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\section{State of the Art and Limits of Current Practice}
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The principal aim of this research is to create autonomous reactor control
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systems that are tractably safe. To understand what is being automated, we must
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first understand how nuclear reactors are operated today. This section examines
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reactor operators and the operating procedures we aim to leverage, then
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investigates limitations of human-based operation, and concludes with current
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formal methods approaches to reactor control systems.
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\subsection{Current Reactor Procedures and Operation}
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Nuclear plant procedures exist in a hierarchy: normal operating procedures for
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routine operations, abnormal operating procedures for off-normal conditions,
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Emergency Operating Procedures (EOPs) for design-basis accidents, Severe
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Accident Management Guidelines (SAMGs) for beyond-design-basis events, and
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Extensive Damage Mitigation Guidelines (EDMGs) for catastrophic damage
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scenarios. These procedures must comply with 10 CFR 50.34(b)(6)(ii) and are
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developed using guidance from NUREG-0900~\cite{NUREG-0899, 10CFR50.34}, but their
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development relies fundamentally on expert judgment and simulator validation
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rather than formal verification. Procedures undergo technical evaluation,
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simulator validation testing, and biennial review as part of operator
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requalification under 10 CFR 55.59~\cite{10CFR55.59}. Despite this rigor,
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procedures fundamentally lack formal verification of key safety properties. No
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mathematical proof exists that procedures cover all possible plant states, that
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required actions can be completed within available timeframes, or that
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transitions between procedure sets maintain safety invariants.
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\textbf{LIMITATION:} \textit{Procedures lack formal verification of correctness
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and completeness.} Current procedure development relies on expert judgment and
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simulator validation. No mathematical proof exists that procedures cover all
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possible plant states, that required actions can be completed within available
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timeframes, or that transitions between procedure sets maintain safety
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invariants. Paper-based procedures cannot ensure correct application, and even
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computer-based procedure systems lack the formal guarantees that automated
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reasoning could provide.
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Nuclear plants operate with multiple control modes: automatic control, where the
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reactor control system maintains target parameters through continuous reactivity
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adjustment; manual control, where operators directly manipulate the reactor; and
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various intermediate modes. In typical pressurized water reactor operation, the
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reactor control system automatically maintains a floating average temperature
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and compensates for power demand changes through reactivity feedback loops
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alone. Safety systems, by contrast, operate with implemented automation. Reactor
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Protection Systems trip automatically on safety signals with millisecond
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response times, and engineered safety features actuate automatically on accident
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signals without operator action required.
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The division between automated and human-controlled functions reveals the
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fundamental challenge of hybrid control. Highly automated systems handle reactor
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protection---automatic trips on safety parameters, emergency core cooling
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actuation, containment isolation, and basic process
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control~\cite{WRPS.Description, gentillon_westinghouse_1999}. Human operators,
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however, retain control of strategic decision-making: power level changes,
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startup/shutdown sequences, mode transitions, and procedure implementation.
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\subsection{Human Factors in Nuclear Accidents}
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Current-generation nuclear power plants employ over 3,600 active NRC-licensed
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reactor operators in the United States~\cite{operator_statistics}. These
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operators divide into Reactor Operators (ROs), who manipulate reactor controls,
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and Senior Reactor Operators (SROs), who direct plant operations and serve as
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shift supervisors~\cite{10CFR55}. Staffing typically requires at least two ROs
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and one SRO for current-generation units~\cite{10CFR50.54}. Becoming a reactor
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operator requires several years of training.
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The persistent role of human error in nuclear safety incidents---despite decades
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of improvements in training and procedures---provides the most compelling
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motivation for formal automated control with mathematical safety guarantees.
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Operators hold legal authority under 10 CFR Part 55 to make critical decisions,
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including departing from normal regulations during emergencies. The Three Mile
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Island (TMI) accident demonstrated how a combination of personnel error, design
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deficiencies, and component failures led to partial meltdown when operators
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misread confusing and contradictory readings and shut off the emergency water
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system~\cite{Kemeny1979}. The President's Commission on TMI identified a
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fundamental ambiguity: placing responsibility for safe power plant operations on
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the licensee without formal verification that operators can fulfill this
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responsibility does not guarantee safety. This tension between operational
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flexibility and safety assurance remains unresolved: the person responsible for
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reactor safety is often the root cause of failures.
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Multiple independent analyses converge on a striking statistic: 70--80\% of
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nuclear power plant events are attributed to human error, versus approximately
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20\% to equipment failures~\cite{WNA2020}. More significantly, the root cause of
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all severe accidents at nuclear power plants---Three Mile Island, Chernobyl, and
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Fukushima Daiichi---has been identified as poor safety management and safety
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culture: primarily human factors~\cite{hogberg_root_2013}. A detailed analysis
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of 190 events at Chinese nuclear power plants from
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2007--2020~\cite{zhang_analysis_2025} found that 53\% of events involved active
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errors, while 92\% were associated with latent errors---organizational and
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systemic weaknesses that create conditions for failure.
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\textbf{LIMITATION:} \textit{Human factors impose fundamental reliability limits
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that cannot be overcome through training alone.} The persistent human
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error contribution despite four decades of improvements demonstrates that these
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limitations are fundamental rather than a remediable part of human-driven control.
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\subsection{HARDENS and Formal Methods}
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The High Assurance Rigorous Digital Engineering for Nuclear Safety (HARDENS)
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project represents the most advanced application of formal methods to nuclear
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reactor control systems to date~\cite{Kiniry2024}.
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HARDENS aimed to address a fundamental dilemma: existing U.S. nuclear control
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rooms rely on analog technologies from the 1950s--60s. This technology is
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obsolete compared to modern control systems and incurs significant risk and
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cost. The NRC contracted Galois, a formal methods firm, to demonstrate that
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Model-Based Systems Engineering and formal methods could design, verify, and
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implement a complex protection system meeting regulatory criteria at a fraction
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of typical cost. The project delivered a Reactor Trip System (RTS)
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implementation with full traceability from NRC Request for Proposals and IEEE
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standards through formal architecture specifications to verified software.
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HARDENS employed formal methods tools and techniques across the verification
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hierarchy. High-level specifications used Lando, SysMLv2, and FRET (NASA Formal
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Requirements Elicitation Tool) to capture stakeholder requirements, domain
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engineering, certification requirements, and safety requirements. Requirements
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were analyzed for consistency, completeness, and realizability using SAT and SMT
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solvers. Executable formal models used Cryptol to create a behavioral model of
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the entire RTS, including all subsystems, components, and limited digital twin
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models of sensors, actuators, and compute infrastructure. Automatic code
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synthesis generated verifiable C implementations and SystemVerilog hardware
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implementations directly from Cryptol models---eliminating the traditional gap
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between specification and implementation where errors commonly arise.
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Despite its accomplishments, HARDENS has a fundamental limitation directly
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relevant to hybrid control synthesis: the project addressed only discrete
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digital control logic without modeling or verifying continuous reactor dynamics.
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The Reactor Trip System specification and verification covered discrete state
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transitions (trip/no-trip decisions), digital sensor input processing through
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discrete logic, and discrete actuation outputs (reactor trip commands). The
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project did not address continuous dynamics of nuclear reactor physics. Real
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reactor safety depends on the interaction between continuous
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processes---temperature, pressure, neutron flux---evolving in response to
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discrete control decisions. HARDENS verified the discrete controller in
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isolation but not the closed-loop hybrid system behavior.
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\textbf{LIMITATION:} \textit{HARDENS addressed discrete control logic without
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continuous dynamics or hybrid system verification.} Verifying discrete control
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logic alone provides no guarantee that the closed-loop system exhibits desired
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continuous behavior such as stability, convergence to setpoints, or maintained
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safety margins.
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HARDENS produced a demonstrator system at Technology Readiness Level 2--3
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(analytical proof of concept with laboratory breadboard validation) rather than
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a deployment-ready system validated through extended operational testing. The
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NRC Final Report explicitly notes~\cite{Kiniry2024} that all material is
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considered in development, not a finalized product, and that ``The demonstration
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of its technical soundness was to be at a level consistent with satisfaction of
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the current regulatory criteria, although with no explicit demonstration of how
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regulatory requirements are met.'' The project did not include deployment in
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actual nuclear facilities, testing with real reactor systems under operational
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conditions, side-by-side validation with operational analog RTS systems,
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systematic failure mode testing (radiation effects, electromagnetic
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interference, temperature extremes), NRC licensing review, or human factors
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validation with licensed operators in realistic control room scenarios.
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\textbf{LIMITATION:} \textit{HARDENS achieved TRL 2--3 without experimental
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validation.} While formal verification provides mathematical correctness
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guarantees for the implemented discrete logic, the gap between formal
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verification and actual system deployment involves myriad practical
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considerations: integration with legacy systems, long-term reliability
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under harsh environments, human-system interaction in realistic
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operational contexts, and regulatory acceptance of formal methods as
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primary assurance evidence.
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@ -1,285 +0,0 @@
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\section{Research Approach}
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This research will overcome the limitations of current practice to build
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high-assurance hybrid control systems for critical infrastructure. Building
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these systems with formal correctness guarantees requires three main thrusts:
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\begin{enumerate}
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\item Translate operating procedures and requirements into temporal logic
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formulae
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\item Create the discrete half of a hybrid controller using reactive synthesis
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\item Develop continuous controllers to operate between modes, and verify
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their correctness
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\end{enumerate}
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Commercial nuclear power operations remain manually controlled by human
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operators, yet the procedures they follow are highly prescriptive and
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well-documented. This suggests that human operators may not be entirely
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necessary given current technology. Written procedures and requirements are
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sufficiently detailed that they may be translatable into logical formulae with
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minimal effort. If successful, this approach enables automation of existing
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procedures without system reengineering. To formalize these procedures, we will
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use temporal logic, which captures system behaviors through temporal relations.
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The most efficient path for this translation is NASA's Formal Requirements
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Elicitation Tool (FRET). FRET employs a specialized requirements language called
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FRETish that restricts requirements to easily understood components while
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eliminating ambiguity~\cite{katis_capture_2022}. FRETish bridges natural language
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and mathematical specifications through a structured English-like syntax
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automatically translatable to temporal logic.
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FRET enforces this structure by requiring all requirements to contain six
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components: %CITE FRET MANUAL
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\begin{enumerate}
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\item Scope: \textit{What modes does this requirement apply to?}
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\item Condition: \textit{Scope plus additional specificity}
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\item Component: \textit{What system element does this requirement affect?}
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\item Shall
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\item Timing: \textit{When does the response occur?}
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\item Response: \textit{What action should be taken?}
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\end{enumerate}
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FRET provides functionality to check system \textit{realizability}. Realizability
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analysis determines whether written requirements are complete by examining the
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six structural components. Complete requirements neither conflict with one
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another nor leave any behavior undefined. Systems that are not realizable from
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their procedure definitions and design requirements present problems beyond
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autonomous control implementation. Such systems contain behavioral
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inconsistencies---the physical equivalent of software bugs. Using FRET during
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autonomous controller development allows systematic identification and
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resolution of these errors.
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The second category of realizability issues involves undefined behaviors
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typically left to human judgment during operations. This ambiguity is
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undesirable for high-assurance systems, since even well-trained humans remain
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prone to errors. Addressing these specification gaps in FRET during development
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yields controllers free from these vulnerabilities.
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FRET exports requirements in temporal logic format compatible with reactive
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synthesis tools. Linear Temporal Logic (LTL) builds upon modal logic's
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foundational operators for necessity ($\Box$, ``box'') and possibility
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($\Diamond$, ``diamond''), extending them to reason about temporal
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behavior~\cite{baier_principles_2008}. The box operator $\Box$ expresses that a
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property holds at all future times (necessarily always), while the diamond
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operator $\Diamond$ expresses that a property holds at some future time
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(possibly eventually). These are complemented by the next operator ($X$) for the
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immediate successor state and the until operator ($U$) for expressing
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persistence conditions.
