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The European Project nanoCOPS for Nanoelectronic Coupled Problems Solutions

  • H. H. J. M. JanssenEmail author
  • P. Benner
  • K. Bittner
  • H.-G. Brachtendorf
  • L. Feng
  • E. J. W. ter Maten
  • R. Pulch
  • W. Schoenmaker
  • S. Schöps
  • C. Tischendorf
Conference paper
Part of the Mathematics in Industry book series (MATHINDUSTRY, volume 22)

Abstract

The project nanoCOPS (http://www.fp7-nanocops.eu) is a collaborative research project within the FP7-ICT research program funded by the European Union. The consortium comprises experts in mathematics and electrical engineering from seven universities (BU Wuppertal, HU Berlin, Brno UT, TU Darmstadt, FH OÖ Hagenberg, U Greifswald, KU Leuven), one research institute (MPI Magdeburg), two industrial partners (NXP Semiconductors Netherlands, ON Semiconductor Belgium) and two SMEs (MAGWEL—Belgium, ACCO Semiconductor—France).

We present an overview of the project subjects addressing the “bottlenecks” in the currently-available infrastructure for nanoelectronic design and simulation. In particular, we discuss the issues of an electro-thermal-stress coupled simulation for Power-MOS device design and of simulation approaches for transceiver designs at high carrier frequencies and baseband waveforms such as OFDM (Orthogonal Frequency Division Multiplex).

Keywords

Coupled problems Nanoelectronics  

Notes

Acknowledgements

We acknowledge the support from the project nanoCOPS, Nanoelectronic COupled Problems Solutions (FP7-ICT-2013-11/619166), http://www.fp7-nanoCOPS.eu/.

