Canonical technical pattern for systems that combine physics, engineering equations, simulation outputs, power curves, constraints, or scientific priors with ML/statistical estimation to forecast performance, estimate scenarios, or improve engineering decisions. Map when model-based or AI-assisted performance estimation is central; use surrogate-modeling instead when the primary claim is a learned replacement for an expensive simulator; do not map deterministic spreadsheets or fixed engineering calculators.