150 lines
4.3 KiB
Markdown
150 lines
4.3 KiB
Markdown
# Thesis Ideas 2025-07-30
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Following our group meeting from Monday, July 28th, Dan
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suggested I write down 6 ideas, and from them we shall
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figure out a possible topic idea that I can really start
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working on.
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I used ChatGPT to do some of the heavy lifting based on the
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papers I've been reading, and leveraged the 'deep research'
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feature. Here are some of my favorite ideas, broken down
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into goals, outcomes, impact, and related papers.
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## **Integrating Shielding into Nuclear Power Control**
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### Goal:
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The goal of this research is to develop machine learning
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control algorithms for nuclear power applications with
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strict safety guarantees.
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### Outcomes:
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If this research is successful, I will have accomplished the
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following:
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1. Develop controller shielding methods for nuclear power
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contexts
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2. Provide concrete safety guarantees for autonomous control
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of a nuclear asset.
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3. ??? <!TODO!>
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### Impact:
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Machine learning based systems have been shown to be more
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efficient than typical PID based controllers, and are able to
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learn more complex objective functions than a typical controller
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can. The problem with these controllers though is that they are
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often unexplainable. This is not acceptable for high assurance
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applications, where slight perturbations on inputs can yield
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wildly different outputs. Shielding can solve this problem,
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helping ensure safety of ML based controllers while not limiting
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their development or construction.
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### Relevant Papers
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[[safe-reinforcement-learning-via-shielding]]
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[[evaluating-robustness-of-neural-networks-with-mixed-integer-programming]]
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___________________________________________________________
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## **Formally Verified Neural Network Control of Control Rod System**
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### Goals:
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The goal of this research is to use formal methods to ensure that
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a neural network based control rod controller will never violate
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safety guarantees of a reactor trip system. To do this, a
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satisfiability modulo theory method will be applied to
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exhaustively search the network for potential failure modes.
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### Outcomes:
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If this research is successful, I will have accomplished the
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following:
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- Build a neural network controller for real time control of a
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control rod system.
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- Formalize safety guarantees of shutdown margin in a
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satisfiability modulo theory embedding
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- Formally verify that the neural network based controller will
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not violate any shutdown margin restrictions
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### Impact:
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SMT solvers and MILP formulations have been applied to neural
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networks to ensure that the network is resilient to input
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perturbations. I think we can expand this to more general
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considerations of the state space, especially when there are a
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relatively small number of states such as in power contexts. The
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benefit of this system is that we would get closer to saying
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neural network based systems can be high assurance for physical
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systems.
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### Related Papers:
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[[reluplex-an-efficient-smt-solver-for-verifying-deep-neural-networks]]
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[[evaluating-robustness-of-neural-networks-with-mixed-integer-programming]]
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[[formal-verification-of-neural-network-controlled-autonomous-systems]]
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___________________________________________________________
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## **Temporal Logic Specifications for Autonomous Controller Shield Synthesis**
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(3)
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### Goals:
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If this research is successful, we will be able to generate
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autonomous controllers that provably adhere to specifications
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written with temporal logic automatically.
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### Outcomes:
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- Create an intermediary shield that mediates signals between an
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optimal control system and the physical plant
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-
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### Impact:
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### Related Papers:
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[[enhancing-cyber-physical-system-dependability-via-synthesis-challenges-and-future-directions]]
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[[safe-reinforcement-learning-via-shielding]]
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## **Formally Verified Runtime Monitoring and Fallback**
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(4)
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### Goals:
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### Outcomes:
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### Impact:
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### Related Papers:
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___________________________________________________________
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## **Data-Driven Model Verification for High-Assurance Digital Twins**
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(8)
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### Goals:
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### Outcomes:
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### Impact:
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### Related Papers:
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___________________________________________________________
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## **Verified Adaptive Control**
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(10)
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### Goals:
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### Outcomes:
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### Impact:
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### Related Papers:
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