Editorial pass: Gopen's Sense of Structure + Heilmeier alignment

Three-pass editorial review:

Pass 1 (Tactical - sentence-level):
- Improved topic-stress positioning for emphasis
- Strengthened verb choice and topic strings
- Broke long, complex sentences into clearer shorter ones
- Fixed parallel structure inconsistencies
- Tightened hedging and unnecessary words

Pass 2 (Operational - paragraph/section):
- Strengthened transitions between subsections
- Improved logical flow within sections
- Enhanced parallel structure in key arguments
- Clarified connections between ideas

Pass 3 (Strategic - document-level):
- Strengthened Heilmeier question alignment in section summaries
- Improved parallel structure in 'three innovations' and 'three factors'
- Made strategic points more prominent and explicit
- Enhanced forward references between sections

Overall: Improved clarity, emphasis, and coherence throughout while maintaining technical accuracy and Dane's analytical voice.

1-goals-and-outcomes/research_statement_v1.tex

@@ -9,9 +9,9 @@ Small modular reactors face a fundamental economic challenge: their per-megawatt
 % APPROACH PARAGRAPH Solution
 I produce hybrid control systems correct by construction, unifying formal methods from computer science with control theory. 
 % Rationale
-Human operators already work this way: discrete logic switches between continuous control modes. Formal methods generate provably correct switching logic but cannot handle continuous dynamics. Control theory verifies continuous behavior but cannot prove discrete switching correctness. End-to-end correctness requires both working together.
+Human operators already work this way: discrete logic switches between continuous control modes. Formal methods generate provably correct switching logic but cannot handle continuous dynamics. Control theory verifies continuous behavior but cannot prove discrete switching correctness. Both must work together to achieve end-to-end correctness.
 % Hypothesis and Technical Approach
-Three stages bridge this gap. First, NASA's Formal Requirements Elicitation Tool (FRET) translates written operating procedures into temporal logic specifications, structuring requirements by scope, condition, component, timing, and response. Realizability checking exposes conflicts and ambiguities before implementation begins. Second, reactive synthesis generates deterministic automata provably correct by construction. Third, reachability analysis verifies that continuous controllers satisfy the requirements each discrete mode imposes. Engineers design these continuous controllers using standard control theory techniques.
+Three stages bridge this gap. First, NASA's Formal Requirements Elicitation Tool (FRET) translates written operating procedures into temporal logic specifications, structuring requirements by scope, condition, component, timing, and response. Realizability checking exposes conflicts and ambiguities before implementation begins. Second, reactive synthesis generates deterministic automata that are provably correct by construction. Third, reachability analysis verifies that continuous controllers satisfy the requirements each discrete mode imposes. Engineers design these continuous controllers using standard control theory techniques.
 
 Control objectives classify continuous modes into three types. Transitory modes drive the plant between conditions. Stabilizing modes maintain operation within regions. Expulsory modes ensure safety under failures. Barrier certificates and assume-guarantee contracts prove safe mode transitions, enabling local verification without global trajectory analysis. The methodology demonstrates on an Emerson Ovation control system—the industrial platform nuclear power plants already use.
 % Pay-off

1-goals-and-outcomes/v1.tex

@@ -13,9 +13,9 @@ This reliance on human operators prevents autonomous control and creates a funda
 % APPROACH PARAGRAPH Solution
 I produce hybrid control systems correct by construction, unifying formal methods with control theory.
 % Rationale
-Human operators already work this way: discrete logic switches between continuous control modes. Formal methods generate provably correct switching logic from written requirements but cannot handle the continuous dynamics governing transitions. Control theory verifies continuous behavior but cannot prove discrete switching correctness. End-to-end correctness requires both approaches working together.
+Human operators already work this way: discrete logic switches between continuous control modes. Formal methods generate provably correct switching logic from written requirements but cannot handle the continuous dynamics governing transitions. Control theory verifies continuous behavior but cannot prove discrete switching correctness. Both approaches must work together to achieve end-to-end correctness.
 % Hypothesis
-Two steps close this gap. First, discrete mode transitions synthesize directly from written operating procedures. Second, continuous behavior between transitions verifies against discrete requirements. This formalizes operating procedures into logical specifications that constrain continuous dynamics, producing autonomous controllers provably free from design defects. 
+Two steps close this gap. First, discrete mode transitions synthesize directly from written operating procedures. Second, continuous behavior between transitions verifies against discrete requirements. This approach formalizes operating procedures into logical specifications that constrain continuous dynamics, producing autonomous controllers provably free from design defects. 
 
