MS 17

Uncertainty Quantification and Probabilistic Learning in Computational Dynamics

Organizers

Eleni Chatzi,
ETH Zurich, Switzerland

Roger Ghanem,
University of Southern California, USA

Vincenzo Gattulli,
Sapienza University of Rome, Italy

Abstract

This mini-symposium focuses on the recent developments in uncertainty quantification and scientific machine learning, with applications in computational dynamics. The applications may concern, among others:

• Computational solid and fluid dynamics.
• Fluid-structure interaction and coupled problems.
• Soil-structure interactions in dynamics.
• Wave propagation in random media and metamaterials.
• Crack propagation in dynamics.
• UQ related aspects linked to structural health monitoring and dynamics.
• Stochastic inverse problems, model updating, and identification methods.
• Designs of experiments and autonomous decision making.
• Digital twins for dynamics problems.
• Reduced-order/Surrogate modeling.
• Multiscale modeling.
• Uncertain multiphysics linear and nonlinear computational dynamics.
• Optimization under uncertainties.