Shock wave prediction in transonic flow fields using domain-informed probabilistic deep learning

B Mufti, A Bhaduri, S Ghosh, L Wang, DN Mavris - Physics of Fluids, 2024 - pubs.aip.org
Transonic flow fields are marked by shock waves of varying strength and location and are
crucial for the aerodynamic design and optimization of high-speed transport aircraft. While …

Accelerating unsteady aerodynamic simulations using predictive reduced-order modeling

Z Li, P He - Aerospace Science and Technology, 2023 - Elsevier
Unsteady computational fluid dynamics (CFD) simulations are essential in aerospace
engineering because they can provide high-fidelity flow fields to better understand transient …

Uncertainty Propagation in High-Dimensional Fields using Non-Intrusive Reduced Order Modeling and Polynomial Chaos

N Iyengar, D Rajaram, K Decker… - AIAA SciTech 2023 Forum, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-1686. vid High-fidelity, physics-
based modeling and simulation have become integral to the design of aircraft, but can have …

Multifidelity Methodology for Reduced-Order Models with High-Dimensional Inputs

B Mufti, C Perron, DN Mavris - AIAA Journal, 2024 - arc.aiaa.org
In the early stages of aerospace design, reduced-order models (ROMs) are crucial for
minimizing computational costs associated with using physics-rich field information in many …

Manifold learning-based reduced-order model for full speed flow field

R Li, S Song - Physics of Fluids, 2024 - pubs.aip.org
Reduced-order models (ROMs) can effectively balance the accuracy and efficiency of
computational fluid dynamics (CFD). The nonlinear flow field characteristics cannot be …

Domain Decomposition Strategy for Combining Nonlinear and Linear Reduced-Order Models

N Iyengar, D Rajaram, D Mavris - AIAA Journal, 2024 - arc.aiaa.org
Increasingly ubiquitous reliance on expensive, high-fidelity numerical simulations has led to
the emergence of reduced-order modeling as an effective method to predict high …

Adaptive Sampling for Non-intrusive Reduced Order Models Using Multi-task Variance

A Dikshit, L Leifsson, S Koziel… - International Conference …, 2024 - Springer
Non-intrusive reduced order modeling methods (ROMs) have become increasingly popular
for science and engineering applications such as predicting the field-based solutions for …

Efficient Design of Transonic Airfoils Using Non-Intrusive Reduced Order Models and Composite Bayesian Optimization

A Dikshit, LT Leifsson - AIAA AVIATION FORUM AND ASCEND 2024, 2024 - arc.aiaa.org
Non-intrusive reduced order models (ROMs) are becoming increasingly popular in the
prediction of aerodynamic flow fields and surface pressure distributions. However, the use of …