Mini-symposium co-organization

The 12th International Conference on Structural Safety & Reliability takes place in Vienna (Austria), on 6-10 August, 2017.

More information about the conference can be found external pageherecall_made.

More information about the mini-symposium "Surrogate models for uncertainty quantification, reliability and sensitivity analysis" is given below:

Organizers

Prof. B. Sudret, ETH Zürich, Switzerland
Prof. J.-M. Bourinet, IFMA, France
Prof. S. Mahadevan, Vanderbilt University, USA
Prof. A. Taflanidis, University of Notre Dame, USA

Abstract

Structural reliability methods and more generally, methods that aim at taking into account model- and parameters uncertainty have received much attention in the mechanical, civil, and aerospace engineering communities over the past two decades. Some well-known methods such as FORM/SORM for reliability analysis, spectral methods for stochastic finite element analysis, global sensitivity analysis (Sobol’ indices), etc. are nowadays applied in an industrial context, e.g. nuclear, aerospace, and automotive industries, among others.

However, accurate computational models (e.g., finite element analysis) of complex structures or systems are often costly. A single run of the model may last minutes to hours, even on powerful computers. In order to use these models for reliability analysis and reliability-based design optimization, which require repeated calls to the computational code, it is necessary to develop a substitute that may be evaluated thousands to millions of times at low cost: these substitutes are referred to as meta- models or surrogate models.

The aim of this mini-symposium is to confront various kinds of advanced meta-modelling techniques in the context of uncertainty propagation including polynomial chaos expansions, Kriging, support vector regression, neural networks, low-rank tensor representations, etc. Papers that present new methodological developments and/or significant applications (in civil, environmental and mechanical engineering, among
others) using surrogate models are welcome.