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Consider a nuclear reactor SCRAM requirement expressed in natural language:
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\textit{``If a high temperature alarm triggers, control rods must immediately
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insert and remain inserted until operator reset.''} This plain language
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requirement can be translated into a rigorous logical specification:
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\begin{equation}
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\Box(HighTemp \rightarrow X(RodsInserted \wedge (\neg
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RodsWithdrawn\ U\ OperatorReset)))
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\end{equation}
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This specification precisely captures the temporal relationship between the
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alarm condition, the required response, and the persistence requirement. The
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necessity operator $\Box$ ensures this safety property holds throughout all
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possible future system executions, while the next operator $X$ enforces
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immediate response. The until operator $U$ maintains the state constraint until
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the reset condition occurs. No ambiguity exists in this scenario because all
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decisions are represented by discrete variables. Formulating operating rules in
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this logic enforces finite, correct operation.
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Reactive synthesis is an active research field focused on generating discrete
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controllers from temporal logic specifications. The term ``reactive'' indicates
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that the system responds to environmental inputs to produce control outputs.
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These synthesized systems are finite, with each node representing a unique
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discrete state. The connections between nodes, called \textit{state
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transitions}, specify the conditions under which the discrete controller moves
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from state to state. This complete mapping of possible states and transitions
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constitutes a \textit{discrete automaton}. Discrete automata can be represented
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graphically as nodes (discrete states) with edges indicating transitions between
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them. From the automaton graph, one can fully describe discrete system dynamics
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and develop intuitive understanding of system behavior. Hybrid systems naturally
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exhibit discrete behavior amenable to formal analysis through these finite state
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representations.
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We will employ state-of-the-art reactive synthesis tools, particularly Strix,
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which has demonstrated superior performance in the Reactive Synthesis
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Competition (SYNTCOMP) through efficient parity game solving
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algorithms~\cite{meyer_strix_2018,jacobs_reactive_2024}. Strix translates linear
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temporal logic specifications into deterministic automata automatically while
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maximizing generated automata quality. Once constructed, the automaton can be
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implemented using standard programming control flow constructs. The graphical
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representation enables inspection and facilitates communication with controls
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programmers who lack formal methods expertise.
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We will use discrete automata to represent the switching behavior of our hybrid
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system. This approach yields an important theoretical guarantee: because the
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discrete automaton is synthesized entirely through automated tools from design
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requirements and operating procedures, the automaton---and therefore our hybrid
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switching behavior---is \textit{correct by construction}. Correctness of the
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switching controller is paramount. Mode switching represents the primary
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responsibility of human operators in control rooms today. Human operators
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possess the advantage of real-time judgment: when mistakes occur, they can
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correct them dynamically with capabilities extending beyond written procedures.
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Autonomous control lacks this adaptive advantage. Instead, autonomous
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controllers replacing human operators must not make switching errors between
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continuous modes. Synthesizing controllers from logical specifications with
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guaranteed correctness eliminates the possibility of switching errors.
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While discrete system components will be synthesized with correctness
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guarantees, they represent only half of the complete system. Autonomous
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controllers like those we are developing exhibit continuous dynamics within
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discrete states. These systems, called hybrid systems, combine continuous
|
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dynamics (flows) with discrete transitions (jumps). These dynamics can be
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formally expressed as~\cite{branicky_multiple_1998}:
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\begin{equation}
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\dot{x}(t) = f(x(t),q(t),u(t))
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\end{equation}
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\begin{equation}
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q(k+1) = \nu(x(k),q(k),u(k))
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\end{equation}
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Here, $f(\cdot)$ defines the continuous dynamics while $\nu(\cdot)$ governs
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discrete transitions. The continuous states $x$, discrete state $q$, and
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control input $u$ interact to produce hybrid behavior. The discrete state $q$
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defines which continuous dynamics mode is currently active. Our focus centers
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on continuous autonomous hybrid systems, where continuous states remain
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unchanged during jumps---a property naturally exhibited by physical systems. For
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example, a nuclear reactor switching from warm-up to load-following control
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cannot instantaneously change its temperature or control rod position, but can
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instantaneously change control laws.
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The approach described for producing discrete automata yields physics-agnostic
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||||||
specifications representing only half of a complete hybrid autonomous
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||||||
controller. These automata alone cannot define the full behavior of the control
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|
||||||
systems we aim to construct. The continuous modes will be developed after
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||||||
discrete automaton construction, leveraging the automaton structure and
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||||||
transitions to design multiple smaller, specialized continuous controllers.
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||||||
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Notably, translation into linear temporal logic creates barriers between
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different control modes. Switching from one mode to another becomes a discrete
|
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boolean variable. \(RodsInserted\) or \(HighTemp\) in the temporal
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|
||||||
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.
|
|
||||||
@ -1,578 +0,0 @@
|
|||||||
\section{Research Approach}
|
|
||||||
\iffalse
|
|
||||||
|
|
||||||
HACS: hybrid autonomous control system
|
|
||||||
HAHACS: High-Assurance Hybrid AUtonomous Control System
|
|
||||||
|
|
||||||
|
|
||||||
The research approach here needs to clearly outline the solution the the problem
|
|
||||||
and identify the actions taken that will advance knowledge and solve the
|
|
||||||
problem.
|
|
||||||
|
|
||||||
First, what is the problem?
|
|
||||||
|
|
||||||
\textit{
|
|
||||||
|
|
||||||
Inhibition to adopt hybrid autonomous control in critical infrastructure is
|
|
||||||
rooted in safety concerns of system stability. Without a human in the loop
|
|
||||||
with general intelligence, HACS have not been trusted where failure modes can
|
|
||||||
be unique and novel.
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
So, what's the solution?
|
|
||||||
|
|
||||||
\textit{
|
|
||||||
|
|
||||||
This research approach develops a methodology to build HACS that are provably
|
|
||||||
safe. This methodology builds on existing technologies, and unifies different
|
|
||||||
research thrusts to build a complete hybrid control system. To do this, the
|
|
||||||
problem of a HAHCS is broken into three distinct pieces:
|
|
||||||
|
|
||||||
\begin{enumerate}
|
|
||||||
|
|
||||||
\item System specification: properties of the HAHaCS such as transition
|
|
||||||
between control modes and system invariants are specified using a formal
|
|
||||||
methods tool.
|
|
||||||
- This provides exact behavior
|
|
||||||
- allows realizabillity checking of controller specs. Can a controller
|
|
||||||
actually be built from these specs?
|
|
||||||
- ?
|
|
||||||
- ?
|
|
||||||
|
|
||||||
\item Discrete Behavior Synthesis: The discrete component of the controller
|
|
||||||
is synthesized directly from system specifications using reactive
|
|
||||||
synthesis.
|
|
||||||
- This ELIMINATES wholesale the possibility of introducing logical bugs
|
|
||||||
in the creation of the strategic part of the HAHCS. Critical decisions
|
|
||||||
that are normally made by a human are automated directly from the
|
|
||||||
formal specifications.
|
|
||||||
- This does two critical things:
|
|
||||||
- It makes the creation of the controller tractable. The reasons the
|
|
||||||
controller changes between modes acn be traced back to the
|
|
||||||
specification (and thus any requirements), which is a trace for
|
|
||||||
liability and justification of system behavior
|
|
||||||
- Discrete control decisions made by humans are reliant on the human
|
|
||||||
operator operating correctly. Humans are intrinsically probabalistic
|
|
||||||
creatures who cannot eliminate human error. By defining the behavior
|
|
||||||
of this system using temporal logics and synthesizing the controller
|
|
||||||
using deterministic algorithims, we are assured that strategic
|
|
||||||
decisions will always be made as according to operating procedures.
|
|
||||||
|
|
||||||
\item Continuous Behavior Synthesis and Verification: The continuous
|
|
||||||
components of the controller are built using existing dynamics and control
|
|
||||||
theory but then verified using reachability and barrier certificats.
|
|
||||||
- It's very challenging (nigh impossible) to say for certain how to
|
|
||||||
build any continuous control mode. That is honestly going to be have to
|
|
||||||
left to the specific control system and its objectives. It's not really
|
|
||||||
the point of this PhD to say how to do that. For that reason, I'm going
|
|
||||||
to assume that controllers between modes are generally possible to
|
|
||||||
build. That is to say that there exists a controller that can transition
|
|
||||||
between modes, but it is a human hunt to find it.
|
|
||||||
- To check if a candidate controller does transition between discrete
|
|
||||||
modes, we do two things:
|
|
||||||
- Check invariants using reachability. Specifications will require
|
|
||||||
that control modes transiiton from one mode to the next, where
|
|
||||||
appropriate. When this is the case, these invariants are extracted to
|
|
||||||
be checked using reachability. The control mode is given the possible
|
|
||||||
entry conditions of the 'entry' mode, and the possible 'exit' states
|
|
||||||
are analyzed. A cont. controller passes this reachability test if
|
|
||||||
there is no reachable state that is not at the exit condition of the
|
|
||||||
state transition.
|
|
||||||
|
|
||||||
--- This needs flushed out more. I think this can really be clarified
|
|
||||||
using entry and exit conditions of Mealy machines. The continuous
|
|
||||||
system IS the transition, and the reachabililty test is saying whether
|
|
||||||
or not the physical system actually satisfies the entry and exit
|
|
||||||
conditions.
|
|
||||||
|
|
||||||
- Then, for systems that need to STAY within one mode, we will use
|
|
||||||
barrier certificates. These can let us define a continuous state
|
|
||||||
boundary, and define for a discrete controller state, the total
|
|
||||||
controller will NOT leave the continuous boundary.
|
|
||||||
|
|
||||||
- One thing that must be considered is the idea that this analysis is
|
|
||||||
predicated on the physical system being correct to the model. If this
|
|
||||||
isn't true, we must define continuous modes that catch failure states.
|
|
||||||
If transition invariants are violated, we must shut down the system, and
|
|
||||||
build safety oriented control modes that we can be sure with a much
|
|
||||||
broader set of entry conditions will safely shut down the plant.
|
|
||||||
|
|
||||||
-- Q for dan: is it critical to really have software to namedrop or is it
|
|
||||||
better to stay amorphous on the technology? Iirc Manyu did a little bit of
|
|
||||||
both.
|
|
||||||
|
|
||||||
\end{enumerate}
|
|
||||||
|
|
||||||
|
|
||||||
What's the intellectual merit?
|
|
||||||
|
|
||||||
\textit{
|
|
||||||
|
|
||||||
There is no outstanding way to build HAHACS. This methodology provides a
|
|
||||||
basis for systems engineers to think about the components of a HAHACS as
|
|
||||||
interlocking pieces whos verification interlinks into a broader system.
|
|
||||||
This will also motivate the adoption of temporal logic to define autonomous
|
|
||||||
control systems, by allowing a close connection and tracability between
|
|
||||||
requirements from regulations to system specifications.
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
}
|
|
||||||
|
|
||||||
Some thoughts on invariants, and how they fit here: There are several types of
|
|
||||||
safety invariants that HAHACS might have.
|
|
||||||
|
|
||||||
1. Conditions that initiate a switch between control modes (reactiive synthesis
|
|
||||||
relevant)
|
|
||||||
|
|
||||||
2. Invariants about the stability of discrete states (barrier certificates)
|
|
||||||
|
|
||||||
3. Invariants ensuring the transition between discrete states (reachability)
|
|
||||||
|
|
||||||
4. Invariants about the timeliness of discrete transitions (??? Reachability?)
|
|
||||||
|
|
||||||
How do we reason about all of these invariants. Well, fundamentally they can
|
|
||||||
all be reasoned about with temporal logic statements. Using next and eventually
|
|
||||||
operators, we can get to the fundamental behavior of all of these modes. What's
|
|
||||||
challenging is the fact that we ensure that all of these specifications are
|
|
||||||
validated differs between the type of invariant. This is really the beauty of
|
|
||||||
this approach, and the intellectual merit. This proposal provides a way for
|
|
||||||
hybrid control systems to be verified for autonomous control systems by
|
|
||||||
diversifying the way that the invariants are checked.
|
|
||||||
|
|
||||||
Reactive synthesis helps us build discrete controllers using specifications
|
|
||||||
that have conditons that don't depend on time. These invariants generally are
|
|
||||||
strategic decisions, such as changing between operating modes, initiating power
|
|
||||||
level changes, or perhaps doing a refueling or shutdown routine. These
|
|
||||||
specifications are able to be nearly directly drawn from operating procedures,
|
|
||||||
and should be closely tied to instructions that would be used for human
|
|
||||||
operators. They have checkpoints for the continuous system in between different
|
|
||||||
control implements. An example is, raise power at a certain rate while ensure
|
|
||||||
temperature remains between certain bounds. These conditions are physical
|
|
||||||
states, but they are a binary result. The condition is really binary, desipite
|
|
||||||
perhaps having units of celsius or %power. When we build discrete controllers
|
|
||||||
from these specifications, we get the validation of the controller of these
|
|
||||||
specs for free by nature of reactive synthesis tools. We get direct
|
|
||||||
traceability from the operating procedure to the discrete controller
|
|
||||||
implementation with minimal human effort.
