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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

Special Issue on Uncertainty Management in Complex Multiphysics Structural Dynamics; Paper submission deadline: Feb 28, 2019


Guest Editor: Sifeng Bi, Michael Beer, Morvan Ouisse, Scott Cogan


It is widely recognized that the unavoidable appearance of uncertainties in both operational experiments and numerical analyses requires efforts to be dedicated in the tasks of model updating, verification, and validation. Non-deterministic modeling approaches enable characterization, propagation, and quantification of the inevitable uncertainties, providing predictions over a possible range of outcomes (distributional, interval, fuzzy, etc.) rather than a unique solution with maximum fidelity to a single experiment. Such approaches applied in structural dynamics significantly promote the tendency towards high accuracy and robustness in computer-aided engineering. However, challenges emerge from modern developments of aerospace, automobile, and mechanical industries, where large-scale and multiphysics systems are designed and employed with huge parameter dimension, discrepant parameter sensitivity, multifarious sources of uncertainties, huge calculation burden, etc. The multiphysics systems, such as vibroacoustics, thermoelastics, and fluid-solid coupled systems, present more challenging domains for non-deterministic modeling because of the severe lack of knowledge in the coupling mechanism between multiple media and environments. Thus, it requires further development of the current techniques for uncertainty treatment to enhance the trustworthiness of computational simulations in complex structural dynamics and multiphysics coupling mechanics. 


  • Verification and Validation (V&V) of numerical models for mechanical systems
  • Uncertainty characterization, propagation, and quantification techniques
  • Modelling of coupling mechanism among multiple media
  • Decoupling of vibroacoustics, thermoelastics, and fluid-solid coupling
  • Stochastic model calibration and validation
  • Bayesian model calibration and advanced Monte Carlo simulation
  • Sensitive analysis of uncertain parameters
  • Robust model calibration
  • Interval and fuzzy model calibration techniques

For more information, please refer to the attached announcement.