Journals

International Journals

1. (In preparation) S. Yang, and K. Yee, “Towards Quantifying Calibrated Uncertainty via Deep Ensembles in Missile Performance Regression Tasks”.

* Keywords: uncertainty quantification, surrogate modeling, Bayesian optimization

2. Y.E. Kang, S. Yang (co-first author), and K. Yee, “Physics-aware reduced-order modeling of transonic flow via β-variational autoencoder”, Physics of Fluids, 34, 076103, (2022)

DOI: https://doi.org/10.1063/5.0097740

* Keywords: generative modeling, reduced-order modeling, feature extraction

3. S. Yang, and K. Yee, “Comment on “Novel approach for selecting low-fidelity scale factor in multifidelity metamodeling””, AIAA Journal, 60, 4, (2022).

DOI: https://doi.org/10.2514/1.J061643

* Keywords: surrogate modeling, multi-fidelity modeling

4. S. Yang, S. Lee, and K. Yee, “Inverse design optimization framework via a two-step deep learning approach: application to a wind turbine airfoil”, Engineering with Computers, (2022).

DOI: https://doi.org/10.1007/s00366-022-01617-6

* Keywords: inverse design, generative modeling, design optimization, surrogate modeling

5. S. Yang, and K. Yee, “Design rule extraction using multi-fidelity surrogate model for unmanned combat aerial vehicles”, Journal of Aircraft, 59, 4, (2022).

DOI: https://doi.org/10.2514/1.C036489

* Keywords: CFD, shape & Bayesian optimization, data mining, multi-fidelity surrogate modeling