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A weighted residual collocation methodology for simulating two-dimensional shear-driven and natural convection flows has been presented. Using a dyadic mesh refinement, the methodology generates a basis and a multiresolution scheme to…

Fluid Dynamics · Physics 2020-07-23 Jahrul Alam , Raymond Walsh , Alamgir Hossain , Andrew Rose

Despite the progress in high performance computing, Computational Fluid Dynamics (CFD) simulations are still computationally expensive for many practical engineering applications such as simulating large computational domains and highly…

Fluid Dynamics · Physics 2017-10-26 Botros N Hanna , Nam T. Dinh , Robert W. Youngblood , Igor A. Bolotnov

This study presents a shape optimization framework that combines a Flux Reconstruction (FR) spatial discretization, Large Eddy Simulation (LES), the Ffowcs-Williams and Hawkings (FW-H) formulation, and the gradient-free Mesh Adaptive Direct…

Fluid Dynamics · Physics 2025-10-14 Mohsen Hamedi , Brian Vermeire

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by…

Fluid flow in the transonic regime finds relevance in aerospace engineering, particularly in the design of commercial air transportation vehicles. Computational fluid dynamics models of transonic flow for aerospace applications are…

Fluid Dynamics · Physics 2020-01-14 S. Ashwin Renganathan , Romit Maulik , Vishwas Rao

Computational fluid dynamics (CFD) is a powerful tool for modeling turbulent flow and is commonly used for urban microclimate simulations. However, traditional CFD methods are computationally intensive, requiring substantial hardware…

Accurate modeling of aerodynamic loads is essential for understanding and predicting the responses of complex structural systems. However, these models often rely on simplifications of the true physical forces, introducing assumptions that…

Machine Learning · Computer Science 2026-05-22 Gledson Rodrigo Tondo , Igor Kavrakov , Guido Morgenthal

Dynamic mode decomposition (DMD) provides a principled approach to extract physically interpretable spatial modes from time-resolved flow field data, along with a linear model for how the amplitudes of these modes evolve in time. Recently,…

Fluid Dynamics · Physics 2020-07-29 Aditya G. Nair , Benjamin Strom , Bingni W. Brunton , Steven L. Brunton

A closed-form analytical solution is found for the nonlinear dynamics of isolated, near-threshold waves in the presence of strong scattering. The proposed solution can be useful in verifying codes across several disciplines, including…

Plasma Physics · Physics 2020-01-17 Vinicius Duarte , Nikolai Gorelenkov

Wind-induced response governs the design of the long-span bridges. The shape of the deck is one of the most important factors that not only affects the mechanical properties but greatly influences the aerodynamic performance of the bridge.…

Fluid Dynamics · Physics 2022-03-29 Tajammal Abbas , Igor Kavrakov , Guido Morgenthal , Tom Lahmer

This work presents an investigation on different methods for the calculation of the angle of attack and the underlying induced velocity on wind turbine blades using data obtained from three-dimensional Computational Fluid Dynamics (CFD).…

A novel approach to reduced-order modeling of high-dimensional time varying systems is proposed. It leverages the formalism of the Dynamic Mode Decomposition technique together with the concept of balanced realization. It is assumed that…

Systems and Control · Electrical Eng. & Systems 2021-06-01 Andrea Iannelli , Urban Fasel , Roy S. Smith

Privacy-preserving distributed machine learning (ML) and aerial connected vehicle (ACV)-assisted edge computing have drawn significant attention lately. Since the onboard sensors of ACVs can capture new data as they move along their…

Machine Learning · Computer Science 2025-08-28 Ferdous Pervej , Richeng Jin , Md Moin Uddin Chowdhury , Simran Singh , İsmail Güvenç , Huaiyu Dai

Computational fluid dynamics (CFD) provides high-fidelity simulations of fluid flows but remains computationally expensive for many-query applications. In recent years deep learning (DL) has been used to construct data-driven fluid-dynamic…

Machine Learning · Computer Science 2026-04-13 David Ramos , Lucas Lacasa , Fermín Gutiérrez , Eusebio Valero , Gonzalo Rubio

As one of the three-dimensional (3D) bioprinting techniques with great application potential, laser-induced-forward-transfer (LIFT) based laser assisted bioprinting (LAB) transfers the bioink through a developed jet flow, and the printing…

Fluid Dynamics · Physics 2021-03-17 Jie Qu , Chaoran Dou , Ben Xu , Jianzhi Li , Zhonghao Rao , Andrew Tsin

In this paper, we study the flux identification problem for a nonlinear time-fractional viscoelastic equation with a general source function based on the boundary measurements. We prove that the direct problem is well-posed, i.e., the…

Analysis of PDEs · Mathematics 2024-07-24 Mohamed BenSalah , Salih Tatar , Suleyman Ulusoy , Masahiro Yamamoto

Accurate modeling of aerodynamic coefficients is crucial for understanding and optimizing the performance of modern aircraft systems. This paper presents the novel deployment of an Evolving Type-2 Quantum Fuzzy Neural Network (eT2QFNN) for…

Systems and Control · Electrical Eng. & Systems 2025-04-29 Aydoğan Soylu , Tufan Kumbasar

Accurately quantifying air-sea fluxes is important for understanding air-sea interactions and improving coupled weather and climate systems. This study introduces a probabilistic framework to represent the highly variable nature of air-sea…

Atmospheric and Oceanic Physics · Physics 2026-01-30 Jiarong Wu , Pavel Perezhogin , David John Gagne , Brandon Reichl , Aneesh C. Subramanian , Elizabeth Thompson , Laure Zanna

Accurate prediction of hypersonic flow fields over a compression ramp is critical for aerodynamic design but remains challenging due to the scarcity of experimental measurements such as velocity. This study systematically develops a data…

Fluid Dynamics · Physics 2025-11-26 Yuan Jia , Guoqin Zhao , Hao Ma , Xin Li , Chi Zhang , Chih-Yung Wen

Computational fluid dynamics (CFD) simulations are broadly applied in engineering and physics. A standard description of fluid dynamics requires solving the Navier-Stokes (N-S) equations in different flow regimes. However, applications of…

Computational Engineering, Finance, and Science · Computer Science 2021-12-14 Shen Wang , Mehdi Nikfar , Joshua C. Agar , Yaling Liu