@sophiehuiberts With uncertainty quantification we're sort of doing the reverse. Take a physical model, look at parameters in the model, the physics, and scenarios that aren't firmly known or are expected to vary, then run 93 sensitivity cases to see where the risk envelope lies around a nominal case. Not so much optimization or goal-seeking bur it gets us thinking about the limits of our tools, methods, and data.