 The University of Pittsburgh Cyber Energy Center provides access to industry collaboration and Emerson control hardware, ensuring solutions align with practical implementation requirements.
 
@@ -64,7 +64,7 @@ If successful, this approach produces three concrete outcomes:
 % IMPACT PARAGRAPH Innovation
 These three outcomes—procedure translation, continuous verification, and hardware demonstration—establish a complete methodology from regulatory documents to deployed systems.
 
-\textbf{What makes this research new?} No existing methodology achieves end-to-end correctness guarantees for hybrid systems. This work unifies discrete synthesis with continuous verification through a key innovation: discrete specifications become contracts that continuous controllers must satisfy. Each layer verifies independently while guaranteeing correct composition—formal methods verify discrete logic, control theory verifies continuous dynamics. Section 2 examines why prior work fails at this integration and identifies the limits of current practice. Section 3 details what is new in this approach and why it will succeed.
+\textbf{What makes this research new?} No existing methodology achieves end-to-end correctness guarantees for hybrid systems. This work unifies discrete synthesis with continuous verification through a key innovation: discrete specifications become contracts that continuous controllers must satisfy. Each layer verifies independently while guaranteeing correct composition. Formal methods verify discrete logic. Control theory verifies continuous dynamics. Section 2 examines why prior work fails at this integration and identifies the limits of current practice. Section 3 details what is new in this approach and why it will succeed.
 
 % Outcome Impact
 If successful, control engineers create autonomous controllers from

2-state-of-the-art/v2.tex

@@ -14,7 +14,7 @@ Understanding the limits of current practice requires examining how nuclear plan
 
 Nuclear plant procedures form a strict hierarchy. Normal operating procedures govern routine operations. Abnormal operating procedures handle off-normal conditions. Emergency Operating Procedures (EOPs) manage design-basis accidents. Severe Accident Management Guidelines (SAMGs) address beyond-design-basis events. Extensive Damage Mitigation Guidelines (EDMGs) cover catastrophic damage. All procedures must comply with 10 CFR 50.34(b)(6)(ii); NUREG-0899 provides development guidance~\cite{NUREG-0899, 10CFR50.34}. 
 
-Procedure development relies on expert judgment and simulator validation—not formal verification. 10 CFR 55.59~\cite{10CFR55.59} requires rigorous assessment through technical evaluation, simulator validation testing, and biennial review. Yet key safety properties escape formal verification: no mathematical proofs confirm that procedures cover all possible plant states, that required actions complete within available timeframes, or that transitions between procedure sets maintain safety invariants.
+Procedure development relies on expert judgment and simulator validation—not formal verification. 10 CFR 55.59~\cite{10CFR55.59} requires rigorous assessment through technical evaluation, simulator validation testing, and biennial review. Yet key safety properties escape formal verification. No mathematical proofs confirm that procedures cover all possible plant states. No proofs show that required actions complete within available timeframes. No proofs demonstrate 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
@@ -31,9 +31,9 @@ This division between automated and human-controlled functions reveals the funda
 
 \subsection{Human Factors in Nuclear Accidents}
 
-The previous subsection established that procedures lack formal verification despite rigorous development—but this represents only half the reliability challenge. Perfect procedures cannot guarantee safe operation when humans execute them imperfectly.
+The previous subsection established that procedures lack formal verification despite rigorous development. This represents only half the reliability challenge. Perfect procedures cannot guarantee safe operation when humans execute them imperfectly.
 
-Human operators—the second pillar of current practice—introduce reliability limitations independent of procedure quality. Procedures define what to do; operators determine when and how. This introduces persistent failure modes that training alone cannot eliminate.
+Human operators—the second pillar of current practice—introduce reliability limitations independent of procedure quality. Procedures define what to do. Operators determine when and how. This introduces persistent failure modes that training alone cannot eliminate.
 
 Current-generation nuclear power plants employ over 3,600 active NRC-licensed
 reactor operators in the United States~\cite{operator_statistics}. These
@@ -43,9 +43,9 @@ 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.
 
