Auto sync: 2025-12-05 22:19:28 (32 files changed)
M .task/backlog.data M .task/pending.data M .task/undo.data M Writing/ERLM/1-goals-and-outcomes/research_statement.tex A Writing/ERLM/1-goals-and-outcomes/research_statement_v2.tex A Writing/ERLM/1-goals-and-outcomes/v8.tex A Writing/ERLM/2-state-of-the-art/v7.tex M Writing/ERLM/3-research-approach/v4.tex
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{"description":"Review and edit Goals and Outcomes section","due":"20251205T050000Z","end":"20251206T004937Z","entry":"20251202T132235Z","modified":"20251206T004937Z","project":"ERLM","status":"completed","uuid":"0888fdb8-f5cd-4374-a589-b7b3c1bbd472","tags":["editing"]}
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{"description":"Review and edit Goals and Outcomes section","due":"20251205T050000Z","end":"20251206T004937Z","entry":"20251202T132235Z","modified":"20251206T004937Z","project":"ERLM","status":"completed","uuid":"0888fdb8-f5cd-4374-a589-b7b3c1bbd472","tags":["editing"]}
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{"description":"Review and edit Research Approach section","due":"20251205T050000Z","end":"20251206T004937Z","entry":"20251202T132235Z","modified":"20251206T004937Z","project":"ERLM","status":"completed","uuid":"9ce7d23c-0f56-49af-b97d-a684966cfbae","tags":["editing"]}
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{"description":"Review and edit Research Approach section","due":"20251205T050000Z","end":"20251206T004937Z","entry":"20251202T132235Z","modified":"20251206T004937Z","project":"ERLM","status":"completed","uuid":"9ce7d23c-0f56-49af-b97d-a684966cfbae","tags":["editing"]}
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{"description":"Review and edit Metrics of Success section","due":"20251205T050000Z","entry":"20251202T132235Z","modified":"20251206T004956Z","project":"ERLM","start":"20251206T004956Z","status":"pending","uuid":"29cc8c63-1fb7-4523-9953-603467b929ee","tags":["editing"]}
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{"description":"Review and edit Metrics of Success section","due":"20251205T050000Z","entry":"20251202T132235Z","modified":"20251206T004956Z","project":"ERLM","start":"20251206T004956Z","status":"pending","uuid":"29cc8c63-1fb7-4523-9953-603467b929ee","tags":["editing"]}
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{"description":"Review and edit Metrics of Success section","due":"20251205T050000Z","end":"20251206T025832Z","entry":"20251202T132235Z","modified":"20251206T025836Z","project":"ERLM","status":"completed","uuid":"29cc8c63-1fb7-4523-9953-603467b929ee","tags":["editing"]}
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{"description":"Review and edit Risks and Contingencies section","due":"20251205T050000Z","end":"20251206T025836Z","entry":"20251202T132235Z","modified":"20251206T025837Z","project":"ERLM","status":"completed","uuid":"e354ab0c-cef7-41e2-bfb4-d98886e512b7","tags":["editing"]}
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{"description":"Review and edit Broader Impacts section","due":"20251205T050000Z","end":"20251206T025837Z","entry":"20251202T132236Z","modified":"20251206T025839Z","project":"ERLM","status":"completed","uuid":"d1fa2409-2f2f-4855-81be-14ee617df5d2","tags":["editing"]}
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{"description":"Review and edit Budget section","due":"20251205T050000Z","end":"20251206T025839Z","entry":"20251202T132236Z","modified":"20251206T025839Z","project":"ERLM","status":"completed","uuid":"689420d6-7191-42b6-b691-94ad39c8e0dd","tags":["editing"]}
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{"description":"Review and edit Schedule section","due":"20251205T050000Z","end":"20251206T025839Z","entry":"20251202T132236Z","modified":"20251206T025842Z","project":"ERLM","status":"completed","uuid":"14fee599-fe0f-4773-90fc-c5f78291f425","tags":["editing"]}
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{"description":"Verify RFP compliance for all sections","due":"20251205T050000Z","end":"20251206T025842Z","entry":"20251202T132246Z","modified":"20251206T025843Z","project":"ERLM","status":"completed","uuid":"a4c027fa-f50d-4efc-ab61-5b8054810a80","tags":["editing"]}
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{"description":"Final proofread and polish entire proposal","due":"20251205T050000Z","end":"20251206T025843Z","entry":"20251202T132246Z","modified":"20251206T025844Z","project":"ERLM","status":"completed","uuid":"5ba3929b-5ec3-4c9d-b30e-30fd8fe20b54","tags":["editing"]}
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[description:"Final proofread and polish entire proposal" due:"1764910800" entry:"1764681766" modified:"1764681766" project:"ERLM" status:"pending" tags:"editing" tags_editing:"x" uuid:"5ba3929b-5ec3-4c9d-b30e-30fd8fe20b54"]
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---
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---
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---
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old [description:"Final proofread and polish entire proposal" due:"1764910800" entry:"1764681766" modified:"1764681766" project:"ERLM" status:"pending" tags:"editing" tags_editing:"x" uuid:"5ba3929b-5ec3-4c9d-b30e-30fd8fe20b54"]
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new [description:"Final proofread and polish entire proposal" due:"1764910800" end:"1764989923" entry:"1764681766" modified:"1764989924" project:"ERLM" status:"completed" tags:"editing" tags_editing:"x" uuid:"5ba3929b-5ec3-4c9d-b30e-30fd8fe20b54"]
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---
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@ -35,9 +35,8 @@ NASA's Formal Requirements Elicitation Tool (FRET), which structures
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requirements into scope, condition, component, timing, and response elements.
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requirements into scope, condition, component, timing, and response elements.
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This structured approach enables realizability checking to identify conflicts
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This structured approach enables realizability checking to identify conflicts
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and ambiguities in procedures before implementation. Second, we will synthesize
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and ambiguities in procedures before implementation. Second, we will synthesize
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discrete mode switching logic from these specifications using reactive synthesis
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discrete mode switching logic using reactive synthesi which generates provably
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tools such as Strix, which generates deterministic automata that are provably
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correct deterministic automata. Third, we will develop continuous
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correct by construction. Third, we will develop and verify continuous
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controllers for each discrete mode using standard control theory and
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controllers for each discrete mode using standard control theory and
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reachability analysis. We will classify continuous modes based on their
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reachability analysis. We will classify continuous modes based on their
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transition objectives, and then employ assume-guarantee contracts and barrier
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transition objectives, and then employ assume-guarantee contracts and barrier
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deterministic automata. This compositional approach enables local verification
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deterministic automata. This compositional approach enables local verification
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of continuous modes without requiring global trajectory analysis across the
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of continuous modes without requiring global trajectory analysis across the
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entire hybrid system. We will demonstrate this methodology by developing an
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entire hybrid system. We will demonstrate this methodology by developing an
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autonomous startup controller for a Small Modular Advanced High Temperature
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autonomous startup controller on an Emerson Ovation control system.
