Filtering in the context of large eddy simulation (LES) is a mathematical operation intended to remove a range of small scales from the solution to the Navier-Stokes equations. Because the principal difficulty in simulating turbulent flows comes from the wide range of length and time scales, this operation makes turbulent flow simulation cheaper by reducing the range of scales that must be resolved. The LES filter operation is low-pass, meaning it filters out the scales associated with high frequencies. (Wikipedia).
From playlist filter (less comfortable)
Introduction to Frequency Selective Filtering
http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Separation of signals based on frequency content using lowpass, highpass, bandpass, etc filters. Filter g
From playlist Introduction to Filter Design
A System for Analog Filter Design, Realization, and Verification Using Mathematica and SystemModeler
Analog filters are an essential part of modern electronics; however, their design, realization and verification can be arduous and time consuming. This paper describes a Mathematica and SystemModeler platform for automated, fast analog filter design and simulation. The platform consists of
From playlist Wolfram Technology Conference 2013
This is part of an online course on beginner/intermediate applied signal processing, which presents theory and implementation in MATLAB and Python. The course is designed for people interested in applying signal processing methods to applications in time series analysis. More info here: h
From playlist Signal processing in MATLAB and Python
Understanding Wavelets, Part 5: Machine Learning and Deep Learning with Wavelet Scattering
Wavelet scattering networks help you obtain low-variance features from signals and images for use in machine learning and deep learning applications. Scattering networks help you automatically obtain features that minimize differences within a class while preserving discriminability across
From playlist Understanding Wavelets
Low Pass Filters & High Pass Filters : Data Science Concepts
What is a low pass filter? What is a high pass filter? Sobel Filter: https://en.wikipedia.org/wiki/Sobel_operator
From playlist Time Series Analysis
Computational prediction technologies for turbulent flows by Charles Meneveau
Turbulence from Angstroms to light years DATE:20 January 2018 to 25 January 2018 VENUE:Ramanujan Lecture Hall, ICTS, Bangalore The study of turbulent fluid flow has always been of immense scientific appeal to engineers, physicists and mathematicians because it plays an important role acr
From playlist Turbulence from Angstroms to light years
DDPS | Large Eddy Simulation Reduced Order Models
Talk Abstract Large eddy simulation (LES) is one of the most popular methods for the numerical simulation of turbulent flows. In this talk, we survey our group's efforts over the last decade to develop a large eddy simulation reduced order modeling (LES-ROM) framework for the numerical s
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Part2. Data assimilation using particle filters... - Cotter - Workshop 2 - CEB T3 2019
Cotter (Imperial College London, UK) / 13.11.2019 Data assimilation using particle filters for class of partially observed stochast ic geophysical fluid dynamics models. Part II ---------------------------------- Vous pouvez nous rejoindre sur les réseaux sociaux pour suivre nos act
From playlist 2019 - T3 - The Mathematics of Climate and the Environment
Turbulence Closure Models: Reynolds Averaged Navier Stokes (RANS) & Large Eddy Simulations (LES)
Turbulent fluid dynamics are often too complex to model every detail. Instead, we tend to model bulk quantities and low-resolution approximations. To remain physical, these reduced approximations of the Navier-Stokes equations must be "closed", and turbulence closure modeling is one of t
From playlist Fluid Dynamics
Understanding the Particle Filter | | Autonomous Navigation, Part 2
Watch the first video in this series here: https://youtu.be/Fw8JQ5Q-ZwU This video presents a high-level understanding of the particle filter and shows how it can be used in Monte Carlo localization to determine the pose of a mobile robot inside a building. We’ll cover why the particle
From playlist Autonomous Navigation
Low Pass Filters and High Pass Filters - RC and RL Circuits
This electronics video tutorial discusses how resistors, capacitors, and inductors can be used to filter out signals according to their frequency. This video include examples such as RC low pass filters, RL low pass filters, RC high pass filters, and RL low pass filters. It provides the
From playlist Electronic Circuits
reaLD 3D glasses filter with a linear polarising filter
This is for a post on my blog: http://blog.stevemould.com
From playlist Everything in chronological order
DDPS | Physics-Guided Deep Learning for Dynamics Forecasting
In this talk from July 9, 2021, University of California, San Diego Computer Science Ph.D. student Rui Wang discusses physics-based modeling with deep learning. Description: Modeling complex physical dynamics is a fundamental task in science and engineering. There is a growing need for in
From playlist Data-driven Physical Simulations (DDPS) Seminar Series
Understanding Laminar and Turbulent Flow
Be one of the first 200 people to sign up to Brilliant using this link and get 20% off your annual subscription! https://brilliant.org/efficientengineer/ There are two main types of fluid flow - laminar flow, in which the fluid flows smoothly in layers, and turbulent flow, which is charac
From playlist Fluid Mechanics
Deep Learning for Turbulence Closure Modeling
Machine learning, and in particular deep neural networks, are currently revolutionizing how we model turbulent fluid dynamics. This video describes how deep learning is being used for turbulence closure modeling, especially for the Reynolds averaged Navier Stokes (RANS) equations and larg
From playlist Fluid Dynamics
Assimilation of Lagrangian data - Chris Jones
PROGRAM: Data Assimilation Research Program Venue: Centre for Applicable Mathematics-TIFR and Indian Institute of Science Dates: 04 - 23 July, 2011 DESCRIPTION: Data assimilation (DA) is a powerful and versatile method for combining observational data of a system with its dynamical mod
From playlist Data Assimilation Research Program
Large Eddy Simulation of Thermally Stratified Turbulent Channel Flow by S F Anwer
Summer school and Discussion Meeting on Buoyancy-driven flows DATE: 12 June 2017 to 20 June 2017 VENUE: Ramanujan Lecture Hall, ICTS, Bengaluru Buoyancy plays a major role in the dynamics of atmosphere and interiors of planets and stars, as well as in engineering applications. This field
From playlist Summer school and Discussion Meeting on Buoyancy-driven flows
Passive RC high pass filter tutorial!
A tutorial on passive RC high pass filters. You can use them to filter out low frequency signals, or remove DC offsets from a signal. Make sure you watch my video on low pass filters first! http://www.youtube.com/watch?v=OBM5T5_kgdI Webpage with more info on all kinds of electronic filters
From playlist Passive filters
Boreal Summer Intraseasonal Variability (Special Tutorial 1) by Eric Daniel Maloney
DISCUSSION MEETING: AIR-SEA INTERACTIONS IN THE BAY OF BENGAL FROM MONSOONS TO MIXING ORGANIZERS : Eric D'Asaro, Rama Govindarajan, Manikandan Mathur, Debasis Sengupta, Emily Shroyer, Jai Sukhatme and Amit Tandon DATE & TIME : 18 February 2019 to 23 February 2019 VENUE : Ramanujan Lecture
From playlist Air-sea Interactions in The Bay of Bengal From Monsoons to Mixing 2019