-Human error persistently contributes to nuclear safety incidents despite decades of improvements in training and procedures. This persistence motivates formal automated control with mathematical safety guarantees. Under 10 CFR Part 55, operators hold legal authority to make critical decisions, including authority to depart from normal regulations during emergencies. The Three Mile Island (TMI) accident demonstrated how personnel error, design deficiencies, and component failures combine to cause disaster: operators misread confusing and contradictory indications, then 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 formally verifying that operators can fulfill this responsibility guarantees nothing. This tension between operational flexibility and safety assurance remains unresolved: the person responsible for reactor safety often becomes the root cause of failure.
+Human error persistently contributes to nuclear safety incidents despite decades of improvements in training and procedures. This persistence motivates the need for formal automated control with mathematical safety guarantees. Under 10 CFR Part 55, operators hold legal authority to make critical decisions, including authority to depart from normal regulations during emergencies. The Three Mile Island (TMI) accident demonstrated how personnel error, design deficiencies, and component failures combine to cause disaster: operators misread confusing and contradictory indications, then 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 formally verifying that operators can fulfill this responsibility guarantees nothing. This tension between operational flexibility and safety assurance remains unresolved: the person responsible for reactor safety often becomes the root cause of failure.
 
-Multiple independent analyses converge on a striking statistic: human error accounts for 70--80\% of nuclear power plant events, compared to approximately 20\% for equipment failures~\cite{WNA2020}. More significantly, human factors—poor safety management and safety culture—caused all severe accidents at nuclear power plants: Three Mile Island, Chernobyl, and Fukushima Daiichi~\cite{hogberg_root_2013}. A detailed analysis
+Multiple independent analyses converge on a striking statistic: human error accounts for 70--80\% of nuclear power plant events, while equipment failures account for approximately 20\%~\cite{WNA2020}. More significantly, human factors—poor safety management and safety culture—caused all severe accidents at nuclear power plants: Three Mile Island, Chernobyl, and Fukushima Daiichi~\cite{hogberg_root_2013}. A detailed analysis
 of 190 events at Chinese nuclear power plants from
 2007--2020~\cite{zhang_analysis_2025} found that active
 errors appeared in 53\% of events, while latent errors—organizational and

3-research-approach/v3.tex

@@ -23,13 +23,13 @@ This section presents the complete technical approach for synthesizing provably
 % ----------------------------------------------------------------------------
 % 1. INTRODUCTION AND HYBRID SYSTEMS DEFINITION
 % ----------------------------------------------------------------------------
-Previous approaches verified either discrete switching logic or continuous control behavior—never both simultaneously. Engineers validate continuous controllers through extensive simulation trials and test discrete switching logic through simulated control room testing and human factors research. Neither method provides rigorous guarantees; both consume enormous resources.
+Previous approaches verified either discrete switching logic or continuous control behavior—never both simultaneously. Engineers validate continuous controllers through extensive simulation trials. They test discrete switching logic through simulated control room testing and human factors research. Neither method provides rigorous guarantees. Both consume enormous resources.
 
-My approach bridges this gap by composing formal methods from computer science with control-theoretic verification, formalizing reactor operations as hybrid automata.
+My approach bridges this gap by composing formal methods from computer science with control-theoretic verification. The approach formalizes reactor operations as hybrid automata.
 
 Hybrid system verification faces a fundamental challenge: discrete transitions change the governing vector field, creating discontinuities through the interaction between discrete and continuous dynamics. Traditional verification techniques cannot handle this interaction directly.
 
-This methodology decomposes the problem, verifying discrete switching logic and continuous mode behavior separately, then composing them to establish guarantees for the complete hybrid system. This two-layer approach mirrors reactor operations: discrete supervisory logic determines which control mode is active; continuous controllers govern plant behavior within each mode.
+This methodology decomposes the problem. It verifies discrete switching logic and continuous mode behavior separately, then composes them to establish guarantees for the complete hybrid system. This two-layer approach mirrors reactor operations: discrete supervisory logic determines which control mode is active, while continuous controllers govern plant behavior within each mode.
 
 A high-assurance hybrid autonomous control system requires a mathematical description. This work draws on automata theory, temporal logic, and control theory to provide that description. A hybrid system is a dynamical system with both continuous and discrete states. This proposal addresses continuous autonomous hybrid systems specifically—systems with no external input where continuous states remain continuous when discrete states change, representing physical quantities that remain Lipschitz continuous. This work follows the nomenclature from the Handbook on Hybrid Systems Control~\cite{HANDBOOK ON HYBRID SYSTEMS}, redefined here for convenience:
 
@@ -56,7 +56,7 @@ where:
 
 A HAHACS requires this tuple together with proof artifacts demonstrating that the control system's actual implementation satisfies its intended behavior.
 
-\textbf{What is new in this research?} Existing approaches verify either discrete logic or continuous dynamics—never both compositionally. Section 2 established this limitation: reactive synthesis, reachability analysis, and barrier certificates exist independently, but prior work has not integrated them into a systematic design methodology spanning from procedures to verified implementation.
+\textbf{What is new in this research?} Existing approaches verify either discrete logic or continuous dynamics—never both compositionally. Section 2 established this limitation: reactive synthesis, reachability analysis, and barrier certificates exist independently. Prior work has not integrated them into a systematic design methodology spanning from procedures to verified implementation.
 
