Канал: Aerodynamic CFD

Simulating a 3D flute in Flow360

Simulating a 3D flute in Flow360

箫 Vertical flute simulation starting

箫 Vertical flute simulation starting

箫 Vertical flute simulation with faster jet starting

箫 Vertical flute simulation with faster jet starting

箫 Vertical Flute Simulation after two seconds

箫 Vertical Flute Simulation after two seconds

A vertical flute Xiao simulated by Jolie Duquene

A vertical flute Xiao simulated by Jolie Duquene

Aerodynamics (MIT 16.100) 2023 Lecture 20

Aerodynamics (MIT 16.100) 2023 Lecture 20

Aerodynamics (MIT 16.100) 2023 Lecture 19

Aerodynamics (MIT 16.100) 2023 Lecture 19

Aerodynamics (MIT 16.100) 2023 Lecture 18

Aerodynamics (MIT 16.100) 2023 Lecture 18

Aerodynamics (MIT 16.100) 2023 Lecture 17

Aerodynamics (MIT 16.100) 2023 Lecture 17

Aerodynamics (MIT 16.100) 2023 Lecture 16

Aerodynamics (MIT 16.100) 2023 Lecture 16

Aerodynamics (MIT 16.100) 2023 Quiz 1 Review

Aerodynamics (MIT 16.100) 2023 Quiz 1 Review

Aerodynamics (MIT 16.100) 2023 Lab CFD Intro

Aerodynamics (MIT 16.100) 2023 Lab CFD Intro

Aerodynamics (MIT 16.100) 2023 Lecture 15

Aerodynamics (MIT 16.100) 2023 Lecture 15

Aerodynamics (MIT 16.100) 2023 Lecture 14

Aerodynamics (MIT 16.100) 2023 Lecture 14

Aerodynamics (MIT 16.100) 2023 Lab Xfoil 2

Aerodynamics (MIT 16.100) 2023 Lab Xfoil 2

Aerodynamics (MIT 16.100) 2023 Lecture 13

Aerodynamics (MIT 16.100) 2023 Lecture 13

Aerodynamics (MIT 16.100) 2023 Lecture 12

Aerodynamics (MIT 16.100) 2023 Lecture 12

Aerodynamics (MIT 16.100) 2023 Lecture 11

Aerodynamics (MIT 16.100) 2023 Lecture 11

Aerodynamics (MIT 16.100) 2023 Lab Xfoil

Aerodynamics (MIT 16.100) 2023 Lab Xfoil

Aerodynamics (MIT 16.100) 2023 Lecture 10

Aerodynamics (MIT 16.100) 2023 Lecture 10

Aerodynamics (MIT 16.100) 2023 Lecture 09

Aerodynamics (MIT 16.100) 2023 Lecture 09

Aerodynamics (MIT 16.100) 2023 Lecture 08

Aerodynamics (MIT 16.100) 2023 Lecture 08

Aerodynamics (MIT 16.100) 2023 Lecture 05

Aerodynamics (MIT 16.100) 2023 Lecture 05

Aerodynamics (MIT 16.100) 2023 Lecture 07

Aerodynamics (MIT 16.100) 2023 Lecture 07

Aerodynamics (MIT 16.100) 2023 Lecture 06

Aerodynamics (MIT 16.100) 2023 Lecture 06

Aerodynamics (MIT 16.100) 2023 Lab AVL

Aerodynamics (MIT 16.100) 2023 Lab AVL

Aerodynamics (MIT 16.100) 2023 Lecture 04

Aerodynamics (MIT 16.100) 2023 Lecture 04

Aerodynamics (MIT 16.100) 2023 Lecture 03

Aerodynamics (MIT 16.100) 2023 Lecture 03

Aerodynamics (MIT 16.100) 2023 Lecture 02

Aerodynamics (MIT 16.100) 2023 Lecture 02

Aerodynamics (MIT 16.100) 2023 Lecture 01

Aerodynamics (MIT 16.100) 2023 Lecture 01

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 21

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 21

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 20

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 20

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 18

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 18

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 17

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 17

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 16

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 16

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 15

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 15

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 14

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 14

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 13

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 13

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 12