References

  1. 1.
    Bartel, A., Brunk, M., Günther, M., Schöps, S.: Dynamic iteration for coupled problems of electric circuits and distributed devices. SIAM J. Sci. Comput. 35(2), B315–B335 (2013)MathSciNetCrossRefzbMATHGoogle Scholar
  2. 2.
    Tischendorf, C., Schoenmaker, W., De Smedt, B., Meuris, P., Baumanns, S., Matthes, M., Jansen, L., Strohm, C.: Dynamic coupled electromagnetic field circuit simulation. Presented in Minisymposium on “Simulation Issues for Nanoelectronic Coupled Problems” at ECMI-2014, 18th European Conference on Mathematics for Industry, Taormina, Sicily, June 11, 2014Google Scholar
  3. 3.
    Schöps, S.: Iterative Schemes for Coupled Multiphysical Problems in Electrical Engineering. Invited talk SCEE-2014 (Scientific Computing in Electrical Engineering), Wuppertal, 2014. IMACM Report 2014-28, pp. 11–12, Bergische Universität Wuppertal. http://www.imacm.uni-wuppertal.de/fileadmin/imacm/preprints/2014/imacm_14_28.pdf (2014)
  4. 4.
    Kaufmann, C., Günther, M., Klagges, D., Knorrenschild, M., Richwin, M., Schöps, S., ter Maten, E.J.W.: Efficient frequency-transient co-simulation of coupled heat-electromagnetic problems. J. Math. Ind. 4, 1 (2014). http://www.mathematicsinindustry.com/content/4/1/1 MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Bittner, K., Brachtendorf, H.-G.: Adaptive multi-rate wavelet method for circuit simulation. Radioengineering 23(1), 300–307 (2014). http://www.radioeng.cz/fulltexts/2014/14_01_0300_0307.pdf zbMATHGoogle Scholar
  6. 6.
    Bittner, K., Brachtendorf, H.-G.: Fast algorithms for adaptive free knot spline approximation using nonuniform biorthogonal spline wavelets. SIAM J. Sci. Comput. 37(2), B283–B304 (2015)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Benner, P., Feng, L.: A robust algorithm for parametric model order reduction based on implicit moment matching. In: A. Quarteroni, G. Rozza (eds.) Reduced Order Methods for Modeling and Computational Reduction. MS &A Series, vol. 9, pp. 159–186. Springer, Cham (2014)Google Scholar
  8. 8.
    Feng, L., Benner, P., Antoulas, A.C.: An a posteriori error bound for reduced order modeling of micro- and nano-electrical(-mechanical) systems. Presented at SCEE-2014 (Scientific Computing in Electrical Engineering), Wuppertal, 2014. IMACM Report 2014–28, pp. 99–100, Bergische Universität Wuppertal. http://www.imacm.uni-wuppertal.de/fileadmin/imacm/preprints/2014/imacm_14_28.pdf (2014)
  9. 9.
    Stavrakakis, K.K.: Model order reduction methods for parameterized systems in electromagnetic field simulations. PhD thesis, TU-Darmstadt (2012)Google Scholar
  10. 10.
    Lutowska, A.: Model order reduction for coupled systems using low-rank approximations. PhD thesis, TU Eindhoven (2012). http://alexandria.tue.nl/extra2/729804.pdf
  11. 11.
    Le Maître, O.P., Knio, O.M.: Spectral Methods for Uncertainty Quantification, with Applications to Computational Fluid Dynamics. Springer, Science+Business Media B.V., Dordrecht (2010)CrossRefzbMATHGoogle Scholar
  12. 12.
    Xiu, D.: Numerical Methods for Stochastic Computations - A Spectral Method Approach. Princeton University Press, Princeton, NJ (2010)zbMATHGoogle Scholar
  13. 13.
    ter Maten, E.J.W., Pulch, R., Schilders, W.H.A., Janssen, H.H.J.M.: Efficient calculation of uncertainty quantification. In: Fontes, M., Günther, M., Marheineke, N. (eds.) Progress in Industrial Mathematics at ECMI 2012. Series Mathematics in Industry, vol. 19, pp. 361–370. Springer, Cham (2014)CrossRefGoogle Scholar
  14. 14.
    Benner, P., Schneider, J.: Uncertainty quantification using reduced-order Maxwell’s equations. Presented at SCEE-2014 (Scientific Computing in Electrical Engineering), Wuppertal. http://fp7-nanocops.eu/ (2014)
  15. 15.
    Bodendiek, A., Bollhöfer, M.: Adaptive-order rational Arnoldi-type methods in computational electromagnetism. BIT Numer. Math. 15(2), 1–24 (2013)MathSciNetzbMATHGoogle Scholar
  16. 16.
    Stroud, A.H.: Remarks on the disposition of points in numerical integration formulas. Math. Tables Other Aids Comput. 11(60), 257–261 (1957)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Genz, A., Keister, B.D.: Fully symmetric interpolatory rules for multiple integrals over infinite regions with Gaussian weight. J. Comput. Appl. Math. 71, 299–309 (1996)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Pulch, R., ter Maten, E.J.W., Augustin, F.: Sensitivity analysis and model order reduction for random linear dynamical systems. Math. Comput. Simul. 111, 80–95 (2015)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Putek, P., Gausling, K., Bartel, A., Gawrylczyk, K.M., ter Maten, E.J.W., Pulch, R., Günther, M.: Robust topology optimization of a permanent magnet synchronous machine using multi-level set and stochastic collocation methods. In: Bartel, A., Clemens, M., Günther, M., ter Maten, E.J.W. (eds.) Scientific Computing in Electrical Engineering SCEE 2014. Mathematics in Industry, vol. 23, pp. 233–242. Springer, Berlin (2016)Google Scholar
  20. 20.
    Di Buccianico, A., ter Maten, J., Pulch, R., Janssen, R., Niehof, J., Hanssen, M., Kapora, S.: Robust and efficient uncertainty quantification and validation of RFIC isolation. Radioengineering 23(1), 308–318 http://www.radioeng.cz/fulltexts/2014/14_01_0308_0318.pdf (2014)

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • H. H. J. M. Janssen
    • 1
    Email author
  • P. Benner
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • K. Bittner
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • H.-G. Brachtendorf
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • L. Feng
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • E. J. W. ter Maten
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • R. Pulch
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • W. Schoenmaker
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • S. Schöps
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  • C. Tischendorf
    • 2
    • 3
    • 4
    • 5
    • 6
    • 7
    • 8
  1. 1.NXP SemiconductorsEindhovenThe Netherlands
  2. 2.Max-Planck-InstitutMagdeburgGermany
  3. 3.University of Applied Sciences Upper AustriaHagenberg im MühlkreisAustria
  4. 4.Bergische Universität WuppertalWuppertalGermany
  5. 5.Ernst-Moritz-Arndt-Universität GreifswaldGreifswaldGermany
  6. 6.Magwel NVLeuvenBelgium
  7. 7.Technische Universität DarmstadtDarmstadtGermany
  8. 8.Humboldt Universität zu BerlinBerlinGermany

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