Machine learning in aerodynamic shape optimization
Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …
optimization (ASO), thanks to the availability of aerodynamic data and continued …
Aerodynamic design optimization: Challenges and perspectives
JRRA Martins - Computers & Fluids, 2022 - Elsevier
Antony Jameson pioneered CFD-based aerodynamic design optimization in the late 1980s.
In addition to developing the fundamental theory, Jameson implemented that theory in …
In addition to developing the fundamental theory, Jameson implemented that theory in …
Complex standard eigenvalue problem derivative computation for laminar–turbulent transition prediction
Y Shi, C Song, Y Chen, H Rao, T Yang - AIAA Journal, 2023 - arc.aiaa.org
As a high-fidelity approach to transition prediction, the coupled Reynolds-averaged Navier–
Stokes (RANS) and linear stability theory (LST)-based e N method is widely used in …
Stokes (RANS) and linear stability theory (LST)-based e N method is widely used in …
Dual-convolutional neural network based aerodynamic prediction and multi-objective optimization of a compact turbine rotor
Y Wang, T Liu, D Zhang, Y Xie - Aerospace Science and Technology, 2021 - Elsevier
With the development of neural network technology, surrogate models and dimensionality
reduction strategies based on machine learning have become the research hotspots of …
reduction strategies based on machine learning have become the research hotspots of …
Hull shape optimization of autonomous underwater vehicles using a full turbulent continuous adjoint solver
The present study aims at simultaneously optimizing the nose and tail of two distinct
Autonomous Underwater Vehicles (AUVs) using a full turbulent continuous adjoint solver …
Autonomous Underwater Vehicles (AUVs) using a full turbulent continuous adjoint solver …
Multifidelity aerodynamic flow field prediction using random forest-based machine learning
J Nagawkar, L Leifsson - Aerospace Science and Technology, 2022 - Elsevier
In this paper, a novel random forest (RF)-based multifidelity machine learning (ML) algorithm
to predict the high-fidelity Reynolds-averaged Navier-Stokes (RANS) flow field is proposed …
to predict the high-fidelity Reynolds-averaged Navier-Stokes (RANS) flow field is proposed …
Intelligent data-driven aerodynamic analysis and optimization of morphing configurations
In this paper, we develop an online, data-based framework for the aircraft airfoil to be able to
optimally morph vertically. The proposed framework combines data-driven analysis …
optimally morph vertically. The proposed framework combines data-driven analysis …
[HTML][HTML] Effects of eccentricity in tube–pod arrangements on hyperloop aerodynamics
The hyperloop, proposed as an innovative tube-train system, offers numerous transportation
advantages yet exhibits inherent asymmetries arising from the design of the tube and the …
advantages yet exhibits inherent asymmetries arising from the design of the tube and the …
Advancing thermal performance through vortex generators morphing
The design of rigid vortex generators (RVG) influences the thermal performance of various
technologies. We employed Discrete Adjoint-Based Optimization to show the optimal …
technologies. We employed Discrete Adjoint-Based Optimization to show the optimal …
Field inversion for transitional flows using continuous adjoint methods
Transition modeling represents one of the key challenges in computational fluid dynamics.
While numerical efforts were traditionally devoted to either improving Reynolds-averaged …
While numerical efforts were traditionally devoted to either improving Reynolds-averaged …