 Three innovations enable this integration:
 
@@ -68,11 +68,11 @@ Three innovations enable this integration:
 
 \textbf{Why will it succeed?} Three factors ensure practical feasibility where prior work has failed.
 
-\textbf{First, existing structure:} Nuclear procedures already decompose operations into discrete phases with explicit transition criteria. The approach formalizes existing structure without imposing artificial abstractions. Domain experts without formal methods training can adopt it.
+\textbf{First, existing structure:} Nuclear procedures already decompose operations into discrete phases with explicit transition criteria. The approach formalizes this existing structure without imposing artificial abstractions. Domain experts without formal methods training can adopt it.
 
 \textbf{Second, bounded complexity:} Mode-level verification checks each mode against local contracts. This avoids global hybrid system analysis. The decomposition bounds computational complexity, transforming an intractable global problem into tractable local verifications.
 
-\textbf{Third, industrial validation:} The Emerson collaboration provides domain expertise to validate procedure formalization and industrial hardware to demonstrate implementation feasibility. Solutions address real deployment constraints, not just theoretical correctness.
+\textbf{Third, industrial validation:} The Emerson collaboration provides domain expertise to validate procedure formalization. It provides industrial hardware to demonstrate implementation feasibility. Solutions address real deployment constraints, not just theoretical correctness.
 
 These factors combine to demonstrate feasibility on production control systems with realistic reactor models—not merely in principle. Figure~\ref{fig:hybrid_automaton} illustrates the hybrid structure for a simplified reactor startup sequence.
 
@@ -142,7 +142,7 @@ These factors combine to demonstrate feasibility on production control systems w
 
 The previous subsection established the hybrid automaton formalism—a mathematical framework describing discrete modes, continuous dynamics, guards, and invariants. Where do these formal descriptions originate?
 
-Nuclear operations already possess a natural hybrid structure that maps directly to the automaton formalism through three control scopes: strategic, operational, and tactical. This approach constructs formal hybrid systems from existing operational knowledge rather than imposing artificial abstractions, leveraging decades of domain expertise already encoded in operating procedures.
+Nuclear operations already possess a natural hybrid structure. This structure maps directly to the automaton formalism through three control scopes: strategic, operational, and tactical. This approach constructs formal hybrid systems from existing operational knowledge rather than imposing artificial abstractions. It leverages decades of domain expertise already encoded in operating procedures.
 
 Human control of nuclear power divides into three scopes: strategic, operational, and tactical. Strategic control represents high-level, long-term decision making spanning months or years, managing labor needs and supply chains to optimize scheduled maintenance and downtime.
 
@@ -258,9 +258,9 @@ FRET has been successfully applied to spacecraft control systems, autonomous veh
 
 \subsection{Discrete Controller Synthesis}
 
-Operating procedures translate into temporal logic specifications using FRET. These specifications define what the system must do—but how do we implement those requirements? 
+Operating procedures translate into temporal logic specifications using FRET. These specifications define what the system must do. But how do we implement those requirements?
 
-Reactive synthesis provides the answer by automatically constructing controllers guaranteed to satisfy temporal logic specifications.
+Reactive synthesis provides the answer. It automatically constructs controllers guaranteed to satisfy temporal logic specifications.
 
 Reactive synthesis automates the creation of reactive programs from temporal logic—programs that take input for a given state and produce output. System requirements defined as temporal logic specifications enable reactive synthesis to build the discrete control system. Our systems fit this model: the current discrete state and status of guard conditions form the input, while the next discrete state forms the output.
 
@@ -293,7 +293,7 @@ Reactive synthesis produces a provably correct discrete controller that determin
 
 This subsection describes continuous control modes and their verification. Control objectives determine the verification approach. Modes classify into three types—transitory, stabilizing, and expulsory—each requiring different verification tools matched to its distinct purpose. 
 
-This methodology's scope requires clarification: this work verifies continuous controllers but does not synthesize them. The distinction parallels model checking in software verification. Model checking confirms whether an implementation satisfies its specification without prescribing how to write the software. Engineers design continuous controllers using standard control theory techniques—this work assumes that capability exists. The contribution lies in the verification framework confirming candidate controllers compose correctly with the discrete layer to produce a safe hybrid system.
+This methodology's scope requires clarification: this work verifies continuous controllers but does not synthesize them. The distinction parallels model checking in software verification. Model checking confirms whether an implementation satisfies its specification without prescribing how to write the software. Engineers design continuous controllers using standard control theory techniques. This work assumes that capability exists. The contribution lies in the verification framework that confirms candidate controllers compose correctly with the discrete layer to produce a safe hybrid system.
 