|
|
||||||
|
|
||||||
That being said, there are no free lunches here. Ultimately, we're controlling
|
|
||||||
physical systems, and while we can automate the controller building between
|
|
||||||
stratgic objectives, it is not trivial to do so for the controller of the
|
|
||||||
physical process. These controllers are going to have to be built manually,
|
|
||||||
with the continuous dynamics of the system in mind. Helpfully, if
|
|
||||||
specifications are complete first, one can obtain discrete controller before
|
|
||||||
building physical controllers. The result of this is a simplification of
|
|
||||||
controller design, becuase the operational goals of each continuous controller
|
|
||||||
is clearly outlined by the invariants that define the goal of each discrete
|
|
||||||
mode. While for reactive synthesis purposes conditions such as a certain
|
|
||||||
temperature being reached or power level attained are binary variables, the
|
|
||||||
continuous physical meaning becomes important in the design and analysis of the
|
|
||||||
physical controllers. The continuous value of these conditions becomes the goal
|
|
||||||
of the continuous controller design, while also providing a basis to check
|
|
||||||
controller performance.
|
|
||||||
|
|
||||||
To check continuous controllers are valid, we can split continuous controller
|
|
||||||
objectives into two types. First, we have continuous controllers that are
|
|
||||||
designed to move the plant between two different discrete modes. These will be
|
|
||||||
called 'transitory' controllers, because their entire purpose is to transition
|
|
||||||
the plant betweeen between discrete control modes. Because of the specification
|
|
||||||
of the hybrid control system a priori, we will have defined what the invariants
|
|
||||||
of these transitions are in continuous state space. Then, once a continuosu
|
|
||||||
controller design is developed, it can be validated using reachability
|
|
||||||
analysis. The input set for the analysis is the possible states that enter this
|
|
||||||
transitory mode, while the reachable states must be entirely contained within
|
|
||||||
the exit invariant for the controller to pass. At the time of writing this
|
|
||||||
proposal, it is not clear what the most efficient way to obetain this
|
|
||||||
continuous controller is, but is generally beyond the scope of this work. It is
|
|
||||||
assumed that they generally won't be so difficult to find for most systems, as
|
|
||||||
the refinement of the discrete controller should simplify the control
|
|
||||||
objectives of the physical controllers significantly.
|
|
||||||
|
|
||||||
The second type of continuous controller that may be utilized in a HAHAHCS is a
|
|
||||||
controller that tries to maintaine a continuous steady state, such that no
|
|
||||||
discrete transitions are triggered. Reachability on these systems may not prove
|
|
||||||
a prudent approach to validating this behavior for a candidate continuous
|
|
||||||
controller, and instead, barrier certificates must be used. Barrier
|
|
||||||
certificates analyze the dynamics of the system to say whether or not flux
|
|
||||||
across a given boudnary exists. That is to say that they evaluate whether or
|
|
||||||
not there is a trajectory or not that leaves a given boundary. This definition
|
|
||||||
is exactly what defines the validity of a stabilizing continuous control mode.
|
|
||||||
Once again, because the design of the discrete controller defines careful
|
|
||||||
boundaries in continuous state space, the barrier is known a priori of which we
|
|
||||||
must satisfy this condition. This will eliminate the search for such a barrier,
|
|
||||||
and minimze complicatoin in validating stabilizing continuous control modes.
|
|
||||||
|
|
||||||
Finally, consideration must be paid for when errors occur. The validation of
|
|
||||||
these continuous control modes hinges upon having an assumption ofcorrect
|
|
||||||
model, which in the case of a mechanical failure will almsot certainly be
|
|
||||||
invalidated. Special continuous controllers for these conditions must be
|
|
||||||
created, called 'explusory' control modes. These controllers will be
|
|
||||||
responsible for ensuring safety in case of failure, and will be designed with
|
|
||||||
reachability, but in this case, additional allocation for the allowing of
|
|
||||||
physical parameters will be allowed in the analysis. Traditional safety
|
|
||||||
analysis will also be used to identify potential failure modes, and the
|
|
||||||
modelling of their worst case dynamics. The HAHCS will be able to idenfity why
|
|
||||||
such a fault occors because an discrte boundary condition will be violated by
|
|
||||||
the continuous physical controller. That is to say, since we will have
|
|
||||||
validated the continuous control modes using reachability and barrier
|
|
||||||
certificates a priori, we will know with certainty that the only room for
|
|
||||||
dynamics to change is a shift in the plant dynamics, not that of the proven
|
|
||||||
controller.
|
|
||||||
|
|
||||||
\fi
|
|
||||||
|
|
||||||
%%%%%%%%%% TABLESETTING
|
|
||||||
|
|
||||||
% what is a hybrid system really for this proposal
|
|
||||||
% Define: A hybrid system with continuous state space X ⊆ ℝⁿ and discrete modes Q = {q₁, q₂, ..., qₘ}
|
|
||||||
% Each discrete mode qᵢ has an associated continuous state region Xᵢ ⊆ X
|
|
||||||
% The discrete controller manages transitions between modes based on continuous state thresholds
|
|
||||||
|
|
||||||
% what are requirements, anyways?
|
|
||||||
|
|
||||||
% why do we care about defining the whole hybrid system into requirements?
|
|
||||||
|
|
||||||
% How do different requirements line up into different parts of the system?
|
|
||||||
% (operational vs strategic requirements and their relevance to different parts
|
|
||||||
% of our system)
|
|
||||||
|
|
||||||
Autonomous control systems are fundamentally different from automatic control
|
|
||||||
systems. The difference between these systems is the level at which
|
|
||||||
they operate. Automatic control systems are purely operational systems,
|
|
||||||
|
|
||||||
To build a high-assurance hybrid autonomous control system (HAHACS), a
|
|
||||||
mathematical description of the system must be established. This work will make
|
|
||||||
use of automata theory while including logical statements and control theory.
|
|
||||||
The nomenclature and lexicon between these fields is far from homogenous, and
|
|
||||||
the reviewer of this proposal is not expected to be an expert in all fields
|
|
||||||
simultaneously. To present the research ideas as clearly as possible in this
|
|
||||||
section, the following syntax is explained.
|
|
||||||
|
|
||||||
A hybrid system is a dynamical system that has both continuous and discrete
|
|
||||||
states. The specific type of system discussed in this proposal are continuous
|
|
||||||
autonomous hybrid systems. This means that these systems a) do not have
|
|
||||||
external input \footnote{This is not strictly true in our case because we allow
|
|
||||||
strategic inputs. For example, a remote powerplant may receive a start-up or
|
|
||||||
shutdown command from a different location, but only this binary high level
|
|
||||||
input is a strategic input.} and b) continuous states do not change
|
|
||||||
instantaneously when discrete states change. For our systems of interest, the
|
|
||||||
continuous states are physical, and are always Lipschitz continuous. This
|
|
||||||
nomenclature is heavily borrowed from \cite{HANDBOOK ON HYBRID SYSTEMS CONTROL},
|
|
||||||
but is redefined here for convenience:
|
|
||||||
|
|
||||||
\begin{equation}
|
|
||||||
H = (\mathcal{Q}, \mathcal{X}, \mathbf{f}, Init, \mathcal{G}, \mathcal{R}, Inv)
|
|
||||||
\end{equation}
|
|
||||||
|
|
||||||
where:
|
|
||||||
|
|
||||||
\begin{itemize}
|
|
||||||
\item \( \mathcal{Q}\): is the discrete states of the system
|
|
||||||
\item \( \mathcal{X}\): is the continuous states of the system
|
|
||||||
\item \(\mathbf{f}: \mathcal{Q} \times \mathbb{R} \rightarrow \mathbb{R} \), where
|
|
||||||
\(\mathbf{f}_i\) is a
|
|
||||||
vector field that defines the continuous dynamics for each \(q_i\)
|
|
||||||
\item \(Init\): the initial states of \(q\) and \(x\)
|
|
||||||
\item \( G\): guard
|
|
||||||
conditions that define when discrete state transitions occur
|
|
||||||
\item \(\delta: \mathcal{Q} \times G \rightarrow \mathcal{Q}\), are the
|
|
||||||
discrete state transition functions
|
|
||||||
\item \mathcal{R}: Reset maps that define state 'jumps'
|
|
||||||
\item \(Inv\): Safety invariants on the continuous dynamics
|
|
||||||
\end{itemize}
|
|
||||||
|
|
||||||
The creation of a HAHACS essentially boils down to the creation of such a tuple
|
|
||||||
where there are proof artifacts that the intended behavior of the control system
|
|
||||||
are satisfied by the actual implementation of the control systems. But to create
|
|
||||||
such a HAHACS, we must first completely describe its behavior.
|
|
||||||
|
|
||||||
%% Brief discussion on what each part of this tuple means for us
|
|
||||||
|
|
||||||
\subsection{System Requirement and Specifications}
|
|
||||||
|
|
||||||
Temporal logic is a powerful set of semantics to build systems that can have
|
|
||||||
complex but deterministic behavior.
|
|
||||||
|
|
||||||
|
|
||||||
%%%%%%%%%%% Building discrete controllers
|
|
||||||
|
|
||||||
% Buildout of requirements from written procedures (this is easy for critical
|
|
||||||
% systems - we already have the requirements)
|
|
||||||
|
|
||||||
% What happens to the invariants that specify a continuous space? Save em for
|
|
||||||
% later. Here they become binary for our purposes
|
|
||||||
% KEY POINT: We don't IMPOSE discrete abstraction - we FORMALIZE existing practice
|
|
||||||
% Operating procedures (esp. nuclear) already define go/no-go conditions as discrete predicates
|
|
||||||
% e.g., "WHEN coolant temp >315°C AND pressurizer level 30-60% THEN MAY initiate load following"
|
|
||||||
% These thresholds come from design-basis safety analysis, validated over decades
|
|
||||||
% Our methodology assumes this domain knowledge exists and provides formalization framework
|
|
||||||
% The discrete predicates p₁, p₂, ... are Boolean functions over continuous state: pᵢ: X → {true, false}
|
|
||||||
% Q: How do we rigorously set thresholds for continuous→discrete abstraction?
|
|
||||||
% Q: How do we handle hysteresis to prevent mode chattering near boundaries?
|
|
||||||
% Q: How do we account for sensor noise and measurement uncertainty?
|
|
||||||
% Q: How do we handle numerical precision issues when creating discrete automata? (relates to task 36)
|
|
||||||
|
|
||||||
% Discrete controller implementation can be realized with reactive synthesis.
|
|
||||||
% LTL specs to automata
|
|
||||||
|
|
||||||
% talk a bit about tools here like FRET. Talk about previous attempts.
|
|
||||||
|
|
||||||
\begin{figure}[htbp]
|
|
||||||
\centering
|
|
||||||
\framebox[0.8\textwidth]{\rule{0pt}{3cm}\textit{Strategic, operational,
|
|
||||||
tactical placeholder}}
|
|
||||||
\caption{Breakdown of control scope}
|
|
||||||
\label{fig:strat_op_tact}
|
|
||||||
\end{figure}
|
|
||||||
|
|
||||||
|
|
||||||
Human control of nuclear power can be divided into three different scopes:
|
|
||||||
strategic, operational, and tactical. Strategic control is the high-level and
|
|
||||||
long term decision making for the plant. This level has objectives that are
|
|
||||||
complex and economic in scale, such as managing labor needs and supply chains to
|
|
||||||
optimize sheduled maintenence and downtime. The time scale on this level of
|
|
||||||
control is long, often over months or years. The lowest level of control is the
|
|
||||||
tactical level. This is the individual control of pumps, turbines, and
|
|
||||||
chemistry of the plant. This level of control has already been somewhat
|
|
||||||
automated today in nuclear power, and is generally considered 'automatic
|
|
||||||
control' when autonomous. These controls are almost always continuous systems,
|
|
||||||
and have a direct impact on the physical state of the plant. Tactical control
|
|
||||||
objectives are things like maintaining a pressurizer level, maintaining a
|
|
||||||
certain core temperature, or adjusting reactivity with a chemical shim. The level of
|
|
||||||
control linking these two levels, then, is the operational control scope.
