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Xiaosong Du
Xiaosong Du
Assistant Professor, Mechanical and Aerospace Engineering, Missouri S&T
Bestätigte E-Mail-Adresse bei mst.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Machine learning in aerodynamic shape optimization
J Li, X Du, JRRA Martins
Progress in Aerospace Sciences 134, 100849, 2022
2292022
Rapid airfoil design optimization via neural networks-based parameterization and surrogate modeling
X Du, P He, JRRA Martins
Aerospace Science and Technology 113, 106701, 2021
1632021
A B-spline-based generative adversarial network model for fast interactive airfoil aerodynamic optimization
X Du, P He, JRRA Martins
AIAA scitech 2020 forum, 2128, 2020
722020
Efficient yield estimation of multiband patch antennas by polynomial chaos‐based Kriging
L Leifsson, X Du, S Koziel
International Journal of Numerical Modelling: Electronic Networks, Devices …, 2020
412020
Aerodynamic inverse design using multifidelity models and manifold mapping
X Du, J Ren, L Leifsson
Aerospace science and technology 85, 371-385, 2019
412019
Application of multifidelity optimization techniques to benchmark aerodynamic design problems
J Ren, AS Thelen, A Amrit, X Du, LT Leifsson, Y Tesfahunegn, S Koziel
54th AIAA aerospace sciences meeting, 1542, 2016
342016
Optimum aerodynamic shape design under uncertainty by utility theory and metamodeling
X Du, L Leifsson
Aerospace Science and Technology 95, 105464, 2019
312019
Learning high-dimensional parametric maps via reduced basis adaptive residual networks
T O’Leary-Roseberry, X Du, A Chaudhuri, JRRA Martins, K Willcox, ...
Computer Methods in Applied Mechanics and Engineering 402, 115730, 2022
292022
Efficient model-assisted probability of detection and sensitivity analysis for ultrasonic testing simulations using stochastic metamodeling
X Du, L Leifsson, W Meeker, P Gurrala, J Song, R Roberts
Journal of Nondestructive Evaluation, Diagnostics and Prognostics of …, 2019
222019
Single-and multipoint aerodynamic shape optimization using multifidelity models and manifold mapping
J Nagawkar, J Ren, X Du, L Leifsson, S Koziel
Journal of Aircraft 58 (3), 591-608, 2021
202021
Multifidelity modeling by polynomial chaos-based cokriging to enable efficient model-based reliability analysis of ndt systems
X Du, L Leifsson
Journal of Nondestructive Evaluation 39 (1), 13, 2020
192020
Multifidelity model-assisted probability of detection via Cokriging
X Du, L Leifsson
NDT & E International 108, 102156, 2019
172019
Efficient uncertainty propagation for MAPOD via polynomial chaos-based Kriging
X Du, L Leifsson
Engineering Computations 37 (1), 73-92, 2020
142020
Applications of polynomial chaos-based cokriging to aerodynamic design optimization benchmark problems
J Nagawkar, LT Leifsson, X Du
AIAA Scitech 2020 Forum, 0542, 2020
112020
Novel adaptive sampling algorithm for POD-based non-intrusive reduced order model
J Wang, X Du, JR Martins
AIAA AVIATION 2021 FORUM, 3051, 2021
92021
Aerodynamic design of a rectangular wing in subsonic inviscid flow by direct and surrogate-based optimization
X Du, A Amrit, AS Thelen, LT Leifsson, Y Zhang, ZH Han, S Koziel
35th AIAA Applied Aerodynamics Conference, 4366, 2017
92017
Super resolution generative adversarial networks for multi-fidelity pressure distribution prediction
X Du, JR Martins
AIAA SCITECH 2023 Forum, 0533, 2023
72023
Adaptive projected residual networks for learning parametric maps from sparse data
T O’Leary-Roseberry, X Du, A Chaudhuri, JR Martins, K Willcox, ...
arXiv preprint arXiv:2112.07096, 2021
72021
Airfoil Design Under Uncertainty Using Non-Intrusive Polynomial Chaos Theory and Utility Functions
X Du, L Leifsson, S Koziel, A Bekasiewicz
Procedia Computer Science 108, 1493-1499, 2017
72017
Aerodynamic Design of the RAE 2822 in Transonic Viscous Flow: Single-and Multi-point Optimization Studies
A Amrit, X Du, AS Thelen, LT Leifsson, S Koziel
35th AIAA Applied Aerodynamics Conference, 3751, 2017
62017
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