Design, Simulation and Optimization of Complex Composite and Complex Material Systems Under Uncertainties

The quantification and propagation of uncertainties have been one of the focuses of research and practice in the design, fabrication, simulation and optimization of complex material systems. Stochastic approaches are widely adopted due to the lack of exact control on the properties of the constituents, the manufacturing process, and the unpredictable working environments. Recent advances in the UQ methodologies, for example, sparse grids, advanced Monte Carlo methods, deep learning algorithms, multilevel methods, bring new opportunities to deal with large number of random variables and a lack of predictive physical model, which directly impact the design, uncertainty analysis and data analytics related to materials and structures both on the component and system levels. We invite research talks on UQ for the design, simulation and optimization of composite or complex material systems, including, but not limited to, forward uncertainty propagation, parameter estimation, design under uncertainties, health monitoring and management, etc.