From 02ecfaad94d2be2e4f4c67395cde7aa14a6c9ff2 Mon Sep 17 00:00:00 2001 From: Split Date: Mon, 9 Mar 2026 22:05:33 -0400 Subject: [PATCH] Clean up repo: remove tracked build artifacts, old versions, cruft Removed from tracking: - Build artifacts (*.aux, *.bbl, *.blg, *.fls, *.fdb_latexmk, *.log, *.toc, *.pdf) - Old versioned files (v1.tex, v2.tex) - content now in renamed files - Empty biblatex.sty placeholder - Vendored todonotes.sty (still in working tree, now gitignored) - .DS_Store Updated .gitignore to prevent re-adding *.sty files --- .DS_Store | Bin 10244 -> 0 bytes .gitignore | 2 + 2-state-of-the-art/v1.tex | 165 ------ 3-research-approach/v1.tex | 285 ---------- 3-research-approach/v2.tex | 578 ------------------- biblatex.sty | 0 main.aux | 248 -------- main.bbl | 52 -- main.blg | 67 --- main.fdb_latexmk | 261 --------- main.fls | 573 ------------------- main.log | 1095 ------------------------------------ main.pdf | Bin 208700 -> 0 bytes main.toc | 27 - todonotes.sty | 586 ------------------- 15 files changed, 2 insertions(+), 3937 deletions(-) delete mode 100644 .DS_Store delete mode 100644 2-state-of-the-art/v1.tex delete mode 100644 3-research-approach/v1.tex delete mode 100644 3-research-approach/v2.tex delete mode 100644 biblatex.sty delete mode 100644 main.aux delete mode 100644 main.bbl delete mode 100644 main.blg delete mode 100644 main.fdb_latexmk delete mode 100644 main.fls delete mode 100644 main.log delete mode 100644 main.pdf delete mode 100644 main.toc delete mode 100644 todonotes.sty diff --git a/.DS_Store b/.DS_Store deleted file mode 100644 index 2835636538d00fa7ba5b50a110a3aab4d43f4867..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 10244 zcmeI1OK%e~5XZ-Dp&QDhK#|%5XeBNjO30&+R9r$I2PBYC!{Y!bWV1=S>UK9|Hx!79 zat1yFUx6!p5cn9}Il+ItOYyobDjWc*c4W`4Gc&e-9y_u_L}Iz`7Kv;kvXEI$o{wSyodyOr+d8P{<6eN>lhuP7fkA73mQ}B^?O$&MOijow zYEg9451Wo3IZX1^I$ht3;zHrG7#STqc6{6#wNwOyZ_S_y-=;RUUpH1OOOR31I>0yo@V4*P){N!wcT zg_W~%^~ssRpt4w;wTqSF&a6EsmKWw{?WM)a&Q8v{aQWKx_4=m26@+i(kVvHa4V_Bf zcgwfGGvH^nUf_p82R7{Q9F+h!0@?<0OM-5rjA=u@HK<3i2KzniRM>~|p@9DI*FjGY z2IVENEtLxldZ|>HwHGQn=hqk)(t(_L9u75Djq!OZgJ_S#7MY1QL6@(ly7=^Du%jkR zSzJVGD&<3ZQ8@pTfG(Aa40^G=3wm*`^alZb$l+?Jr)Umfd54Gr)&pq10}P2nI>HXp z#D}Lr+dl+PtqOaF=3&7eBHENb_#Tn>A>M%kc=u3t;446l$3C^``>J_7OAD}e(&=_# z(ZjokzIG7^O?cEijPMdw`*eaTu!x|`OVh<@d}?J|mHXg3Wgpzv#*Lc3gFOuX=_I=3 zA^Yk2e@=Nc5z`CJF|T>magJ8#7Mi<9tF#82EpoFKBcHVHPov8Wu|@SX>bpQ0q0UE5 z8_zv>;aw#5j>rbu+wFj5b?mGH#8`kUa`V>HTYU5pRb-E*Q|7<6M?=Je$)_n8y ztG+GS6Q1Hcdeo=qnm*R1IIUn-^&O_E>BIjo^nL1R`Uswk{-n~MHu~>ij6Y{=i#D_N z96A|$wSVosY&mSis{_X4V`jAe5u)Kh{r&hdFV+7UWjqnRkc)_aeK`6$^fEgdUYr?g zbu`jS(`R~WYgzq}npu5GOV!UIp4Px*6|uE%Y>%#Jv3(kG)LSjwz92B zc3%|MaAlGqUEq_R zb{qK#GAGs>CQ_Q9kk|2$@;V+bd>wxUnRN>+IpMjQ%3&f=gY?(`3^3<^bN<)Q*WzfM G|Gxw6V-oiO diff --git a/.gitignore b/.gitignore index 1318e90..ac7666c 100644 --- a/.gitignore +++ b/.gitignore @@ -36,3 +36,5 @@ Thumbs.db *.swo .vscode/ .idea/ +*.sty +.DS_Store diff --git a/2-state-of-the-art/v1.tex b/2-state-of-the-art/v1.tex deleted file mode 100644 index 307278c..0000000 --- a/2-state-of-the-art/v1.tex +++ /dev/null @@ -1,165 +0,0 @@ -\section{State of the Art and Limits of Current Practice} - -The principal aim of this research is to create autonomous reactor control -systems that are tractably safe. To understand what is being automated, we must -first understand how nuclear reactors are operated today. This section examines -reactor operators and the operating procedures we aim to leverage, then -investigates limitations of human-based operation, and concludes with current -formal methods approaches to reactor control systems. - -\subsection{Current Reactor Procedures and Operation} - -Nuclear plant procedures exist in a hierarchy: normal operating procedures for -routine operations, abnormal operating procedures for off-normal conditions, -Emergency Operating Procedures (EOPs) for design-basis accidents, Severe -Accident Management Guidelines (SAMGs) for beyond-design-basis events, and -Extensive Damage Mitigation Guidelines (EDMGs) for catastrophic damage -scenarios. These procedures must comply with 10 CFR 50.34(b)(6)(ii) and are -developed using guidance from NUREG-0900~\cite{NUREG-0899, 10CFR50.34}, but their -development relies fundamentally on expert judgment and simulator validation -rather than formal verification. Procedures undergo technical evaluation, -simulator validation testing, and biennial review as part of operator -requalification under 10 CFR 55.59~\cite{10CFR55.59}. Despite this rigor, -procedures fundamentally lack formal verification of key safety properties. No -mathematical proof exists that procedures cover all possible plant states, that -required actions can be completed within available timeframes, or that -transitions between procedure sets maintain safety invariants. - -\textbf{LIMITATION:} \textit{Procedures lack formal verification of correctness -and completeness.} Current procedure development relies on expert judgment and -simulator validation. No mathematical proof exists that procedures cover all -possible plant states, that required actions can be completed within available -timeframes, or that transitions between procedure sets maintain safety -invariants. Paper-based procedures cannot ensure correct application, and even -computer-based procedure systems lack the formal guarantees that automated -reasoning could provide. - -Nuclear plants operate with multiple control modes: automatic control, where the -reactor control system maintains target parameters through continuous reactivity -adjustment; manual control, where operators directly manipulate the reactor; and -various intermediate modes. In typical pressurized water reactor operation, the -reactor control system automatically maintains a floating average temperature -and compensates for power demand changes through reactivity feedback loops -alone. Safety systems, by contrast, operate with implemented automation. Reactor -Protection Systems trip automatically on safety signals with millisecond -response times, and engineered safety features actuate automatically on accident -signals without operator action required. - -The division between automated and human-controlled functions reveals the -fundamental challenge of hybrid control. Highly automated systems handle reactor -protection---automatic trips on safety parameters, emergency core cooling -actuation, containment isolation, and basic process -control~\cite{WRPS.Description, gentillon_westinghouse_1999}. Human operators, -however, retain control of strategic decision-making: power level changes, -startup/shutdown sequences, mode transitions, and procedure implementation. - -\subsection{Human Factors in Nuclear Accidents} - -Current-generation nuclear power plants employ over 3,600 active NRC-licensed -reactor operators in the United States~\cite{operator_statistics}. These -operators divide into Reactor Operators (ROs), who manipulate reactor controls, -and Senior Reactor Operators (SROs), who direct plant operations and serve as -shift supervisors~\cite{10CFR55}. Staffing typically requires at least two ROs -and one SRO for current-generation units~\cite{10CFR50.54}. Becoming a reactor -operator requires several years of training. - -The persistent role of human error in nuclear safety incidents---despite decades -of improvements in training and procedures---provides the most compelling -motivation for formal automated control with mathematical safety guarantees. -Operators hold legal authority under 10 CFR Part 55 to make critical decisions, -including departing from normal regulations during emergencies. The Three Mile -Island (TMI) accident demonstrated how a combination of personnel error, design -deficiencies, and component failures led to partial meltdown when operators -misread confusing and contradictory readings and shut off the emergency water -system~\cite{Kemeny1979}. The President's Commission on TMI identified a -fundamental ambiguity: placing responsibility for safe power plant operations on -the licensee without formal verification that operators can fulfill this -responsibility does not guarantee safety. This tension between operational -flexibility and safety assurance remains unresolved: the person responsible for -reactor safety is often the root cause of failures. - -Multiple independent analyses converge on a striking statistic: 70--80\% of -nuclear power plant events are attributed to human error, versus approximately -20\% to equipment failures~\cite{WNA2020}. More significantly, the root cause of -all severe accidents at nuclear power plants---Three Mile Island, Chernobyl, and -Fukushima Daiichi---has been identified as poor safety management and safety -culture: primarily human factors~\cite{hogberg_root_2013}. A detailed analysis -of 190 events at Chinese nuclear power plants from -2007--2020~\cite{zhang_analysis_2025} found that 53\% of events involved active -errors, while 92\% were associated with latent errors---organizational and -systemic weaknesses that create conditions for failure. - - -\textbf{LIMITATION:} \textit{Human factors impose fundamental reliability limits -that cannot be overcome through training alone.} The persistent human -error contribution despite four decades of improvements demonstrates that these -limitations are fundamental rather than a remediable part of human-driven control. - -\subsection{HARDENS and Formal Methods} - -The High Assurance Rigorous Digital Engineering for Nuclear Safety (HARDENS) -project represents the most advanced application of formal methods to nuclear -reactor control systems to date~\cite{Kiniry2024}. - -HARDENS aimed to address a fundamental dilemma: existing U.S. nuclear control -rooms rely on analog technologies from the 1950s--60s. This technology is -obsolete compared to modern control systems and incurs significant risk and -cost. The NRC contracted Galois, a formal methods firm, to demonstrate that -Model-Based Systems Engineering and formal methods could design, verify, and -implement a complex protection system meeting regulatory criteria at a fraction -of typical cost. The project delivered a Reactor Trip System (RTS) -implementation with full traceability from NRC Request for Proposals and IEEE -standards through formal architecture specifications to verified software. - -HARDENS employed formal methods tools and techniques across the verification -hierarchy. High-level specifications used Lando, SysMLv2, and FRET (NASA Formal -Requirements Elicitation Tool) to capture stakeholder requirements, domain -engineering, certification requirements, and safety requirements. Requirements -were analyzed for consistency, completeness, and realizability using SAT and SMT -solvers. Executable formal models used Cryptol to create a behavioral model of -the entire RTS, including all subsystems, components, and limited digital twin -models of sensors, actuators, and compute infrastructure. Automatic code -synthesis