 The operational control scope defines go/no-go decisions that determine what
 kind of continuous control to implement. The entry or exit conditions of a
@@ -342,7 +342,7 @@ Continuous controllers classify into three types based on their control objectiv
 
 \subsubsection{Transitory Modes}
 
-Transitory modes—the first of three continuous controller types—execute transitions between operating conditions. Their purpose is to move the plant from one discrete operating condition to another: start from entry conditions, reach exit conditions, and maintain safety invariants throughout. Examples include power ramp-up sequences, cooldown procedures, and load-following maneuvers.
+Transitory modes—the first of three continuous controller types—execute transitions between operating conditions. Their purpose is to move the plant from one discrete operating condition to another. They start from entry conditions, reach exit conditions, and maintain safety invariants throughout. Examples include power ramp-up sequences, cooldown procedures, and load-following maneuvers.
 
 The control objective for a transitory mode has a formal statement. Given entry conditions $\mathcal{X}_{entry}$, exit conditions $\mathcal{X}_{exit}$, safety invariant $\mathcal{X}_{safe}$, and closed-loop dynamics $\dot{x} = f(x, u(x))$, the controller must satisfy:
 \[
@@ -390,7 +390,7 @@ appropriate to the fidelity of the reactor models available.
 
 \subsubsection{Stabilizing Modes}
 
-Transitory modes drive the system toward exit conditions. They answer: "can we reach the target?"
+Transitory modes drive the system toward exit conditions. They answer one question: "can we reach the target?"
 
 Stabilizing modes address a fundamentally different question: "will we stay within bounds?" These modes maintain the system within a desired operating region indefinitely. Examples include steady-state power operation, hot standby, and load-following at constant power level. This different control objective requires a different verification approach.
 
@@ -441,9 +441,9 @@ controller.
 
 \subsubsection{Expulsory Modes}
 
-The first two mode types handle nominal operations. Transitory modes move the plant between conditions. Stabilizing modes maintain the plant within regions. Both assume plant dynamics match the design model. Both assume the plant behaves as expected.
+The first two mode types handle nominal operations. Transitory modes move the plant between conditions. Stabilizing modes maintain the plant within regions. Both assume the plant dynamics match the design model. Both assume the plant behaves as expected.
 
-Expulsory modes address a fundamentally different scenario: situations where the plant deviates from expected behavior. This deviation may result from component failures, sensor degradation, or unanticipated disturbances. Here, robustness matters more than optimality.
+Expulsory modes address a fundamentally different scenario. They handle situations where the plant deviates from expected behavior. This deviation may result from component failures, sensor degradation, or unanticipated disturbances. Here, robustness matters more than optimality.
 
 Expulsory controllers prioritize robustness over optimality. The control objective shifts from reaching targets or maintaining regions to driving the plant to a safe shutdown state from potentially anywhere in the state space, under degraded or uncertain dynamics. Examples include emergency core cooling, reactor SCRAM sequences, and controlled depressurization procedures.
 
@@ -524,11 +524,23 @@ outcomes can align best with customer needs.
 
 This section answered two critical Heilmeier questions: What is new? Why will it succeed?
 
-\textbf{What is new in this research?} This work integrates reactive synthesis, reachability analysis, and barrier certificates into a compositional methodology for hybrid control synthesis through three innovations. First, contract-based decomposition inverts traditional global analysis—discrete synthesis defines verification contracts that bound continuous verification. Second, mode classification enables mode-local analysis with provable composition guarantees by matching continuous modes to appropriate verification tools. Third, procedure-driven structure leverages existing procedural decomposition to avoid intractable state explosion.
+\textbf{What is new in this research?} This work integrates reactive synthesis, reachability analysis, and barrier certificates into a compositional methodology for hybrid control synthesis through three innovations. 
+
+First: contract-based decomposition inverts traditional global analysis. Discrete synthesis defines verification contracts that bound continuous verification. 
+
+Second: mode classification enables mode-local analysis with provable composition guarantees. It matches continuous modes to appropriate verification tools. 
+
+Third: procedure-driven structure leverages existing procedural decomposition. This avoids intractable state explosion.
 
 Section 2 established that prior work verified either discrete logic or continuous dynamics—never both compositionally. This compositional verification enables what global analysis cannot achieve.
 
