET},
author={Giannakopoulou, Dimitra and Mavridou, Anastasia and Rhein, Julian and Pressburger, Thomas and Schumann, Johann and Shi, Nija},
institution={NASA Ames Research Center},
year={2022},
number={NASA/TM-20220007610}
}
@inproceedings{fulton2015keymaera,
title={KeYmaera X: An axiomatic tactical theorem prover for hybrid systems},
author={Fulton, Nathan and Mitsch, Stefan and Quesel, Jan-David and V{\"o}lp, Marcus and Platzer, Andr{\'e}},
booktitle={International Conference on Automated Deduction},
pages={527--538},
year={2015},
publisher={Springer}
}
@inproceedings{frehse2011spaceex,
title={SpaceEx: Scalable verification of hybrid systems},
author={Frehse, Goran and Le Guernic, Colas and Donz{\'e}, Alexandre and Cotton, Scott and Ray, Rajarshi and Lebeltel, Olivier and Ripado, Rodolfo and Girard, Antoine and Dang, Thao and Maler, Oded},
booktitle={International Conference on Computer Aided Verification},
pages={379--395},
year={2011},
publisher={Springer}
}
@inproceedings{chen2013flow,
title={Flow*: An analyzer for non-linear hybrid systems},
author={Chen, Xin and {\'A}brah{\'a}m, Erika and Sankaranarayanan, Sriram},
booktitle={International Conference on Computer Aided Verification},
pages={258--263},
year={2013},
publisher={Springer}
}
@inproceedings{larsen1997uppaal,
title={UPPAAL in a nutshell},
author={Larsen, Kim G and Pettersson, Paul and Yi, Wang},
journal={International Journal on Software Tools for Technology Transfer},
volume={1},
number={1-2},
pages={134--152},
year={1997},
publisher={Springer}
}
% Reachability and Verification
@INPROCEEDINGS{bansal2017hamilton,
author={Bansal, Somil and Chen, Mo and Herbert, Sylvia and Tomlin, Claire J.},
booktitle={2017 IEEE 56th Annual Conference on Decision and Control (CDC)},
title={Hamilton-Jacobi reachability: A brief overview and recent advances},
year={2017},
volume={},
pages={2242-2253},
keywords={Games;Safety;Tools;Trajectory;Tutorials;Level set;Aircraft},
doi={10.1109/CDC.2017.8263977}
}
@article{althoff2021set,
title={Set propagation techniques for reachability analysis},
author={Althoff, Matthias and Frehse, Goran and Girard, Antoine},
journal={Annual Review of Control, Robotics, and Autonomous Systems},
volume={4},
pages={369--395},
year={2021},
publisher={Annual Reviews}
}
@inproceedings{tabuada2004compositional,
title={Compositional abstractions of hybrid control systems},
author={Tabuada, Paulo and Pappas, George J and Lima, Pedro},
journal={Discrete Event Dynamic Systems},
volume={14},
number={2},
pages={203--238},
year={2004},
publisher={Springer}
}
% Applications
@article{varaiya1993smart,
title={Smart cars on smart roads: Problems of control},
author={Varaiya, Pravin},
journal={IEEE Transactions on Automatic Control},
volume={38},
number={2},
pages={195--207},
year={1993},
publisher={IEEE}
}
@article{verlinden2024hybrid,
title={Hybrid reliability modeling of nuclear safety systems: A case study on the reactor protection system of a research reactor},
author={Verlinden, S and Deridder, F and Wagemans, P},
journal={Nuclear Engineering and Design},
volume={417},
pages={112868},
year={2024},
publisher={Elsevier}
}
% Competitions and Benchmarks
@inproceedings{hscc2024proceedings,
title={Proceedings of the 27th ACM International Conference on Hybrid Systems: Computation and Control},
booktitle={HSCC '24},
year={2024},
publisher={ACM},
address={New York, NY, USA}
}
@inproceedings{jacobs2017syntcomp,
title={The 4th reactive synthesis competition (SYNTCOMP 2017): Benchmarks, participants \& results},
author={Jacobs, Swen and Bloem, Roderick and Brenguier, Romain and others},
booktitle={6th Workshop on Synthesis},
year={2017},
series={EPTCS},
volume={260}
}
% Supporting Papers
@article{wabersich2018linear,
title={Linear model predictive safety certification for learning-based control},
author={Wabersich, Kim P and Zeilinger, Melanie N},
journal={Automatica},
volume={97},
pages={48--59},
year={2018},
publisher={Elsevier}
}
@inproceedings{prajna2004safety,
title={Safety verification of hybrid systems using barrier certificates},
author={Prajna, Stephen and Jadbabaie, Ali},
booktitle={International Workshop on Hybrid Systems: Computation and Control},
pages={477--492},
year={2004},
publisher={Springer}
}
@article{ames2017control,
title={Control barrier function based quadratic programs for safety critical systems},
author={Ames, Aaron D and Xu, Xiangru and Grizzle, Jessy W and Tabuada, Paulo},