generated verifiable C implementations and SystemVerilog hardware -implementations directly from Cryptol models---eliminating the traditional gap -between specification and implementation where errors commonly arise. - -Despite its accomplishments, HARDENS has a fundamental limitation directly -relevant to hybrid control synthesis: the project addressed only discrete -digital control logic without modeling or verifying continuous reactor dynamics. -The Reactor Trip System specification and verification covered discrete state -transitions (trip/no-trip decisions), digital sensor input processing through -discrete logic, and discrete actuation outputs (reactor trip commands). The -project did not address continuous dynamics of nuclear reactor physics. Real -reactor safety depends on the interaction between continuous -processes---temperature, pressure, neutron flux---evolving in response to -discrete control decisions. HARDENS verified the discrete controller in -isolation but not the closed-loop hybrid system behavior. - -\textbf{LIMITATION:} \textit{HARDENS addressed discrete control logic without -continuous dynamics or hybrid system verification.} Verifying discrete control -logic alone provides no guarantee that the closed-loop system exhibits desired -continuous behavior such as stability, convergence to setpoints, or maintained -safety margins. - -HARDENS produced a demonstrator system at Technology Readiness Level 2--3 -(analytical proof of concept with laboratory breadboard validation) rather than -a deployment-ready system validated through extended operational testing. The -NRC Final Report explicitly notes~\cite{Kiniry2024} that all material is -considered in development, not a finalized product, and that ``The demonstration -of its technical soundness was to be at a level consistent with satisfaction of -the current regulatory criteria, although with no explicit demonstration of how -regulatory requirements are met.'' The project did not include deployment in -actual nuclear facilities, testing with real reactor systems under operational -conditions, side-by-side validation with operational analog RTS systems, -systematic failure mode testing (radiation effects, electromagnetic -interference, temperature extremes), NRC licensing review, or human factors -validation with licensed operators in realistic control room scenarios. - -\textbf{LIMITATION:} \textit{HARDENS achieved TRL 2--3 without experimental -validation.} While formal verification provides mathematical correctness -guarantees for the implemented discrete logic, the gap between formal -verification and actual system deployment involves myriad practical -considerations: integration with legacy systems, long-term reliability -under harsh environments, human-system interaction in realistic -operational contexts, and regulatory acceptance of formal methods as -primary assurance evidence. diff --git a/3-research-approach/v1.tex b/3-research-approach/v1.tex deleted file mode 100644 index 25de1a4..0000000 --- a/3-research-approach/v1.tex +++ /dev/null @@ -1,285 +0,0 @@ -\section{Research Approach} - -This research will overcome the limitations of current practice to build -high-assurance hybrid control systems for critical infrastructure. Building -these systems with formal correctness guarantees requires three main thrusts: - -\begin{enumerate} - \item Translate operating procedures and requirements into temporal logic - formulae - - \item Create the discrete half of a hybrid controller using reactive synthesis - - \item Develop continuous controllers to operate between modes, and verify - their correctness - -\end{enumerate} - -Commercial nuclear power operations remain manually controlled by human -operators, yet the procedures they follow are highly prescriptive and -well-documented. This suggests that human operators may not be entirely -necessary given current technology. Written procedures and requirements are -sufficiently detailed that they may be translatable into logical formulae with -minimal effort. If successful, this approach enables automation of existing -procedures without system reengineering. To formalize these procedures, we will -use temporal logic, which captures system behaviors through temporal relations. - -The most efficient path for this translation is NASA's Formal Requirements -Elicitation Tool (FRET). FRET employs a specialized requirements language called -FRETish that restricts requirements to easily understood components while -eliminating ambiguity~\cite{katis_capture_2022}. FRETish bridges natural language -and mathematical specifications through a structured English-like syntax -automatically translatable to temporal logic. - -FRET enforces this structure by requiring all requirements to contain six -components: %CITE FRET MANUAL - -\begin{enumerate} - \item Scope: \textit{What modes does this requirement apply to?} - \item Condition: \textit{Scope plus additional specificity} - \item Component: \textit{What system element does this requirement affect?} - \item Shall - \item Timing: \textit{When does the response occur?} - \item Response: \textit{What action should be taken?