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Reactor (SmAHTR) and implementing it on an Emerson Ovation control system using
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the ARCADE hardware-in-the-loop platform.
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% Pay-off
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% Pay-off
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This approach will demonstrate autonomous control can be used for complex
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This approach will demonstrate autonomous control can be used for complex
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nuclear power operations while maintaining safety guarantees.
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nuclear power operations while maintaining safety guarantees.
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@ -85,27 +82,9 @@ If this research is successful, we will be able to do the following:
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guarantees. }
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guarantees. }
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% Strategy
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% Strategy
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We will implement this methodology on a small modular reactor simulation
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We will implement this methodology on a small modular reactor simulation
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using industry-standard control hardware. This trial will include multiple
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using industry-standard control hardware. % Outcome
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coordinated control modes from cold shutdown through criticality to power
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operation on a SmAHTR reactor simulation in a hardware-in-the-loop
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experiment.
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% Outcome
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Control engineers will be able to implement high-assurance autonomous
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Control engineers will be able to implement high-assurance autonomous
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controls on industrial platforms they already use, enabling users to
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controls on industrial platforms they already use, enabling users to
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achieve autonomy without retraining costs or developing new equipment.
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achieve autonomy without retraining costs or developing new equipment.
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\end{enumerate}
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\end{enumerate}
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%
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% % IMPACT PARAGRAPH Innovation
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% The innovation is unifying discrete synthesis and continuous verification to
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% enable end-to-end correctness guarantees for hybrid systems.
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% % Outcome Impact
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% If successful, control engineers will be able to create autonomous controllers from existing
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% procedures with mathematical proof of correct behavior, making high-assurance
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% autonomous control practical for safety-critical applications.
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% % Impact/Pay-off
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% This capability is essential for economic viability of next-generation nuclear
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% power. Small modular reactors represent a promising solution to growing energy
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% demands, but success depends on reducing per-megawatt operating costs through
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% increased autonomy. This research will provide the tools to achieve that autonomy
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% while maintaining the exceptional safety record required by the nuclear industry.
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82
Writing/ERLM/1-goals-and-outcomes/research_statement_v2.tex
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% GOAL PARAGRAPH
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The goal of this research is to develop a methodology for creating autonomous
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control systems with event-driven control laws that have guarantees of safe and
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correct behavior.
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% INTRODUCTORY PARAGRAPH Hook
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Nuclear power relies on extensively trained operators who follow detailed
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written procedures to manage reactor control. Based on these procedures and
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operators' interpretation of plant conditions, operators make critical decisions
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about when to switch between control objectives.
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% Gap
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But, reliance on human operators has created an economic challenge for
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next-generation nuclear power plants. Small modular reactors face significantly
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higher per-megawatt staffing costs than conventional plants. Autonomous control
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systems are needed that can safely manage complex operational sequences with the
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same assurance as human-operated systems, but without constant supervision.
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% APPROACH PARAGRAPH Solution
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To address this need, we will combine formal methods from computer science with
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control theory to build hybrid control systems that are correct by construction.
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% Rationale
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Hybrid systems use discrete logic to switch between continuous control modes,
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similar to how operators change control strategies. Existing formal methods
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generate provably correct switching logic but cannot handle continuous dynamics
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during transitions, while traditional control theory verifies continuous
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behavior but lacks tools for proving discrete switching correctness.
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% Hypothesis and Technical Approach
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We will bridge this gap through a three-stage methodology. First, we will
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translate written operating procedures into temporal logic specifications using
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NASA's Formal Requirements Elicitation Tool (FRET), which structures
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requirements into scope, condition, component, timing, and response elements.
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This structured approach enables realizability checking to identify conflicts
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and ambiguities in procedures before implementation. Second, we will synthesize
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discrete mode switching logic using reactive synthesis
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to generate deterministic automata that are provably
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correct by construction. Third, we will develop continuous
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controllers for each discrete mode using standard control theory and
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reachability analysis. We will classify continuous modes based on their
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||||||
|
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}
|
||||||
114
Writing/ERLM/1-goals-and-outcomes/v8.tex
Normal file
114
Writing/ERLM/1-goals-and-outcomes/v8.tex
Normal file
@ -0,0 +1,114 @@
|
|||||||
|
\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.
|
||||||
165
Writing/ERLM/2-state-of-the-art/v7.tex
Normal file
165
Writing/ERLM/2-state-of-the-art/v7.tex
Normal file
@ -0,0 +1,165 @@
|
|||||||
|
\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.
|
||||||
@ -93,6 +93,8 @@ scenario because all decisions are represented by discrete variables.
|
|||||||
Formulating operating rules using this logic enforces a finite and correct way
|
Formulating operating rules using this logic enforces a finite and correct way
|
||||||
of operating.
|
of operating.
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
Reactive synthesis is an active research field in computer science focused on
|
Reactive synthesis is an active research field in computer science focused on
|
||||||
generating discrete controllers from temporal logic specifications. The term
|
generating discrete controllers from temporal logic specifications. The term
|
||||||
``reactive'' indicates that the system responds to environmental inputs to
|
``reactive'' indicates that the system responds to environmental inputs to
|
||||||
@ -166,6 +168,18 @@ control systems we aim to construct. The continuous modes will be developed
|
|||||||
after discrete automaton construction, leveraging the automaton structure and
|
after discrete automaton construction, leveraging the automaton structure and
|
||||||
transitions to design multiple smaller, specialized continuous controllers.
|
transitions to design multiple smaller, specialized continuous controllers.
|
||||||
|
|
||||||
|
Of note is the fact that the translation into this linear temporal logic does
|
||||||
|
something to create barriers between different control modes. Switching from one
|
||||||
|
mode to another mode becomes a discrete, boolean variable. \(RodsInserted\) or
|
||||||
|
\(HighTemp\) in the temporal specifications are booleans, but in the real system
|
||||||
|
can represent a physical feature in the state space. These features are where
|
||||||
|
continuous control modes end and begin, and their definition is critical in
|
||||||
|
defining which control mode is active at any given time. This information of
|
||||||
|
where in the state space these conditions represent will be preserved from the
|
||||||
|
original requirements by including them in the development of the continuous
|
||||||
|
control modes, but will not be considered as numeric values in the synthesis of
|
||||||
|
the discrete mode switching portion of the autonomous controller.
