Heterogeneous uncertainty quantification using Bayesian inference for simulation-based design optimization

Heterogeneous uncertainties due to model imperfection, lack of training data, and input variations coexist in simulation-based design optimization. In this work, a Bayesian-enhanced meta-model is developed to handle heterogeneous uncertainties concurrently in reliability-based design optimization. To account for model form uncertainty, a Bayesian model inference approach is first employed to calibrate unknown parameters of simulation models....