-\textbf{Why will this approach succeed?} Three factors ensure practical feasibility. First, nuclear procedures already decompose operations into discrete phases with explicit transition criteria, allowing formalization of existing structure without imposing artificial abstractions. Second, mode-level verification bounds each verification problem locally, avoiding the state explosion that makes global hybrid system analysis intractable. Third, the Emerson collaboration provides domain expertise to validate procedure formalization and industrial hardware to demonstrate implementation feasibility, ensuring solutions address real deployment constraints.
+\textbf{Why will this approach succeed?} Three factors ensure practical feasibility. 
+
+First: nuclear procedures already decompose operations into discrete phases with explicit transition criteria. This allows formalization of existing structure without imposing artificial abstractions. 
+
+Second: mode-level verification bounds each verification problem locally. This avoids the state explosion that makes global hybrid system analysis intractable. 
+
+Third: the Emerson collaboration provides domain expertise to validate procedure formalization. It provides industrial hardware to demonstrate implementation feasibility. This ensures solutions address real deployment constraints.
 
 The complete methodology encompasses procedure formalization, discrete synthesis, continuous verification across three mode types, and hardware implementation.
 

4-metrics-of-success/v1.tex

@@ -2,7 +2,7 @@
 
 \textbf{Heilmeier Question: How do we measure success?}
 
-Section 3 established the technical approach, answering what is new (compositional verification bridging discrete synthesis with continuous control) and why it will succeed (existing procedural structure, bounded complexity, industrial validation). This section addresses the next Heilmeier question: how to measure success. 
+Section 3 established the technical approach. It answered what is new: compositional verification bridging discrete synthesis with continuous control. It answered why the approach will succeed: existing procedural structure, bounded complexity, and industrial validation. This section addresses the next Heilmeier question: how to measure success. 
 
 The answer: Technology Readiness Level advancement from fundamental concepts (TRL 2--3) to validated prototype demonstration (TRL 5).
 
@@ -10,7 +10,7 @@ My work begins at TRL 2--3 and aims to reach TRL 5, where system components oper
 
 Technology Readiness Levels provide the ideal success metric. They explicitly measure the gap between academic proof-of-concept and practical deployment. This is precisely what my work bridges. 
 
-Academic metrics like papers published or theorems proved fail to capture practical feasibility. Empirical metrics like simulation accuracy or computational speed fail to demonstrate theoretical rigor. TRLs measure both.
+Academic metrics—papers published or theorems proved—fail to capture practical feasibility. Empirical metrics—simulation accuracy or computational speed—fail to demonstrate theoretical rigor. TRLs measure both.
 
 Advancing from TRL 3 to TRL 5 requires maintaining theoretical rigor while progressively demonstrating practical feasibility. The system moves from individual components to integrated hardware testing. Two requirements constrain this progression. First: formal verification must remain valid throughout. Second: the proofs must compose as the system scales.
 
@@ -85,8 +85,16 @@ controllers implementable with current technology.
 
 This section answered the Heilmeier question: How do we measure success?
 
-\textbf{Answer:} Technology Readiness Level advancement from 2--3 to 5 demonstrates both theoretical correctness and practical feasibility through progressively integrated validation. TRL 3 proves component-level correctness: each part works independently. TRL 4 demonstrates system-level integration in simulation: the parts compose correctly. TRL 5 validates hardware implementation in a relevant environment: the complete system works on real control hardware. Achieving TRL 5 proves the methodology produces verified controllers implementable with current technology.
+\textbf{Answer:} Technology Readiness Level advancement from 2--3 to 5 demonstrates both theoretical correctness and practical feasibility through progressively integrated validation. 
 
-Success, however, depends on several critical assumptions. If these assumptions prove false, research could stall at lower readiness levels despite sound methodology.
+TRL 3 proves component-level correctness. Each part works independently. 
+
+TRL 4 demonstrates system-level integration in simulation. The parts compose correctly. 
+
+TRL 5 validates hardware implementation in a relevant environment. The complete system works on real control hardware. 
+
+Achieving TRL 5 proves the methodology produces verified controllers implementable with current technology.
+
+Success depends on several critical assumptions. If these assumptions prove false, research could stall at lower readiness levels despite sound methodology.
 
 Section 5 addresses the complementary question: What could prevent success?

5-risks-and-contingencies/v1.tex

@@ -4,13 +4,13 @@
 
 Section 4 defined success as reaching TRL 5 through component validation, system integration, and hardware demonstration.
 