journal={IEEE Transactions on Automatic Control},
volume={62},
number={8},
pages={3861--3876},
year={2017},
publisher={IEEE}
}
@article{srinivasan2018control,
title={Control of mobile robots using barrier functions under temporal logic specifications},
author={Srinivasan, Mohit and Coogan, Samuel},
journal={IEEE Transactions on Robotics},
volume={37},
number={2},
pages={363--374},
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},
month = {March},
type = {Report},
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}
}
@techreport{DOE-HDBK-1028-2009,
title = {Human Performance Handbook},
author = {{U.S. Department of Energy}},
institution = {U.S. Department of Energy},
year = {2009},
number = {DOE-HDBK-1028-2009},
type = {Handbook}
}
@misc{WNA2020,
title = {Safety of Nuclear Power Reactors},
author = {{World Nuclear Association}},
year = {2020},
howpublished = {\url{https://www.world-nuclear.org/information-library/safety-and-security/safety-of-plants/safety-of-nuclear-power-reactors.aspx}}
}
@article{Wang2025,
title = {Analysis of Human Error in Nuclear Power Plant Operations: A Systematic Review of Events from 2007--2020},
author = {Wang, Y. and others},
journal = {Journal of Nuclear Safety},
year = {2025},
note = {Analysis of 190 events at Chinese nuclear power plants}
}
@misc{10CFR55,
title = {Operators' Licenses},
author = {{U.S. Nuclear Regulatory Commission}},
howpublished = {10 CFR Part 55},
note = {Code of Federal Regulations}
}
@techreport{Kemeny1979,
title = {Report of the President's Commission on the Accident at Three Mile Island},
author = {Kemeny, John G. and others},
institution = {President's Commission on the Accident at Three Mile Island},
year = {1979},
month = {October}
}
@misc{10CFR50,
title = {Domestic Licensing of Production and Utilization Facilities},
author = {{U.S. Nuclear Regulatory Commission}},
howpublished = {10 CFR Part 50},
note = {Code of Federal Regulations}
}
@techreport{NUREG-0899,
title = {Guidelines for the Preparation of Emergency Operating Procedures},
author = {{U.S. Nuclear Regulatory Commission}},
institution = {U.S. Nuclear Regulatory Commission},
year = {1982},
number = {NUREG-0899}
}
@techreport{IAEA-TECDOC-1580,
title = {Good Practices for Cost Effective Maintenance of Nuclear Power Plants},
author = {{International Atomic Energy Agency}},
institution = {International Atomic Energy Agency},
year = {2007},
number = {TECDOC-1580}
}
@techreport{NUREG-2114,
title = {Cognitive Basis for Human Reliability Analysis},
author = {{U.S. Nuclear Regulatory Commission}},
institution = {U.S. Nuclear Regulatory Commission},
year = {2016},
number = {NUREG-2114}
}
@article{Zerovnik2023,
title = {Knowledge Transfer Challenges in Nuclear Operations},
author = {\v{Z}erovnik, Gašper and others},
journal = {Nuclear Engineering and Design},
year = {2023},
note = {Analysis of knowledge transfer from experienced operators}
}
@article{Jo2021,
title = {Automation Paradox in Nuclear Power Plant Control: Effects on Operator Situation Awareness},
author = {Jo, Y. and others},
journal = {Nuclear Engineering and Technology},
year = {2021},
note = {Empirical study of automation effects on operator performance}
}
@techreport{IAEA2008,
title = {Modern Instrumentation and Control for Nuclear Power Plants: A Guidebook},
author = {{International Atomic Energy Agency}},
institution = {International Atomic Energy Agency},
year = {2008},
number = {Technical Reports Series No. 387}
}
@article{Lee2019,
title = {Autonomous Control of Nuclear Reactors Using Long Short-Term Memory Networks},
author = {Lee, D. and others},
journal = {Nuclear Engineering and Technology},
year = {2019},
note = {Demonstration of LSTM-based autonomous control in LOC and SGTR scenarios}
}
@inproceedings{IEEE2019,
title = {Formal Verification Challenges for Nuclear I\&C Systems},
author = {{IEEE Working Group}},
booktitle = {IEEE Conference on Nuclear Power Instrumentation, Control and Human-Machine Interface Technologies},
year = {2019},
note = {Discussion of state space explosion in formal verification}
}
@misc{IAEA-severe-accidents,
title = {Human Error as Root Cause in Severe Nuclear Accidents},
author = {{International Atomic Energy Agency}},
howpublished = {IAEA Safety Report},
note = {Analysis of TMI, Chernobyl, and Fukushima accidents}
}
@article{Dumas1999,
title = {Worker Error and Safety in Nuclear Facilities},
