A Bayesian Calibration–Prediction Method for Reducing Model-Form Uncertainties with Application in RANS Simulations

@article{Wu2016ABC,
  title={A Bayesian Calibration–Prediction Method for Reducing Model-Form Uncertainties with Application in RANS Simulations},
  author={J.-L. Wu and J. M. Wang and Han Xiao},
  journal={Flow, Turbulence and Combustion},
  year={2016},
  volume={97},
  pages={761-786}
}
Model-form uncertainties in complex mechanics systems are a major obstacle for predictive simulations. Reducing these uncertainties is critical for stake-holders to make risk-informed decisions based on numerical simulations. For example, Reynolds-Averaged Navier-Stokes (RANS) simulations are increasingly used in the design, analysis, and safety assessment of mission-critical systems involving turbulent flows. However, for many practical flows the RANS predictions have large model-form… CONTINUE READING
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