|
||||||
|
|
||||||
The discrete automaton transitions are key to the supervisory behavior of the
|
The discrete automaton transitions are key to the supervisory behavior of the
|
||||||
autonomous controller. These transitions mark decision points for switching
|
autonomous controller. These transitions mark decision points for switching
|
||||||
between continuous control modes and define their strategic objectives. We
|
between continuous control modes and define their strategic objectives. We
|
||||||
|
|||||||
285
Writing/ERLM/3-research-approach/v5.tex
Normal file
285
Writing/ERLM/3-research-approach/v5.tex
Normal file
@ -0,0 +1,285 @@
|
|||||||
|
\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.
|
||||||
@ -1,12 +1,12 @@
|
|||||||
\newpage
|
|
||||||
\section{Metrics for Success}
|
\section{Metrics for Success}
|
||||||
|
|
||||||
This research will be measured by advancement through Technology Readiness
|
This research will be measured by advancement through Technology Readiness
|
||||||
Levels, progressing from fundamental concepts to validated prototype
|
Levels, progressing from fundamental concepts to validated prototype
|
||||||
demonstration. The work begins at TRL 2-3 and aims to reach TRL 5, where system
|
demonstration. The work presented in HARDENS begins at TRL 2-3 and aims to reach
|
||||||
components operate successfully in a relevant laboratory environment. This
|
TRL 5, where system components operate successfully in a relevant laboratory
|
||||||
section explains why TRL advancement provides the most appropriate success
|
environment. This section explains why TRL advancement provides the most
|
||||||
metric and defines the specific criteria required to achieve TRL 5.
|
appropriate success metric and defines the specific criteria required to achieve
|
||||||
|
TRL 5.
|
||||||
|
|
||||||
Technology Readiness Levels provide the ideal success metric because they
|
Technology Readiness Levels provide the ideal success metric because they
|
||||||
explicitly measure the gap between academic proof-of-concept and practical
|
explicitly measure the gap between academic proof-of-concept and practical
|
||||||
@ -30,18 +30,12 @@ uses TRLs for technology assessment, making this metric directly relevant to
|
|||||||
potential adopters. Reaching TRL 5 provides a clear answer to industry questions
|
potential adopters. Reaching TRL 5 provides a clear answer to industry questions
|
||||||
about feasibility and maturity in a way that academic publications alone cannot.
|
about feasibility and maturity in a way that academic publications alone cannot.
|
||||||
|
|
||||||
The work currently exists at TRL 2-3. Formal synthesis and hybrid control
|
Moving from current state to target requires achieving three intermediate
|
||||||
verification principles have been established through prior research, placing
|
levels, each representing a distinct validation milestone:
|
||||||
the fundamental approach at TRL 2. The SmAHTR simulation model and initial
|
|
||||||
procedure analysis place specific components at early TRL 3, where proof of
|
|
||||||
concept has been partially demonstrated for individual elements but not
|
|
||||||
integrated. The target state is TRL 5. 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}}
|
\paragraph{TRL 3 \textit{Critical Function and Proof of Concept}}
|
||||||
For this research, TRL 3 means demonstrating that each component of the
|
For this research, TRL 3 means demonstrating that each component of the
|
||||||
methodology works in isolation. SmAHTR startup procedures must be translated
|
methodology works in isolation. Startup procedures must be translated
|
||||||
into temporal logic specifications that pass realizability analysis. A discrete
|
into temporal logic specifications that pass realizability analysis. A discrete
|
||||||
automaton must be synthesized with interpretable structure. At least one
|
automaton must be synthesized with interpretable structure. At least one
|
||||||
continuous controller must be designed with reachability analysis proving that
|
continuous controller must be designed with reachability analysis proving that
|
||||||
@ -51,7 +45,7 @@ approach on a simplified startup sequence.
|
|||||||
|
|
||||||
\paragraph{TRL 4 \textit{Laboratory Testing of Integrated Components}}
|
\paragraph{TRL 4 \textit{Laboratory Testing of Integrated Components}}
|
||||||
For this research, TRL 4 means demonstrating a complete integrated hybrid
|
For this research, TRL 4 means demonstrating a complete integrated hybrid
|
||||||
controller in simulation. All SmAHTR startup procedures must be formalized with
|
controller in simulation. All startup procedures must be formalized with
|
||||||
a synthesized automaton covering all operational modes. Continuous controllers
|
a synthesized automaton covering all operational modes. Continuous controllers
|
||||||
must exist for all discrete modes. Verification must be complete for all mode
|
must exist for all discrete modes. Verification must be complete for all mode
|
||||||
transitions using reachability analysis, barrier certificates, and
|
transitions using reachability analysis, barrier certificates, and
|
||||||
@ -60,28 +54,23 @@ startup sequences in software simulation with zero safety violations across
|
|||||||
multiple consecutive runs. This proves that formal correctness guarantees can be
|
multiple consecutive runs. This proves that formal correctness guarantees can be
|
||||||
maintained throughout system integration.
|
maintained throughout system integration.
|
||||||
|
|
||||||
\paragraph{TRL 5 \textit{Laboratory Testing in Relevant Environment}}
|
\paragraph{TRL 5 \textit{Laboratory Testing in Relevant Environment}} For this
|
||||||
For this research, TRL 5 means demonstrating the verified controller on
|
research, TRL 5 means demonstrating the verified controller on industrial
|
||||||
industrial control hardware through hardware-in-the-loop testing. The discrete
|
control hardware through hardware-in-the-loop testing. The discrete automaton
|
||||||
automaton must be implemented on the Emerson Ovation control system and verified
|
must be implemented on the Emerson Ovation control system and verified to match
|
||||||
to match synthesized specifications exactly. Continuous controllers must execute
|
synthesized specifications exactly. Continuous controllers must execute at
|
||||||
at required rates. The ARCADE interface must establish stable real-time
|
required rates. The ARCADE interface must establish stable real-time
|
||||||
communication between Ovation hardware and SmAHTR simulation. Complete
|
communication between the Emerson Ovation hardware and SmAHTR simulation.
