IUTAM Symposium on Multiscale Problems in Stochastic Mechanics
25. June 2012 - 29. June 2012
Aims and Scope
In recent years, there has been growing interest in multiscale phenomena in science and engineering. If uncertainties have to be taken into account on some of the scales, the problem of propagation of uncertainties through the scales has to be considered. Typical examples for such a situation are material heterogeneities on the microscale level, which may influence the macroscopic behaviour. As a consequence, a better understanding of fundamental mechanisms, for example failure due to fracture of heterogeneous materials has been achieved, leading to innovative, more robust and less conservative structural designs.
During the last decade, new methods have been developed for data representation, order reduction, variational multiscale analysis and uncertainty quantification. Probabilistic methods for solids and structures have been established at a level where they can be applied to industrial size problems. However, the treatment of uncertainties in problems with scale coupling is still a computational challenging task. Several techniques based on operator upscaling and stochastic variational multiscale methods are currently under development and have been applied for example to the analysis of heterogeneous materials and to the study of flow through porous media with first promising results. Further approaches that allow for a coupling of different sources of uncertainties, a detailed error analysis and a construction of adequate reduced order models are highly needed.
From 1972, more than ten IUTAM symposia on various aspects of stochastic mechanics were organized. The aim of this IUTAM symposium is to bring a limited number of researchers from several disciplines such as applied mathematics, materials science and mechanics into discussion on stochastic phenomena in multiscale modelling.
Topics of the symposium will cover:
• Data acquisition and stochastic modelling
• Order reduction
• Stochastic boundary value problems
• Stochastic variational multiscale methods
• Uncertainty quantification