Data-driven modeling for unsteady aerodynamics and aeroelasticity

J Kou, W Zhang - Progress in Aerospace Sciences, 2021 - Elsevier
Aerodynamic modeling plays an important role in multiphysics and design problems, in
addition to experiment and numerical simulation, due to its low-dimensional representation …

Electro-thermal heating element with a nickel-plated carbon fabric for the leading edge of a wing-shaped composite application

J Lee, H Jo, H Choe, D Lee, H Jeong, H Lee… - Composite structures, 2022 - Elsevier
We propose a wing-shaped composite structure that uses an electroless nickel-plated
carbon fabric as an electro-thermal heating element, thus improving the electrical and …

Neural network prediction for ice shapes on airfoils using icefoam simulations

S Strijhak, D Ryazanov, K Koshelev, A Ivanov - Aerospace, 2022 - mdpi.com
In this article the procedure and method for the ice accretion prediction for different airfoils
using artificial neural networks (ANNs) are discussed. A dataset for the neural network is …

Performance evaluation of electrothermal anti-icing systems for a rotorcraft engine air intake using a meta model

SK Jung, LP Raj, A Rahimi, H Jeong… - Aerospace Science and …, 2020 - Elsevier
A meta model was developed to evaluate the performance of electrothermal anti-icing
systems for a rotorcraft engine air intake. A reduced-order model based on proper …

Surrogate modeling of aerodynamic simulations for multiple operating conditions using machine learning

R Dupuis, JC Jouhaud, P Sagaut - Aiaa Journal, 2018 - arc.aiaa.org
This paper describes a methodology, called local decomposition method, which aims at
building a surrogate model based on steady turbulent aerodynamic fields at multiple …

A localized reduced-order modeling approach for PDEs with bifurcating solutions

M Hess, A Alla, A Quaini, G Rozza… - Computer Methods in …, 2019 - Elsevier
Reduced-order modeling (ROM) commonly refers to the construction, based on a few
solutions (referred to as snapshots) of an expensive discretized partial differential equation …

A zonal Galerkin-free POD model for incompressible flows

M Bergmann, A Ferrero, A Iollo, E Lombardi… - Journal of …, 2018 - Elsevier
A domain decomposition method which couples a high and a low-fidelity model is proposed
to reduce the computational cost of a flow simulation. This approach requires to solve the …

Data-driven machine learning model for aircraft icing severity evaluation

S Li, J Qin, R Paoli - Journal of Aerospace Information Systems, 2021 - arc.aiaa.org
AIRCRAFT icing represents a serious hazard to aviation that caused many tragic fatalities
over the past decades [1]. The physical formation process of ice is affected by a variety of …

Local non‐intrusive reduced order modeling based on soft clustering and classification algorithm

YE Kang, S Shon, K Yee - International Journal for Numerical …, 2022 - Wiley Online Library
The use of non‐intrusive reduced order modeling (NIROM) to approximate high‐fidelity
computer models has been steadily increased over the past decade. Recently, local NIROM …

Eulerian method for ice crystal icing

E Norde, ETA van der Weide, HWM Hoeijmakers - AIAA journal, 2018 - arc.aiaa.org
In this study, an ice accretion method aimed at ice crystal icing in turbofan engines is
developed and demonstrated for glaciated as well as mixed-phase icing conditions. The …