# 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} }

- Published 2016
DOI:10.1007/s10494-016-9725-6

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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