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Aerodynamic force and flow structures of two airfoils in tandem configuration performing flapping motions are studied, using the method of solving the Navier-Stokes equations in moving overset grids. Three typical phase differences between…

Fluid Dynamics · Physics 2007-05-23 Shi Long Lan , Mao Sun

Traditional machine learning (ML) algorithms, such as multiple regression, require human analysts to make decisions on how to treat the data. These decisions can make the model building process subjective and difficult to replicate for…

Machine Learning · Computer Science 2022-01-31 William Franz Lamberti

Two-dimensional potential flows of an ideal fluid with a free surface are considered in situations when shape of the bottom depends on time due to external reasons. Exact nonlinear equations describing surface waves in terms of the so…

Fluid Dynamics · Physics 2009-11-10 V. P. Ruban

Despite the fact that the calculations of drag coefficient and pressure distribution for airfoils can be completed by using Navier-Stoke's equation with help of experimental parameters and advanced computer programming, a simple theoretical…

Fluid Dynamics · Physics 2018-10-11 Maomao Zhao , Yufei Liu

We present Design-by-Morphing (DbM), a novel design methodology applicable to creating a search space for topology optimization of 2D airfoils. Most design techniques impose geometric constraints and sometimes designers' bias on the design…

Geometric Topology · Mathematics 2025-10-20 Haris Moazam Sheikh , Sangjoon Lee , Jinge Wang , Philip S. Marcus

Many traditional methods for wind turbine design and analysis assume quasi-steady aerodynamics, but atmospheric flows are inherently unsteady and modern turbine blades are susceptible to aeroelastic deformations. This study therefore…

Fluid Dynamics · Physics 2024-06-18 Nathaniel J. Wei , Omkar B. Shende

We revisit a classical airfoil design problem: the search for shapes that maximize aerodynamic performance metrics, targeting the underexplored intermediate Reynolds-number regime between 1 and 3000, relevant to small animals and miniature…

Fluid Dynamics · Physics 2026-05-20 Gleb Zhdanko , Dmitry Kolomenskiy

A simplified model of the bird skeleton along with elongation parameters for the flight feathers is used to explore the diversity of bird shapes. Varying a small number of parameters simulates a wide range of observed bird silhouettes. The…

Other Quantitative Biology · Quantitative Biology 2007-08-17 Shyamal Lakshminarayanan

This chapter present a fats boundary integral equation method for numerical computing of uniform potential flow past multiple aerofoils. The presented fast multipole-based iterative solution procedure requires only $O(nm\ln n)$ operations…

Fluid Dynamics · Physics 2013-09-02 Mohamed M. S. Nasser , Munira Ismail

Recent applications of machine learning, in particular deep learning, motivate the need to address the generalizability of the statistical inference approaches in physical sciences. In this letter, we introduce a modular physics guided…

Machine Learning · Computer Science 2021-02-03 Suraj Pawar , Omer San , Burak Aksoylu , Adil Rasheed , Trond Kvamsdal

A nonlinear differential equation about optimal shapes for blades of a fan. A boundary value differential problem from engineering, geometrical or physical bonds. A relation between linear profiles and constant speed along the side under…

Classical Analysis and ODEs · Mathematics 2008-03-27 Gianluca Argentini

Airfoil shape optimization presents a challenge where classical solvers frequently struggle with computational efficiency and local minima. In the promising paradigm of quantum computing, the coherent Ising machine (CIM), a specialized…

Quantum Physics · Physics 2026-03-12 Hao Ni , Qi Gao , Zhen Lu , Yue Yang

Where a 2D problem of optimal profile in variable speed flow is resolved in a class of convex Bezier curves, using symbolic and numerical computations.

History and Overview · Mathematics 2009-02-05 Gianluca Argentini

Governing equations for two-dimensional inviscid free-surface flows with constant vorticity over arbitrary non-uniform bottom profile are presented in exact and compact form using conformal variables. An efficient and very accurate…

Fluid Dynamics · Physics 2017-04-13 V. P. Ruban

The rich analytic structure of hadronic form factors makes a theoretically consistent yet easily applicable parametrisation cumbersome. Consequently, most parametrisations are limited to reproducing the simplest analytic features sufficient…

High Energy Physics - Phenomenology · Physics 2026-01-30 Nienke C. Balz , Florian Herren , Bastian Kubis , Simon Mutke , Méril Reboud

This study investigates the influence of aerofoil shape optimisation on blade aerodynamic performance under curvilinear and unsteady kinematics characteristic of vertical-axis turbines and cycloidal propellers. Using a cyclorotor in hover…

Fluid Dynamics · Physics 2026-03-10 Benjamin Irwin , David Toal , Swathi Krishna

Artificial intelligence techniques are considered an effective means to accelerate flow field simulations. However, current deep learning methods struggle to achieve generalization to flow field resolutions while ensuring computational…

Fluid Dynamics · Physics 2024-05-15 Kuijun Zuo , Zhengyin Ye , Linyang Zhu , Xianxu Yuan , Weiwei Zhang

Fluid flow past one or more solid bodies is a fundamental problem of much practical importance. Standard solutions of simplified problems involving incompressible inviscid irrotational flow past common geometries such as circular cylinders…

Fluid Dynamics · Physics 2026-01-01 Ankur Jain

The detailed analysis of model of the hydrodynamical vortice on a plane is executed. The derivation of the corresponding equation and its simplified variant is given, a partial solutions are constructed. The question on application of…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 E. Sh. Gutshabash

Accurate machine-learning models for aerodynamic prediction are essential for accelerating shape optimization, yet remain challenging to develop for complex three-dimensional configurations due to the high cost of generating training data.…

Machine Learning · Computer Science 2026-04-21 Yunjia Yang , Babak Gholami , Caglar Gurbuz , Mohammad Rashed , Nils Thuerey