author = {Dumas, Lloyd},
journal = {Journal of Nuclear Safety},
year = {1999},
note = {Study of incidents at 10 nuclear centers}
}
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title = {Summary Report on the Post-Accident Review Meeting on the Chernobyl Accident},
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}

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% PROJECT SUMMARY
\section*{Project Summary}
\subsection*{Overview}
This research will develop a methodology for creating autonomous hybrid control
systems with mathematical guarantees of safe and correct behavior. Nuclear power
plants require the highest levels of control system reliability, where failures
can result in significant economic losses or radiological release. Currently,
nuclear operations rely on extensively trained human operators who follow
detailed written procedures to manage reactor control. However, reliance on
human operators prevents introduction of autonomous control capabilities and
creates fundamental economic challenges for next-generation reactor designs.
Without introducing automation, emerging technologies like small modular
reactors face significantly higher per-megawatt staffing costs than conventional
plants, threatening their economic viability.
To address this need, we will combine formal methods from computer science
with control theory to build hybrid control systems that are correct by
construction. Hybrid systems use discrete logic to switch between continuous
control modes, similar to how operators change control strategies. Existing
formal methods can generate provably correct switching logic from written
requirements, but they cannot handle the continuous dynamics that occur during
transitions between modes. Meanwhile, traditional control theory can verify
continuous behavior but lacks tools for proving correctness of discrete
switching decisions. By synthesizing discrete mode transitions directly from
written operating procedures and verifying continuous behavior between
transitions, we can create hybrid control systems with end-to-end correctness
guarantees.
\subsection*{Intellectual Merit}
The intellectual merit lies in unifying discrete synthesis and continuous
verification to enable end-to-end correctness guarantees for hybrid systems.
This research will advance knowledge by developing a systematic,
tool-supported methodology for translating written procedures into temporal
logic, synthesizing provably correct discrete switching logic, and developing
verified continuous controllers. The approach addresses a fundamental gap in
hybrid system design by bridging formal methods from computer science and
control theory.
\subsection*{Broader Impacts}
This research directly addresses the multi-billion dollar operations and
maintenance cost challenge facing nuclear power deployment. By synthesizing
provably correct hybrid controllers, we can automate routine operational
sequences that currently require constant human oversight, enabling a shift
from direct operator control to supervisory monitoring. Beyond nuclear
applications, this research will establish a generalizable framework for
autonomous control of safety-critical systems including chemical process
control, aerospace systems, and autonomous transportation.
\newpage
% RESEARCH DESCRIPTION
\section*{Research Description}
\section{Objectives}
% GOAL PARAGRAPH
The goal of this research is to develop a methodology for creating autonomous
control systems with event-driven control laws that have guarantees of safe and
correct behavior.
% INTRODUCTORY PARAGRAPH Hook
Nuclear power relies on extensively trained operators who follow detailed
written procedures to manage reactor control. Based on these procedures and
operators' interpretation of plant conditions, operators make critical decisions
about when to switch between control objectives.
% Gap
While human operators have maintained the nuclear industry's exceptional safety
record, reliance on human operators has created an economic challenge for
next-generation nuclear power plants. Small modular reactors face significantly
higher per-megawatt staffing costs than conventional plants, threatening their
economic viability. Autonomous control systems are needed that can safely manage
complex operational sequences with the same assurance as human-operated systems,
but without constant supervision.
