Drag reduction mechanisms on a generic square-back vehicle using an optimised yaw-insensitive base cavity

M Urquhart, M Varney, S Sebben, M Passmore - Experiments in Fluids, 2021 - Springer
Regulations on global greenhouse gas emission are driving the development of more
energy-efficient passenger vehicles. One of the key factors influencing energy consumption …

Multifidelity prediction framework with convolutional neural networks using high-dimensional data

H Emre Tekaslan, M Nikbay - Journal of Aerospace Information Systems, 2023 - arc.aiaa.org
This paper proposes two novel multifidelity neural network architectures developed for high-
dimensional inputs such as computational flowfields. We employed a two-dimensional flow …

Aerodynamic shape optimization using gradient-enhanced multifidelity neural networks

JR Nagawkar, LT Leifsson, P He - AIAA SciTech 2022 Forum, 2022 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2022-2350. vid In this work, the gradient-
enhanced multifidelity neural networks (GEMFNN) algorithm is extended to handle multiple …

Applications of polynomial chaos-based cokriging to simulation-based analysis and design under uncertainty

J Nagawkar, L Leifsson - … and Information in …, 2020 - asmedigitalcollection.asme.org
This paper demonstrates the use of the polynomial chaos-based Cokriging (PC-Cokriging)
on various simulation-based problems, namely an analytical borehole function, an ultrasonic …

A Multi-fidelity Prediction with Convolutional Neural Networks Using High-Dimensional Data

HE Tekaslan, M Nikbay - AIAA Aviation 2022 Forum, 2022 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2022-3719. vid This paper proposes two
novel multi-fidelity neural network architectures tailored for high-dimensional inputs such as …

Co-Kriging based multi-fidelity aerodynamic optimization for flying wing UAV with multi-shape wingtip design

R Wang, Y Yang, X Wang, B Wang… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Wingtip aerodynamic optimization is an important supplementary to improve the
aerodynamic performance of flying wing UAVs. Based on the Co-Kriging model, this paper …

Multi-Fidelity and Multi-Disciplinary Design Optimization of A Low-Boom Supersonic Transport Aircraft

M Nikbay, D Kilic, E Cakmak, HE Tekaslan… - AIAA SCITECH 2023 …, 2023 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2023-1478. vid The purpose of this study
is to demonstrate the conceptual design of a low-boom supersonic transport aircraft by …

Missile Flight Simulation With Surrogate Aerodynamic Models and Robust Control Autopilot

ER Joyce, KB Kidambi, MP Rumpfkeil - AIAA SCITECH 2025 Forum, 2025 - arc.aiaa.org
This paper presents an approach to explore the relationships between the missile
aerodynamics model, two potential autopilot configurations, and the resulting closed-loop …

Missile Flight Simulation Using Multi-Fidelity Surrogate Aerodynamic Models

ER Joyce - 2024 - rave.ohiolink.edu
Modeling and simulation is widely used within the aerospace industry to inform technology
development, acquisition, and operations and sustainment decisions. Accurate simulation of …

Gradient-enhanced multifidelity neural networks for high-dimensional function approximation

J Nagawkar, L Leifsson - … and Information in …, 2021 - asmedigitalcollection.asme.org
In this work, a novel multifidelity machine learning (ML) algorithm, the gradient-enhanced
multifidelity neural networks (GEMFNN) algorithm, is proposed. This is a multifidelity …