} -\end{enumerate} - -FRET provides functionality to check system \textit{realizability}. Realizability -analysis determines whether written requirements are complete by examining the -six structural components. Complete requirements neither conflict with one -another nor leave any behavior undefined. Systems that are not realizable from -their procedure definitions and design requirements present problems beyond -autonomous control implementation. Such systems contain behavioral -inconsistencies---the physical equivalent of software bugs. Using FRET during -autonomous controller development allows systematic identification and -resolution of these errors. - -The second category of realizability issues involves undefined behaviors -typically left to human judgment during operations. This ambiguity is -undesirable for high-assurance systems, since even well-trained humans remain -prone to errors. Addressing these specification gaps in FRET during development -yields controllers free from these vulnerabilities. - -FRET exports requirements in temporal logic format compatible with reactive -synthesis tools. Linear Temporal Logic (LTL) builds upon modal logic's -foundational operators for necessity ($\Box$, ``box'') and possibility -($\Diamond$, ``diamond''), extending them to reason about temporal -behavior~\cite{baier_principles_2008}. The box operator $\Box$ expresses that a -property holds at all future times (necessarily always), while the diamond -operator $\Diamond$ expresses that a property holds at some future time -(possibly eventually). These are complemented by the next operator ($X$) for the -immediate successor state and the until operator ($U$) for expressing -persistence conditions. - -Consider a nuclear reactor SCRAM requirement expressed in natural language: -\textit{``If a high temperature alarm triggers, control rods must immediately -insert and remain inserted until operator reset.''} This plain language -requirement can be translated into a rigorous logical specification: - -\begin{equation} - \Box(HighTemp \rightarrow X(RodsInserted \wedge (\neg - RodsWithdrawn\ U\ OperatorReset))) -\end{equation} - -This specification precisely captures the temporal relationship between the -alarm condition, the required response, and the persistence requirement. The -necessity operator $\Box$ ensures this safety property holds throughout all -possible future system executions, while the next operator $X$ enforces -immediate response. The until operator $U$ maintains the state constraint until -the reset condition occurs. No ambiguity exists in this scenario because all -decisions are represented by discrete variables. Formulating operating rules in -this logic enforces finite, correct operation. - -Reactive synthesis is an active research field focused on generating discrete -controllers from temporal logic specifications. The term ``reactive'' indicates -that the system responds to environmental inputs to produce control outputs. -These synthesized systems are finite, with each node representing a unique -discrete state. The connections between nodes, called \textit{state -transitions}, specify the conditions under which the discrete controller moves -from state to state. This complete mapping of possible states and transitions -constitutes a \textit{discrete automaton}. Discrete automata can be represented -graphically as nodes (discrete states) with edges indicating transitions between -them. From the automaton graph, one can fully describe discrete system dynamics -and develop intuitive understanding of system behavior. Hybrid systems naturally -exhibit discrete behavior amenable to formal analysis through these finite state -representations. - -We will employ state-of-the-art reactive synthesis tools, particularly Strix, -which has demonstrated superior performance in the Reactive Synthesis -Competition (SYNTCOMP) through efficient parity game solving -algorithms~\cite{meyer_strix_2018,jacobs_reactive_2024}. Strix translates linear -temporal logic specifications into deterministic automata automatically while -maximizing generated automata quality. Once constructed, the automaton can be -implemented using standard programming control flow constructs. The graphical -representation enables inspection and facilitates communication with controls -programmers who lack formal methods expertise. - -We will use discrete automata to represent the switching behavior of our hybrid -system. This approach yields an important theoretical guarantee: because the -discrete automaton is synthesized entirely through automated tools from design -requirements and operating procedures, the automaton---and therefore our hybrid -switching behavior---is \textit{correct by construction}. Correctness of the -switching controller is paramount. Mode switching represents the primary -responsibility of human operators in control rooms today. Human operators -possess the advantage of real-time judgment: when mistakes occur, they can -correct them dynamically with capabilities extending beyond written procedures. -Autonomous control lacks this adaptive advantage. Instead, autonomous -controllers replacing human operators must not make switching errors between -continuous modes. Synthesizing controllers from logical specifications with -guaranteed correctness eliminates the possibility of switching errors. - -While discrete system components will be synthesized with correctness -guarantees, they represent only half of the complete system. Autonomous -controllers like those we are developing exhibit continuous dynamics within -discrete states. These systems, called hybrid systems, combine continuous -dynamics (flows) with discrete transitions (jumps). These dynamics can be -formally expressed as~\cite{branicky_multiple_1998}: - -\begin{equation} -\dot{x}(t) = f(x(t),q(t),u(t)) -\end{equation} - -\begin{equation} -q(k+1) = \nu(x(k),q(k),u(k)) -\end{equation} - -Here, $f(\cdot)$ defines the continuous dynamics while $\nu(\cdot)$ governs -discrete transitions. The continuous states $x$, discrete state $q$, and -control input $u$ interact to produce hybrid behavior. The discrete state $q$ -defines which continuous dynamics mode is currently active. Our focus centers -on continuous autonomous hybrid systems, where continuous states remain -unchanged during jumps---a property naturally exhibited by physical systems. For -example, a nuclear reactor switching from warm-up to load-following control -cannot instantaneously change its temperature or control rod position, but can -instantaneously change control laws. - -The approach described for producing discrete automata yields physics-agnostic -specifications representing only half of a complete hybrid autonomous -controller. These automata alone cannot define the full behavior of the control -systems we aim to construct. The continuous modes will be developed after -discrete automaton construction, leveraging the automaton structure and -transitions to design multiple smaller, specialized continuous controllers. - -Notably, translation into linear temporal logic creates barriers between -different control modes. Switching from one mode to another becomes a discrete -boolean variable. \(RodsInserted\) or \(HighTemp\) in the temporal -specifications are booleans, but in the real system they represent physical -features in the state space. These features mark where continuous control modes -end and begin; their definition is critical for determining which control mode -is active at any given time. Information about where in the state space these -conditions exist will be preserved from the original requirements and included -in continuous control mode development, but will not appear as numeric values in -discrete mode switching synthesis. - -The discrete automaton transitions are key to the supervisory behavior of the -autonomous controller. These transitions mark decision points for switching -between continuous control modes and define their strategic objectives. We -will classify three types of high-level continuous controller objectives based -on discrete mode transitions: - -\begin{enumerate} - \item \textbf{Stabilizing:} A stabilizing control mode has one primary - objective: maintaining the hybrid system within its current discrete mode. - This corresponds to steady-state normal operating modes, such as a - full-power load-following controller in a nuclear power plant. Stabilizing - modes can be identified from discrete automata as nodes with only incoming - transitions. - - \item \textbf{Transitory:} A transitory control mode has the primary goal of - transitioning the hybrid system from one discrete state to another. In - nuclear applications, this might represent a controlled warm-up procedure. - Transitory modes ultimately drive the system toward a stabilizing - steady-state mode. These modes may have secondary objectives within a - discrete state, such as maintaining specific temperature ramp rates before - reaching full-power operation. - - \item \textbf{Expulsory:} An expulsory mode is a specialized transitory mode - with additional safety constraints. Expulsory modes ensure the system is - directed to a safe stabilizing mode during failure conditions. For example, - if a transitory mode fails to achieve its intended transition, the - expulsory mode activates to immediately and irreversibly guide the system - toward a globally safe state. A reactor SCRAM exemplifies an expulsory - continuous mode: when initiated, it must reliably terminate the nuclear - reaction and direct the reactor toward stabilizing decay heat removal. - -\end{enumerate} - -Building continuous modes after constructing discrete automata enables local -controller design focused on satisfying discrete transitions. The primary -challenge in hybrid system verification is ensuring global stability across -transitions~\cite{branicky_multiple_1998}. Current techniques struggle with this -problem because dynamic discontinuities complicate -verification~\cite{bansal_hamilton-jacobi_2017,guernic_reachability_2009}. This -work alleviates these problems by designing continuous controllers specifically -with transitions in mind. Decomposing continuous modes according to their -required behavior at transition points avoids solving trajectories through the -entire hybrid system. Instead, local behavior information at transition -boundaries suffices. To ensure continuous modes satisfy their requirements, we -employ three main techniques: reachability analysis, assume-guarantee contracts, -and barrier certificates. - -Reachability analysis computes the reachable set of states for a given input -set. While trivial for linear continuous systems, recent advances have extended -reachability to complex nonlinear -systems~\cite{frehse_spaceex_2011,mitchell_time-dependent_2005}. We use -reachability to define continuous state ranges at discrete transition boundaries -and verify that requirements are satisfied within continuous modes. -Assume-guarantee contracts apply when continuous state boundaries are not -explicitly defined. For any given mode, the input range for reachability -analysis is defined by the output ranges of discrete modes that transition to -it. This compositional approach ensures each continuous controller