Multi-Index Stochastic Collocation for forward UQ of single- and multi-disciplinary systems

Lorenzo Tamellini (CNR-IMATI, Pavia)

May 13. 2022, 11:40 — 12:30

In this talk, we present the multi-index stochastic collocation (MISC) method, which is the
multi-fidelity counterpart of the classical sparse grid stochastic collocation method
for Uncertainty Quantification. In the first part of the talk we introduce the method,
discuss the available convergence results and showcase its efficacy on a few numerical tests.
Then, we will focus on a recent development, namely, how to efficiently apply MISC
to problems where the system at hand is formed by multiple components (disciplines),
by computing a MISC surrogate model of each component first and then suitably combining
the surrogates together.


Further Information
ESI Boltzmann Lecture Hall
Associated Event:
Computational Uncertainty Quantification: Mathematical Foundations, Methodology & Data (Thematic Programme)
Clemens Heitzinger (TU Vienna)
Fabio Nobile (EPFL Lausanne)
Robert Scheichl (U Heidelberg)
Christoph Schwab (ETH Zürich)
Sara van de Geer (ETH Zürich)
Karen Willcox (U of Texas, Austin)