A high power dissipation density in todays miniature electronic/mechanical systems makes on-chip thermal management very important. In order to achieve quick to evaluate, yet accurate thermo-electric models, needed for the thermal management of microsystems, a model order reduction is necessary. Recently the Krylov-subspace-based methods have been used for automatic model order reduction. In this paper, we use Krylov-subspace methods for order reduction of thermo-electric MEMS model, illustrated by a novel type of micropropulsion device. Comparison between different moment-matching algorithms including a new two-sided Arnoldi algorithm, is performed.
Journal: TechConnect Briefs
Volume: 2, Technical Proceedings of the 2003 Nanotechnology Conference and Trade Show, Volume 2
Published: February 23, 2003
Pages: 582 - 585
Industry sectors: Advanced Materials & Manufacturing | Sensors, MEMS, Electronics
Topics: Informatics, Modeling & Simulation