|
||||||
autonomous startup sequences must execute via hardware-in-the-loop across the
|
Complete autonomous startup sequences must execute via hardware-in-the-loop
|
||||||
full operational envelope. The controller must handle off-nominal scenarios to
|
across the full operational envelope. The controller must handle off-nominal
|
||||||
validate that expulsory modes function correctly. For example, simulated sensor
|
scenarios to validate that expulsory modes function correctly. For example,
|
||||||
failures must trigger appropriate fault detection and mode transitions, and loss
|
simulated sensor failures must trigger appropriate fault detection and mode
|
||||||
of cooling scenarios must activate SCRAM procedures as specified. Graded
|
transitions, and loss of cooling scenarios must activate SCRAM procedures as
|
||||||
responses to minor disturbances are outside the scope of this work. Formal
|
specified. Graded responses to minor disturbances are outside the scope of this
|
||||||
verification results must remain valid with discrete behavior matching
|
work. Formal verification results must remain valid with discrete behavior
|
||||||
specifications and continuous trajectories remaining within verified bounds.
|
matching specifications and continuous trajectories remaining within verified
|
||||||
This proves that the methodology produces verified controllers implementable on
|
bounds. This proves that the methodology produces verified controllers
|
||||||
industrial hardware.
|
implementable on industrial hardware.
|
||||||
|
|
||||||
These levels define progressively more demanding demonstrations. TRL 3 proves
|
|
||||||
individual components work. TRL 4 proves they work together in simulation. TRL 5
|
|
||||||
proves they work on actual hardware in realistic conditions. Each level builds
|
|
||||||
on the previous while adding new validation requirements.
|
|
||||||
|
|
||||||
Progress will be assessed quarterly through collection of specific data
|
Progress will be assessed quarterly through collection of specific data
|
||||||
comparing actual results against TRL advancement criteria. Specification
|
comparing actual results against TRL advancement criteria. Specification
|
||||||
@ -89,18 +78,9 @@ development status indicates progress toward TRL 3. Synthesis results and
|
|||||||
verification coverage indicate progress toward TRL 4. Simulation performance
|
verification coverage indicate progress toward TRL 4. Simulation performance
|
||||||
metrics and hardware integration milestones indicate progress toward TRL 5. The
|
metrics and hardware integration milestones indicate progress toward TRL 5. The
|
||||||
research plan will be revised only when new data invalidates fundamental
|
research plan will be revised only when new data invalidates fundamental
|
||||||
assumptions. Unrealizable specifications indicate procedure conflicts requiring
|
assumptions. This research succeeds if it achieves TRL 5 by demonstrating a complete
|
||||||
refinement or alternative reactor selection. Unverifiable dynamics suggest model
|
|
||||||
simplification or alternative verification methods are needed. Unachievable
|
|
||||||
real-time performance requires controller simplification or hardware upgrades.
|
|
||||||
Any revision will document the invalidating data, the failed assumption, and the
|
|
||||||
modified pathway with adjusted scope.
|
|
||||||
|
|
||||||
This research succeeds if it achieves TRL 5 by demonstrating a complete
|
|
||||||
autonomous hybrid controller with formal correctness guarantees operating on
|
autonomous hybrid controller with formal correctness guarantees operating on
|
||||||
industrial control hardware through hardware-in-the-loop testing in a relevant
|
industrial control hardware through hardware-in-the-loop testing in a relevant
|
||||||
laboratory environment. This establishes both theoretical validity and practical
|
laboratory environment. This establishes both theoretical validity and practical
|
||||||
feasibility, proving that the methodology produces verified controllers and that
|
feasibility, proving that the methodology produces verified controllers and that
|
||||||
implementation is achievable with current technology. It provides a clear
|
implementation is achievable with current technology.
|
||||||
pathway for nuclear industry adoption and broader application to safety-critical
|
|
||||||
autonomous systems.
|
|
||||||
|
|||||||
88
Writing/ERLM/4-metrics-of-success/v3.tex
Normal file
88
Writing/ERLM/4-metrics-of-success/v3.tex
Normal file
@ -0,0 +1,88 @@
|
|||||||
|
\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.
|
||||||
@ -1,4 +1,3 @@
|
|||||||
\newpage
|
|
||||||
\section{Risks and Contingencies}
|
\section{Risks and Contingencies}
|
||||||
|
|
||||||
This research relies on several critical assumptions that, if invalidated,
|
This research relies on several critical assumptions that, if invalidated,
|
||||||
@ -30,7 +29,7 @@ problems. Synthesis times exceeding 24 hours for simplified procedure subsets
|
|||||||
would suggest that complete procedures are intractable. Generated automata
|
would suggest that complete procedures are intractable. Generated automata
|
||||||
containing more than 1,000 discrete states would indicate that the discrete
|
containing more than 1,000 discrete states would indicate that the discrete
|
||||||
state space is too large for efficient verification. Specifications flagged as
|
state space is too large for efficient verification. Specifications flagged as
|
||||||
unrealizable by FRET or STRIX would reveal fundamental conflicts in the
|
unrealizable by FRET or Strix would reveal fundamental conflicts in the
|
||||||
formalized procedures. Reachability analysis failing to converge within
|
formalized procedures. Reachability analysis failing to converge within
|
||||||
reasonable time bounds would show that continuous mode verification cannot be
|
reasonable time bounds would show that continuous mode verification cannot be
|
||||||
completed with available computational resources.
|
completed with available computational resources.
|
||||||
@ -45,24 +44,6 @@ synthesis is achievable for safety-critical nuclear applications. The limitation
|
|||||||
to simplified operational sequences would be explicitly documented as a
|
to simplified operational sequences would be explicitly documented as a
|
||||||
constraint rather than a failure.
|
constraint rather than a failure.
|
||||||
|
|
||||||
Reachability analysis specifically can exploit time-scale separation inherent in
|
|
||||||
reactor dynamics. Fast thermal transients can be treated quasi-steady relative
|
|
||||||
to slower nuclear kinetics, which enables decomposition into smaller subsystems.
|
|
||||||
Temperature dynamics operate on time scales of seconds to minutes, while neutron
|
|
||||||
kinetics respond in milliseconds to seconds for prompt effects and hours for
|
|
||||||
xenon poisoning. These distinct time scales permit separate analysis with
|
|
||||||
conservative coupling assumptions between subsystems, dramatically reducing the
|
|
||||||
dimensionality of reachability computations.
|
|
||||||
|
|
||||||
Mitigation strategies exist even before contingency plans become necessary.
|
|
||||||
Access to the University of Pittsburgh Center for Research Computing provides
|
|
||||||
high-performance computing resources if single-workstation computation proves
|
|
||||||
insufficient. Parallel synthesis algorithms and distributed reachability
|
|
||||||
analysis can leverage these resources to extend computational feasibility.