-Every research plan rests on assumptions that might prove false. This section identifies four primary risks that could prevent successful completion: computational tractability of synthesis and verification, complexity of the discrete-continuous interface, completeness of procedure formalization, and hardware-in-the-loop integration challenges. 
+Every research plan rests on assumptions that might prove false. This section identifies four primary risks that could prevent successful completion. First: computational tractability of synthesis and verification. Second: complexity of the discrete-continuous interface. Third: completeness of procedure formalization. Fourth: hardware-in-the-loop integration challenges. 
 
 Each risk carries associated early warning indicators and contingency plans that preserve research value even when core assumptions fail. The staged project structure ensures that partial success yields publishable results and clearly identifies remaining barriers to deployment even when full success proves elusive.
 
 \subsection{Computational Tractability of Synthesis}
 
-Computational tractability represents the first major risk. The assumption: formalized startup procedures will yield automata small enough for efficient synthesis and verification. This assumption may fail. Reactive synthesis scales exponentially with specification complexity. Temporal logic specifications from complete startup procedures may produce automata with thousands of states. Synthesis times may exceed days or weeks, preventing completion within project timelines. Reachability analysis for continuous modes with high-dimensional state spaces may similarly prove intractable. Either barrier would constitute a fundamental obstacle to achieving research objectives.
+Computational tractability represents the first major risk. The assumption: formalized startup procedures will yield automata small enough for efficient synthesis and verification. This assumption may fail. Reactive synthesis scales exponentially with specification complexity. Temporal logic specifications from complete startup procedures may produce automata with thousands of states. Synthesis times may exceed days or weeks, preventing completion within project timelines. Reachability analysis for continuous modes with high-dimensional state spaces may similarly prove intractable. Either barrier would constitute a fundamental obstacle.
 
 Several indicators would provide early warning of computational tractability
 problems. Synthesis times exceeding 24 hours for simplified procedure subsets
@@ -132,11 +132,11 @@ quirks.
 
 This section answered the Heilmeier question: What could prevent success?
 
-\textbf{Answer:} Four primary risks threaten project completion: computational tractability of synthesis and verification, complexity of the discrete-continuous interface, completeness of procedure formalization, and hardware-in-the-loop integration challenges. 
+\textbf{Answer:} Four primary risks threaten project completion. First: computational tractability of synthesis and verification. Second: complexity of the discrete-continuous interface. Third: completeness of procedure formalization. Fourth: hardware-in-the-loop integration challenges. 
 
-Each risk has identifiable early warning indicators enabling detection before failure becomes inevitable. Each risk has viable mitigation strategies preserving research value even when core assumptions fail. 
+Each risk has identifiable early warning indicators. These enable detection before failure becomes inevitable. Each risk has viable mitigation strategies. These preserve research value even when core assumptions fail. 
 
-The staged project structure ensures partial success yields publishable results and identifies remaining barriers to deployment. This design feature maintains contribution regardless of which technical obstacles prove insurmountable. Even "failure" advances the field by documenting precisely which barriers remain.
+The staged project structure ensures partial success yields publishable results. It identifies remaining barriers to deployment. This design feature maintains contribution regardless of which technical obstacles prove insurmountable. Even "failure" advances the field by documenting precisely which barriers remain.
 
 The technical research plan is complete. Section 3 established what will be done and why it will succeed. Section 4 established how to measure success. This section established what might prevent success and how to mitigate risks.
 

6-broader-impacts/v1.tex

@@ -2,7 +2,7 @@
 
 \textbf{Heilmeier Questions: Who cares? Why now? What difference will it make?}
 
-Sections 2--5 established the complete technical research plan. Section 2 answered what has been done and identified the limits of current practice. Section 3 answered what is new and why it will succeed. Section 4 answered how success will be measured through TRL advancement. Section 5 answered what could prevent success and provided mitigation strategies for each risk.
+Sections 2--5 established the complete technical research plan. Section 2 answered what has been done. It identified the limits of current practice. Section 3 answered what is new and why the approach will succeed. Section 4 answered how success will be measured through TRL advancement. Section 5 answered what could prevent success. It provided mitigation strategies for each risk.
 
 This section addresses the remaining Heilmeier questions by connecting technical methodology to economic and societal impact.
 
@@ -12,13 +12,13 @@ This research directly addresses a \$21--28 billion annual cost barrier by enabl
 
 Why now? Exponentially growing AI infrastructure demands have transformed this longstanding challenge into an immediate crisis. This creates a market demanding solutions that did not exist before.
 
-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. SMRs deployed at datacenter sites minimize transmission losses and eliminate emissions. At this scale, however, nuclear power economics demand careful attention to operating costs.
+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. SMRs deployed at datacenter sites minimize transmission losses and eliminate emissions. At this scale, nuclear power economics demand careful attention to operating costs.
 
