Model reduction applied to square to rectangular martensitic transformations using proper orthogonal decomposition

Model Reduction via Proper Orthogonal Decomposition

Model Reduction by Proper Orthogonal Decomposition (POD)

Mathematical models for human tissue and blood flow both represent time dependent nonlinear partial differential equations in three space dimensions. Their numerical solution based on appropriate space/time discretizations requires computational times that even when using state-of-the-art algorithmic solvers are far from being acceptable for real time OR scenarios. A way to overcome this diffic...

Model Reduction for fluids, Using Balanced Proper Orthogonal Decomposition

Many of the tools of dynamical systems and control theory have gone largely unused for fluids, because the governing equations are so dynamically complex, both high-dimensional and nonlinear. Model reduction involves finding low-dimensional models that approximate the full high-dimensional dynamics. This paper compares three different methods of model reduction: proper orthogonal decomposition ...

Balanced Model Reduction via the Proper Orthogonal Decomposition

A new method for performing a balanced reduction of a high-order linear system is presented. The technique combines the proper orthogonal decomposition and concepts from balanced realization theory. The method of snapshots is used to obtain low-rank, reduced-rangeapproximationsto the system controllabilityand observability grammiansin either the timeor frequency domain.The approximationsare the...

Model Reduction of Population Balance Systems by Proper Orthogonal Decomposition

Zusammenfassung Der Beitrag beschreibt den Einsatz der Proper Orthogonal Decomposition (POD) für die Modellreduktion von Partikelprozessen in fluider Strömung. Diese Prozessklasse ist von großer Bedeutung für die chemische und pharmazeutische Industrie. Physikalische Modelle solcher Prozesse sind häufig sehr komplex und für Regelungsaufgaben wenig geeignet. POD bietet hier eine attraktive Mögli...