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 12

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 11

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 11

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 10

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 10

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 9

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 9

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 8

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 8

Computer Vision and Artificial Intelligence Lecture 1

Computer Vision and Artificial Intelligence Lecture 1

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 7

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 7

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 6

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 6

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 5

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 5

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 4

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 4

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 2-3

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 2-3

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 1

Theory, Computation, and Applications of Nonlinear Dynamical Systems Lecture 1

Aerodynamics (MIT 16.100) 2022 Lecture 22

Aerodynamics (MIT 16.100) 2022 Lecture 22

Aerodynamics (MIT 16.100) 2022 Lecture 21

Aerodynamics (MIT 16.100) 2022 Lecture 21

Aerodynamics (MIT 16.100) 2022 Lecture 20

Aerodynamics (MIT 16.100) 2022 Lecture 20

Aerodynamics (MIT 6.100) 2022 Lecture 19

Aerodynamics (MIT 6.100) 2022 Lecture 19

Aerodynamics (MIT 16.100) 2022 Lecture 18

Aerodynamics (MIT 16.100) 2022 Lecture 18

Aerodynamics (MIT 16100) 2022 Lecture 17: Oblique Shocks and Supersonic Aerodynamics

Aerodynamics (MIT 16100) 2022 Lecture 17: Oblique Shocks and Supersonic Aerodynamics

Aerodynamics (MIT 16.100) 2022 Lecture 16: Compressibility and shock wave

Aerodynamics (MIT 16.100) 2022 Lecture 16: Compressibility and shock wave

Aerodynamics (MIT 16.100) 2022 Lecture 15: Boundary Layer Separation and High Lift Airfoils

Aerodynamics (MIT 16.100) 2022 Lecture 15: Boundary Layer Separation and High Lift Airfoils

Aerodynamics (MIT 16.100) 2022 Lecture 14: Boundary layer thicknesses and effect of pressure

Aerodynamics (MIT 16.100) 2022 Lecture 14: Boundary layer thicknesses and effect of pressure

Aerodynamics (MIT 16.100) 2022 Lecture 13: Complex 2D potential flows

Aerodynamics (MIT 16.100) 2022 Lecture 13: Complex 2D potential flows

Aerodynamics (MIT 16.100 2022) Lecture 12: Three dimensional vortices

Aerodynamics (MIT 16.100 2022) Lecture 12: Three dimensional vortices

Aerodynamics (MIT 16.100) 2022 Lecture 11: Aerodynamic stability

Aerodynamics (MIT 16.100) 2022 Lecture 11: Aerodynamic stability

Aerodynamics (MIT 16.100) 2022 Lecture 10: Center of lift on an airfoil

Aerodynamics (MIT 16.100) 2022 Lecture 10: Center of lift on an airfoil

Aerodynamics (MIT 16.100) 2022 Lecture 9: Potential flow over symmetric airfoils

Aerodynamics (MIT 16.100) 2022 Lecture 9: Potential flow over symmetric airfoils

Aerodynamics (MIT 16.100) 2022 Lecture 8: incompressible potential flow theory

Aerodynamics (MIT 16.100) 2022 Lecture 8: incompressible potential flow theory

Aerodynamics (MIT 16.100) 2022 Lecture 7: rotational and irrotational flows

Aerodynamics (MIT 16.100) 2022 Lecture 7: rotational and irrotational flows

Aerodynamics (MIT 16.100) 2022 Lecture 6: what is vorticity?

Aerodynamics (MIT 16.100) 2022 Lecture 6: what is vorticity?