|
|
||||||
Compositional verification approaches using assume-guarantee reasoning can
|
|
||||||
decompose monolithic verification problems into tractable subproblems, each of
|
|
||||||
which can be solved independently before composition.
|
|
||||||
|
|
||||||
\subsection{Discrete-Continuous Interface Formalization}
|
\subsection{Discrete-Continuous Interface Formalization}
|
||||||
|
|
||||||
The second critical assumption concerns the mapping between boolean guard
|
The second critical assumption concerns the mapping between boolean guard
|
||||||
@ -121,7 +102,7 @@ computational resources where they matter most for safety assurance.
|
|||||||
|
|
||||||
\subsection{Procedure Formalization Completeness}
|
\subsection{Procedure Formalization Completeness}
|
||||||
|
|
||||||
The third assumption is that existing SmAHTR startup procedures contain
|
The third assumption is that existing startup procedures contain
|
||||||
sufficient detail and clarity for translation into temporal logic specifications.
|
sufficient detail and clarity for translation into temporal logic specifications.
|
||||||
Nuclear operating procedures, while extensively detailed, were written for human
|
Nuclear operating procedures, while extensively detailed, were written for human
|
||||||
operators who bring contextual understanding and adaptive reasoning to their
|
operators who bring contextual understanding and adaptive reasoning to their
|
||||||
@ -175,58 +156,5 @@ water reactors, and advanced designs---may reveal common patterns and standard
|
|||||||
ambiguities amenable to systematic resolution. This cross-design analysis would
|
ambiguities amenable to systematic resolution. This cross-design analysis would
|
||||||
strengthen the generalizability of any proposed specification language
|
strengthen the generalizability of any proposed specification language
|
||||||
extensions, ensuring they address industry-wide practices rather than
|
extensions, ensuring they address industry-wide practices rather than
|
||||||
SmAHTR-specific quirks.
|
specific quirks.
|
||||||
|
|
||||||
\subsection{Hardware-in-the-Loop Integration Complexity}
|
|
||||||
|
|
||||||
The fourth assumption is that the ARCADE interface can provide stable real-time
|
|
||||||
communication between Simulink simulation and Ovation control hardware at
|
|
||||||
control rates required for reactor dynamics. Hardware-in-the-loop testing
|
|
||||||
introduces timing constraints, communication latency, and platform compatibility
|
|
||||||
challenges that are absent in pure simulation. Control rates for reactor systems
|
|
||||||
typically range from 10-100 Hz for continuous control to millisecond response
|
|
||||||
times for protection system actions. Control loop jitter, communication
|
|
||||||
dropouts, or computational limitations in the Ovation PLC could prevent
|
|
||||||
successful HIL validation even if the synthesized controller is theoretically
|
|
||||||
correct. Real-time operating system constraints, network latency, and hardware
|
|
||||||
execution speed may prove incompatible with verified timing assumptions embedded
|
|
||||||
in the controller design.
|
|
||||||
|
|
||||||
Early indicators would identify hardware integration problems before they derail
|
|
||||||
the entire validation effort. Communication dropouts or buffer overruns between ARCADE
|
|
||||||
and Ovation would indicate that the interface cannot maintain stable real-time
|
|
||||||
data exchange. The Ovation PLC proving unable to execute the synthesized
|
|
||||||
automaton at required speed would reveal fundamental computational limitations
|
|
||||||
of the target hardware platform. Timing analysis showing that hardware cannot
|
|
||||||
meet real-time deadlines assumed during verification would demonstrate
|
|
||||||
incompatibility between formal guarantees and physical implementation
|
|
||||||
constraints.
|
|
||||||
|
|
||||||
The contingency plan is to demonstrate the controller in software-in-the-loop
|
|
||||||
configuration with detailed timing analysis showing industrial hardware
|
|
||||||
feasibility. Software-in-the-loop testing executes the complete verified
|
|
||||||
controller in a real-time software environment that emulates hardware timing
|
|
||||||
constraints without requiring physical hardware. Combined with worst-case
|
|
||||||
execution time analysis of the synthesized automaton and continuous control
|
|
||||||
algorithms, software-in-the-loop validation can provide strong evidence of
|
|
||||||
implementability even without physical hardware demonstration. This approach
|
|
||||||
maintains TRL 4 rather than TRL 5, but still validates
|
|
||||||
the synthesis methodology and establishes a clear pathway to hardware
|
|
||||||
deployment. The research contribution remains intact: demonstrating that formal
|
|
||||||
hybrid control synthesis produces implementable controllers, with remaining
|
|
||||||
barriers clearly identified as hardware integration challenges rather than
|
|
||||||
fundamental methodological limitations.
|
|
||||||
|
|
||||||
Mitigation strategies leverage existing infrastructure and adopt early testing
|
|
||||||
practices. ARCADE has been successfully used for reactor simulation HIL testing
|
|
||||||
at the University of Pittsburgh, establishing feasibility in principle and
|
|
||||||
providing institutional knowledge about common integration challenges. Conducting
|
|
||||||
early integration testing during the synthesis phase, rather than deferring HIL
|
|
||||||
attempts until late in the project, identifies timing constraints and
|
|
||||||
communication requirements that can inform controller design. Early testing
|
|
||||||
ensures that synthesized controllers are compatible with hardware limitations
|
|
||||||
from the outset, rather than discovering incompatibilities after synthesis is
|
|
||||||
complete. The Ovation platform supports multiple implementation approaches
|
|
||||||
including function blocks, structured text, and ladder logic, which provides
|
|
||||||
flexibility in how synthesized automata are realized and may enable workarounds
|
|
||||||
if one implementation approach proves problematic.
|
|
||||||
|
|||||||
158
Writing/ERLM/5-risks-and-contingencies/v3.tex
Normal file
158
Writing/ERLM/5-risks-and-contingencies/v3.tex
Normal file
@ -0,0 +1,158 @@
|
|||||||
|
\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.
|
||||||
@ -1,4 +1,3 @@
|
|||||||
\newpage
|
|
||||||
\section{Broader Impacts}
|
\section{Broader Impacts}
|
||||||
|
|
||||||
Nuclear power presents both a compelling application domain and an urgent
|
Nuclear power presents both a compelling application domain and an urgent
|
||||||
|
|||||||
71
Writing/ERLM/6-broader-impacts/v3.tex
Normal file
71
Writing/ERLM/6-broader-impacts/v3.tex
Normal file
@ -0,0 +1,71 @@
|
|||||||
|
\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.