is prepared -for its possible input range, enabling reachability analysis without global -system analysis. Finally, barrier certificates prove that mode transitions are -satisfied. Barrier certificates ensure that continuous modes on either side of a -transition behave appropriately by preventing system trajectories from crossing -a given barrier. Control barrier functions certify safety by establishing -differential inequality conditions that guarantee forward invariance of safe -sets~\cite{prajna_safety_2004}. For example, a barrier certificate can guarantee -that a transitory mode transferring control to a stabilizing mode will always -move away from the transition boundary, rather than destabilizing the target -stabilizing mode. - -This compositional approach has several advantages. First, this approach breaks -down autonomous controller design into smaller pieces. For designers of future -autonomous control systems, the barrier to entry is low, and design milestones -are clear due to the procedural nature of this research plan. Second, measurable -design progress also enables measurement of regulatory adherence. Each step in -this development procedure generates an artifact that can be independently -evaluated as proof of safety and performance. Finally, the compositional nature -of this development plan enables incremental refinement between control system -layers. For example, difficulty developing a continuous mode may reflect a -discrete automaton that is too restrictive, prompting refinement of system -design requirements. This synthesis between levels promotes broader -understanding of the autonomous controller. - -To demonstrate this methodology, we will develop an autonomous startup -controller for a Small Modular Advanced High Temperature Reactor (SmAHTR). We -have already developed a high-fidelity SmAHTR model in Simulink that captures -the thermal-hydraulic and neutron kinetics behavior essential for verifying -continuous controller performance under realistic plant dynamics. The -synthesized hybrid controller will be implemented on an Emerson Ovation control -system platform, representative of industry-standard control hardware deployed -in modern nuclear facilities. The Advanced Reactor Cyber Analysis and -Development Environment (ARCADE) suite will serve as the integration layer, -managing real-time communication between the Simulink simulation and the Ovation -controller. This hardware-in-the-loop configuration enables validation of the -controller implementation on actual industrial control equipment interfacing -with a realistic reactor simulation, assessing computational performance, -real-time execution constraints, and communication latency effects. -Demonstrating autonomous startup control on this representative platform will -establish both the theoretical validity and practical feasibility of the -synthesis methodology for deployment in actual small modular reactor systems. - -This unified approach addresses a fundamental gap in hybrid system design by -bridging formal methods and control theory through a systematic, tool-supported -methodology. Translating existing nuclear procedures into temporal logic, -synthesizing provably correct discrete switching logic, and developing verified -continuous controllers creates a complete framework for autonomous hybrid -control with mathematical guarantees. The result is an autonomous controller -that not only replicates human operator decision-making but does so with formal -assurance that switching logic is correct by construction and continuous -behavior satisfies safety requirements. This methodology transforms nuclear -reactor control from a manually intensive operation requiring constant human -oversight into a fully autonomous system with higher reliability than -human-operated alternatives. More broadly, this approach establishes a -replicable framework for developing high-assurance autonomous controllers in any -domain where operating procedures are well-documented and safety is paramount. diff --git a/3-research-approach/v2.tex b/3-research-approach/v2.tex deleted file mode 100644 index 9fc9cba..0000000 --- a/3-research-approach/v2.tex +++ /dev/null @@ -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? -% ripe partnership with Westinghouse -% Likely build a model with a ccng plant. They already have sophisticated models -% of them -% build controller with simplified model, then test with high fidelity digital -% twin - - - - -% -%%%%%%%%%% diff --git a/biblatex.sty b/biblatex.sty deleted file mode 100644 index e69de29..0000000 diff --git a/main.aux b/main.aux deleted file mode 100644 index 24afa03..0000000 --- a/main.aux +++ /dev/null @@ -1,248 +0,0 @@ -\relax -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Strong, direct opening. Sets scope immediately.}{i}{}\protected@file@percent } -\pgfsyspdfmark {pgfid1}{12703339}{44941311} -\pgfsyspdfmark {pgfid4}{31254300}{44915575} -\pgfsyspdfmark {pgfid5}{35899615}{44675891} -\@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 } -\pgfsyspdfmark {pgfid6}{24172130}{41140223} -\pgfsyspdfmark {pgfid9}{31254300}{41114487} -\pgfsyspdfmark {pgfid10}{35899615}{40874803} -\@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 } -\pgfsyspdfmark {pgfid11}{12694016}{39239679} -\pgfsyspdfmark {pgfid14}{31254300}{34211341} -\pgfsyspdfmark {pgfid15}{35899615}{33971657} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{yellow!60}{\textcolor {yellow!60}{o}}\ ``are needed that can'' — passive. Try: ``Autonomous control systems must safely manage...''