One-Semester CDEEP Course On

Computational Fluid Dynamics and Heat Transfer (CFDHT)

January-April, 2009 

 
COURSE INSTRUCTOR: Prof. Atul Sharma

CENTER FOR DISTANCE ENGINEERING EDUCATION PROGRAMME (CDEEP)
 

Indian Institute of Technology Bombay

   Powai,  Mumbai - 400 076 

A 6 min. Video on "Brief Overview on CFD"

  Computational Fluid Dynamics (CFD) is a methodology for computer simulation of fluid mechanics and heat transfer problems. The simulation results in prediction of the flow fields in the domain of interest and engineering parameters, which are very useful in the design and optimization of processes and equipments.  It is an open ended application of UG core courses of fluid mechanics and heat transfer. CFD reduces the time and cost for designing and analyzing engineering systems and is slowly becoming part and parcel of Computer Aided Engineering.

 CFD is taught as a one-semester course through CDEEP (Center for Distance Engineering Education Programme), IIT Bombay, for the last two years to UG as well as PG students of various engineering branches using modern teaching methodology. The teaching material is prepared using technology enhanced teaching tools and consists of lots of colorful figures and animations. Animations enhance learning retention as compared to simple graphics/figures. Thus, animated teaching materials are designed using logical and data dependencies. Although this course is advanced in nature, mostly taught to postgraduate students, it is becoming undergraduate course for various branches in many collages due to its increased usage, lack of trained manpower and importance in engineering software development, application and analysis. However, there is lack of trained teachers for this course.

  Four steps are required to develop/apply a general-purpose CFD code to an industrial problem. First, the domain with boundary and initial conditions must be defined. This amounts to constructing the geometry for the problem, which is typically done using a computer-assisted design (CAD) like preprocessor. The solution is obtained at certain discrete points in the domain whose specification known as grid generation is the second step. In the third step, the conservation laws are discretized over the specified grid using finite volume method, and the resulting linear algebraic equations are solved. The fourth step is to analyze the solution to obtain the desired information which may be an engineering parameter extracted from the solution data set, an animation illustrating the transient evolution of the entire flow field, or anything in between. Because the data sets can be quite large, robust CFD postprocessor are often required for the analysis of data set.

  This course is introductory for persons with basic knowledge of fluid mechanics, heat transfer and numerical methods but also includes advanced topics such as computational multi-fluid dynamics. The objective is to develop an appreciation of the theory behind the computer screen, so that a participant can develop/use CFD software intelligently. Furthermore, the objective is to appreciate the nuances of the concepts though the computer simulation of carefully designed exercise problems. With this two-pronged approach of theory and exercise problems, the participant will be firmly set on the path of becoming a CFD expert.

• Fundamentals of Fluid Mechanics and Heat Transfer: External and Internal Flow, modes of heat transfer, conservation laws, governing differential equations, initial and bounday conditions, fluid & flow properties and non-dimensional governing & engineering parameters.
  
• Computational Heat Conduction: Finite Volume Discretization, Explicit and Implicit methods, Implementation Details, Pseudo code and solution algorithm. Multi-solid heat conduction. Non-linear Heat Conduction, Example problems.
• Grid Generation: Structured and Unstructured Grids. Algebraic and Elliptic Methods. Examples of O-type, C- type and H-type structured grid generation.
• Computational Heat Conduction in Complex Domains: Finite Volume Discretization, Implementation Details and Solution Algorithm, Example Problems.
  
• Computational Heat Advection and Convection(Advection-Diffusion): Finite Volume Discretization, advection schemes, Pseudo code and solution algorithm. Example Problems.
• Computational Fluid Dynamics and Heat Transfer: in simple as well as complex domains, Finite Volume Discretization, Explicit and Implicit methods, Solution Algorithms, Example Problems.
• Computational Multi-Fluid/Phase Dynamics: Volume of Fluid and Level Set Method. Example problems  with and without phase change.