Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Lecture

Self Similar Solutions and Stokes Second Problem

In course

ME-444: Hydrodynamics

Nondimensionalized Navier-Stokes equations result in a great variety of models (Stokes, Lubrication, Euler, Potential) depending on the Reynolds number. The concept of boundary layer enables us then to identify the different components of the hydrodynamic ...

Description

This lecture covers the concept of self-similar solutions and the Stokes second problem, discussing the separation of variables, Fourier transform, Laplace transform, and non-dimensional polynomial magic ansatz. It also explores the conditions under which the equation remains the same and the Gaussian error function.

This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.

Watch on Mediaspace

Instructor

François Gallaire

Né le 26 février 1975, François Gallaire obtient, en 1998, le diplôme dingénieur de lEcole Polytechnique à Paris et, en 1999, un master en « Physique des liquides » à lUniversité Pierre et Marie Curie, toujours à Paris. Il rejoint ensuite le Laboratoire dhydrodynamique (LadHyX) à lEcole polytechnique où il soutient, en 2003, une thèse sur le thème des instabilités des jets tournants et sur le contrôle de léclatement tourbillonnaire sous la direction de Jean-Marrc Chomaz. En 2003, il est nommé chargé de recherche au CNRS au Laboratoire J.A. Dieudonné de lUniversité de Nice Sophia-Antipolis.En 2009, il rejoint l'EPFL pour y fonder le laboratoire des mécanique des fluides et instabilités (LFMI). Ses recherches se concentrent sur létude des propriétés fondamentales de stabilité des écoulements de fluides et sont guidées par les applications réelles, en particulier le contrôle des écoulements. Récemment, il a réalisé dimportantes contributions dans les domaines de la micro-fluidique (lanalyse de la manipulation par laser dune goutte dans un micro-canal) et la dynamique des bio-fluides (le descriptif mécanique de lanévrisme de laorte abdominale).

Official source

Ontological neighbourhood

Information engineering

Signal processing: Fourier analysis

Related concepts (13)

Fourier transform

In physics and mathematics, the Fourier transform (FT) is a transform that converts a function into a form that describes the frequencies present in the original function. The output of the transform is a complex-valued function of frequency. The term Fourier transform refers to both this complex-valued function and the mathematical operation. When a distinction needs to be made the Fourier transform is sometimes called the frequency domain representation of the original function.

Discrete Fourier transform

In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT (IDFT) is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies.

Fourier analysis

In mathematics, Fourier analysis (ˈfʊrieɪ,_-iər) is the study of the way general functions may be represented or approximated by sums of simpler trigonometric functions. Fourier analysis grew from the study of Fourier series, and is named after Joseph Fourier, who showed that representing a function as a sum of trigonometric functions greatly simplifies the study of heat transfer. The subject of Fourier analysis encompasses a vast spectrum of mathematics.

Inverse Laplace transform

In mathematics, the inverse Laplace transform of a function F(s) is the piecewise-continuous and exponentially-restricted real function f(t) which has the property: where denotes the Laplace transform. It can be proven that, if a function F(s) has the inverse Laplace transform f(t), then f(t) is uniquely determined (considering functions which differ from each other only on a point set having Lebesgue measure zero as the same). This result was first proven by Mathias Lerch in 1903 and is known as Lerch's theorem.

Discrete-time Fourier transform

In mathematics, the discrete-time Fourier transform (DTFT), also called the finite Fourier transform, is a form of Fourier analysis that is applicable to a sequence of values. The DTFT is often used to analyze samples of a continuous function. The term discrete-time refers to the fact that the transform operates on discrete data, often samples whose interval has units of time. From uniformly spaced samples it produces a function of frequency that is a periodic summation of the continuous Fourier transform of the original continuous function.

Related lectures (53)

Harmonic Analysis: Schwerte Functions

Explores Schwerte functions in harmonic analysis, emphasizing compact support and function convergence.

Convolution and Laplace Transform

Explores control of dynamic systems, impulse response, Laplace transform, and Fourier transform for solving differential equations.

Properties of Fourier and inverse Fourier transforms

Explores the properties of Fourier and inverse Fourier transforms, analyzing finite wave trains, Gaussian functions, and 3D space transformations.

Signal Representation: Fourier Transforms

Covers the representation of signals using Fourier transforms and the properties of signal vectors.

Fourier and Laplace Transforms: Concepts and Applications Log in to Mediaspace to watch this video