Abstract
The G-Scheme is a well established framework for multi-scale adaptive model reduction, whose effectiveness was demonstrated with reference to a number of test models, together with an identification of the critical areas that were in need of further theoretical and computational refinement. In this communication, we report on how we enhanced the solver performance. Two new features involving (i) the criteria to identify the fast and slow subspace dimensions, and (ii) a criterion to decide if and when the reuse of the CSP Basis is feasible without deteriorating the overall performance of the solver, have been proved able to increase significantly the computational efficiency of the solver without sacrificing its accuracy.
Published Version
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