|
|
||||||
Operational control is the primary responsibility of human operators today.
|
|
||||||
Operational control takes the current strategic objective, and implements
|
|
||||||
tactical control objectives to drive the plant towards strategic goals. In this
|
|
||||||
way, it is the bridge between high and low level goals. A strategic goal may be
|
|
||||||
to perform refueling at a certain time, while the tactical level of the plant
|
|
||||||
currently is focused on mainting a certain core temperature. The operational
|
|
||||||
level is what issues the shutdown procedure of the plant, using several smaller
|
|
||||||
tactical goals along the way to achieve this objective. Thus, the combination of
|
|
||||||
the operational and tactical level of the plant fundamentally forms a hybrid
|
|
||||||
controller. The tactical level is the continuous evolution of the plant
|
|
||||||
according to the control input and control law, while the operational level is a
|
|
||||||
discrete state evolution which determines the tactical control law to reach
|
|
||||||
different operational states.
|
|
||||||
|
|
||||||
This operational control level is the main reason for the requirement of human
|
|
||||||
opeartors in nuclear control today. The hybrid nature of this control system
|
|
||||||
makes it difficult to prove that a controller will perform according to the
|
|
||||||
strategic requirements, as the infrastructure to build hybrid systems today
|
|
||||||
dooes not exist. Humans have been used for this layer because the general
|
|
||||||
intelleigence of humans has be relied upon as a safe way to manage the hybrid
|
|
||||||
nature of this system. But, these operators are using prescriptive operating
|
|
||||||
manuals to perform their control with strict procedures on what control to
|
|
||||||
implement at a given time. These procedures are the key to the operational
|
|
||||||
control scope.
|
|
||||||
|
|
||||||
The method of constructing a HAHACS in this proposal leverages two key points of
|
|
||||||
the way this control scope is done today: first, the operational scope control
|
|
||||||
is effectively discrete control. Second, the rules of implementing this control
|
|
||||||
are described a priori to their implementation in operating procedures. We can
|
|
||||||
make great use of these facts by formalizing the rules for transitioning between
|
|
||||||
discrete states. To do this, we will use temporal logic to formalize discrete
|
|
||||||
switching behavior.
|
|
||||||
|
|
||||||
Temporal logic is a rich syntax that allows for the definition of logical
|
|
||||||
calculations including time related bounds. For this reason, we can make
|
|
||||||
statements relating discrete control modes to one another. Using temporal logic,
|
|
||||||
we can effectively describe all of the requirements of a HAHACS. The guard
|
|
||||||
conditions \(G\) are easily defined by determining boundary conditions between
|
|
||||||
discrete states and defining their behavior, while continuous mode invariants
|
|
||||||
can be defined using temporal logic statements as well. These form the basis of
|
|
||||||
any proofs about a HAHACS, and are the fundamental 'truth' statements about what
|
|
||||||
the behavior of the system is designed to be.
|
|
||||||
|
|
||||||
To build these temporal logic statements, an intermediary tool called FRET is
|
|
||||||
planned to be used. FRET stands for Formal Requirements Elicitation Tool, and
|
|
||||||
was designed by NASA to build high assurance timed systems. FRET is an
|
|
||||||
intermediarly language between temporal logic and natural language that allows
|
|
||||||
for rigid definitions of temporal behvarior while using a logic-novice friendly
|
|
||||||
syntax. This benefit is crucial for the feasibility of this methodology for
|
|
||||||
industry, as minimizing the barrier to formal methods is a critical component of
|
|
||||||
their scucess. By reducing the expert knowledge required to use these tools,
|
|
||||||
their adoption with current workforce becomes easier.
|
|
||||||
|
|
||||||
A key feature of FRET is the ability to start with logically imprecise
|
|
||||||
statements and consecutively refine them into a well-posited specification. We
|
|
||||||
can use this to our advantage by directly dumping in operating procedures and
|
|
||||||
design requirements into FRET in natural language, and iteratively refining them
|
|
||||||
into the specifications for a HAHACS. This has two distinct but important
|
|
||||||
benefits. First, it allows us to draw a direct link from the design
|
|
||||||
documentation to the digital system implementation. Second, it clearly
|
|
||||||
demonstrates where the natural language documents are insufficient. These
|
|
||||||
procedures may still be used by human operators, so any wiggle room for
|
|
||||||
interpretation is a weakness that must be addressed.
|
|
||||||
|
|
||||||
%Talk about how we go from temp logic to reactive synth. Metnion fret can
|
|
||||||
%export, or naturlly support reactive synth solver ltlsynt, a sota react synth
|
|
||||||
%solver
|
|
||||||
|
|
||||||
Once system requirements we defined as temporal logic specifications we will use
|
|
||||||
the specifications to build the discrete control system. To do this, reactive
|
|
||||||
synthesis tools will be utilized. Reactive synthesis is a field in computer
|
|
||||||
science that deals with the automated creation of reactive programs from
|
|
||||||
temporal logic specifications. A reactive program is one that for a given state
|
|
||||||
takes an input, and produces an output. Our systems, such as the discrete
|
|
||||||
portion of the controller, fit exactly this this mold. The current discrete
|
|
||||||
state, and status of guard conditions are the input to the system, while the
|
|
||||||
output is the next discrete state. The output of a reactive synthesis algorithim
|
|
||||||
is a discrete automata.
|
|
||||||
|
|
||||||
Reactive synthesis' main advantage is the fact that at no point in the
|
|
||||||
production of a discrete automata of the program is human engineering required.
|
|
||||||
The resultant automata is correct by construction. This method of construction
|
|
||||||
eliminates the possibility of human error outright at the implementation state.
|
|
||||||
Instead, the effort on the human designer is directed at the specification of
|
|
||||||
the system behavior itself.
|
|
||||||
|
|
||||||
% talk about what the benefits of reactive synth are. Proof chain, machine
|
|
||||||
% checkable, blah blah blah
|
|
||||||
|
|
||||||
%%%%% I NEED TO WRITE ABOUT HOW REQUIREMENTS ARE EXTRACTED AND WHAT BECOME
|
|
||||||
CONTINUOUS CONTROLLER TRANSITIONS VS DISCRETE GUARD CONDITIONS
|
|
||||||
|
|
||||||
%%%%%%%%%%%% Building continuous controllers
|
|
||||||
\subsection{Continuous Controllers}
|
|
||||||
|
|
||||||
% The whole point of a hybrid system is that there are continuous components
|
|
||||||
% underneath the digital system. We built the discrete like the physical doesn't
|
|
||||||
% exist, but it really does. So how do we capture the physical system too?
|
|
||||||
|
|
||||||
% SCOPE FRAMING: This methodology VERIFIES continuous controllers, not SYNTHESIZES them
|
|
||||||
% Compare to model checking: doesn't tell you HOW to design software, verifies if it satisfies specs
|
|
||||||
% We assume controllers can be designed using standard control theory techniques
|
|
||||||
% Our contribution: verification that candidate controllers compose correctly with discrete layer
|
|
||||||
|
|
||||||
% What are the main different kinds of continuous modes we may see?
|
|
||||||
% Mathematical structure: Each discrete mode qᵢ provides three key pieces of information:
|
|
||||||
% 1. Entry conditions: X_entry,i ⊆ X (initial state set)
|
|
||||||
% 2. Exit conditions: X_exit,i ⊆ X (target state set)
|
|
||||||
% 3. Invariants: X_safe,i ⊆ X (safety envelope during operation)
|
|
||||||
% These come from the discrete controller synthesis and define objectives for continuous control
|
|
||||||
% Q: Who designs the continuous controllers and how? This methodology verifies
|
|
||||||
% them, but doesn't synthesize them. Is this a scope problem?
|
|
||||||
|
|
||||||
The synthesis of the discrete operational controller is only half of an
|
|
||||||
autonomous controller. These control systems are hybrid, with both discrete and
|
|
||||||
continuous components. In this section, we will talk about the continuous
|
|
||||||
control modes that are the transitions between discrete modes, how they may be
|
|
||||||
synthesized, and how we plan to verify them.
|
|
||||||
|
|
||||||
The operational control scope defines go/no-go decisions that themselves are
|
|
||||||
deciding what kind of continuous control to implement. To this end, the entry or
|
|
||||||
exit of a discrete state triggers are themselves the guard conditions \(G\) that
|
|
||||||
define the barriers of the continuous controller. These continuous controllers
|
|
||||||
all share a large state space, but each individual continuous control mode
|
|
||||||
operates within it's own partition defined by the discrete state \(q_i\) and
|
|
||||||
guard conditions \(G\). This partitioning of the continuous state space amongst
|
|
||||||
several discrete vector fields controlled by the given \(q_i\) has traditionally
|
|
||||||
been a difficult problem for validation and verification of systems properties.
|
|
||||||
Typically, the discontinuity of the vector fields at discrete state interfaces
|
|
||||||
make things like reachability analysis computationally expensive, and analytic
|
|
||||||
solutions become intractable.
|
|
||||||
|
|
||||||
We circumnavigate these issues by designing our hybrid system from the bottom up
|
|
||||||
with this verification in mind. Each continuous control mode has an input and
|
|
||||||
output set clearly defined by our discrete transitions \textit{a priori}.
|
|
||||||
Consider that we define the continuous state space as \(X\). Whenever we create
|
|
||||||
guard functions from our design requirements for a given system, we are
|
|
||||||
effectively creating subsets \(X_{entry,i}\) and \(X_{exit,i}\) for each
|
|
||||||
discrete mode \(q_i\). These subsets define when the state transitions occur
|
|
||||||
between discrete modes, but more importantly when building continuous control
|
|
||||||
modes, they become control objectives.
|
|
||||||
|
|
||||||
% Start talking about what it means to build controlelrs to the objectives
|
|
||||||
% rahter than the other why around. ALso why it makes things much easier to
|
|
||||||
% verify and validate
|
|
||||||
|
|
||||||
%%%%%% Transitory modes
|
|
||||||
|
|
||||||
% entry and exit conditions
|
|
||||||
% the goal is getting from one physical state to another
|
|
||||||
% MATHEMATICAL FORMULATION:
|
|
||||||
% Control objective: reach(X_entry,i) → reach(X_exit,i) while maintaining x(t) ∈ X_safe,i
|
|
||||||
% Standard control techniques (LQR, MPC, trajectory optimization) applied with these constraints
|
|
||||||
%
|
|
||||||
% VERIFICATION: Reachability analysis confirms ALL trajectories starting in X_entry,i
|
|
||||||
% reach X_exit,i without violating X_safe,i
|
|
||||||
% Formally: Reach(X_entry,i, f(x,u), T) ⊆ X_exit,i ∪ X_safe,i
|
|
||||||
% where f(x,u) is the closed-loop continuous dynamics
|
|
||||||
%
|
|
||||||
% we have the physical requirements from earlier specifications. Here we use
|
|
||||||
% them in a reachability analysis. This time, we use the actual physical values
|
|
||||||
% instead of the binary yes/no we used for discrete
|
|
||||||
% Q: How do we verify timing constraints? If a transitory controller eventually
|
|
||||||
% reaches the exit condition but takes too long, that violates safety. Timed
|
|
||||||
% automata? Timed reachability?
|
|
||||||
% Q: Should formalize the Mealy machine perspective - continuous system IS the
|
|
||||||
% transition, and entry/exit conditions are the discrete states. This could be
|
|
||||||
% a unifying conceptual framework.
|
|
||||||
|
|
||||||
%%%%%% stabilizing modes
|
|
||||||
|
|
||||||
% these are control modes with an objective of KEEPING a certain discrete state
|
|
||||||
% stable
|
|
||||||
%
|
|
||||||
% MATHEMATICAL FORMULATION:
|
|
||||||
% Control objective: remain(X_target,i) where X_target,i ⊂ X_safe,i
|
|
||||||
% Standard feedback control (PID, state feedback, LQG) applied to maintain equilibrium
|
|
||||||
%
|
|
||||||
% VERIFICATION: Barrier certificates prove closed-loop dynamics cannot escape X_safe,i
|
|
||||||
% Formally: Find B(x) s.t. ∇B(x)·f(x,u) ≤ 0 for all x ∈ ∂X_safe,i
|
|
||||||
% This proves no trajectory can cross the boundary (no flux out of safety region)
|
|
||||||
%
|
|
||||||
% we also have the physical requirements for this. These can be used for barrier
|
|
||||||
% certificates. We can prove that our model won't leave a given area without
|
|
||||||
% some disturbance.