Aerodynamics (MIT 16.100) 2022 Lecture 5: boundary layer and flow regimes

Aerodynamics (MIT 16.100) 2022 Lecture 5: boundary layer and flow regimes

Aerodynamics (MIT 16.100) 2022 Lecture 4: drag decomposition and boundary layer

Aerodynamics (MIT 16.100) 2022 Lecture 4: drag decomposition and boundary layer

Aerodynamics (MIT 16.100) 2022 Lecture 3: thermodynamics and compressible flow sensitivities

Aerodynamics (MIT 16.100) 2022 Lecture 3: thermodynamics and compressible flow sensitivities

Aerodynamics (MIT 16.100) 2022 Lecture 2: drag and energy consumption

Aerodynamics (MIT 16.100) 2022 Lecture 2: drag and energy consumption

Aerodynamics (MIT 16.100) 2022 Lecture 1: applications of aerodynamic forces

Aerodynamics (MIT 16.100) 2022 Lecture 1: applications of aerodynamic forces

Blade Line Model Simulation of a Lift+Cruise vehicle in Flow360

Blade Line Model Simulation of a Lift+Cruise vehicle in Flow360

Blade Line Model Simulation of a Lift+Cruise vehicle in Flow360

Blade Line Model Simulation of a Lift+Cruise vehicle in Flow360

Blade Line Simulation in Flow360

Blade Line Simulation in Flow360

Blade Line Model in Flow360

Blade Line Model in Flow360

Blade Element Theory simulation in Flow360

Blade Element Theory simulation in Flow360

How to run CFD for your project

How to run CFD for your project

Design Project Considerations

Design Project Considerations

Common mistake in Quiz2 fairing stability

Common mistake in Quiz2 fairing stability

Common mistake in Quiz2 airplane balance and stability

Common mistake in Quiz2 airplane balance and stability

Velocity Fields around a Supersonic Airfoil 2

Velocity Fields around a Supersonic Airfoil 2

Velocity Fields around a Supersonic Airfoil 1

Velocity Fields around a Supersonic Airfoil 1

Pressure Fields on a Supersonic Airfoild 3

Pressure Fields on a Supersonic Airfoild 3

Pressure Fields on a Supersonic Airfoil 2

Pressure Fields on a Supersonic Airfoil 2

Pressure Fields on a Supersonic Airfoil 1

Pressure Fields on a Supersonic Airfoil 1

Pressure Field on a Supersonic Airplane 2

Pressure Field on a Supersonic Airplane 2

Pressure Field on a Supersonic Airplane 1

Pressure Field on a Supersonic Airplane 1

Pressure around a supersonic airplane at Mach 2.4 computed with Flow360

Pressure around a supersonic airplane at Mach 2.4 computed with Flow360

Pressure around a supersonic airplane at Mach 1.4 computed with Flow360

Pressure around a supersonic airplane at Mach 1.4 computed with Flow360

Impulse start of a lifting airplane

Impulse start of a lifting airplane

Simulating XV-15 using Flow360

Simulating XV-15 using Flow360

Introduction to Flow360

Introduction to Flow360

MIT Aerodynamics Physics and mathematics of momentum conservation Part 1

MIT Aerodynamics Physics and mathematics of momentum conservation Part 1

MIT Aerodynamics Physics and mathematics of momentum conservation Part 2

MIT Aerodynamics Physics and mathematics of momentum conservation Part 2

MIT Aerodynamics Physics and mathematics of momentum conservation Part 3

MIT Aerodynamics Physics and mathematics of momentum conservation Part 3

MIT Aerodynamics Physics and mathematics of momentum conservation Part 4

MIT Aerodynamics Physics and mathematics of momentum conservation Part 4

MIT Aerodynamics Momentum conservation example source sink

MIT Aerodynamics Momentum conservation example source sink

MIT Aerodynamics Bernouli's equation

MIT Aerodynamics Bernouli's equation

