A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems

Numerical simulation of large-scale dynamical systems plays a fundamental role in studying a wide range of complex physical phenomena; however, the inherent large-scale nature of the models often leads to unmanageable demands on computational resources. Model reduction aims to reduce this computational burden by generating reduced models that are faster and cheaper to simulate, yet accurately represent the original large-scale system behavior. Model reduction of linear, nonparametric dynamical systems has reached a considerable level of maturity, as reflected by several survey papers and books. However, parametric model reduction has emerged only more recently as an important and vibrant research area, with…

• NS
  National Science Foundation

  Awards: 1217156, DE-FG02-08ER2585, DMS-1217156
• UD
  U.S. Department of Energy

  Awards: DE-FG02-08ER2585, DE-FG02-, DE-SC0009297, DE-FG02
• DF
  Deutsche Forschungsgemeinschaft
• OO
  Office of Science

  Award: DE-SC0009297
• AS
  Advanced Scientific Computing Research

  Awards: DE-FG02-08ER2585, DE-SC0009297
• AF
  Air Force Office of Scientific Research

  Awards: FA9550-, FA9550, FA9550-12, FA9550-12-1