|
|
||||||
|
|
||||||
%%%%%% expulsory modes
|
|
||||||
% I've made an implicit assumption when talking about transitory and stabilizing
|
|
||||||
% modes. That our model is correct. This might not be true
|
|
||||||
|
|
||||||
% In the case of a failure, our model will almost certainly be incorrect. For
|
|
||||||
% this, we have to build safe shutdown modes too, since a human won't be in the
|
|
||||||
% loop to shut things down.
|
|
||||||
%
|
|
||||||
% MATHEMATICAL FORMULATION:
|
|
||||||
% Control objective: reach(X_current) → reach(X_safe_shutdown) under parameter uncertainty
|
|
||||||
% where X_current may be anywhere in X (worst-case entry conditions)
|
|
||||||
% Dynamics have parametric uncertainty: f(x,u,θ) where θ ∈ Θ_failure
|
|
||||||
%
|
|
||||||
% VERIFICATION: Parametric reachability analysis with robustness margins
|
|
||||||
% Reach(X_current, f(x,u,θ), T) ⊆ X_safe_shutdown for all θ ∈ Θ_failure
|
|
||||||
% Conservative bounds on Θ_failure come from FMEA/traditional safety analysis
|
|
||||||
|
|
||||||
% WE can detect physical failures exist because our physical controllers have
|
|
||||||
% previously been proven as correct by reachability and barrier certificates. We
|
|
||||||
% KNOW our controller cannot be incorrect for the plant, so if an invariant is
|
|
||||||
% violated, we KNOW it's the plant that has changed.
|
|
||||||
% Q: What about sensor failures (wrong readings vs actual plant failure)?
|
|
||||||
% Q: What about unmodeled disturbances that aren't failures?
|
|
||||||
% Q: What if model uncertainty was too optimistic to begin with?
|
|
||||||
% Need to be more precise about what "model failure" means and detect-ability.
|
|
||||||
|
|
||||||
% We do this using continuous modes that shutdown the system, and using
|
|
||||||
% reachability analysis with parametric uncertainty, we can prove for a range of
|
|
||||||
% error conditions we can maintain safe shutdown.
|
|
||||||
% Q: How much parametric uncertainty is enough? How do we determine bounds for
|
|
||||||
% worst-case failure dynamics? Need methodology for this.
|
|
||||||
|
|
||||||
%%%%%%%%%%%% Implementation with industrial partnerships
|
|
||||||
%%%%%%% Emerson
|
|
||||||
%talk about this
|
|
||||||
% ovation system
|
|
||||||
% scenic? Is that what they call it?
|
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||||||
% ripe partnership with Westinghouse
|
|
||||||
% Likely build a model with a ccng plant. They already have sophisticated models
|
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||||||
% of them
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||||||
% build controller with simplified model, then test with high fidelity digital
|
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||||||
% twin
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%
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{yellow!60}{\textcolor {yellow!60}{o}}\ Consider: ``operators'' appears 3x in two sentences. Maybe: ``Based on these procedures and their interpretation of plant conditions, they make critical decisions...''}{i}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{orange!50}{\textcolor {orange!50}{o}}\ ``But, reliance'' — the comma after ``But'' is unusual. Either drop it or restructure: ``However, this reliance...'' or ``This reliance, however, has created...''}{i}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{yellow!60}{\textcolor {yellow!60}{o}}\ The ``and'' here joins two distinct issues (autonomy barrier + economics). Consider making the causal link explicit: ``This reliance on human operators not only prevents autonomous control capabilities but also creates...'' or split into two sentences.}{1}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{orange!50}{\textcolor {orange!50}{o}}\ ``What is needed is'' — Gopen would call this a weak topic position. The sentence buries the subject. Try: ``Autonomous control systems must safely manage complex operational sequences...'' Puts the actor in the topic position.}{1}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Excellent setup of the gap — shows why neither approach alone is sufficient.}{1}{}\protected@file@percent }
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|
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||||||
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||||||
\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{yellow!60}{\textcolor {yellow!60}{o}}\ This paragraph is doing a lot. Consider splitting: first paragraph on the hierarchy and compliance, second on the lack of formal verification. The ``No mathematical proof exists...'' sentence is powerful and deserves emphasis.}{3}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{orange!50}{\textcolor {orange!50}{o}}\ This repeats the ``No mathematical proof exists...'' sentence almost verbatim from the paragraph above. Either cut it from the paragraph or from the LIMITATION box.}{3}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{red!40}{\textcolor {red!40}{o}}\ Typo: ``ivariant'' should be ``invariant''}{6}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{yellow!60}{\textcolor {yellow!60}{o}}\ Consider adding a concrete example here — ``For instance, a system with N modes and M continuous state variables...'' to give readers a sense of the scaling problem.}{6}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{orange!50}{\textcolor {orange!50}{o}}\ ``but are far from a complete methodology to design systems with'' — awkward ending preposition. Try: ``but remain far from a complete design methodology'' or ``but do not yet constitute a complete design methodology.''}{6}{}\protected@file@percent }
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\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Your comment here is spot-on. You should add a LIMITATION box: \textit {Differential dynamic logic has been used for post-hoc analysis of existing systems, not for the constructive design of autonomous controllers.} This is exactly the gap you're filling — you're doing synthesis, not just verification.}{6}{}\protected@file@percent }
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||||||
\newlabel{fig:hybrid_automaton}{{1}{9}{Research Approach}{figure.1}{}}
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||||||
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||||||
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\@writefile{lof}{\contentsline {figure}{\numberline {2}{\ignorespaces Control scope hierarchy in nuclear power operations. Strategic control (long-term planning) remains with human management. HAHACS addresses the operational level (discrete mode switching) and tactical level (continuous control within modes), which together form a hybrid control system.}}{10}{}\protected@file@percent }
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||||||
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||||||
\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ This three-mode taxonomy is elegant — maps verification tools to control objectives cleanly.}{14}{}\protected@file@percent }
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52
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|
||||||
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|
||||||
\bibitem{NUREG-0899}
|
|
||||||
{U.S. Nuclear Regulatory Commission}, ``Guidelines for the preparation of emergency operating procedures,'' Tech. Rep. NUREG-0899, U.S. Nuclear Regulatory Commission, 1982.
|
|
||||||
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|
||||||
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|
|
||||||
{U.S. Nuclear Regulatory Commission}, ``{10 CFR Part 50.34}.'' Code of Federal Regulations.
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|
||||||
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|
||||||
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|
||||||
{U.S. Nuclear Regulatory Commission}, ``{10 CFR Part 55.59}.'' Code of Federal Regulations.
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|
||||||
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|
||||||
\bibitem{WRPS.Description}
|
|
||||||
``{Westinghouse RPS System Description},'' tech. rep., Westinghouse Electric Corporation.
|
|
||||||
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|
||||||
\bibitem{gentillon_westinghouse_1999}
|
|
||||||
C.~D. Gentillon, D.~Marksberry, D.~Rasmuson, M.~B. Calley, S.~A. Eide, and T.~Wierman, ``Westinghouse reactor protection system unavailability, 1984-1995.''
|
|
||||||
\newblock Number: {INEEL}/{CON}-99-00374 Publisher: Idaho National Engineering and Environmental Laboratory.
|
|
||||||
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|
||||||
\bibitem{operator_statistics}
|
|
||||||
{U.S. Nuclear Regulatory Commission}, ``{Operator Licensing}.'' \url{https://www.nrc.gov/reactors/operator-licensing}.
|
|
||||||
|
|
||||||
\bibitem{10CFR55}
|
|
||||||
{U.S. Nuclear Regulatory Commission}, ``{Part 55—Operators' Licenses}.'' \url{https://www.nrc.gov/reading-rm/doc-collections/cfr/part055/full-text}.
|
|
||||||
|
|
||||||
\bibitem{10CFR50.54}
|
|
||||||
{U.S. Nuclear Regulatory Commission}, ``{§ 50.54 Conditions of Licenses}.'' \url{https://www.nrc.gov/reading-rm/doc-collections/cfr/part050/part050-0054}.
|
|
||||||
|
|
||||||
\bibitem{Kemeny1979}
|
|
||||||
J.~G. Kemeny {\em et~al.}, ``Report of the president's commission on the accident at three mile island,'' tech. rep., President's Commission on the Accident at Three Mile Island, October 1979.
|
|
||||||
|
|
||||||
\bibitem{WNA2020}
|
|
||||||
{World Nuclear Association}, ``Safety of nuclear power reactors.'' \url{https://www.world-nuclear.org/information-library/safety-and-security/safety-of-plants/safety-of-nuclear-power-reactors.aspx}, 2020.
|
|
||||||
|
|
||||||
\bibitem{hogberg_root_2013}
|
|
||||||
L.~Högberg, ``Root causes and impacts of severe accidents at large nuclear power plants,'' vol.~42, no.~3, pp.~267--284.
|
|
||||||
|
|
||||||
\bibitem{zhang_analysis_2025}
|
|
||||||
M.~Zhang, L.~Dai, W.~Chen, and E.~Pang, ``Analysis of human errors in nuclear power plant event reports,'' vol.~57, no.~10, p.~103687.
|
|
||||||
|
|
||||||
\bibitem{Kiniry2024}
|
|
||||||
J.~Kiniry, A.~Bakst, S.~Hansen, M.~Podhradsky, and A.~Bivin, ``High assurance rigorous digital engineering for nuclear safety (hardens) final technical report,'' Tech. Rep. TLR-RES-RES/DE-2024-005, Galois, Inc. / U.S. Nuclear Regulatory Commission, 2024.
|
|
||||||
\newblock NRC Contract 31310021C0014.
|
|
||||||
|
|
||||||
\bibitem{eia_lcoe_2022}
|
|
||||||
{U.S. Energy Information Administration}, ``Levelized costs of new generation resources in the annual energy outlook 2022,'' report, U.S. Energy Information Administration, March 2022.
|
|
||||||
\newblock See Table 1b, page 9.
|
|
||||||
|
|
||||||
\bibitem{eesi_datacenter_2024}
|
|
||||||
{Environmental and Energy Study Institute}, ``Data center energy needs are upending power grids and threatening the climate.'' Web article, 2024.
|
|
||||||
\newblock Accessed: 2025-09-29.
|
|
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|
|
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INPUT /Users/split/Library/TinyTeX/texmf-dist/fonts/type1/urw/times/utmri8a.pfb
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|
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27
main.toc
27
main.toc
@ -1,27 +0,0 @@
|
|||||||
\contentsline {section}{Contents}{iii}{}%
|
|
||||||
\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}{3}{}%
|
|
||||||
\contentsline {subsection}{\numberline {2.1}Current Reactor Procedures and Operation}{3}{}%
|
|
||||||
\contentsline {subsection}{\numberline {2.2}Human Factors in Nuclear Accidents}{4}{}%
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|
||||||
\contentsline {subsection}{\numberline {2.3}Formal Methods}{5}{}%
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|
||||||
\contentsline {subsubsection}{\numberline {2.3.1}HARDENS}{5}{}%
|
|
||||||
\contentsline {subsubsection}{\numberline {2.3.2}Sequent Calculus and Differential Dynamic Logic}{6}{}%
|
|
||||||
\contentsline {section}{\numberline {3}Research Approach}{8}{}%
|
|
||||||
\contentsline {subsection}{\numberline {3.1}System Requirements, Specifications, and Discrete Controllers}{9}{}%
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|
||||||
\contentsline {subsection}{\numberline {3.2}Continuous Control Modes}{13}{}%
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|
||||||
\contentsline {subsubsection}{\numberline {3.2.1}Transitory Modes}{14}{}%
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|
||||||
\contentsline {subsubsection}{\numberline {3.2.2}Stabilizing Modes}{15}{}%
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|
||||||
\contentsline {subsubsection}{\numberline {3.2.3}Expulsory Modes}{16}{}%
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|
||||||
\contentsline {subsection}{\numberline {3.3}Industrial Implementation}{17}{}%
|
|
||||||
\contentsline {section}{\numberline {4}Metrics for Success}{18}{}%
|
|
||||||
\contentsline {paragraph}{TRL 3 \textit {Critical Function and Proof of Concept}}{18}{}%
|
|
||||||
\contentsline {paragraph}{TRL 4 \textit {Laboratory Testing of Integrated Components}}{18}{}%
|
|
||||||
\contentsline {paragraph}{TRL 5 \textit {Laboratory Testing in Relevant Environment}}{19}{}%
|
|
||||||
\contentsline {section}{\numberline {5}Risks and Contingencies}{20}{}%
|
|
||||||
\contentsline {subsection}{\numberline {5.1}Computational Tractability of Synthesis}{20}{}%
|
|
||||||
\contentsline {subsection}{\numberline {5.2}Discrete-Continuous Interface Formalization}{20}{}%
|
|
||||||
\contentsline {subsection}{\numberline {5.3}Procedure Formalization Completeness}{22}{}%
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|
||||||
\contentsline {section}{\numberline {6}Broader Impacts}{24}{}%
|
|
||||||
\contentsline {section}{\numberline {7}Schedule, Milestones, and Deliverables}{26}{}%
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|
||||||
\contentsline {subsection}{\numberline {7.1}Milestones and Deliverables}{26}{}%
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|
||||||
\contentsline {section}{References}{27}{}%
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||||||
586
todonotes.sty
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todonotes.sty
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%%
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||||||
%% This is file `todonotes.sty',
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||||||
%% generated with the docstrip utility.