% APPROACH PARAGRAPH Solution
To address this need, we will combine formal methods from computer science with
control theory to build hybrid control systems that are correct by construction.
% Rationale
Hybrid systems use discrete logic to switch between continuous control modes,
similar to how operators change control strategies. Existing formal methods
generate provably correct switching logic but cannot handle continuous dynamics
during transitions, while traditional control theory verifies continuous
behavior but lacks tools for proving discrete switching correctness.
% Hypothesis and Technical Approach
We will bridge this gap through a three-stage methodology. First, we will
translate written operating procedures into temporal logic specifications using
NASA's Formal Requirements Elicitation Tool (FRET), which structures
requirements into scope, condition, component, timing, and response elements.
This structured approach enables realizability checking to identify conflicts
and ambiguities in procedures before implementation. Second, we will synthesize
discrete mode switching logic from these specifications using reactive synthesis
tools such as Strix, which generates deterministic automata that are provably
correct by construction. Third, we will develop and verify continuous
controllers for each discrete mode using standard control theory and
reachability analysis. We will classify continuous modes based on their
transition objectives, and then employ assume-guarantee contracts and barrier
certificates to prove that mode transitions occur safely and as defined by the
deterministic automata. This compositional approach enables local verification
of continuous modes without requiring global trajectory analysis across the
entire hybrid system. We will demonstrate this methodology by developing an
autonomous startup controller for a Small Modular Advanced High Temperature
Reactor (SmAHTR) and implementing it on an Emerson Ovation control system using
the ARCADE hardware-in-the-loop platform.
% Pay-off
This approach will demonstrate autonomous control can be used for complex
nuclear power operations while maintaining safety guarantees.
\vspace{11pt}
% OUTCOMES PARAGRAPHS
If this research is successful, we will be able to do the following:
\begin{enumerate}
% OUTCOME 1 Title
\item \textit{Synthesize written procedures into verified control logic.}
% Strategy
We will develop a methodology for converting written operating procedures
into formal specifications. These specifications will be synthesized into
discrete control logic using reactive synthesis tools. This process uses
structured intermediate representations to bridge natural language and
mathematical logic.
% Outcome
Control engineers will be able to generate mode-switching controllers from
regulatory procedures with little formal methods expertise, reducing
barriers to high-assurance control systems.
% OUTCOME 2 Title
\item \textit{Verify continuous control behavior across mode transitions. }
% Strategy
We will develop methods using reachability analysis to ensure continuous control modes
satisfy discrete transition requirements.
% Outcome
Engineers will be able to design continuous controllers using standard
practices while ensuring system correctness and proving mode transitions
occur safely at the right times.
% OUTCOME 3 Title
\item \textit{Demonstrate autonomous reactor startup control with safety
guarantees. }
% Strategy
We will implement this methodology on a small modular reactor simulation
using industry-standard control hardware. This trial will include multiple
coordinated control modes from cold shutdown through criticality to power
operation on a SmAHTR reactor simulation in a hardware-in-the-loop
experiment.
% Outcome
Control engineers will be able to implement high-assurance autonomous
controls on industrial platforms they already use, enabling users to
achieve autonomy without retraining costs or developing new equipment.
\end{enumerate}
\section{State of the Art and Limits of Current Practice}
Automation of some nuclear power operations is already performed today. Highly
automated systems handle reactor protection and emergency core cooling, while
human operators retain strategic decision-making. Autonomous systems are trusted
to handle emergency situations that are considered terminal operations, but
otherwise introduce too much risk to reactor operations. Contrary to this notion
is the fact that 70--80\% of all nuclear power plant events are attributed to
human error rather than equipment failures. The persistence of this ratio despite
four decades of improvements to procedures and control rooms suggests
fundamental cognitive limitations rather than remediable deficiencies.
The Nuclear Regulatory Commission has recognized that introducing automation
into the control room is the only way forward. Recent efforts to apply formal
methods to nuclear control have shown both promise and remaining gaps. The High
Assurance Rigorous Digital Engineering for Nuclear Safety (HARDENS) project
represents the most advanced application to date. HARDENS produced a complete
Reactor Trip System with full traceability from NRC requirements through formal
specifications to verified binaries of a controller implementation. The project
employed formal methods along the control design stack. This comprehensive
approach demonstrated that formal methods may be technically feasible and
economically viable for nuclear protection systems.
