Parametric optimisation study #182
Description
Instead of a "deterministic" simulation, users should be able to set parameters as free parameters and run parametric optimisation studies based on a set of constraints and goals.
Examples:
- In the ARC fuel cycle simulation, minimise the startup storage inventory while ensuring the total energy produced in the first year is greater than X.
- Find the mass transfer coefficients that fit the tritium release curve that was experimentally measured (see this tutorial)
UI needs:
- Set a parameter as free parameter: similar to Parametric studies #181 users would be able to set a parameter as "free"
- Give bounds to a parameter (eg. parameter A cannot be negative)
- Define a cost function/error python function
def error(p): ... return e - Select an optimiser (from
scipy.optimisemethods?)