Uncertainty Quantification in Computational Fluid Dynamics (STO-AVT 326) at Stanford University, USA

Date: Thursday 10 October 2019 to Friday 11 October 2019

Location : Stanford University, USA
Contact : VKI secretariat, This email address is being protected from spambots. You need JavaScript enabled to view it.; Phone: +32 2 359 96 04



VKI Lecture Series STO-AVT-236 on Uncertainty Quantification on Computational Fluid Dynamics

The availability of powerful computational resources and general‐purpose numerical algorithms creates increasing opportunities to perform flow simulations in complex systems. This raises several questions: How accurate are the resulting predictions? Are the mathematical and physical models correct? Do we have sufficient information to define relevant operating conditions? In general, how can we establish “error bars” on the results?

At the interface between physics, mathematics, probability and optimization, there have been significant advances in uncertainty quantification (UQ) efforts in computational science over the past decade. This two-day lecture series will present an introduction to UQ in computational fluid dynamics, including lectures on novel methods for optimization under uncertainty and applications.

These lecture series sponsored by the Science & Technology Organization Educational Programme (STO 326) is co-organised by Professor Catherine Gorlé from Stanford University, Professor Gianluca Iaccarino from Stanford University and Professor Thierry Magin from the von Karman Institute for Fluid Dynamics.


Thursday 10 October 2019

09:00 AM – 10:30 AM    Reflection on UQ techniques and applications
Prof. Gianluca Iaccarino, Stanford University, USA

10:45 AM – 12:15 PM    Non-intrusive methods for Uncertainty Quantification
Dr. Paul Constantine, University of Colorado, USA

01:45 PM – 03:15 PM   The curse of dimensionality: problems and strategies
Dr. Zach Del Rosario, Stanford University, USA

 03:30 PM – 05:00 PM    Uncertainty Quantification in biomedical applications
Dr. Allison Marsden, Stanford university, USA


Friday 11 October 2019

09:00 AM – 10:30 AM Multifidelity UQ and optimization under uncertainty. Part 1: Monte Carlo-based methods
Dr. Gianluca Geraci, Sandia National Laboratories, USA

10:45 AM – 12:15 PM Multifidelity UQ and optimization under uncertainty, Part 2: Surrogate-based methods
Dr. Mike Eldred, Sandia National Laboratories, USA

01:45 PM– 03:15 PM Generalized polynomial chaos and stochastic collocation methods for UQ in aerodynamics
Dr. Jacques Peter, ONERA, France

03:30 PM– 05: 00 PM UQ in computational wind engineering: inflow and turbulence model uncertainties
Dr. Catherine Gorlé, Stanford Unversity, USA

Free Registration

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