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SUMMARY A high power dissipation density in today's miniature electronic/mechanical systems makes on-chip thermal management very important. In order to achieve quick to evaluate, yet accurate electro-thermal models, needed for the thermal management of microsystems, a model order reduction is necessary. In this paper, we present an automatic,(More)
An overview of electro-thermal modeling of microsystems is presented. We consider the most important coupling between thermal and electrical phenomena, and then focus on the indus-try's central concern, that of Joule heating. A description of different solution approaches for the heat transfer partial differential equation, which constitutes the central(More)
In this paper, we present three heuristic error indicators for the iterative model order reduction of electro-thermal MEMS models via the Arnoldi algorithm. Such error indicators help a designer to choose an optimal order of the reduced model, required to achieve a desired accuracy, and hence allow a completely automatic extraction of heat-transfer(More)
Different methodologies to extract a dynamic compact thermal model of a microelectronic or MEMS device have been developed in recent years. They include strategies based on data fitting, a time-constant spectrum, modal analysis and finally formal model reduction. Researchers seek compact thermal multiport representation for system level simulation. However,(More)
In this paper we present an automatic, Arnoldi-based model order reduction of a 3D electro-thermal model for a novel sensor device. Model order reduction is essential for achieving a quickly evaluable, yet still accurate, macromodel of the device, needed for system-level simulation. We present below numerical simulation results of the full-scale finite(More)
A modelling strategy for a microthruster array based on solid fuel is presented. We review the theory of operation of the microthruster that includes an electro-thermal process, ignition, sustained combustion, membrane rupture and gas dynamics. The recommended level of theory is chosen to answer practical engineering questions, so as to make the recommended(More)
Model reduction is a very helpful tool to generate compact models for system-level simulation. Quite often however, system matrices depend on design parameters and the new goal is not only to reduce the original system but also to preserve system parameters in the symbolic form during model reduction. We introduce multivariate moment matching as a possible(More)
This work presents the application of mathematical methods of parametric model order reduction (pMOR) for automatic generation of the highly accurate, parametric compact models of radio-frequency micro-devices. More specifically, the miniaturized Faraday-induction-based magnetic resonance sensor is considered. Unlike conventional approaches, when magnetic(More)