Finite element based Model Order Reduction for parametrized one-way coupled steady state linear thermo-mechanical problems

This contribution focuses on the development of Model Order Reduction (MOR) for one-way coupled steady state linear thermo-mechanical problems in a finite element setting. We apply Proper Orthogonal Decomposition (POD) computation reduced basis space. On other hand, evaluation modal coefficients, we use two different methodologies: one based Galerkin projection (G) and Artificial Neural Network (ANN). aim to compare POD-G POD-ANN terms relevant features including errors computational efficiency. In this context, both physical geometrical parametrization are considered. also carry out validation Full (FOM) customized benchmarks order provide complete pipeline. The framework proposed is applied industrial problem related investigation phenomena arising blast furnace hearth walls.