Surrogate Modelling of Potential Progressive Coating Loss Effects in Novel Aero-Engine CMC Seal Segments

Ceramic-matrix-composite (CMC) turbine seal segments lose their gas-side coatings in service. Assessing one loss configuration takes a thermal and a mechanical finite-element solve, and there are too many admissible configurations to solve them all. A surrogate makes it affordable and follows it as the loss progresses. We build one on 5452 solves of a published seal-segment model with coating added, specify its toolchain in full, and compare four digital-twin techniques: a neural network against reduced-basis and full-field Gaussian processes. Swapping a lost cell to a higher-conductivity material instead of deleting it costs about 1∘C in the mean but 100∘C at the rim, an error that stays on the sacrificial coating and under-reads the substrate by at most 11.5∘C. That error is one-signed: a bias to be carried, not a scatter. On a reduced basis the basis binds, not the regressor: neither model improves with data. Restricting the design to the service-marked loss zones is worth 3.4× on one layer and 3.1 to 4.9× on two. The recommended full-field twin returns the peak coating-interface temperature within 0.23∘C at 3 ms per pattern, but a free superposition baseline beats it in the maintenance regime.