But despite these accomplishments, HARDENS has a fundamental limitation directly
relevant to our work. The project addressed only discrete digital control logic
without modeling or verifying continuous reactor dynamics. Real reactor safety
depends on interaction between continuous processes and discrete control
decisions. HARDENS verified the discrete controller in isolation but not the
closed-loop hybrid system behavior.
\section{Research Approach}
This research will overcome the identified limitations by combining formal
methods from computer science with control theory to build hybrid control
systems that are correct by construction. We accomplish this through three
main thrusts:
\begin{enumerate}
\item We will translate natural language procedures and
requirements into temporal logic specifications using the Formal Requirements
Elicitation Tool (FRET).
\item We will synthesize these temporal logic
specifications into the discrete component of the hybrid controller using
reactive synthesis.
\item We will build continuous control modes that satisfy discrete controller
transition requirements.
\end{enumerate}
Commercial nuclear power operations remain manually controlled despite
significant advances in control systems. The key insight is that procedures
performed by human operators are highly prescriptive and well-documented. To
formalize these procedures, we will use temporal logic, which captures system
behaviors through temporal relations. Linear Temporal Logic provides four
fundamental operators: next ($X$), eventually ($F$), globally ($G$), and until
($U$). These operators enable precise specification of time-dependent
requirements. The most efficient path to accomplish this translation is through
NASA's Formal Requirements Elicitation Tool (FRET). FRET employs FRETish, a
specialized requirements language that restricts requirements to easily
understood components while eliminating ambiguity. FRET enforces structure by
requiring all requirements to contain six components: Scope, Condition,
Component, Shall, Timing, and Response.
FRET provides functionality to check realizability of a system. Realizability
analysis determines whether written requirements are complete by examining the
six structural components. Complete requirements neither conflict with one
another nor leave any behavior undefined. Systems that are not realizable
contain behavioral inconsistencies that represent the physical equivalent of
software bugs. Using FRET during autonomous controller development allows us
to identify and resolve these errors systematically. FRET exports requirements
in temporal logic format compatible with reactive synthesis tools, enabling
the second thrust of our approach.
Reactive synthesis is an active research field focused on generating discrete
controllers from temporal logic specifications. The term reactive indicates
that the system responds to environmental inputs to produce control outputs.
These synthesized systems are finite in size, where each node represents a
unique discrete state. The connections between nodes, called state
transitions, specify the conditions under which the discrete controller moves
from state to state. This complete mapping constitutes a discrete automaton.
We will employ reactive synthesis tools which translate linear temporal logic
specifications into deterministic automata automatically while maximizing
generated automata quality. Once constructed, the automaton can be
straightforwardly implemented using standard programming control flow
constructs. The discrete automata representation yields an important theoretical
guarantee. Because the discrete automaton is synthesized entirely through
automated tools from design requirements and operating procedures, we can
prove that the automaton---and therefore our hybrid switching behavior---is
correct by construction.
This correctness guarantee is paramount. Mode switching represents the primary
responsibility of human operators in control rooms today. Human operators
possess the advantage of real-time judgment. When mistakes occur, they can
correct them dynamically. Autonomous control lacks this adaptive advantage. By
synthesizing controllers from logical specifications with guaranteed
correctness, we eliminate the possibility of switching errors.
While discrete system components will be synthesized with correctness
guarantees, they represent only half of the complete system. The continuous
modes will be developed after discrete automaton construction, leveraging the
automaton structure and transitions to design multiple smaller, specialized
continuous controllers.
The discrete automaton transitions mark decision points for switching between
continuous control modes and define their strategic objectives. We will
classify three types of high-level continuous controller objectives:
Stabilizing modes maintain the hybrid system within its current discrete mode,
corresponding to steady-state normal operating modes like full-power
load-following control. Transitory modes have the primary goal of
transitioning the hybrid system from one discrete state to another, such as
controlled warm-up procedures. Expulsory modes are specialized transitory
modes with additional safety constraints that ensure the system is directed to
a safe stabilizing mode during failure conditions, such as reactor SCRAM.
Building continuous modes after constructing discrete automata enables local
controller design focused on satisfying discrete transitions. The primary
challenge in hybrid system verification is ensuring global stability across
transitions. Current techniques struggle with this problem because dynamic
discontinuities complicate verification. This work alleviates these problems
by designing continuous controllers specifically with transitions in mind. By
decomposing continuous modes according to their required behavior at
transition points, we avoid solving trajectories through the entire hybrid
system.
