Need for Computational Fluid Dynamics CFD

Posted on Posted in Blog, Mechanical Engineering, Mid Level

Here we first discuss some basic concepts utilized in the field of Fluid Mechanics. Majority of Engineering students find it difficult to understand the major difference between these basic concepts and how to categorize certain fluid flow conditions.

As the blog advances, the need for CFD in fluid flow analysis is explained along with a brief description of some common yet important CFD applications.

Basic Concepts

Mechanics: The oldest physical science that deals with both stationary and moving bodies under the influence of forces.

Statics: The branch of mechanics that deals with bodies at rest.

Dynamics: The branch that deals with bodies in motion.

Fluid Mechanics: The science that deals with the behaviour of fluids at rest (fluid statics) or in motion (fluid dynamics), and the interaction of fluids with solids or other fluids at the boundaries.

Fluid mechanics can be divided into three divisions:

Hydrostatics: that studies the mechanics of fluids at absolute and relative rest.

Kinematics: deals with translation, rotation and deformation of fluid without considering the force and energy causing such a motion.

Dynamics: that prescribes the relation between velocities and acceleration and the forces which are exerted by or upon the moving fluids.

Applications:

Applications Applications

                           Aerospace and Avionics                                                                            Automobiles

Applications Applications

Medical Science                                                                                Piping and Plumbing

Applications Applications

Cruise Industry                                                                                         Wind Turbines

 

Fluid Flow Examples:

  • Meteorological phenomena (rain, wind, hurricanes, floods).
  • Environmental hazards (air pollution, transport of contaminants).
  • Heating, ventilation and air conditioning of buildings, cars etc.
  • Combustion in automobile engines and other propulsion systems.
  • Interaction of various objects with the surrounding air/water.
  • Complex flows in furnaces, heat exchangers, chemical reactors etc.
  • Processes in human body (blood flow, respiratory air flow.
  • In daily life like: breathing, smoking, drinking, digesting, jogging, cycling, swimming, playing golf, badminton, cricket, surfing, sailing, parachuting etc.

Fluid Dynamics Analysis: Approaches

In Fluid dynamics, we normally need to do analysis of the following flow parameters:

  • Flow velocities.
  • Pressure.
  • Temperature.

Currently we have the following three approaches available:

Experimental Fluid Dynamics (EFD): Experimental evaluation of flow properties at discrete points (experimental correlations in continuous form).

Computational Fluid Dynamics (CFD): Solution of Partial differential equations on a discrete grid (flow properties evaluation in discrete form at specific points).

Analytic Fluid Dynamics (AFD): Simplification of governing PDEs into ODEs by using certain assumptions (flow properties relations in continuous form).

Fluid Dynamics Analysis: Approaches

Need for Computational Fluid Dynamics CFD

  • Increasing complexity of unsolved engineering problems.
  • Need for quick solutions of acceptable accuracy.
  • Absence of analytical solutions.
  • The prohibitive costs involved in performing even scaled laboratory experiments.
  • Efficient solution algorithms.
  • Developments in computers in terms of speed and storage.
  • Parallel computing.
  • Sophisticated pre and post processing facilities.

Introduction to CFD

Fluid (gas and liquid) flows are governed by partial differential equations which represent conservation laws for the mass, momentum, and energy. Computational Fluid Dynamics (CFD) is the art of replacing such Partial Differential Equations PDE systems by a set of algebraic equations which can be solved using digital computers.

Three basic domains involved in CFD

  1. Physical knowledge of the system and boundary conditions.
  2. mathematical modeling (partial differential equations) and numerical methods (discretization and solution techniques).
  3. software tools (solvers, pre-processing and post-processing utilities).

 

CFD Analysis Process

Problem statement:

  • Flow domain, known information about the flow: external or internal.
  • Physical phenomena consideration: laminar or turbulent. Compressibility effects.
  • Type of flow: steady/unsteady.
  • Objective of analysis: integral properties, flow field information, design optimization, understanding of flow physics.

Mathematical model:

  • Governing equations.
  • Simplification/modelling of the physical phenomena.
  • Specification of initial conditions and boundary conditions.

Mesh generation:

  • Decomposing the flow domain in small cells, elements.
  • Structured or unstructured grid.
  • Mesh size, adaptive grid refinement.

Space discretization:

  • Finite differences/volumes/elements.
  • High- and low-order approximations.

Temporal discretization:

  • Explicit vs. implicit schemes.
  • Stability and accuracy constraints.

 

CFD Analysis Process

Solution strategy:

  • Iterative or direct.
  • Selection of solution method and convergence criteria.
  • The sparsity of unknown matrix: optimization techniques.

CFD software/Computer code:

  • Usually written in FORTRAN.
  • Hardware, parallelization.

Verification and Validation:

  • Order of accuracy of simulation.
  • Comparison with analytic solution/experimental data.
  • Grid independence and time step independence test.

Postprocessing:

  • Calculation of integral quantities (lift and drag).
  • Calculation of derived quantities (stream function, vorticity)
  • Flow visualizations: 1D data (graphs), 2D data (streamlines, contour levels), 3D data (iso-surfaces), animations.

Types of Errors:

  • Physical modeling error: due to uncertainty and deliberate simplifications
  • Discretization error: approximation of PDEs by algebraic equations.
  • Round-off errors: due to the finite precision of computer arithmetic.
  • Computer programming error: bugs in coding and logical mistakes.
  • Usage error: wrong parameter values, models or boundary conditions.

Advantages of using CFD

  • CFD enables scientists and engineers to perform numerical experiments (i.e. computer simulations) in a virtual flow laboratory.
  • CFD complements its experimental and analytic counter-part.
  • Better visualization and enhanced understanding of designs.
  • Testing many variations until one arrives at an optimal result before physical prototyping and testing.
  • Increased efficiency in design process.

Applications of CFD

Numerical simulations of fluid flow enable:

  • architects to design comfortable and safe living environments.
  • designers of vehicles to improve the aerodynamic characteristics.
  • surgeons to cure arterial diseases and help diagnose the disease (computational hemodynamics).
  • meteorologists to forecast the weather and warn of natural disasters.
  • safety experts to reduce health risks from radiation and other hazards.
  • military organizations to develop weapons and estimate the damage.

Applications of CFD Applications of CFD Applications of CFD

Reference

Lecture notes on Computational Fluid Dynamics-I by Dr. Tariq Talha,

College of EME, NUST, Islamabad, Pakistan.

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