• DocumentCode
    3564607
  • Title

    Parametric model extraction for MEMS based on variational finite element techniques

  • Author

    Mehner, Jan E. ; Schaporin, Alexey ; Kolchuzhin, Vladimir ; Doetzel, Wolfram ; Gessner, Thomas

  • Author_Institution
    Dept. Micro Devices & Equip., Fraunhofer Inst. for Reliability & Microintegration, Germany
  • Volume
    1
  • fYear
    2005
  • Firstpage
    776
  • Abstract
    This article is focused on new finite element technologies which account for parameter variations in a single finite element run. The key idea of the new approach is to compute not only the governing system matrices of the FE problem but also n high order partial derivatives with regard to design parameters by means of automatic differentiation (AD). As result, Taylor vectors of the system´s response can be expanded in the vicinity of the initial position capturing dimensions and physical parameter. Essential speed-up can be achieved for shape optimization, sensitivity analyses and data sampling needed for reduced order modeling of MEMS.
  • Keywords
    differentiation; finite element analysis; micromechanical devices; partial differential equations; reduced order systems; variational techniques; FE system matrices; MEMS parametric model extraction; Taylor series expansion; automatic differentiation; data sampling; high order partial derivatives; reduced order modeling; sensitivity analyses; shape optimization; system response Taylor vectors; variational finite element techniques; Capacitive sensors; Electromagnetic devices; Electromagnetic fields; Finite element methods; Micromechanical devices; Parametric statistics; Precision engineering; Reduced order systems; Sensitivity analysis; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid-State Sensors, Actuators and Microsystems, 2005. Digest of Technical Papers. TRANSDUCERS '05. The 13th International Conference on
  • Print_ISBN
    0-7803-8994-8
  • Type

    conf

  • DOI
    10.1109/SENSOR.2005.1496532
  • Filename
    1496532