 The U.S. Energy Information Administration's Annual Energy Outlook 2022 projects advanced nuclear power entering service in 2027 will 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}. Nuclear power supplying this demand would generate total annual costs exceeding \$92 billion. 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 total levelized cost, translating to \$21--28 billion annually for projected datacenter demand.
 
 \textbf{What difference will it make?} This research directly addresses the \$21--28 billion annual O\&M cost challenge. High-assurance autonomous control makes small modular reactors economically viable for datacenter power while maintaining nuclear safety standards.
 
-Current nuclear operations require full control room staffing for each reactor—whether large conventional units or small modular designs. For large reactors producing 1,000+ MW, staffing costs spread across substantial output. Small modular reactors producing 50-300 MW face the same staffing requirements with far lower output. This makes per-megawatt costs prohibitive. These staffing requirements drive the economic challenge that threatens SMR deployment for datacenter applications.
+Current nuclear operations require full control room staffing for each reactor—whether large conventional units or small modular designs. For large reactors producing 1,000+ MW, staffing costs spread across substantial output. Small modular reactors producing 50-300 MW face the same staffing requirements with far lower output. This makes per-megawatt costs prohibitive. These staffing requirements drive the economic challenge threatening SMR deployment for datacenter applications.
 
 Synthesizing provably correct hybrid controllers from formal specifications automates routine operational sequences that currently require constant human oversight. This enables a fundamental shift from direct operator control to supervisory monitoring. Operators oversee multiple autonomous reactors rather than manually controlling individual units.
 
@@ -62,12 +62,26 @@ adoption across critical infrastructure.
 
 This section answered three critical Heilmeier questions: Who cares? Why now? What difference will it make?
 
-\textbf{Who cares?} Three stakeholder groups face the same constraint. The nuclear industry faces an economic crisis for small modular reactors due to per-megawatt staffing costs. Datacenter operators need hundreds of megawatts of continuous clean power for AI infrastructure. Clean energy advocates need nuclear power to be economically competitive. All three groups need autonomous control with safety guarantees.
+\textbf{Who cares?} Three stakeholder groups face the same constraint. 
 
-\textbf{Why now?} Two forces converge. First, exponentially growing AI infrastructure demands create immediate need for economical nuclear power at datacenter scale. Projections show datacenter electricity demand reaching 1,050 terawatt-hours annually by 2030. Second, formal methods tools have matured sufficiently to make compositional hybrid verification computationally achievable. What was theoretically possible but practically intractable a decade ago is now feasible. The problem is urgent. The tools exist.
+The nuclear industry faces an economic crisis for small modular reactors due to per-megawatt staffing costs. 
 
-\textbf{What difference will it make?} This research addresses a \$21--28 billion annual cost barrier and enables autonomous control with mathematical safety guarantees. Beyond immediate economic impact, the methodology establishes a generalizable framework for safety-critical autonomous systems across critical infrastructure. Impact extends beyond nuclear power to any safety-critical system requiring provable correctness.
+Datacenter operators need hundreds of megawatts of continuous clean power for AI infrastructure. 
+
+Clean energy advocates need nuclear power to be economically competitive. 
+
+All three groups need autonomous control with safety guarantees.
+
+\textbf{Why now?} Two forces converge. 
+
+First: exponentially growing AI infrastructure demands create immediate need for economical nuclear power at datacenter scale. Projections show datacenter electricity demand reaching 1,050 terawatt-hours annually by 2030. 
+
+Second: formal methods tools have matured sufficiently to make compositional hybrid verification computationally achievable. What was theoretically possible but practically intractable a decade ago is now feasible. 
+
+The problem is urgent. The tools exist.
+
+\textbf{What difference will it make?} This research addresses a \$21--28 billion annual cost barrier. It enables autonomous control with mathematical safety guarantees. Beyond immediate economic impact, the methodology establishes a generalizable framework for safety-critical autonomous systems across critical infrastructure. Impact extends beyond nuclear power to any safety-critical system requiring provable correctness.
 
 The complete research plan spans technical approach, success metrics, risk mitigation, and broader impact. One final Heilmeier question remains: How long will it take?
 
-Section 8 provides a structured 24-month research plan progressing through milestones tied to Technology Readiness Level advancement, demonstrating the proposed work is achievable within a doctoral timeline.
+Section 8 provides a structured 24-month research plan progressing through milestones tied to Technology Readiness Level advancement. This demonstrates the proposed work is achievable within a doctoral timeline.