diff --git a/Zettelkasten/Permanent Notes/thesis-ideas.md b/Zettelkasten/Permanent Notes/thesis-ideas.md
index 652940cc8..8d33fec52 100644
--- a/Zettelkasten/Permanent Notes/thesis-ideas.md	
+++ b/Zettelkasten/Permanent Notes/thesis-ideas.md	
@@ -323,45 +323,50 @@ ___________________________________________________________
 
 ### Goals:
 
-The goal of this research is to create an adaptive controller
-that can adjust to system dynamics changes over time to maintain
-an optimal control, while using formal methods to provide strong
-safety guarantees about the malleable control law.
+The goal of this research is to create an adaptive
+controller for a reactor control system that can adjust to
+system dynamics changes from component degredation or
+post-maintenance effects to maintain an optimal control,
+while using formal methods to provide strong safety
+guarantees that all adaptations remain within verified
+safety limits.
 
 ### Outcomes:
 
 For this research to be successful, I will accomplish the
 following:
 
-- Create a simulation suite for the Small Modular Advanced High
-Temperature Reactor (SmAHTR) to simulate component degradation
-such as heat exchanger blockages and fuel concentration burn-up.*
+1. Create a simulation suite for the Small Modular Advanced
+   High Temperature Reactor (SmAHTR) to simulate component
+degradation such as heat exchanger fouling or chemistry
+changes following maintenance.
 
-- Create an adaptive control rod controller to maximize load following
-precision for a simulated power grid demand.
+2. Create a parameter adaptive control rod controller to maximize
+   load following precision for a simulated power grid
+demand.
 
-- Use contract based verification at runtime to ensure that
-learned parameters for the adaptive controller remain within
-safety specification limits
-
-*Is this actually even a problem for SmAHTR? Figuring the fuel is
-suspended in the salt I'd assume chemistry is pretty strictly
-controlled. I'm sure I can find other examples.
+3. Use contract based verification at runtime to ensure that
+   learned parameters for the adaptive controller remain
+within safety specification limits.
 
 ### Impact:
 
-Certain reactor control systems are already automatic systems,
-such as constant temperature or pressure controls for operating
-at steady state. These simple controllers are able to follow load
-changes from the power grid on their own, but over will lose
-efficiency as the underlying plant mechanics become less
-efficient, or maintenance is performed and components are
-refreshed. For nuclear power contexts, fine control is ideal to
-maximize profits and to minimize energy wasteage. This is not an
-easy problem to solve, however, as the dynamics of the underlying
-plant are constantly changing. Adaptive control can help address
-this issue, but learnable controllers must come with guarantees
-of safety in order to be attractive to the nuclear industry.
+Many reactor control systems already automate steady-state
+operation and basic load-following, but their performance
+degrades over time as plant equipment wears or is replaced.
+Without retuning, controllers may become less efficient,
+leading to suboptimal thermal efficiency, reduced grid
+responsiveness, and unnecessary operational margins that can
+lead to unnecessary shutdowns. Adaptive control can address
+these challenges by continuously tuning control parameters
+to match the evolving plant dynamics. However, without
+provable safety guarantees, such adaptation is unlikely to
+be accepted in high-assurance domains without proof of
+controller safety. By embedding formal, contract-based
+verification into the adaptation process, this work will
+enable the use of responsive and efficient control
+strategies that maintain regulatory compliance while
+improving plant performance and availability.
 
 ### Related Papers: