133 lines
3.7 KiB
Markdown
133 lines
3.7 KiB
Markdown
# Notes on [[thesis-ideas-2025-07-30]]
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What needs done:
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- [X] 1 needs edited and reviewed
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- [X] Review outcomes. I really don't like outcome
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number 1.
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- [X] Review and edit 2
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- [X] Review and edit 3
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- [X] Write an impact section
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- [X] Review and edit 4
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- [X] Needs more goal
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- [X] Review and edit 5
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- [X] Review and edit 6
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## Discussion Cheat Sheet
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Chat helped with this
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### Temporal Logic Specifications for Autonomous Controller
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Synthesis
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- **Feasibility:** ★★★★★
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- **Impact:** ★★★★☆
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- **Merit:** ★★★★★
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**Scope Boundaries:** Focus on one subsystem (e.g., rod
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supervisory control), one specification language, and
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existing synthesis tools (TLA+, FRET, Strix).
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**Key Risk:** State space explosion during synthesis could
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make controller generation intractable.
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**Mitigation Strategy:** Use bounded abstractions,
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compositional synthesis, and validate the synthesized
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controller on a high-fidelity simulation before scaling up.
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---
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### Formally Verified Runtime Monitoring and Fallback
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- **Feasibility:** ★★★★★
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- **Impact:** ★★★★☆
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- **Merit:** ★★★★☆
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**Scope Boundaries:** Single primary controller with one
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fallback controller, one LTL specification set, and
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integration with ARCADE.
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**Key Risk:** Limited novelty if scoped too narrowly or
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perceived as a straightforward engineering integration.
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**Mitigation Strategy:** Emphasize automation of
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specification-to-monitor translation, nuclear-specific
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verification, and proof artifact generation to show novelty.
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---
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### Verified Adaptive Control
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- **Feasibility:** ★★★★☆
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- **Impact:** ★★★★☆
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- **Merit:** ★★★★☆
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**Scope Boundaries:** One subsystem (rod control), one
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adaptation method, runtime contract monitoring only.
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**Key Risk:** Over-scoping to multiple adaptation targets
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or attempting plant-wide adaptive control.
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**Mitigation Strategy:** Pick representative degradation
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types (e.g., HX fouling, pump efficiency drop); limit
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adaptation to parameter tuning inside pre-verified safe
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envelopes.
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---
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### Integrating Shielding into Nuclear Power Control
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- **Feasibility:** ★★★★☆
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- **Impact:** ★★★★☆
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- **Merit:** ★★★★☆
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**Scope Boundaries:** One ML control task (e.g., startup or
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load-following), one shield synthesis approach from temporal
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logic.
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**Key Risk:** Regulatory and industry reluctance toward ML
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in safety-critical nuclear applications.
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**Mitigation Strategy:** Demonstrate shielding benefits for
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both ML and conventional controllers to broaden acceptance.
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---
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### Improved: Data-Driven Fault Detection Using
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High-Assurance Digital Twins
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- **Feasibility:** ★★★★☆
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- **Impact:** ★★★★☆
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- **Merit:** ★★★★☆
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**Scope Boundaries:** Limit to 3–4 high-impact fault types
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(e.g., secondary coolant loss, HX fouling, sensor drift),
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residual-based detection with physics-informed models.
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**Key Risk:** Scope creep into too many fault scenarios or
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overly complex ML methods.
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**Mitigation Strategy:** Focus on explainable,
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physics-informed detection; tie mitigation responses
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directly to NRC-aligned safety procedures.
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---
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### Formally Verified Neural Network Control of Control Rod
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System
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- **Feasibility:** ★★★☆☆
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- **Impact:** ★★★★☆
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- **Merit:** ★★★☆☆
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**Scope Boundaries:** Small, well-structured NN
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architecture; bounded state space; one primary safety
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property (shutdown margin).
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**Key Risk:** Scalability issues in SMT/MILP verification
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for larger or more complex networks.
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**Mitigation Strategy:** Constrain network size and
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complexity; limit verification domain to tractable operating
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regions; focus on proof-of-concept that shows
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nuclear-specific applicability.
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