Active subspaces of airfoil shape parameterizations
ZJ Grey, PG Constantine - AIAA Journal, 2018 - arc.aiaa.org
Design and optimization benefit from understanding the dependence of a quantity of interest
(eg, a design objective or constraint function) on the design variables. A low-dimensional …
(eg, a design objective or constraint function) on the design variables. A low-dimensional …
On kernel functions for bi-fidelity Gaussian process regressions
This paper investigates the impact of kernel functions on the accuracy of bi-fidelity Gaussian
process regressions (GPR) for engineering applications. The potential of composite kernel …
process regressions (GPR) for engineering applications. The potential of composite kernel …
Forecasting three-dimensional unsteady multi-phase flow fields in the coal-supercritical water fluidized bed reactor via graph neural networks
Y Hao, X Xie, P Zhao, X Wang, J Ding, R Xie, H Liu - Energy, 2023 - Elsevier
The study of three-dimensional unsteady multi-phase flows inside the coal-supercritical
water fluidized bed (SCWFB) reactor coupled with fluid dynamics, heat transfer and …
water fluidized bed (SCWFB) reactor coupled with fluid dynamics, heat transfer and …
[HTML][HTML] On the explainability of machine-learning-assisted turbulence modeling for transonic flows
Abstract Machine learning (ML) is a rising and promising tool for Reynolds-Averaged Navier–
Stokes (RANS) turbulence model developments, but its application to industrial flows is …
Stokes (RANS) turbulence model developments, but its application to industrial flows is …
Transfer learning for flow reconstruction based on multifidelity data
Reduced-order modeling for multifidelity flow reconstruction offers increased accuracy while
saving cost in data generation. The key to obtaining successful multifidelity models lies in …
saving cost in data generation. The key to obtaining successful multifidelity models lies in …
Optimization of expensive black-box problems via Gradient-enhanced Kriging
This paper explores the use of Gradient-enhanced Kriging for optimization of expensive
black-box design problems, which is not completely limited by the conventional Efficient …
black-box design problems, which is not completely limited by the conventional Efficient …
Simulation of supersonic axisymmetric base flow with a data-driven turbulence model
Axisymmetric base flow involves massive flow separation which is challenging for a typical
Reynolds-averaged Navier-Stokes (RANS) turbulence model. Furthermore, a supersonic …
Reynolds-averaged Navier-Stokes (RANS) turbulence model. Furthermore, a supersonic …
RHEA: an open-source Reproducible Hybrid-architecture flow solver Engineered for Academia
L Jofre Cruanyes, AMA Abdellatif… - Journal of Open …, 2023 - upcommons.upc.edu
The study of complex multiscale flows (Groen et al., 2014), like for example the motion of
small-scale turbulent eddies over large aerodynamic structures (Jofre & Doostan, 2022) …
small-scale turbulent eddies over large aerodynamic structures (Jofre & Doostan, 2022) …
High-fidelity aeroelastic transonic analysis using higher-order structural models
A novel computational approach for static aeroelastic analysis of metal and composite wings
in transonic flows is proposed. Static aeroelastic analysis is often performed coupling …
in transonic flows is proposed. Static aeroelastic analysis is often performed coupling …
A computational aeroelastic framework based on high-order structural models and high-fidelity aerodynamics
M Grifò, A Da Ronch, I Benedetti - Aerospace Science and Technology, 2023 - Elsevier
A computational framework for high-fidelity static aeroelastic analysis is presented.
Aeroelastic analysis traditionally employs a beam stick representation for the structure and …
Aeroelastic analysis traditionally employs a beam stick representation for the structure and …