MIT Aerodynamics Introduction to 2D incompressible inviscid aerodynamics

MIT Aerodynamics Introduction to 2D incompressible inviscid aerodynamics

MIT Aerodynamics Mass conservation example source sink Part 2

MIT Aerodynamics Mass conservation example source sink Part 2

MIT Aerodynamics The physics and mathematics of mass conservation Part 2

MIT Aerodynamics The physics and mathematics of mass conservation Part 2

MIT Aerodynamics The physics and mathematics of mass conservation Part 1

MIT Aerodynamics The physics and mathematics of mass conservation Part 1

MIT Aerodynamics Physics and mathenmatics of momentum conservation

MIT Aerodynamics Physics and mathenmatics of momentum conservation

MIT Aerodynamics Mass conservation example Stagnation flow

MIT Aerodynamics Mass conservation example Stagnation flow

MIT Aerodynamics Mass conservation example source sink

MIT Aerodynamics Mass conservation example source sink

MIT Aerodynamics Course overview viscous areodynamics

MIT Aerodynamics Course overview viscous areodynamics

MIT Aerodynamics Module 1 how do racecars and helicopters produce lift

MIT Aerodynamics Module 1 how do racecars and helicopters produce lift

MIT Aerodynamics Module 1 how does a kite generate lift

MIT Aerodynamics Module 1 how does a kite generate lift

MIT Aerodynamics Module 1 lift at work in ships

MIT Aerodynamics Module 1 lift at work in ships

MIT Aerodynamics Lift from an airfoil

MIT Aerodynamics Lift from an airfoil

MIT Aerodynamics Course overview 2D incompressible inviscid aerodynamics

MIT Aerodynamics Course overview 2D incompressible inviscid aerodynamics

MIT Aerodynamics Course overview compressible aerodynamics

MIT Aerodynamics Course overview compressible aerodynamics

MIT Aerodynamics Course overview three dimensional aerodynamics

MIT Aerodynamics Course overview three dimensional aerodynamics

Inside the Lorenz attractor (10, 70, 8/3)

Inside the Lorenz attractor (10, 70, 8/3)

Inside the Lorenz system (10, 38, 8/3)

Inside the Lorenz system (10, 38, 8/3)

Inside the Lorenz system (10, 28, 8/3)

Inside the Lorenz system (10, 28, 8/3)

What if a butterfly can control the climate?

What if a butterfly can control the climate?

Shadowing produces quasi-physical solutions

Shadowing produces quasi-physical solutions

Quasi-physical solutions and shadowing

Quasi-physical solutions and shadowing

The tent map and its symbolic dynamics

The tent map and its symbolic dynamics

Periodic nonphysical solutions and the Lorenz map

Periodic nonphysical solutions and the Lorenz map

What are nonphysical solutions of chaotic systems?

What are nonphysical solutions of chaotic systems?

What is shadowing in dynamical systems?

What is shadowing in dynamical systems?

Ergodicity and the butterfly effect of climate

Ergodicity and the butterfly effect of climate

What is Ergodicity?

What is Ergodicity?

Arguments: can a butterfly control the climate?

Arguments: can a butterfly control the climate?

Is there a butterfly effect of Climate?

Is there a butterfly effect of Climate?

Lyapunov exponents and chaotic dynamics

Lyapunov exponents and chaotic dynamics

The butterfly effect of Edward Lorenz

The butterfly effect of Edward Lorenz

Lorenz system at (10, 38, 8/3)

Lorenz system at (10, 38, 8/3)

Lorenz system at (10, 70, 8/3)

Lorenz system at (10, 70, 8/3)

Lorenz system at (10, 28, 8/3)

Lorenz system at (10, 28, 8/3)

Can a butterfly in Brazil control the climate of Texas?

Can a butterfly in Brazil control the climate of Texas?

