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Advances in Model Order Reduction Techniques

Model Order Reduction is experiencing continuous advances for becoming more efficient, more robust and for embracing challenging applications of scientific and technological relevance. The present issue is expected grouping recent advanced techniques pushing forward the limits of nowadays model reduction techniques in engineering sciences. It is expected covering techniques like POD, RB and PGD techniques and their application of complex entering problems, covering aspects related to their mathematical foundations, the algorithmic aspects and their applicative potential.

Edited by: Pierre Ladeveze, Francisco Chinesta, and Tomas Chacon Rebollo

  1. Multi-scale processes governed on each scale by separate principles for evolution or equilibrium are coupled by matching the stored energy and dissipation in line with the Hill-Mandel principle. We are interes...

    Authors: Muhammad S. Sarfaraz, Bojana V. Rosić, Hermann G. Matthies and Adnan Ibrahimbegović

    Citation: Advanced Modeling and Simulation in Engineering Sciences 2020 7:50

    Content type: Research article

    Published on:

  2. Parametric entities appear in many contexts, be it in optimisation, control, modelling of random quantities, or uncertainty quantification. These are all fields where reduced order models (ROMs) have a place t...

    Authors: Hermann G. Matthies and Roger Ohayon

    Citation: Advanced Modeling and Simulation in Engineering Sciences 2020 7:41

    Content type: Research article

    Published on:

  3. In this paper we present a collection of techniques used to formulate a projection-based reduced order model (ROM) for zero Mach limit thermally coupled Navier–Stokes equations. The formulation derives from a ...

    Authors: Ricardo Reyes, Ramon Codina, Joan Baiges and Sergio Idelsohn

    Citation: Advanced Modeling and Simulation in Engineering Sciences 2018 5:28

    Content type: Research article

    Published on: