UNCECOMP 2023 is the fifth edition of the International Conference on Uncertainty Quantification in Computational Science and Engineering and one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). UNCECOMP 2023 will be held in conjunction with the 9th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2023), also an ECCOMAS Thematic Conference.
The objective of UNCECOMP Conference is to reflect the recent research efforts and progress towards analysis and design processes with uncertainty quantification, with emphasis in multiscale analysis and design of complex systems. The aim of the conference is to bring together researchers seeking interactions among stochastic methods and computational mechanics in order to obtain reliable predictions of the behavior of physical systems. The UNCECOMP conference will serve as a forum for facilitating the exchange of ideas and as a platform for establishing links between research groups with complementary activities.
Sessions related to specific topics of the Conference will be introduced by Keynote Lectures which will be complemented by invited Minisymposia, organized by recognized experts in research areas of current interest, as well as by contributed papers.
The conference topics include (the list is indicative):
Convergence and error estimation
Large-scale stochastic finite element applications
Markov Chain Monte Carlo methods
Methods for improving the efficiency of Monte Carlo Simulation
Multiple time scale modeling of nonlinear/chaotic systems, e.g. molecular dynamics
Multiscale methods involving uncertainties
Multiscale stochastic dynamics
Multiscale stochastic finite element methods
Random field modeling of multiscale systems
Simulation of random fields
Solution of stochastic partial differential equations
Stochastic fracture and damage
System reliability analysis, design and risk assessment
Upscaling of statistical defects at micro- and nano-scale
Validation of stochastic modeling techniques
Wave propagation in micro-structured random media