English
Related papers

Related papers: A Time-Domain Linear Method for Jet Noise Predicti…

200 papers

Learning and forecasting stochastic time series is essential in various scientific fields. However, despite the proposals of nonlinear filters and deep-learning methods, it remains challenging to capture nonlinear dynamics from a few noisy…

Methodology · Statistics 2025-02-21 Christian Donner , Anuj Mishra , Hideaki Shimazaki

Recent simulations indicate that streamwise-preferential porous materials have the potential to reduce drag in wall-bounded turbulent flows(Gomez-de-Segura & Garcia-Mayoral 2019). This paper extends the resolvent formulation to study the…

Fluid Dynamics · Physics 2021-03-26 Andrew Chavarin , Garazi Gomez-de-Segura , Ricardo Garcia-Mayoral , Mitul Luhar

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

Fluid Dynamics · Physics 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

We consider the Navier-Stokes equations in a channel with a narrowing of varying height. The model is discretized with high-order spectral element ansatz functions, resulting in 6372 degrees of freedom. The steady-state snapshot solutions…

Numerical Analysis · Mathematics 2019-04-29 Martin W. Hess , Annalisa Quaini , Gianluigi Rozza

Global regularity for the three-dimensional incompressible Navier-Stokes equations remains unresolved partly because weak, mild, and strong formulations employ incompatible functional settings. The present study introduces a…

General Mathematics · Mathematics 2025-07-21 Daria Nikitaeva

A semi-implicit, residual-based variational multiscale (VMS) formulation is developed for the incompressible Navier--Stokes equations. The approach linearizes convection using an extrapolated (Oseen-type) convecting velocity, producing a…

We study a turbulent jet issuing from a cylindrical nozzle to characterise coherent structures evolving in the turbulent boundary layer. The analysis is performed using data from a large-eddy simulation of a Mach 0.4 jet. Azimuthal…

Fluid Dynamics · Physics 2021-08-11 Oğuzhan Kaplan , Peter Jordan , André Cavalieri , Guillaume A. Brès

Coherent turbulent wave-packet structures in a jet at Reynolds number 460000 and Mach number 0.4 are extracted from experimental measurements and are modeled as linear fluctuations around the mean flow. The linear model is based on harmonic…

Conduits generated by the buoyant dynamics between two miscible, Stokes fluids with high viscosity contrast exhibit rich nonlinear wave dynamics. However, little is known about the fundamental wave dispersion properties of the medium. In…

Fluid Dynamics · Physics 2023-01-18 Yifeng Mao , Mark A. Hoefer

The companion paper "Higher-order in time quasi-unconditionally stable ADI solvers for the compressible Navier-Stokes equations in 2D and 3D curvilinear domains", which is referred to as Part I in what follows, introduces ADI (Alternating…

Computational Physics · Physics 2018-01-11 Oscar Bruno , Max Cubillos

Simulations of turbulent fluid flow around long cylindrical structures are computationally expensive because of the vast range of length scales, requiring simplifications such as dimensional reduction. Current dimensionality reduction…

Fluid Dynamics · Physics 2021-02-25 Bernat Font , Gabriel D. Weymouth , Vinh-Tan Nguyen , Owen R. Tutty

The present study investigates the accurate inference of Reynolds-averaged Navier-Stokes solutions for the compressible flow over aerofoils in two dimensions with a deep neural network. Our approach yields networks that learn to generate…

Fluid Dynamics · Physics 2022-11-17 Li-Wei Chen , Nils Thuerey

There is a significant need for precise and reliable forecasting of the far-field noise emanating from shipping vessels. Conventional full-order models based on the Navier-Stokes equations are unsuitable, and sophisticated model reduction…

Machine Learning · Computer Science 2024-04-15 Indu Kant Deo , Akash Venkateshwaran , Rajeev K. Jaiman

The paper addresses an error analysis of an Eulerian finite element method used for solving a linearized Navier--Stokes problem in a time-dependent domain. In this study, the domain's evolution is assumed to be known and independent of the…

Numerical Analysis · Mathematics 2024-08-26 Michael Neilan , Maxim Olshanskii

We develop a new approach for regularity estimates, especially vorticity estimates, of solutions of the three-dimensional Navier-Stokes equations with periodic initial data, by exploiting carefully formulated linearized vorticity equations.…

Analysis of PDEs · Mathematics 2022-10-11 Gui-Qiang G. Chen , Zhongmin Qian

Prediction of dynamical time series with additive noise using support vector machines or kernel based regression has been proved to be consistent for certain classes of discrete dynamical systems. Consistency implies that these methods are…

Machine Learning · Statistics 2018-06-21 Raymundo Navarrete , Divakar Viswanath

Terahertz Time Domain Spectroscopy (THz-TDS) systems have emerged as mature technologies with significant potential across various research fields and industries. However, the lack of standardized methods for signal and noise estimation and…

The Navier--Stokes (NS) equations describe fluid dynamics through a high-dimensional, nonlinear system of partial differential equations (PDEs). Despite their fundamental importance, their behavior in turbulent regimes remains incompletely…

Mathematical Physics · Physics 2025-04-04 Alexander Migdal

This article presents an innovative approach for developing an efficient reduced-order model to study the dispersion of urban air pollutants. The need for real-time air quality monitoring has become increasingly important, given the rise in…

Numerical Analysis · Mathematics 2023-05-29 Moaad Khamlich , Giovanni Stabile , Gianluigi Rozza , László Környei , Zoltán Horváth

This work presents a scalable control framework based on nonlinear Model Predictive Control for high-dimensional dynamical systems. The proposed approach addresses the key challenges of model scalability and partial observability by…