Lecture20.06. Classification as an optimization problem and measuring model quality

Lecture20.06. Classification as an optimization problem and measuring model quality

Lecture20.07. Cross-validation

Lecture20.07. Cross-validation

Lecture20.08. Regularization

Lecture20.08. Regularization

Lecture20.04. Introduction to statistical learning in engineering: regression and classification

Lecture20.04. Introduction to statistical learning in engineering: regression and classification

Lecture20.11. Course review, pt. III: FVM for PDEs

Lecture20.11. Course review, pt. III: FVM for PDEs

Lecture20.12. Course review, pt. IV: FEM for PDEs

Lecture20.12. Course review, pt. IV: FEM for PDEs

Lecture20.10. Course review, pt. II: FD for PDEs

Lecture20.10. Course review, pt. II: FD for PDEs

Lecture20.13. Course review, pt. V: Statistical methods for engineering

Lecture20.13. Course review, pt. V: Statistical methods for engineering

Lecture20.03. Back propogation of derivatives

Lecture20.03. Back propogation of derivatives

Lecture20.01. Forward propogation of derivatives

Lecture20.01. Forward propogation of derivatives

Lecture20.02. Tracing through a computational graph for foward propogation

Lecture20.02. Tracing through a computational graph for foward propogation

Lecture20.05. Regression as an optimization problem

Lecture20.05. Regression as an optimization problem

Lecture20.09. Course review, pt. I: ODEs

Lecture20.09. Course review, pt. I: ODEs

Lecture19.05. Moving from quadratic to general function optimization

Lecture19.05. Moving from quadratic to general function optimization

Lecture19.11. Computation of gradients for optimization

Lecture19.11. Computation of gradients for optimization

Lecture19.10. KKT conditions allow optimization on the constraint

Lecture19.10. KKT conditions allow optimization on the constraint

Lecture19.03. Implementation of a quadratic objective function

Lecture19.03. Implementation of a quadratic objective function

Lecture19.09. Variations and improvements: heuristic approaches and linear constraints

Lecture19.09. Variations and improvements: heuristic approaches and linear constraints

Lecture19.08. Line search method for preventing divergence

Lecture19.08. Line search method for preventing divergence

Lecture19.07. Quadratic approximation as a Newton scheme; necessity of extra safeguards

Lecture19.07. Quadratic approximation as a Newton scheme; necessity of extra safeguards

Lecture19.06. Local quadratic approximation for optimization of smooth functions

Lecture19.06. Local quadratic approximation for optimization of smooth functions

Lecture19.04. Interpreting quadratic terms as a Hessian and gradient

Lecture19.04. Interpreting quadratic terms as a Hessian and gradient

Lecture19.02. Optimization of a quadratic function in one or more variables

Lecture19.02. Optimization of a quadratic function in one or more variables

Lecture19.01. Introducting optimization by example: airfoil shape optimization

Lecture19.01. Introducting optimization by example: airfoil shape optimization

Lecture 18.04. Improving error estimation by increasing number of samples

Lecture 18.04. Improving error estimation by increasing number of samples

Lecture 18.05. Estimating the accuracy of the estimator

Lecture 18.05. Estimating the accuracy of the estimator

Lecture 18.06. The normal distribution and its ties to the Monte Carlo method

Lecture 18.06. The normal distribution and its ties to the Monte Carlo method

Lecture 18.07. The central limit theorem

Lecture 18.07. The central limit theorem

Lecture 18.08. Monte Carlo wrapup; introduction to Design of Experiments

Lecture 18.08. Monte Carlo wrapup; introduction to Design of Experiments

Lecture 18.09. Design of Experiments methods: full factorial design and parameter studies

Lecture 18.09. Design of Experiments methods: full factorial design and parameter studies

Lecture 18.10. Lattin hypercube method

Lecture 18.10. Lattin hypercube method

Lecture 18.01. Standard deviation and standard error

Lecture 18.01. Standard deviation and standard error

Lecture 18.02. Estimating the error in using a single sample

Lecture 18.02. Estimating the error in using a single sample

Lecture 18.03. Expanding error formula for multiple samples

Lecture 18.03. Expanding error formula for multiple samples

Lecture17.01. Asteroid mining: a stochastic adventure

Lecture17.01. Asteroid mining: a stochastic adventure

Lecture17.04. Implementing an inverse CDF sampler for the exponential distribution

Lecture17.04. Implementing an inverse CDF sampler for the exponential distribution