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||||||
%%
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||||||
%% The original source files were:
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%%
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||||||
%% todonotes.dtx (with options: `package')
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||||||
%%
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||||||
%% This is a generated file.
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||||||
%%
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|
||||||
%% Copyright (C) 2008 by Henrik Skov Midtiby <henrikmidtiby@gmail.com>
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|
||||||
%%
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|
||||||
%% This file may be distributed and/or modified under the conditions of
|
|
||||||
%% the LaTeX Project Public License, either version 1.2 of this license
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|
||||||
%% or (at your option) any later version. The latest version of this
|
|
||||||
%% license is in:
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|
||||||
%%
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|
||||||
%% http://www.latex-project.org/lppl.txt
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|
||||||
%%
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%% and version 1.2 or later is part of all distributions of LaTeX version
|
|
||||||
%% 1999/12/01 or later.
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||||||
%%
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|
||||||
\NeedsTeXFormat{LaTeX2e}[1999/12/01]
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|
||||||
\ProvidesPackage{todonotes}
|
|
||||||
[2024/01/05 v1.1.7 Todonotes source and documentation.]
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|
||||||
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|
||||||
\ProvidesPackage{todonotes}[2024/01/05]
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|
||||||
\RequirePackage{ifthen}
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|
||||||
\RequirePackage{xkeyval}
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|
||||||
\RequirePackage{xcolor}
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|
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\RequirePackage{tikz}
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|
||||||
\usetikzlibrary{positioning}
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|
||||||
\RequirePackage{calc}
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|
||||||
\newcommand\setuptodonotes[1]{\presetkeys{todonotes}{#1}{}}
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|
||||||
\newcommand{\@todonotes@text}{}%
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|
||||||
\newcommand{\@todonotes@backgroundcolor}{orange}
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|
||||||
\newcommand{\@todonotes@textcolor}{black}
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|
||||||
\newcommand{\@todonotes@linecolor}{orange}
|
|
||||||
\newcommand{\@todonotes@bordercolor}{black}
|
|
||||||
\newcommand{\@todonotes@tickmarkheight}{unused value}
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|
||||||
\newcommand{\@todonotes@textwidth}{\marginparwidth}
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|
||||||
\newcommand{\@todonotes@textsize}{\normalsize}
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|
||||||
\newcommand{\@todonotes@figwidth}{\linewidth}
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|
||||||
\newcommand{\@todonotes@figheight}{4cm}
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|
||||||
\newcommand{\@todonotes@figcolor}{black!40}
|
|
||||||
\AtBeginDocument{
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|
||||||
\ifx\undefined\phantomsection
|
|
||||||
\newcommand{\phantomsection}{}
|
|
||||||
\fi
|
|
||||||
\ifdim \marginparwidth < 2cm
|
|
||||||
\PackageWarning{todonotes}{The length marginparwidth is
|
|
||||||
less than 2cm and will most likely cause issues with the
|
|
||||||
appearance of inserted todonotes.
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|
||||||
The issue can be solved by adding a line like
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|
||||||
\setlength{\marginparwidth}{2cm}
|
|
||||||
prior to loading the todonotes package.} \else\fi%
|
|
||||||
}
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|
||||||
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|
||||||
\newcommand{\@todonotes@todolistname}{Todo list}
|
|
||||||
\newcommand{\@todonotes@MissingFigureText}{Figure}
|
|
||||||
\newcommand{\@todonotes@MissingFigureUp}{Missing}
|
|
||||||
\newcommand{\@todonotes@MissingFigureDown}{figure}
|
|
||||||
\newcommand{\@todonotes@SetTodoListName}[1]
|
|
||||||
{\renewcommand{\@todonotes@todolistname}{#1}}
|
|
||||||
\newcommand{\@todonotes@SetMissingFigureText}[1]
|
|
||||||
{\renewcommand{\@todonotes@MissingFigureText}{#1}}
|
|
||||||
\newcommand{\@todonotes@SetMissingFigureUp}[1]
|
|
||||||
{\renewcommand{\@todonotes@MissingFigureUp}{#1}}
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|
||||||
\newcommand{\@todonotes@SetMissingFigureDown}[1]
|
|
||||||
{\renewcommand{\@todonotes@MissingFigureDown}{#1}}
|
|
||||||
\newif{\if@todonotes@reverseMissingFigureTriangle}
|
|
||||||
\DeclareOptionX{catalan}{
|
|
||||||
\@todonotes@SetTodoListName{Llista de feines pendents}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureDown{pendent}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{croatian}{%
|
|
||||||
\@todonotes@SetTodoListName{Popis obveza}%
|
|
||||||
\@todonotes@SetMissingFigureText{Slika}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Nedostaje}%
|
|
||||||
\@todonotes@SetMissingFigureDown{slika}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{danish}{%
|
|
||||||
\@todonotes@SetTodoListName{G\o{}rem\aa{}lsliste}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figur}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Manglende}%
|
|
||||||
\@todonotes@SetMissingFigureDown{figur}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{dutch}{%
|
|
||||||
\@todonotes@SetTodoListName{Lijst van onafgewerkte taken}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figuur}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Ontbrekende}%
|
|
||||||
\@todonotes@SetMissingFigureDown{figuur}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{english}{%
|
|
||||||
\@todonotes@SetTodoListName{Todo list}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figure}%
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|
||||||
\@todonotes@SetMissingFigureUp{Missing}%
|
|
||||||
\@todonotes@SetMissingFigureDown{figure}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{french}{%
|
|
||||||
\@todonotes@SetTodoListName{Liste des points \`a traiter}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figure}%
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|
||||||
\@todonotes@SetMissingFigureUp{Figure}%
|
|
||||||
\@todonotes@SetMissingFigureDown{manquante}%
|
|
||||||
\@todonotes@reverseMissingFigureTrianglefalse
|
|
||||||
}
|
|
||||||
\DeclareOptionX{german}{%
|
|
||||||
\@todonotes@SetTodoListName{Liste der noch zu erledigenden Punkte}%
|
|
||||||
\@todonotes@SetMissingFigureText{Abbildung}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Fehlende}%
|
|
||||||
\@todonotes@SetMissingFigureDown{Abbildung}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{italian}{
|
|
||||||
\@todonotes@SetTodoListName{Elenco delle cose da fare}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureDown{mancante}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{ngerman}{%
|
|
||||||
\@todonotes@SetTodoListName{Liste der noch zu erledigenden Punkte}%
|
|
||||||
\@todonotes@SetMissingFigureText{Abbildung}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Fehlende}%
|
|
||||||
\@todonotes@SetMissingFigureDown{Abbildung}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{portuguese}{
|
|
||||||
\@todonotes@SetTodoListName{Lista de tarefas pendentes}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureDown{pendente}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{spanish}{
|
|
||||||
\@todonotes@SetTodoListName{Lista de tareas pendientes}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Figura}%
|
|
||||||
\@todonotes@SetMissingFigureDown{pendiente}%
|
|
||||||
}
|
|
||||||
\DeclareOptionX{swedish}{%
|
|
||||||
\@todonotes@SetTodoListName{Att g\"{o}ra-lista}%
|
|
||||||
\@todonotes@SetMissingFigureText{Figur}%
|
|
||||||
\@todonotes@SetMissingFigureUp{Figur}%
|
|
||||||
\@todonotes@SetMissingFigureDown{saknas}%
|
|
||||||
}
|
|
||||||
\providecommand{\@tocrmarg}{2.55em}
|
|
||||||
\providecommand{\@dotsep}{4.5}
|
|
||||||
\providecommand{\@pnumwidth}{1.55em}
|
|
||||||
\newcounter{@todonotes@numberoftodonotes}
|
|
||||||
\newif{\if@todonotes@obeyDraft}
|
|
||||||
\DeclareOptionX{obeyDraft}{\@todonotes@obeyDrafttrue}
|
|
||||||
\newif{\if@todonotes@isDraft}
|
|
||||||
\DeclareOptionX{draft}{\@todonotes@isDrafttrue}
|
|
||||||
\DeclareOptionX{draftcls}{\@todonotes@isDrafttrue}
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|
||||||
\DeclareOptionX{draftclsnofoot}{\@todonotes@isDrafttrue}
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|
||||||
\newif{\if@todonotes@obeyFinal}
|
|
||||||
\DeclareOptionX{obeyFinal}{\@todonotes@obeyFinaltrue}
|
|
||||||
\newif{\if@todonotes@isFinal}
|
|
||||||
\DeclareOptionX{final}{\@todonotes@isFinaltrue}
|
|
||||||
\newif{\if@todonotes@disabled}
|
|
||||||
\DeclareOptionX{disable}{\@todonotes@disabledtrue}
|
|
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\newif{\if@todonotes@colorinlistoftodos}
|
|
||||||
\DeclareOptionX{colorinlistoftodos}{\@todonotes@colorinlistoftodostrue}
|
|
||||||
\newif{\if@todonotes@dviStyle}
|
|
||||||
\DeclareOptionX{dvistyle}{\@todonotes@dviStyletrue}
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|
||||||
\define@key{todonotes.sty}%
|
|
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{color}{
|
|
||||||
\renewcommand{\@todonotes@backgroundcolor}{#1}
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|
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\renewcommand{\@todonotes@linecolor}{#1}}
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|
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\define@key{todonotes.sty}%
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|
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{backgroundcolor}{\renewcommand{\@todonotes@backgroundcolor}{#1}}
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|
||||||
\define@key{todonotes.sty}%
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|
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{textcolor}{\renewcommand{\@todonotes@textcolor}{#1}}
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|
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\define@key{todonotes.sty}%
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|
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{linecolor}{\renewcommand{\@todonotes@linecolor}{#1}}
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|
||||||
\define@key{todonotes.sty}%
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|
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{bordercolor}{\renewcommand{\@todonotes@bordercolor}{#1}}
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|
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\newcommand{\@todonotes@defaulttickmarkheight}{0cm}
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\renewcommand{\@todonotes@defaulttickmarkheight}{#1}}%
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|
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|