|
||||||
182
Writing/ERLM/7-budget/v2.tex
Normal file
182
Writing/ERLM/7-budget/v2.tex
Normal file
@ -0,0 +1,182 @@
|
|||||||
|
% Required packages:
|
||||||
|
% \usepackage{booktabs}
|
||||||
|
% \usepackage{tabularx}
|
||||||
|
% \usepackage{multirow}
|
||||||
|
% \usepackage{array}
|
||||||
|
% \usepackage[table]{xcolor} % optional, for alternating row colors
|
||||||
|
|
||||||
|
\section{Budget and Budget Justification}
|
||||||
|
|
||||||
|
\subsection{Budget Summary}
|
||||||
|
|
||||||
|
The proposed research will be conducted over three (3) years,
|
||||||
|
corresponding to the expected completion timeline for the PhD
|
||||||
|
dissertation. Table~\ref{tab:budget} provides a detailed breakdown
|
||||||
|
of costs by category and year.
|
||||||
|
|
||||||
|
\begin{table}[htbp]
|
||||||
|
\centering
|
||||||
|
\caption{Proposed Budget by Year and Category}
|
||||||
|
\label{tab:budget}
|
||||||
|
\small
|
||||||
|
\begin{tabular}{@{}lrrrr@{}}
|
||||||
|
\toprule
|
||||||
|
\textbf{Category} & \textbf{Year 1} & \textbf{Year 2} &
|
||||||
|
\textbf{Year 3} & \textbf{Total} \\
|
||||||
|
\midrule
|
||||||
|
\multicolumn{5}{l}{\textbf{Senior Personnel}} \\
|
||||||
|
\quad Faculty (PI Advisor, 1 mo.) & \$12,083 & \$12,566 &
|
||||||
|
\$13,069 & \$37,718 \\
|
||||||
|
\addlinespace
|
||||||
|
\multicolumn{5}{l}{\textbf{Other Personnel}} \\
|
||||||
|
\quad Graduate Research Assistant & \$38,000 & \$39,520 &
|
||||||
|
\$41,101 & \$118,621 \\
|
||||||
|
\addlinespace
|
||||||
|
\multicolumn{5}{l}{\textbf{Fringe Benefits}} \\
|
||||||
|
\quad Faculty Fringe Benefits (29.6\%) & \$3,577 & \$3,720 &
|
||||||
|
\$3,868 & \$11,165 \\
|
||||||
|
\quad GRA Fringe Benefits (50\%) & \$19,000 & \$19,760 &
|
||||||
|
\$20,551 & \$59,311 \\
|
||||||
|
\cmidrule{2-5}
|
||||||
|
\quad \textit{Fringe Benefits Subtotal} & \$22,577 & \$23,480 &
|
||||||
|
\$24,419 & \$70,476 \\
|
||||||
|
\addlinespace
|
||||||
|
\multicolumn{5}{l}{\textbf{Equipment}} \\
|
||||||
|
\quad (No equipment over \$5,000) & --- & --- & --- & --- \\
|
||||||
|
\addlinespace
|
||||||
|
\multicolumn{5}{l}{\textbf{Travel}} \\
|
||||||
|
\quad Conference Travel (Domestic) & \$4,000 & \$4,000 &
|
||||||
|
\$4,000 & \$12,000 \\
|
||||||
|
\quad Industry Collaboration Visits & \$1,500 & \$1,500 &
|
||||||
|
\$1,500 & \$4,500 \\
|
||||||
|
\cmidrule{2-5}
|
||||||
|
\quad \textit{Travel Subtotal} & \$5,500 & \$5,500 &
|
||||||
|
\$5,500 & \$16,500 \\
|
||||||
|
\addlinespace
|
||||||
|
\multicolumn{5}{l}{\textbf{Participant Support Costs}} \\
|
||||||
|
\quad (Not applicable) & --- & --- & --- & --- \\
|
||||||
|
\addlinespace
|
||||||
|
\multicolumn{5}{l}{\textbf{Other Direct Costs}} \\
|
||||||
|
\quad \textit{Materials and Supplies:} & & & & \\
|
||||||
|
\quad \quad High-Performance Workstation & \$3,500 & --- &
|
||||||
|
--- & \$3,500 \\
|
||||||
|
\quad \quad Laboratory Materials \& Supplies & \$1,500 & \$1,000 &
|
||||||
|
\$1,000 & \$3,500 \\
|
||||||
|
\quad \textit{Publication Costs} & \$1,000 & \$1,500 &
|
||||||
|
\$2,000 & \$4,500 \\
|
||||||
|
\quad \textit{Computing/Cloud Services} & \$1,500 & \$1,500 &
|
||||||
|
\$1,500 & \$4,500 \\
|
||||||
|
\cmidrule{2-5}
|
||||||
|
\quad \textit{Other Direct Costs Subtotal} & \$7,500 & \$4,000 &
|
||||||
|
\$4,500 & \$16,000 \\
|
||||||
|
\addlinespace
|
||||||
|
\midrule
|
||||||
|
\textbf{Total Direct Costs} & \$85,660 & \$85,066 &
|
||||||
|
\$88,589 & \$259,315 \\
|
||||||
|
\addlinespace
|
||||||
|
\multicolumn{5}{l}{\textbf{H. Indirect Costs (F\&A)}} \\
|
||||||
|
\quad On-Campus Research (56\% MTDC) & \$35,326 & \$34,488 &
|
||||||
|
\$35,935 & \$105,749 \\
|
||||||
|
\addlinespace
|
||||||
|
\midrule
|
||||||
|
\textbf{TOTAL PROJECT COST} & \$120,986 & \$119,554 &
|
||||||
|
\$124,524 & \$365,064 \\
|
||||||
|
\bottomrule
|
||||||
|
\end{tabular}
|
||||||
|
\end{table}
|
||||||
|
|
||||||
|
\subsection{Budget Justification}
|
||||||
|
|
||||||
|
\subsubsection{Senior Personnel}
|
||||||
|
|
||||||
|
\paragraph{Faculty Advisor}
|
||||||
|
Funds are requested to support one month of summer salary per year
|
||||||
|
for the faculty advisor (estimated at Associate Professor level,
|
||||||
|
\$96,459/year base salary for 8 academic months = \$12,083/month).
|
||||||
|
A 4\% annual salary increase is applied in subsequent years.
|
||||||
|
|
||||||
|
\subsubsection{Other Personnel}
|
||||||
|
|
||||||
|
\paragraph{Graduate Research Assistant (Principal Investigator)}
|
||||||
|
Funds are requested to support one full-time graduate research
|
||||||
|
assistant (the PI) for the entire duration of the project at
|
||||||
|
\$38,000 per year in Year 1. This represents a standard graduate
|
||||||
|
research assistantship stipend at the University of Pittsburgh for
|
||||||
|
a PhD student in the Swanson School of Engineering. A 4\% annual
|
||||||
|
salary increase is included in Years 2 and 3 to account for
|
||||||
|
cost-of-living adjustments.
