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Uncertainty quantification of MEMS using a data-dependent adaptive stochastic collocation method
 

Summary: Uncertainty quantification of MEMS using a data-dependent adaptive
stochastic collocation method
Aravind Alwan, N.R. Aluru
Department of Mechanical Science and Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign,
405 N. Mathews Avenue, Urbana, IL 61801, United States
a r t i c l e i n f o
Article history:
Received 23 December 2010
Received in revised form 22 June 2011
Accepted 23 June 2011
Available online 1 July 2011
Keywords:
Uncertainty quantification
Hybrid electrothermomechanical (ETM)
actuation
Microelectromechanical systems (MEMS)
Stochastic collocation
Adaptive analysis
a b s t r a c t
This paper presents a unified framework for uncertainty quantification (UQ) in microelectromechanical

  

Source: Aluru, Narayana R. - Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign

 

Collections: Engineering; Materials Science