A novel model reduction technique for static systems is presented. The method is developed using a goal‐oriented framework, and it extends the concept of snapshots for proper orthogonal decomposition (POD) to include (sensitivity) derivatives of the …
A Petrov--Galerkin projection method is proposed for reducing the dimension of a discrete non‐linear static or dynamic computational model in view of enabling its processing in real time. The right reduced‐order basis is chosen to be invariant and is …
Reduced basis methods are powerful tools that can significantly speed up computationally expensive analyses in a variety of 'many-query' and real-time applications, including de- sign optimization. Unfortunately, these techniques produce …