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+# A random thesis idea I had
+
+This is kind of connected to the high assurance digital twin
+idea, but I am currently in the middle of reading and needed
+to get this out of my head.
+
+Here's the situation:
+
+Manyu's work made a lot of progress to apply contract based
+formal methods to nuclear power. To do this, an assumption
+of a certain components output is fed into the input of the
+next component. Math is done, and then the output of that
+component becomes a guarantee, which is then the assumption
+for the next component in line after that.
+
+But here's a question: how do you know that your assumptions
+and guarantee's are valid on a real system, in real time?
+These contracts are based on having a model of the system
+with which you can evaluate the assumptions/guarantee pairs.
+But, real systems never will line up perfectly with a model,
+and over time or different conditions, will absolutely have
+different physical behaviors. Knowing if the contracts still
+hold for the real system is a significant problem.
+
+Here's where some online modeling in simulation can come in.
+Perhaps, we can use a digital twin to estimate what the
+critical model parameters for the contract methods are in
+the real system. This is probably most easily accomplished
+with either a physics informed neural network (PINN) or some
+sort of particle filter bayesian nonsense. Once those
+parameters are identified, we can reevaluate the contracts
+to know a) if our system is safe, b) what our new
+assumptions and safe operating range are, and c) make
+strategic decisions about the plant control if necessary. 
+
+This relates to the [autonomous framework paper](/Zettelkasten/Literature%20Notes/albertiAutomationLevelsNuclear2023.md) 
+that talks about getting to higher levels of automation.
+Level 3 is exactly this, the automated reactor operation
+system being able to detect and diagnose what an error is.