The proper treatment of uncertainties is a fundamental prerequisite for determining reliable system response and reliability estimates. Considering the complexity of real-world engineering problems, potent mathematical tools are employed for sophisticated modeling of the excitations and the associated engineering systems. Nonlinearities, hysteresis, joint time-frequency representations, as well as generalized/fractional calculus are expected to raise the complexity of the governing equations, whereas the consideration of stochasticity leads to the formulation of particularly challenging problems from a computational perspective. The objective of this MS is to present recent advances and emerging cross-disciplinary approaches in the broad field of computational methods for stochastic engineering dynamics with a focus on uncertainty modeling and propagation. Further, this MS intends to provide a forum for a fruitful exchange of ideas and interaction among diverse technical and scientific disciplines. Specific contributions related both to fundamental research and to engineering applications of computational stochastic dynamics and signal processing methodologies are welcome. A non-exhaustive list includes joint time-frequency analysis tools, sparse representations and, stochastic/fractional calculus modeling and applications, nonlinear stochastic dynamics, stochastic model/dimension reduction techniques, Monte Carlo simulation methods, and risk/reliability assessment applications.

For more information, please refer to the website of EURODYN 2020.