To ensure continuous modes satisfy their requirements, we will employ three
complementary techniques. Reachability analysis computes the reachable set of
states for a given input set. We will use reachability when continuous
state ranges at discrete transition boundaries are defined and verify that
continuous modes only can reach such defined ranges. Otherwise, assume-guarantee contracts will be
employed when continuous state boundaries are not explicitly defined. For any
given mode, the input range for reachability analysis is defined by the output
ranges of discrete modes that transition to it. This compositional approach
ensures each continuous controller is prepared for its possible input range.
Finally, barrier certificates will prove that mode transitions are satisfied. Control
barrier functions provide a method to certify safety by establishing
differential inequality conditions that guarantee forward invariance of safe
sets.
Combining these three techniques will enable us to prove that continuous
components satisfy discrete requirements and thus complete system behavior. To
demonstrate this methodology, we will develop an autonomous startup controller
for a Small Modular Advanced High Temperature Reactor (SmAHTR). SmAHTR
represents an ideal test case with well-documented startup procedures that
must transition through multiple distinct operational modes: initial cold
conditions, controlled heating to operating temperature, approach to
criticality, low-power physics testing, and power ascension to full operating
capacity. We have access to an already developed high-fidelity SmAHTR model in Simulink that
captures the thermal-hydraulic and neutron kinetics behavior.
The synthesized hybrid controller will be implemented on an Emerson Ovation
control system platform, which is representative of industry-standard control
hardware. This control system will be used in a hardware-in-the-loop simulation,
where the Advanced Reactor Cyber Analysis and Development Environment
(ARCADE) suite will serve as the integration layer. This
hardware-in-the-loop configuration enables validation of the controller
implementation on actual industrial control equipment.
\section{Metrics of Success}
This research will be measured by advancement through Technology Readiness
Levels, progressing from fundamental concepts to validated prototype
demonstration. The work begins at TRL 2--3 and aims to reach TRL 5, where system
components operate successfully in a relevant laboratory environment. TRLs
provide the ideal success metric because they explicitly measure the gap between
academic proof-of-concept and practical deployment. This gap is precisely what
our work aims to bridge. TRLs capture both theoretical rigor and practical
feasibility simultaneously. The nuclear industry already uses TRLs for
technology assessment, making this metric directly relevant to potential
adopters.
Moving from current state (TRL 2--3) to target (TRL 5) requires progressing
through component isolation, system integration, and hardware validation. By
reaching TRL 5, we will have demonstrated a complete autonomous hybrid
controller operating on industrial control hardware through hardware-in-the-loop
testing. Achieving TRL 5 establishes both theoretical validity and practical
feasibility, proving that the methodology produces verified controllers
implementable with current technology and providing a clear pathway for nuclear
industry adoption and broader application to safety-critical autonomous systems.
\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 for hyperscale
datacenters. According to the U.S. Energy Information Administration, advanced
nuclear power entering service in 2027 is projected to cost \$88.24 per
megawatt-hour. With datacenter electricity demand projected to reach 1,050
terawatt-hours annually by 2030, operations and maintenance costs represent
approximately 23--30\% of total levelized cost, translating to \$21--28
billion annually for projected datacenter demand.
This research directly addresses the multi-billion dollar O\&M cost challenge.
Current nuclear operations require full control room staffing for each reactor.
These staffing requirements drive high O\&M costs, particularly for smaller
reactor designs where the same overhead must be spread across lower power
output. The economic burden threatens the viability of next-generation nuclear
technologies. But, by synthesizing provably correct hybrid controllers, we can
automate routine operational sequences that currently require constant human
oversight. This enables a change from direct operator control to
supervisory monitoring where operators oversee multiple autonomous reactors
rather than manually controlling individual units. The transition fundamentally
changes the economics of nuclear operations.
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
discrete mode-switching logic and continuous control behavior, this research
will produce controllers with mathematical proofs of correctness. These
guarantees enable automation to safely handle routine operations that
currently require human operators to follow written procedures.
Beyond nuclear applications, 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. These domains share similar economic and safety considerations
that favor increased autonomy with provable correctness guarantees. By
demonstrating this approach in nuclear power this research will establish both
technical feasibility and regulatory pathways for broader adoption across
critical infrastructure.
\newpage
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