|
||||||
|
|
||||||
|
\subsubsection{Fringe Benefits}
|
||||||
|
|
||||||
|
\paragraph{Faculty Fringe Benefits}
|
||||||
|
Faculty fringe benefits are calculated at 29.6\%, the University of
|
||||||
|
Pittsburgh's approved rate for academic year faculty, covering
|
||||||
|
retirement contributions, health insurance, and other benefits.
|
||||||
|
|
||||||
|
\paragraph{Graduate Research Assistant Fringe Benefits}
|
||||||
|
Fringe benefits for the GRA are calculated at 50\% of salary,
|
||||||
|
consistent with University of Pittsburgh rates for graduate students
|
||||||
|
on research assistantships.
|
||||||
|
|
||||||
|
\subsubsection{Travel}
|
||||||
|
|
||||||
|
\paragraph{Conference Travel (\$4,000 per year)} Funds are requested for the PI
|
||||||
|
and faculty advisor to attend one major control systems conference annually to
|
||||||
|
disseminate research results. The budget assumes domestic conference attendance
|
||||||
|
with costs including: airfare, hotel, meals and incidentals, ground
|
||||||
|
transportation, and registration for both attendees per conference.
|
||||||
|
\paragraph{Industry Collaboration Visits (\$1,500 per year)} Funds are requested
|
||||||
|
for travel to industry partner sites and potential nuclear facilities to: (1)
|
||||||
|
validate reactor operating procedures with domain experts; (2) present research
|
||||||
|
progress to industry stakeholders; (3) gather feedback on practical
|
||||||
|
implementation considerations; and (4) explore deployment pathways for the
|
||||||
|
developed technology.
|
||||||
|
|
||||||
|
\subsubsection{Other Direct Costs}
|
||||||
|
|
||||||
|
\paragraph{Materials and Supplies}
|
||||||
|
|
||||||
|
\textit{High-Performance Workstation (\$3,500, Year 1):} A dedicated
|
||||||
|
high-performance workstation is required for computationally intensive tasks
|
||||||
|
including. The workstation specifications include: Intel Core i9 or AMD Ryzen 9
|
||||||
|
processor (minimum 16 cores), 64 GB RAM, 2 TB NVMe SSD storage, and NVIDIA GPU
|
||||||
|
for potential acceleration of numerical computations.
|
||||||
|
|
||||||
|
\textit{Laboratory Materials and Supplies (\$1,500 Year 1; \$1,000 Years 2--3):}
|
||||||
|
Funds are requested for laboratory supplies and materials including: electronic
|
||||||
|
components and sensors for hardware integration, cables and connectors for
|
||||||
|
hardware-in-the-loop setup, and miscellaneous computing accessories such as
|
||||||
|
external storage devices and backup media.
|
||||||
|
|
||||||
|
\paragraph{Publication Costs}
|
||||||
|
Funds are requested to cover publication fees for disseminating
|
||||||
|
research results in high-quality peer-reviewed venues. Budget
|
||||||
|
includes:
|
||||||
|
\begin{itemize}
|
||||||
|
\item Year 1 (\$1,000): Conference proceedings fees and one journal
|
||||||
|
submission
|
||||||
|
\item Year 2 (\$1,500): Open-access publication charges for first
|
||||||
|
major journal paper
|
||||||
|
\item Year 3 (\$2,000): Open-access publication charges for
|
||||||
|
dissertation-culminating journal papers
|
||||||
|
\end{itemize}
|
||||||
|
|
||||||
|
Open-access publication is prioritized to maximize research impact
|
||||||
|
and accessibility, particularly important for work with potential
|
||||||
|
nuclear safety applications. Many high-impact journals (IEEE
|
||||||
|
Transactions on Automatic Control, Automatica) charge
|
||||||
|
\$1,000--\$2,000 for open access.
|
||||||
|
|
||||||
|
\paragraph{Computing and Cloud Services} Funds are requested for cloud computing
|
||||||
|
resources and online services. Cloud computing provides scalable
|
||||||
|
computational resources for particularly demanding verification problems without
|
||||||
|
requiring additional capital equipment purchases.
|
||||||
|
|
||||||
|
\subsubsection{H. Indirect Costs (Facilities \& Administrative)}
|
||||||
|
|
||||||
|
Indirect costs are calculated at 56\% of Modified Total Direct Costs
|
||||||
|
(MTDC), which is the University of Pittsburgh's federally negotiated
|
||||||
|
rate for on-campus research. MTDC includes all direct costs except
|
||||||
|
equipment purchases over \$5,000, tuition remission, and certain
|
||||||
|
other exclusions. The calculation base includes all personnel costs,
|
||||||
|
travel, and other direct costs as shown in the budget table.
|
||||||
96
Writing/ERLM/8-schedule/v2.tex
Normal file
96
Writing/ERLM/8-schedule/v2.tex
Normal file
@ -0,0 +1,96 @@
|
|||||||
|
\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.
|
||||||
BIN
Writing/ERLM/ERLM_Request_for_Proposals.pdf
Normal file
BIN
Writing/ERLM/ERLM_Request_for_Proposals.pdf
Normal file
Binary file not shown.
BIN
Writing/ERLM/SABO_FINAL_ERLM_PROPOSAL.pdf
Normal file
BIN
Writing/ERLM/SABO_FINAL_ERLM_PROPOSAL.pdf
Normal file
Binary file not shown.