}{i}{}\protected@file@percent } -\pgfsyspdfmark {pgfid16}{9008701}{35438591} -\pgfsyspdfmark {pgfid19}{31254300}{28106555} -\pgfsyspdfmark {pgfid20}{35899615}{27866871} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Clear statement of approach.}{i}{}\protected@file@percent } -\pgfsyspdfmark {pgfid21}{8902520}{32587775} -\pgfsyspdfmark {pgfid24}{31254300}{23730167} -\pgfsyspdfmark {pgfid25}{35899615}{23490483} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Nice parallel structure showing the gap.}{i}{}\protected@file@percent } -\pgfsyspdfmark {pgfid26}{11177092}{27836415} -\pgfsyspdfmark {pgfid29}{31254300}{22027649} -\pgfsyspdfmark {pgfid30}{35899615}{21787965} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{yellow!60}{\textcolor {yellow!60}{o}}\ This paragraph is dense. Consider breaking after the three stages, then a new paragraph for the compositional verification point and Emerson demo.}{i}{}\protected@file@percent } -\pgfsyspdfmark {pgfid31}{4749422}{12632063} -\pgfsyspdfmark {pgfid34}{31254300}{12606327} -\pgfsyspdfmark {pgfid35}{35899615}{12366643} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{orange!50}{\textcolor {orange!50}{o}}\ ``can be used for'' — weak. Try: ``...will demonstrate that autonomous control can manage complex nuclear power operations while maintaining safety guarantees.'' Or even stronger: ``...enables autonomous management of complex nuclear power operations with safety guarantees.''}{i}{}\protected@file@percent } -\pgfsyspdfmark {pgfid36}{26033217}{11681791} -\pgfsyspdfmark {pgfid39}{31254300}{6594471} -\pgfsyspdfmark {pgfid40}{35899615}{6354787} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Good practical framing — emphasizes accessibility.}{ii}{}\protected@file@percent } -\pgfsyspdfmark {pgfid41}{14318560}{45891583} -\pgfsyspdfmark {pgfid44}{31254300}{45865847} -\pgfsyspdfmark {pgfid45}{35899615}{45626163} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Strong industrial grounding — the ``platforms they already use'' point is compelling for adoption.}{ii}{}\protected@file@percent } -\pgfsyspdfmark {pgfid46}{6062694}{33538047} -\pgfsyspdfmark {pgfid49}{31254300}{33512311} -\pgfsyspdfmark {pgfid50}{35899615}{33272627} -\@writefile{toc}{\contentsline {section}{Contents}{iii}{}\protected@file@percent } -\@writefile{toc}{\contentsline {section}{\numberline {1}Goals and Outcomes}{1}{}\protected@file@percent } -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Clear thesis statement. Gets right to it.}{1}{}\protected@file@percent } -\pgfsyspdfmark {pgfid51}{7637198}{43613118} -\pgfsyspdfmark {pgfid54}{31254300}{43587382} -\pgfsyspdfmark {pgfid55}{35899615}{43347698} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Stakes established immediately — good hook.}{1}{}\protected@file@percent } -\pgfsyspdfmark {pgfid56}{12512020}{40762302} -\pgfsyspdfmark {pgfid59}{31254300}{40736566} -\pgfsyspdfmark {pgfid60}{35899615}{40496882} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{yellow!60}{\textcolor {yellow!60}{o}}\ The ``and'' here joins two distinct issues (autonomy barrier + economics). 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The ``four decades'' point drives it home.}{4}{}\protected@file@percent } -\pgfsyspdfmark {pgfid136}{4792689}{5302953} -\pgfsyspdfmark {pgfid139}{31254300}{4760899} -\pgfsyspdfmark {pgfid140}{35899615}{4521215} -\citation{Kiniry2024} -\@writefile{toc}{\contentsline {subsection}{\numberline {2.3}Formal Methods}{5}{}\protected@file@percent } -\@writefile{toc}{\contentsline {subsubsection}{\numberline {2.3.1}HARDENS}{5}{}\protected@file@percent } -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Good technical depth on HARDENS toolchain.}{5}{}\protected@file@percent } -\pgfsyspdfmark {pgfid141}{20999294}{21457577} -\pgfsyspdfmark {pgfid144}{31254300}{21431841} -\pgfsyspdfmark {pgfid145}{35899615}{21192157} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Clear articulation of the gap your work fills.}{5}{}\protected@file@percent } -\pgfsyspdfmark {pgfid146}{23128957}{11004585} -\pgfsyspdfmark {pgfid149}{31254300}{10978849} -\pgfsyspdfmark {pgfid150}{35899615}{10739165} -\@writefile{toc}{\contentsline {subsubsection}{\numberline {2.3.2}Sequent Calculus and Differential Dynamic Logic}{6}{}\protected@file@percent } -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{red!40}{\textcolor {red!40}{o}}\ Typo: ``ivariant'' should be ``invariant''}{6}{}\protected@file@percent } -\pgfsyspdfmark {pgfid151}{4749422}{20507305} -\pgfsyspdfmark {pgfid154}{31254300}{20481569} -\pgfsyspdfmark {pgfid155}{35899615}{20241885} -\@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 } -\pgfsyspdfmark {pgfid156}{18750152}{12905129} -\pgfsyspdfmark {pgfid159}{31254300}{12879393} -\pgfsyspdfmark {pgfid160}{35899615}{12639709} -\@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. 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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 } -\pgfsyspdfmark {pgfid166}{14192475}{45403152} -\citation{HANDBOOK ON HYBRID SYSTEMS} -\@writefile{toc}{\contentsline {section}{\numberline {3}Research Approach}{8}{}\protected@file@percent } -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{orange!50}{\textcolor {orange!50}{o}}\ Missing space before ``Our}{8}{}\protected@file@percent } -\pgfsyspdfmark {pgfid167}{21351522}{32209854} -\pgfsyspdfmark {pgfid170}{31254300}{32184118} -\pgfsyspdfmark {pgfid171}{35899615}{31944434} -\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces Simplified hybrid automaton for reactor startup. Each discrete state $q_i$ has associated continuous dynamics $f_i$. Guard conditions on transitions (e.g., $T_{avg} > T_{min}$) are predicates over continuous state. Invariant violations ($\neg Inv_i$) trigger transitions to the SCRAM state. 