Lecture17.05. Implementing the physical model and using it to generate probabilies

Lecture17.05. Implementing the physical model and using it to generate probabilies

Lecture17.07. Quantifying error in estimating the percentages

Lecture17.07. Quantifying error in estimating the percentages

Lecture17.06. Quantifying the error in probabilistic estimates

Lecture17.06. Quantifying the error in probabilistic estimates

Lecture17.03. Implementing a acceptance sampler for the triangle distribution

Lecture17.03. Implementing a acceptance sampler for the triangle distribution

Lecture17.02. Planning an implementation of a stochastic simulation

Lecture17.02. Planning an implementation of a stochastic simulation

Lecture16.02. Randomness, random variables, and events

Lecture16.02. Randomness, random variables, and events

Lecture16.11. Issues with infinite tails; hybrid accept-reject/inverse-CDF methods

Lecture16.11. Issues with infinite tails; hybrid accept-reject/inverse-CDF methods

Lecture16.08. Accept-reject algorithm demo

Lecture16.08. Accept-reject algorithm demo

Lecture16.07. Sampling from triangle distribution using acceptance samplers

Lecture16.07. Sampling from triangle distribution using acceptance samplers

Lecture16.10. Sampling from analytical distributions using the inverse-CDF method

Lecture16.10. Sampling from analytical distributions using the inverse-CDF method

Lecture16.12. Using random samples to compute probabilities

Lecture16.12. Using random samples to compute probabilities

Lecture16.06. Sampling from uniform distributions

Lecture16.06. Sampling from uniform distributions

Lecture16.09. Exponential distribution and how to sample from it

Lecture16.09. Exponential distribution and how to sample from it

Lecture16.05. Generating random samples

Lecture16.05. Generating random samples

Lecture16.01. Probabilistic methods: motivation by example

Lecture16.01. Probabilistic methods: motivation by example

Lecture16.04. The power of random variables: quantifying probabilistic events of interest

Lecture16.04. The power of random variables: quantifying probabilistic events of interest

Lecture16.03. Interpreting events and their likelihoods using probability measures

Lecture16.03. Interpreting events and their likelihoods using probability measures

Lecture15.07. Extending finite difference to multi-dimensional problems; mesh challenges

Lecture15.07. Extending finite difference to multi-dimensional problems; mesh challenges

Lecture15.09. Multi-dimensional flux functions

Lecture15.09. Multi-dimensional flux functions

Lecture15.06. Fourier analysis demonstrates how upwinding adds stability to a system

Lecture15.06. Fourier analysis demonstrates how upwinding adds stability to a system

Lecture15.11. Applying FEM to the multi-dimensional problem

Lecture15.11. Applying FEM to the multi-dimensional problem

Lecture15.08. Extending finite volume to multi-dimensional problems; divergence theorem

Lecture15.08. Extending finite volume to multi-dimensional problems; divergence theorem

Lecture15.02. Fourier stability analysis intoduction

Lecture15.02. Fourier stability analysis intoduction

Lecture15.05. Using Fourier to quantify stability for central differencing and upwinding

Lecture15.05. Using Fourier to quantify stability for central differencing and upwinding

Lecture15.04. Application of Fourier analysis to discrete PDEs

Lecture15.04. Application of Fourier analysis to discrete PDEs

Lecture15.03. Application of Fourier analysis to PDEs

Lecture15.03. Application of Fourier analysis to PDEs

Lecture15.10. Extending finite element to multi-dimensional problems; extreme integration by parts

Lecture15.10. Extending finite element to multi-dimensional problems; extreme integration by parts

Lecture15.01. Project review

Lecture15.01. Project review

Lecture14.08. Order of accuracy of FEM: seeking the best approximation of u

Lecture14.08. Order of accuracy of FEM: seeking the best approximation of u

Lecture14.07. Temporal scheme choices for FEM/discretization of advective terms

Lecture14.07. Temporal scheme choices for FEM/discretization of advective terms