Uncertainty Analysis in Complex, Multi-Physics Applications

July 25-26 2008
Stanford University
Stanford CA

Despite the considerable success of computer simulation technology in science and engineering, it remains difficult to construct objective confidence bounds on the numerical predictions. One of the challenges is that in realistic systems, only limited information is available to characterize the operating conditions and approximations are typically used to represent complex physical phenomena. This is in stark contrast to the usual assumptions in current computational model that typically requires well-defined (deterministic) inputs.

The large increase in computational resource expected during the next decade provides an exceptional opportunity to build novel computational methodologies that incorporate uncertainty quantification algorithms.

The scope of this two-day workshop is to bring together experts in the blooming field of uncertainty analysis for an open, informal discussion about the most recent research trends. The plan is to organize the contributions in three main areas of interest:

  • Identification of the uncertainties: formulation of the boundary conditions, approximations in the physical models, estimation of numerical discretization errors, PDF constructions, etc.
  • Uncertainty propagation: methods for time-dependent problems, model reduction and curse of dimensionality, intrusive vs. non-intrusive approaches, adjoint and adjoint-free approaches, etc.
  • Certification: a posteriori error estimates, validation metrics, confidence intervals, etc. 

It is expected that the contributions will cover a vast range of application areas and, therefore, the focus of the workshop is on methodologies and algorithms. Participants will be required to provide written notes of their contributions to be published as Proceedings of the Workshop.

The workshop is sponsored by the new DoE PSAAP (Predictive Science Accademic Alliance Program) Center recently established at Stanford University.

Contact Info:

  • Gianluca Iaccarino, ICME & Mechanical Engineering (jops@stanford.edu)
  • George Papanicolaou, ICME & Mathematics (papanico@math.stanford.edu)
  • Alireza Doostan, Mechanical Engineering (doostan@stanford.edu)
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