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Brief justification helps.}{19}{}\protected@file@percent } -\pgfsyspdfmark {pgfid199}{15785403}{27497812} -\pgfsyspdfmark {pgfid202}{31254300}{27472076} -\pgfsyspdfmark {pgfid203}{35899615}{27232392} -\@writefile{tdo}{\contentsline {todo}{\fcolorbox {black}{green!40}{\textcolor {green!40}{o}}\ Clear success criteria. 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Rep. NUREG-0899, U.S. Nuclear Regulatory Commission, 1982. - -\bibitem{10CFR50.34} -{U.S. Nuclear Regulatory Commission}, ``{10 CFR Part 50.34}.'' Code of Federal Regulations. - -\bibitem{10CFR55.59} -{U.S. Nuclear Regulatory Commission}, ``{10 CFR Part 55.59}.'' Code of Federal Regulations. - -\bibitem{WRPS.Description} -``{Westinghouse RPS System Description},'' tech. rep., Westinghouse Electric Corporation. - -\bibitem{gentillon_westinghouse_1999} -C.~D. Gentillon, D.~Marksberry, D.~Rasmuson, M.~B. Calley, S.~A. Eide, and T.~Wierman, ``Westinghouse reactor protection system unavailability, 1984-1995.'' -\newblock Number: {INEEL}/{CON}-99-00374 Publisher: Idaho National Engineering and Environmental Laboratory. - -\bibitem{operator_statistics} -{U.S. Nuclear Regulatory Commission}, ``{Operator Licensing}.'' \url{https://www.nrc.gov/reactors/operator-licensing}. - -\bibitem{10CFR55} -{U.S. Nuclear Regulatory Commission}, ``{Part 55—Operators' Licenses}.'' \url{https://www.nrc.gov/reading-rm/doc-collections/cfr/part055/full-text}. - -\bibitem{10CFR50.54} -{U.S. Nuclear Regulatory Commission}, ``{§ 50.54 Conditions of Licenses}.'' \url{https://www.nrc.gov/reading-rm/doc-collections/cfr/part050/part050-0054}. - -\bibitem{Kemeny1979} -J.~G. Kemeny {\em et~al.}, ``Report of the president's commission on the accident at three mile island,'' tech. rep., President's Commission on the Accident at Three Mile Island, October 1979. - -\bibitem{WNA2020} -{World Nuclear Association}, ``Safety of nuclear power reactors.'' \url{https://www.world-nuclear.org/information-library/safety-and-security/safety-of-plants/safety-of-nuclear-power-reactors.aspx}, 2020. - -\bibitem{hogberg_root_2013} -L.~Högberg, ``Root causes and impacts of severe accidents at large nuclear power plants,'' vol.~42, no.~3, pp.~267--284. - -\bibitem{zhang_analysis_2025} -M.~Zhang, L.~Dai, W.~Chen, and E.~Pang, ``Analysis of human errors in nuclear power plant event reports,'' vol.~57, no.~10, p.~103687. - -\bibitem{Kiniry2024} -J.~Kiniry, A.~Bakst, S.~Hansen, M.~Podhradsky, and A.~Bivin, ``High assurance rigorous digital engineering for nuclear safety (hardens) final technical report,'' Tech. Rep. TLR-RES-RES/DE-2024-005, Galois, Inc. / U.S. Nuclear Regulatory Commission, 2024. -\newblock NRC Contract 31310021C0014. - -\bibitem{eia_lcoe_2022} -{U.S. Energy Information Administration}, ``Levelized costs of new generation resources in the annual energy outlook 2022,'' report, U.S. Energy Information Administration, March 2022. -\newblock See Table 1b, page 9. - -\bibitem{eesi_datacenter_2024} -{Environmental and Energy Study Institute}, ``Data center energy needs are upending power grids and threatening the climate.'' Web article, 2024. -\newblock Accessed: 2025-09-29. - -\end{thebibliography} diff --git a/main.blg b/main.blg deleted file mode 100644 index 971eb21..0000000 --- a/main.blg +++ /dev/null @@ -1,67 +0,0 @@ -This is BibTeX, Version 0.99d (TeX Live 2025) -Capacity: max_strings=200000, hash_size=200000, hash_prime=170003 -The top-level auxiliary file: main.aux -White space in argument---line 156 of file main.aux - : \citation{HANDBOOK - : ON HYBRID SYSTEMS} -I'm skipping whatever remains of this command -White space in argument---line 171 of file main.aux - : \citation{MANYUS - : THESIS} -I'm skipping whatever remains of this command -The style file: ieeetr.bst -Database file #1: references.bib -Warning--entry type for "gentillon_westinghouse_1999" isn't style-file defined ---line 32 of file references.bib -Warning--entry type for "operator_statistics" isn't style-file defined ---line 45 of file references.bib -Warning--entry type for "10CFR50.54" isn't style-file defined ---line 59 of file 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{textsize}{\renewcommand{\@todonotes@textsize}{#1}} -\define@key{todonotes.sty}% - {size}{\renewcommand{\@todonotes@textsize}{#1}} -\newif\if@todonotes@shadowlibraryloaded -\@todonotes@shadowlibraryloadedfalse -\DeclareOptionX{loadshadowlibrary}{% - \usetikzlibrary{shadows}% - \@todonotes@shadowlibraryloadedtrue} -\newcommand{\@todonotes@shadowenabledbydefault}{noshadow} -\DeclareOptionX{shadow}{% - \renewcommand{\@todonotes@shadowenabledbydefault}{shadow}} -\define@key{todonotes.sty}% - {figwidth}{\renewcommand{\@todonotes@figwidth}{#1}} -\define@key{todonotes.sty}% - {figheight}{\renewcommand{\@todonotes@figheight}{#1}} -\define@key{todonotes.sty}% - {figcolor}{\renewcommand{\@todonotes@figcolor}{#1}} -\ProcessOptionsX* -\if@todonotes@disabled -\else -\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}% -\newcommand{\@todonotes@author}{}% -\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'.