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Computational Fluid Dynamics of Mech IV yr-II Sem (Elective-IV)

Computational Fluid Mechanics for Mechanical Engineers Video Course By S. Chakraborty (IIT KHANPUR)
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Students Enrolled: 0 Total Lecturs: 43
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What will I learn from this course?

  • Appriciate and understand Computational Fluid Dynamics

Requirements

  • Fluid Mechanics ,Heat Transfer, Transport Phenomena, Elementary Numerical Analysis, ODE PDE

Who is the target audience?

  • Any Stream of B.Tech and B.E Students

Course Curriculum

Total: 43 lectures

  • 58m 20s

    Lec 1: Introduction to Computational Fluid Dynamics and Principles of Conservation

  • 59m 4s

    Lec 2: Conservation of Mass and Momentum: Continuity and Navier Stokes Equation

  • 56m 41s

    Lec 3: Equation Navier Stokes Equation

  • 58m 36s

    Lec 4: Enerfy Equation and General Structure of Conservation Equations

  • 57m 1s

    Lec 5: Classification of Partial Differential Equations and Physical Behaviour

  • 58m 36s

    Lec 6: Contd of Classification of Partial Differential Equations and Physical Behaviour

  • 58m 45s

    Lec 7: Approximate Solutions of Differential Equations: Error Minimization Principles

  • 59m 22s

    Lec 8: Variational Principles and Weighted Residual Approach

  • 58m 54s

    Lec 9: Weighted Residual Appoach and Introduction to Discretization

  • 56m 59s

    Lec 10: Fundemental of Discretization: Finite Element Method

  • 57m 57s

    Lec 11: Fundemental of Discretization: Finite Difference and Finite Volume Method

  • 58m 27s

    Lec 12: Contd to Fundemental of Discretization

  • 56m 4s

    Lec 13: 1-D Steady State Diffusion

  • 58m 30s

    Lec 14: Discretization of Unsteady State Problems

  • 55m 53s

    Lec 15: Finite Volume Method ;Discretization of Unsteady State Problems

  • 54m 7s

    Lec 16: Important Consequences of Discretization

  • 1h 30m 00s

    Lec 17: Contd to Important Consequences of Discretization

  • 56m 35s

    Lec18: Discretization of Hyperbolic Equations: Stability Analysis

  • 57m 23s

    Lec 19: Stability of Second Order Hyperbolic Equations

  • 58m 25s

    Lec 20: Finite Volume Discretization of 2-D

  • 58m 40s

    Lec 21: Solutions of Systems of Linear Algebraic Equations

  • 57m 57s

    Lec 22: Elimination Methods

  • 59m 12s

    Lec 23: Contd to Elimination Methods

  • 58m 58s

    Lec 24: Elimination Methods: Error ananlysis

  • 58m s

    Lec 25: Iterative Methods for Numerical Solution

  • 55m 35s

    Lec 26: Contd to Iterative Methods for Numerical Solution

  • 58m 48s

    Lec 27: Iterative Methods; Further Examples

  • 57m 52s

    Lec 28: Introduction to Gardient Search Methods

  • 57m 51s

    Lec 29: Contd to Gardient Search Methods

  • 57m 58s

    Lec 30: A Finite Volume approach

  • 58m 27s

    Lec 31: Contd to A Finite Volume approach

  • 58m 51s

    Lec 32: Contd to A Finite Volume approach

  • 58m 44s

    Lec 33: Contd to A Finite Volume Approach

  • 57m 55s

    Lec 34: Contd to A Finite Volume Approch

  • 59m 34s

    Lec 35: Discretization of Navier Stoke Eqution

  • 1h 27m 00s

    Lec 36: Contd to Discretization of Navier Stoke Eqution

  • 57m 59s

    Lec 37: Contd to Discretization of Navier Stoke Eqution

  • 59m 2s

    Lec 38: Contd to Above Lec 38 Eqtn and Unstructed Grid Formation

  • 58m 33s

    Lec 39: Contd to Unstructed Grid Formation

  • 56m 31s

    Lec 40: Whats the Implementing in CFD Code

  • 58m 31s

    Lec 41: Introduction to Turbulence Modeling

  • 58m 47s

    Lec 42: Contd Introduction to Turbulence Modeling

  • 58m 11s

    Lec 43: End Semister Questions Review

Description

(1)Insight into the philosophy and power of CFD; (2) an understanding of the nature of the fluid dynamics equations; (3) a familiarity with finite volume method (FVM), the core of most in-house CFD codes and commercial CFD packages, which includes e.g., different levels of discretization, different spatial and temporal discretization schemes, assessment of the schemes, pressure-velocity coupling algorithms, under-relaxation, boundary conditions, solvers, and so on; (4) practices and demos on solving relatively simple problems by programming;

About Tutor

  • Tutor: S. Chakraborty (IIT KHANPUR)
  • Tests Packages: 0
  • Students: 0
4.4

Dr. Saikat Chakrabarti as Senior Member, IEEE; Member, CIGRE
Associate Professor, Department of Electrical Engineering
Indian Institute of Technology Kanpur.

Professional and research experience

• Associate Professor, Department of Electrical Engineering, Indian Institute of Technology,
Kanpur, India. June 2014 to Present.
• Assistant Professor, Department of Electrical Engineering, Indian Institute of Technology,
Kanpur, India. December 2009 to June 2014.
• Lecturer, Department of Electrical Engineering, Faculty of Built Environment and Engineering,
Queensland University of Technology, Brisbane, Australia. February 2009 to
November 2009.
• Research Associate, Department of Electrical Engineering, Faculty of Built Environment
and Engineering, Queensland University of Technology, Brisbane, Australia. August 2008
to January 2009.

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