Download Scientific Computing in Electrical Engineering: SCEE 2014, by Andreas Bartel, Markus Clemens, Michael Günther, E. Jan W. PDF
By Andreas Bartel, Markus Clemens, Michael Günther, E. Jan W. ter Maten
This booklet is a suite of chosen papers offered on the tenth overseas convention on medical Computing in electric Engineering (SCEE), held in Wuppertal, Germany in 2014. The ebook is split into 5 components, reflecting the most instructions of SCEE 2014: 1. equipment Modeling, electrical Circuits and Simulation, 2. Computational Electromagnetics, three. Coupled difficulties, four. version Order relief, and five. Uncertainty Quantification. each one half starts off with a basic advent by means of the particular papers.
the purpose of the SCEE 2014 convention was once to compile scientists from academia and undefined, mathematicians, electric engineers, desktop scientists, and physicists, with the objective of fostering in depth discussions on industrially proper mathematical difficulties, with an emphasis at the modeling and numerical simulation of digital circuits and units, electromagnetic fields, and paired difficulties. The methodological concentration used to be on version order relief and uncertainty quantification.
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The abstracts and papers during this quantity have been awarded on the 5th Annual foreign Computing and Combinatorics convention (COCOON ’99), which used to be held in Tokyo, Japan from July 26 to twenty-eight, 1999. the subjects disguise such a lot points of theoretical laptop technological know-how and combinatorics referring to computing.
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Extra info for Scientific Computing in Electrical Engineering: SCEE 2014, Wuppertal, Germany, July 2014
Sample text
Supposing that the numerical solution of the same problem is treated by the finite integration technique [7], finally it yields to a standard eigenvalue problem Ax D x (2) for a given symmetric sparse matrix A 2 Rn n . The novelty of this work is towards efficient, robust, and accurate determination of many interior eigenpairs for (2). For validation purposes, the numerical results are compared to the measurements. Despite the fact that various types of numerical methods for eigenvalue determination (Krylov-Schur, Jacobi-Davidson, Arnoldi) are available in different software packages, not as many are specifically adapted for computing thousands of eigenpairs.
Thesis, Delft University of Technology (2010) 4. : High-isolation CPW MEMS shunt switches—part 1: modeling. IEEE Trans. Microw. Theory Tech. 48(6), 1045–1052 (2000) 5. : Nonlinear circuit simulation of MEMS components: controlled current source approach. In: ECCTD’01 - European Conference on Circuit Theory and Design, August 28–31, 2001, Espoo, Finland, vol. III, pp. 377–380 (2001) 6. : System-level modeling and simulation of MEMS-based sensors. In: 9th International Multitopic Conference, IEEE INMIC 2005, pp.
4 Conclusions A mixed macromodel of a RF-MEMS switch, with few degrees of freedom, was extracted from several analyses of the device with distributed parameters. All parameters are combined in a single Spice circuit model, which is controlled by the MEMS actuation voltage and is excited with the RF signal. A relative error less than 3 % in the S parameters and less than 1 % in the pull-in voltage is obtained, which is very satisfactory given the low order imposed for the reduced model. Our future studies will continue, the next step being to improve the multiphysics part, by including damping and contact phenomena, in order that the macromodel be able to carry out RF simulations up to the down position as well as transient simulations needed for the extraction of switching time and pull-out voltage.