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\@todonotes@prependcaptionglobalfalse
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|
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\DeclareOptionX{prependcaption}{\@todonotes@prependcaptionglobaltrue}
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|
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\define@key{todonotes.sty}%
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|
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{textwidth}{\renewcommand{\@todonotes@textwidth}{#1}}
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|
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\newcommand{\todoformat}[1]{#1}
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|
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\define@key{todonotes.sty}%
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|
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{format}{\renewcommand{\todoformat}{\@nameuse{#1}}}
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|
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\define@key{todonotes.sty}%
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|
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{textsize}{\renewcommand{\@todonotes@textsize}{#1}}
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|
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\define@key{todonotes.sty}%
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|
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{size}{\renewcommand{\@todonotes@textsize}{#1}}
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|
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\newif\if@todonotes@shadowlibraryloaded
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|
||||||
\@todonotes@shadowlibraryloadedfalse
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|
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|
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|
||||||
\@todonotes@shadowlibraryloadedtrue}
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|
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|
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|
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\renewcommand{\@todonotes@shadowenabledbydefault}{shadow}}
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|
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\define@key{todonotes.sty}%
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|
||||||
{figwidth}{\renewcommand{\@todonotes@figwidth}{#1}}
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|
||||||
\define@key{todonotes.sty}%
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|
||||||
{figheight}{\renewcommand{\@todonotes@figheight}{#1}}
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|
||||||
\define@key{todonotes.sty}%
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|
||||||
{figcolor}{\renewcommand{\@todonotes@figcolor}{#1}}
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|
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\ProcessOptionsX*
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|
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\if@todonotes@disabled
|
|
||||||
\else
|
|
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\if@todonotes@obeyDraft
|
|
||||||
\@todonotes@disabledtrue
|
|
||||||
\if@todonotes@isDraft
|
|
||||||
\@todonotes@disabledfalse
|
|
||||||
\fi
|
|
||||||
\fi
|
|
||||||
\if@todonotes@obeyFinal
|
|
||||||
\@todonotes@disabledfalse
|
|
||||||
\if@todonotes@isFinal
|
|
||||||
\@todonotes@disabledtrue
|
|
||||||
\fi
|
|
||||||
\fi
|
|
||||||
\fi
|
|
||||||
|
|
||||||
\gdef\@todonotes@currentlinecolor{\@todonotes@linecolor}%
|
|
||||||
\gdef\@todonotes@currentbackgroundcolor{\@todonotes@backgroundcolor}%
|
|
||||||
\gdef\@todonotes@currenttextcolor{\@todonotes@textcolor}%
|
|
||||||
\gdef\@todonotes@currentbordercolor{\@todonotes@bordercolor}%
|
|
||||||
\define@key{todonotes}{color}{%
|
|
||||||
\gdef\@todonotes@currentlinecolor{#1}%
|
|
||||||
\gdef\@todonotes@currentbackgroundcolor{#1}}%
|
|
||||||
\define@key{todonotes}{linecolor}{%
|
|
||||||
\gdef\@todonotes@currentlinecolor{#1}}%
|
|
||||||
\define@key{todonotes}{backgroundcolor}{%
|
|
||||||
\gdef\@todonotes@currentbackgroundcolor{#1}}%
|
|
||||||
\define@key{todonotes}{textcolor}{%
|
|
||||||
\gdef\@todonotes@currenttextcolor{#1}}%
|
|
||||||
\define@key{todonotes}{bordercolor}{%
|
|
||||||
\gdef\@todonotes@currentbordercolor{#1}}%
|
|
||||||
\newif\if@todonotes@useshadow%
|
|
||||||
\define@key{todonotes}{shadow}[]{\@todonotes@useshadowtrue}%
|
|
||||||
\define@key{todonotes}{noshadow}[]{\@todonotes@useshadowfalse}%
|
|
||||||
\define@key{todonotes}{tickmarkheight}{%
|
|
||||||
\renewcommand{\@todonotes@tickmarkheight}{#1}}%
|
|
||||||
\newcommand{\@todonotes@format}{\todoformat}%
|
|
||||||
\define@key{todonotes}{format}{%
|
|
||||||
\renewcommand{\@todonotes@format}{\@nameuse{#1}}}%
|
|
||||||
\newcommand{\@todonotes@sizecommand}{}%
|
|
||||||
\define@key{todonotes}{size}{\renewcommand{\@todonotes@sizecommand}{#1}%
|
|
||||||
}%
|
|
||||||
\newif\if@todonotes@localdisable%
|
|
||||||
\define@key{todonotes}{disable}[]{\@todonotes@localdisabletrue}%
|
|
||||||
\define@key{todonotes}{nodisable}[]{\@todonotes@localdisablefalse}%
|
|
||||||
\newif\if@todonotes@appendtolistoftodos%
|
|
||||||
\define@key{todonotes}{list}[]{\@todonotes@appendtolistoftodostrue}%
|
|
||||||
\define@key{todonotes}{nolist}[]{\@todonotes@appendtolistoftodosfalse}%
|
|
||||||
\newif\if@todonotes@inlinenote%
|
|
||||||
\define@key{todonotes}{inline}[]{\@todonotes@inlinenotetrue}%
|
|
||||||
\define@key{todonotes}{noinline}[]{\@todonotes@inlinenotefalse}%
|
|
||||||
\newif\if@todonotes@prependcaption%
|
|
||||||
\define@key{todonotes}{prepend}[]{\@todonotes@prependcaptiontrue}%
|
|
||||||
\define@key{todonotes}{noprepend}[]{\@todonotes@prependcaptionfalse}%
|
|
||||||
\newif\if@todonotes@line%
|
|
||||||
\define@key{todonotes}{line}[]{\@todonotes@linetrue}%
|
|
||||||
\define@key{todonotes}{noline}[]{\@todonotes@linefalse}%
|
|
||||||
\newif\if@todonotes@fancyline\@todonotes@fancylinefalse%
|
|
||||||
\define@key{todonotes}{fancyline}[]{\@todonotes@fancylinetrue}%
|
|
||||||
\define@key{todonotes}{nofancyline}[]{\@todonotes@fancylinefalse}%
|
|
||||||
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|
|
||||||
\newif\if@todonotes@authorgiven%
|
|
||||||
\define@key{todonotes}{author}{%
|
|
||||||
\renewcommand{\@todonotes@author}{#1}%
|
|
||||||
\@todonotes@authorgiventrue}%
|
|
||||||
\define@key{todonotes}{noauthor}[]{\@todonotes@authorgivenfalse}%
|
|
||||||
\newcommand{\@todonotes@caption}{}%
|
|
||||||
\newif\if@todonotes@captiongiven%
|
|
||||||
\define@key{todonotes}{caption}%
|
|
||||||
{\renewcommand{\@todonotes@caption}{#1}%
|
|
||||||
\@todonotes@captiongiventrue}%
|
|
||||||
\define@key{todonotes}{nocaption}[]{\@todonotes@captiongivenfalse}%
|
|
||||||
\newcommand{\@todonotes@currentfigwidth}{\@todonotes@figwidth}
|
|
||||||
\define@key{todonotes}%
|
|
||||||
{figwidth}{\renewcommand{\@todonotes@currentfigwidth}{#1-2pt}}
|
|
||||||
\newcommand{\@todonotes@currentfigheight}{\@todonotes@figheight}
|
|
||||||
\define@key{todonotes}%
|
|
||||||
{figheight}{\renewcommand{\@todonotes@currentfigheight}{#1-2pt}}
|
|
||||||
\newcommand{\@todonotes@currentfigcolor}{\@todonotes@figcolor}
|
|
||||||
\define@key{todonotes}%
|
|
||||||
{figcolor}{\renewcommand{\@todonotes@currentfigcolor}{#1}}
|
|
||||||
\newcommand{\@todonotes@inlinewidth}{\linewidth}%
|
|
||||||
\define@key{todonotes}%
|
|
||||||
{inlinewidth}{\renewcommand{\@todonotes@inlinewidth}{#1}}
|
|
||||||
\newif\if@todonotes@inlinepar
|
|
||||||
\@todonotes@inlinepartrue
|
|
||||||
\define@key{todonotes}{inlinepar}[]{\@todonotes@inlinepartrue}%
|
|
||||||
\define@key{todonotes}{noinlinepar}[]{\@todonotes@inlineparfalse}%
|
|
||||||
\presetkeys%
|
|
||||||
{todonotes}%
|
|
||||||
{linecolor=\@todonotes@linecolor,%
|
|
||||||
backgroundcolor=\@todonotes@backgroundcolor,%
|
|
||||||
textcolor=\@todonotes@textcolor,%
|
|
||||||
bordercolor=\@todonotes@bordercolor,%
|
|
||||||
format=todoformat,%
|
|
||||||
tickmarkheight=\@todonotes@defaulttickmarkheight,%
|
|
||||||
nofancyline,%
|
|
||||||
nodisable,%
|
|
||||||
noinline,%
|
|
||||||
nocaption,%
|
|
||||||
noauthor,%
|
|
||||||
\@todonotes@shadowenabledbydefault,%
|
|
||||||
figwidth=\@todonotes@figwidth,%
|
|
||||||
figheight=\@todonotes@figheight,%
|
|
||||||
figcolor=\@todonotes@figcolor,%
|
|
||||||
line, list,%
|
|
||||||
inlinewidth=\linewidth,
|
|
||||||
inlinepar}{}%
|
|
||||||
\@temptokena\expandafter{\@todonotes@textsize}
|
|
||||||
\edef\next{\noexpand\presetkeys{todonotes}{size=\the\@temptokena}{}}
|
|
||||||
\next
|
|
||||||
\if@todonotes@disabled%
|
|
||||||
\newcommand{\listoftodos}[1][]{}
|
|
||||||
\newcommand{\@todo}[2][]{}
|
|
||||||
\newcommand{\missingfigure}[2][]{}
|
|
||||||
\else % \if@todonotes@disabled
|
|
||||||
\newcommand{\listoftodos}[1][\@todonotes@todolistname]
|
|
||||||
{\@ifundefined{chapter}{\section*{#1}}{\chapter*{#1}} \@starttoc{tdo}}
|
|
||||||
\newcommand{\l@todo}
|
|
||||||
{\@dottedtocline{1}{0em}{2.3em}}
|
|
||||||
\tikzstyle{notestyleraw} = [
|
|
||||||
draw=\@todonotes@currentbordercolor,
|
|
||||||
fill=\@todonotes@currentbackgroundcolor,
|
|
||||||
text=\@todonotes@currenttextcolor,
|
|
||||||
line width=0.5pt,
|
|
||||||
text width = \@todonotes@textwidth - 1.6 ex - 1pt,
|
|
||||||
inner sep = 0.8 ex,
|
|
||||||
rounded corners=4pt]
|
|
||||||
\newcommand{\@todo}[2][]{%
|
|
||||||
\if@todonotes@prependcaptionglobal%
|
|
||||||
\@todonotes@prependcaptiontrue%
|
|
||||||
\else%
|
|
||||||
\@todonotes@prependcaptionfalse%
|
|
||||||
\fi%
|
|
||||||
\renewcommand{\@todonotes@text}{#2}%
|
|
||||||
\renewcommand{\@todonotes@caption}{#2}%
|
|
||||||
\setkeys{todonotes}{#1}%
|
|
||||||
\if@todonotes@useshadow%
|
|
||||||
\if@todonotes@shadowlibraryloaded%
|
|
||||||
\tikzstyle{notestyle} = [notestyleraw,%
|
|
||||||
general shadow={shadow xshift=0.5ex, shadow yshift=-0.5ex,%
|
|
||||||
opacity=1,fill=black!50}]%
|
|
||||||
\else%
|
|
||||||
\PackageWarning{todonotes}{Trying to put a shadow below a todonote,%
|
|
||||||
but the loadshadowlibrary option was not given when loading%
|
|
||||||
the todonotes package}%
|
|
||||||
\tikzstyle{notestyle} = [notestyleraw]%
|
|
||||||
\fi%
|
|
||||||
\else%
|
|
||||||
\tikzstyle{notestyle} = [notestyleraw]%
|
|
||||||
\fi%
|
|
||||||
\tikzstyle{notestyleleft} = [%
|
|
||||||
notestyle,%
|
|
||||||
left]%
|
|
||||||
\tikzstyle{connectstyle} = [%
|
|
||||||
thick,%
|
|
||||||
draw=\@todonotes@currentlinecolor]%
|
|
||||||
\tikzstyle{inlinenotestyle} = [%
|
|
||||||
notestyle,%
|
|
||||||
text width=\@todonotes@inlinewidth - 1.6 ex - 1 pt]%
|
|
||||||
\if@todonotes@localdisable%
|
|
||||||
\else%
|
|
||||||
\addtocounter{@todonotes@numberoftodonotes}{1}%
|
|
||||||
\if@todonotes@appendtolistoftodos%
|
|
||||||
\phantomsection%
|
|
||||||
\if@todonotes@captiongiven%
|
|
||||||
\else%
|
|
||||||
\renewcommand{\@todonotes@caption}{#2}%
|
|
||||||
\fi%
|
|
||||||
\@todonotes@addElementToListOfTodos%
|
|
||||||
\fi%
|
|
||||||
\if@todonotes@captiongiven%
|
|
||||||
\if@todonotes@prependcaption%
|
|
||||||
\renewcommand{\@todonotes@text}{\@todonotes@caption: #2}%
|
|
||||||
\fi%
|
|
||||||
\fi%
|
|
||||||
\if@todonotes@inlinenote%
|
|
||||||
\@todonotes@drawInlineNote%
|
|
||||||
\else%
|
|
||||||
\@todonotes@drawMarginNoteWithLine%
|
|
||||||
\fi%\if@todonotes@inlinenote
|
|
||||||
\fi%\if@todonotes@localdisable
|
|
||||||
}%
|
|
||||||
\newcommand{\@todonotes@drawMarginNoteWithLine}{%
|
|
||||||
\ifvmode
|
|
||||||
\vspace*{-\parskip}% % backup if we are already in vertical mode
|
|
||||||
\vskip-\baselineskip % (and don't loose that space after a
|
|
||||||
% pagebreak ...
|
|
||||||
\noindent
|
|
||||||
\fi
|
|
||||||
\begin{tikzpicture}[remember picture, overlay, baseline=-0.75ex]%
|
|
||||||
\node [coordinate] (inText) {};%
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\marginpar[{% Draw note in left margin
|
|
||||||
\@todonotes@drawMarginNote%
|
|
||||||
\@todonotes@drawLineToLeftMargin%
|
|
||||||
}]{% Draw note in right margin
|
|
||||||
\@todonotes@drawMarginNote%
|
|
||||||
\@todonotes@drawLineToRightMargin%
|
|
||||||
}%
|
|
||||||
}%
|
|
||||||
\newcommand{\@todonotes@addElementToListOfTodos}{%
|
|
||||||
\if@todonotes@colorinlistoftodos%
|
|
||||||
\addcontentsline{tdo}{todo}{%
|
|
||||||
\fcolorbox{\@todonotes@currentbordercolor}%
|
|
||||||
{\@todonotes@currentbackgroundcolor}%
|
|
||||||
{\textcolor{\@todonotes@currentbackgroundcolor}{o}}%
|
|
||||||
\ \@todonotes@caption}%
|
|
||||||
\else%
|
|
||||||
\addcontentsline{tdo}{todo}{\@todonotes@caption}%
|
|
||||||
\fi}%
|
|
||||||
\newcommand{\@todonotes@useSizeCommand}{%
|
|
||||||
\ifcsname \expandafter\string\@todonotes@sizecommand\endcsname
|
|
||||||
\csname \expandafter\string\@todonotes@sizecommand\endcsname%
|
|
||||||
\else
|
|
||||||
\@todonotes@sizecommand
|
|
||||||
\fi%
|
|
||||||
}%
|
|
||||||
\newcommand{\@todonotes@drawInlineNote}{%
|
|
||||||
\if@todonotes@dviStyle%
|
|
||||||
{\if@todonotes@inlinepar\par\noindent\fi%
|
|
||||||
\begin{tikzpicture}[remember picture]%
|
|
||||||
\draw node[inlinenotestyle] {};
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\if@todonotes@inlinepar\par\fi}%
|
|
||||||
\if@todonotes@authorgiven%
|
|
||||||
{\noindent \@todonotes@useSizeCommand \@todonotes@author:\,\@todonotes@format{\@todonotes@text}}%
|
|
||||||
\else%
|
|
||||||
{\noindent \@todonotes@useSizeCommand%
|
|
||||||
\@todonotes@format{\@todonotes@text}}%
|
|
||||||
\fi
|
|
||||||
{\if@todonotes@inlinepar\par\noindent\fi%
|
|
||||||
\begin{tikzpicture}[remember picture]%
|
|
||||||
\draw node[inlinenotestyle] {};
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\if@todonotes@inlinepar\par\fi}%
|
|
||||||
\else%
|
|
||||||
{\if@todonotes@inlinepar\par\noindent\fi%
|
|
||||||
\begin{tikzpicture}[remember picture]%
|
|
||||||
\draw node[inlinenotestyle,font=\@todonotes@useSizeCommand]{%
|
|
||||||
\if@todonotes@authorgiven%
|
|
||||||
{\noindent \@todonotes@author:\,%
|
|
||||||
\@todonotes@format{\@todonotes@text}}%
|
|
||||||
\else%
|
|
||||||
{\noindent \@todonotes@format{\@todonotes@text}}%
|
|
||||||
\fi};%
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\if@todonotes@inlinepar\par\fi}%
|
|
||||||
\fi}%
|
|
||||||
\newcommand{\@todonotes@drawMarginNote}{%
|
|
||||||
\if@todonotes@dviStyle%
|
|
||||||
\begin{tikzpicture}[remember picture]%
|
|
||||||
\draw node[notestyle] {};%
|
|
||||||
\end{tikzpicture}\\%
|
|
||||||
\begin{minipage}{\@todonotes@textwidth}%
|
|
||||||
\if@todonotes@authorgiven%
|
|
||||||
\@todonotes@useSizeCommand \@todonotes@author:\,
|
|
||||||
\@todonotes@format{\@todonotes@text}%
|
|
||||||
\else%
|
|
||||||
\@todonotes@useSizeCommand\@todonotes@format{\@todonotes@text}%
|
|
||||||
\fi%
|
|
||||||
\end{minipage}\\%
|
|
||||||
\begin{tikzpicture}[remember picture]%
|
|
||||||
\draw node[notestyle] (inNote) {};%
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\else%
|
|
||||||
\let\originalHbadness\hbadness%
|
|
||||||
\hbadness 100000%
|
|
||||||
\begin{tikzpicture}[remember picture,baseline=(X.base)]%
|
|
||||||
\node(X){\vphantom{\@todonotes@useSizeCommand X}};%
|
|
||||||
\if@todonotes@authorgiven%
|
|
||||||
\draw node[notestyle,font=\@todonotes@useSizeCommand,anchor=north] (inNote) at (X.north)%
|
|
||||||
{\@todonotes@author};%
|
|
||||||
\node(Y)[below=of X]{};%
|
|
||||||
\draw node[notestyle,font=\@todonotes@useSizeCommand,anchor=north] (inNote) at (X.south)%
|
|
||||||
{\@todonotes@format{\@todonotes@text}};%
|
|
||||||
\else%
|
|
||||||
\draw node[notestyle,font=\@todonotes@useSizeCommand,anchor=north] (inNote) at (X.north)%
|
|
||||||
{\@todonotes@format{\@todonotes@text}};%
|
|
||||||
\fi%
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\hbadness \originalHbadness%
|
|
||||||
\fi}%
|
|
||||||
\newcommand{\@todonotes@drawLineToRightMargin}{%
|
|
||||||
\if@todonotes@line%
|
|
||||||
\if@todonotes@fancyline%
|
|
||||||
\tikz[remember picture,overlay]{%
|
|
||||||
\tikzstyle{both}=[line width=3pt, draw, opacity=0.15]%
|
|
||||||
\tikzstyle{line}=[shorten >=5pt, line cap=round]%
|
|
||||||
\tikzstyle{head}=[shorten >=-1pt, dash pattern=on 0pt off 1pt, ->]%
|
|
||||||
\foreach \s in {line,head}{%
|
|
||||||
\draw[both,\s]%
|
|
||||||
(inNote.north west).. controls +(0:0) and +(90:1.5)..([yshift=1ex] inText);%
|
|
||||||
}%
|
|
||||||
}%
|
|
||||||
\else%
|
|
||||||
\begin{tikzpicture}[remember picture, overlay]%
|
|
||||||
\draw[connectstyle]%
|
|
||||||
([yshift=-0.2cm + \@todonotes@tickmarkheight] inText)%
|
|
||||||
-| ([yshift=-0.2cm] inText)%
|
|
||||||
-| ([xshift=-0.2cm] inNote.west)%
|
|
||||||
-| (inNote.west);%
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\fi%
|
|
||||||
\fi}%
|
|
||||||
\newcommand{\@todonotes@drawLineToLeftMargin}{%
|
|
||||||
\if@todonotes@line%
|
|
||||||
\if@todonotes@fancyline%
|
|
||||||
\tikz[remember picture,overlay]{%
|
|
||||||
\tikzstyle{both}=[line width=3pt, draw, opacity=0.15]%
|
|
||||||
\tikzstyle{line}=[shorten >=5pt, line cap=round]%
|
|
||||||
\tikzstyle{head}=[shorten >=-1pt, dash pattern=on 0pt off 1pt,->]%
|
|
||||||
\foreach \s in {line,head}{%
|
|
||||||
\draw[both,\s]%
|
|
||||||
(inNote.north east).. controls +(0:0) and +(90:1.5)..([yshift=1ex] inText);%
|
|
||||||
}%
|
|
||||||
}%
|
|
||||||
\else%
|
|
||||||
\begin{tikzpicture}[remember picture, overlay]%
|
|
||||||
\draw[connectstyle]%
|
|
||||||
([yshift=-0.2cm + \@todonotes@tickmarkheight] inText)%
|
|
||||||
-| ([yshift=-0.2cm] inText)%
|
|
||||||
-| ([xshift=0.2cm] inNote.east)%
|
|
||||||
-| (inNote.east);%
|
|
||||||
\end{tikzpicture}%
|
|
||||||
\fi%
|
|
||||||
\fi}%
|
|
||||||
\newcommand{\missingfigure}[2][]{%
|
|
||||||
\setkeys{todonotes}{#1}%
|
|
||||||
\addcontentsline{tdo}{todo}{\@todonotes@MissingFigureText: #2}%
|
|
||||||
\par
|
|
||||||
\noindent
|
|
||||||
\hfill
|
|
||||||
\begin{tikzpicture}
|
|
||||||
\draw[fill=\@todonotes@currentfigcolor, draw = black!40, line width=2pt]
|
|
||||||
(-2, -0.5*\@todonotes@currentfigheight-0.5cm)
|
|
||||||
rectangle +(\@todonotes@currentfigwidth, \@todonotes@currentfigheight);
|
|
||||||
\draw (2, -0.5) node[right, text
|
|
||||||
width=\@todonotes@currentfigwidth-4.5cm, font=\@todonotes@useSizeCommand] {#2};
|
|
||||||
\draw[red, fill=white, rounded corners = 5pt, line width=10pt]
|
|
||||||
(30:2cm) -- (150:2cm) -- (270:2cm) -- cycle;
|
|
||||||
\draw (0, 0.3) node {\@todonotes@MissingFigureUp};
|
|
||||||
\draw (0, -0.3) node {\@todonotes@MissingFigureDown};
|
|
||||||
\end{tikzpicture}\hfill
|
|
||||||
\null\par
|
|
||||||
}% Ending \missingfigure command
|
|
||||||
\fi% Ending \@todonotes@ifdisabled
|
|
||||||
\newcommand{\todototoc}
|
|
||||||
{%
|
|
||||||
\if@todonotes@disabled
|
|
||||||
\else
|
|
||||||
\addcontentsline{toc}{\@ifundefined{chapter}{section}{chapter}}{\@todonotes@todolistname}%
|
|
||||||
\fi
|
|
||||||
}
|
|
||||||
\newcommand{\todo}[2][]{%
|
|
||||||
% Needed to output any dangling \item of a noskip section (see #36):
|
|
||||||
\if@inlabel \leavevmode \fi
|
|
||||||
\if@noskipsec \leavevmode \fi
|
|
||||||
\if@todonotes@inlinepar
|
|
||||||
\ifhmode
|
|
||||||
\@bsphack
|
|
||||||
\@todonotes@vmodefalse
|
|
||||||
\else
|
|
||||||
\@savsf\@m
|
|
||||||
\@savsk\z@
|
|
||||||
\@todonotes@vmodetrue
|
|
||||||
\fi
|
|
||||||
{\@todo[#1]{#2}}%
|
|
||||||
\@esphack%
|
|
||||||
\if@todonotes@vmode \par \fi
|
|
||||||
\else%
|
|
||||||
\@todo[#1]{#2}%
|
|
||||||
\fi}
|
|
||||||
\newif\if@todonotes@vmode
|
|
||||||
\newcommand*{\todostyle}[2]{%
|
|
||||||
\define@key{todonotes}{#1}[]{%
|
|
||||||
\setkeys{todonotes}{#2}}}
|
|
||||||
\endinput
|
|
||||||
%%
|
|
||||||
%% End of file `todonotes.sty'.
|
|
||||||
Loading…
x
Reference in New Issue
Block a user