@ -95,7 +95,7 @@
|
|||||||
\newcommand{\emphitem}[1]{\item \emph{#1:}}
|
\newcommand{\emphitem}[1]{\item \emph{#1:}}
|
||||||
|
|
||||||
% Default document metadata (can be overridden)
|
% Default document metadata (can be overridden)
|
||||||
\title{From Cold Start to Critical:\\ Formal Synthesis of Hybrid Controllers}
|
\title{From Cold Start to Critical:\\ Formal Synthesis of Autonomous Hybrid Controllers}
|
||||||
\author{%
|
\author{%
|
||||||
PI: Dane A. Sabo\\
|
PI: Dane A. Sabo\\
|
||||||
dane.sabo@pitt.edu\\
|
dane.sabo@pitt.edu\\
|
||||||
|
|||||||
@ -1,5 +1,6 @@
|
|||||||
\relax
|
\relax
|
||||||
\providecommand \oddpage@label [2]{}
|
\providecommand \oddpage@label [2]{}
|
||||||
|
\@writefile{toc}{\contentsline {section}{Contents}{ii}{}\protected@file@percent }
|
||||||
\@writefile{toc}{\contentsline {section}{\numberline {1}Goals and Outcomes}{1}{}\protected@file@percent }
|
\@writefile{toc}{\contentsline {section}{\numberline {1}Goals and Outcomes}{1}{}\protected@file@percent }
|
||||||
\citation{NUREG-0899,10CFR50.34}
|
\citation{NUREG-0899,10CFR50.34}
|
||||||
\citation{10CFR55.59}
|
\citation{10CFR55.59}
|
||||||
@ -13,33 +14,36 @@
|
|||||||
\citation{WNA2020}
|
\citation{WNA2020}
|
||||||
\citation{hogberg_root_2013}
|
\citation{hogberg_root_2013}
|
||||||
\citation{zhang_analysis_2025}
|
\citation{zhang_analysis_2025}
|
||||||
\@writefile{toc}{\contentsline {subsection}{\numberline {2.2}Human Factors in Nuclear Accidents}{3}{}\protected@file@percent }
|
|
||||||
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|
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|
||||||
|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
\citation{baier_principles_2008}
|
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|
||||||
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|
\citation{meyer_strix_2018,jacobs_reactive_2024}
|
||||||
\citation{a}
|
|
||||||
\citation{branicky_multiple_1998}
|
\citation{branicky_multiple_1998}
|
||||||
\citation{branicky_multiple_1998}
|
\citation{branicky_multiple_1998}
|
||||||
\citation{bansal_hamilton-jacobi_2017,guernic_reachability_2009}
|
\citation{bansal_hamilton-jacobi_2017,guernic_reachability_2009}
|
||||||
\citation{frehse_spaceex_2011,mitchell_time-dependent_2005}
|
\citation{frehse_spaceex_2011,mitchell_time-dependent_2005}
|
||||||
\citation{prajna_safety_2004}
|
\citation{prajna_safety_2004}
|
||||||
\@writefile{toc}{\contentsline {section}{\numberline {4}Metrics for Success}{10}{}\protected@file@percent }
|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
|
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|
||||||
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|
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|
||||||
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|
||||||
|
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|
||||||
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|
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|
||||||
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|
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|
||||||
\bibcite{NUREG-0899}{1}
|
\bibcite{NUREG-0899}{1}
|
||||||
@ -59,7 +63,7 @@
|
|||||||
\bibcite{baier_principles_2008}{15}
|
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|
||||||
\bibcite{meyer_strix_2018}{16}
|
\bibcite{meyer_strix_2018}{16}
|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
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|
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|
||||||
@ -68,41 +72,28 @@
|
|||||||
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|
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|
||||||
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||||||
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|
||||||
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|
||||||
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||||||
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|
||||||
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|
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||||||
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||||||
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||||||
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||||||
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||||||
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\contentsline {section}{Contents}{ii}{}%
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\contentsline {section}{\numberline {1}Goals and Outcomes}{1}{}%
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\contentsline {section}{\numberline {2}State of the Art and Limits of Current Practice}{2}{}%
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\contentsline {subsection}{\numberline {2.1}Current Reactor Procedures and Operation}{2}{}%
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\contentsline {subsection}{\numberline {2.2}Human Factors in Nuclear Accidents}{3}{}%
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\contentsline {subsection}{\numberline {2.3}HARDENS and Formal Methods}{4}{}%
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\contentsline {section}{\numberline {3}Research Approach}{5}{}%
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\contentsline {section}{\numberline {4}Metrics for Success}{9}{}%
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\contentsline {paragraph}{TRL 3 \textit {Critical Function and Proof of Concept}}{10}{}%
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\contentsline {paragraph}{TRL 4 \textit {Laboratory Testing of Integrated Components}}{10}{}%
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\contentsline {paragraph}{TRL 5 \textit {Laboratory Testing in Relevant Environment}}{10}{}%
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\contentsline {section}{\numberline {5}Risks and Contingencies}{11}{}%
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\contentsline {subsection}{\numberline {5.1}Computational Tractability of Synthesis}{11}{}%
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\contentsline {section}{\numberline {6}Broader Impacts}{13}{}%
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\contentsline {section}{\numberline {7}Schedule, Milestones, and Deliverables}{14}{}%
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\contentsline {subsection}{\numberline {7.1}Milestones and Deliverables}{15}{}%
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\contentsline {section}{References}{16}{}%
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\contentsline {section}{\numberline {8}Budget and Budget Justification}{I}{}%
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\contentsline {subsection}{\numberline {8.1}Budget Summary}{I}{}%
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\contentsline {subsection}{\numberline {8.2}Budget Justification}{II}{}%
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\contentsline {subsubsection}{\numberline {8.2.1}Senior Personnel}{II}{}%
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\contentsline {paragraph}{Faculty Advisor}{II}{}%
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\contentsline {subsubsection}{\numberline {8.2.2}Other Personnel}{II}{}%
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\contentsline {paragraph}{Graduate Research Assistant (Principal Investigator)}{II}{}%
|
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\contentsline {subsubsection}{\numberline {8.2.3}Fringe Benefits}{II}{}%
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\contentsline {paragraph}{Faculty Fringe Benefits}{II}{}%
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\contentsline {paragraph}{Graduate Research Assistant Fringe Benefits}{II}{}%
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\contentsline {subsubsection}{\numberline {8.2.4}Travel}{II}{}%
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\contentsline {paragraph}{Conference Travel (\$4,000 per year)}{II}{}%
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\contentsline {paragraph}{Industry Collaboration Visits (\$1,500 per year)}{II}{}%
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\contentsline {subsubsection}{\numberline {8.2.5}Other Direct Costs}{II}{}%
|
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\contentsline {paragraph}{Materials and Supplies}{II}{}%
|
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\contentsline {paragraph}{Publication Costs}{II}{}%
|
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\contentsline {paragraph}{Computing and Cloud Services}{III}{}%
|
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\contentsline {subsubsection}{\numberline {8.2.6}H. Indirect Costs (Facilities \& Administrative)}{III}{}%
|
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\contentsline {section}{\numberline {9}Supplemental Sections}{III}{}%
|
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|
\contentsline {subsection}{\numberline {9.1}Biosketch}{III}{}%
|
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\contentsline {subsection}{\numberline {9.2}Data Management Plan}{VI}{}%
|
||||||
|
\contentsline {subsection}{\numberline {9.3}Facilities}{X}{}%
|
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