Introduction to Computational Fluid Dynamics

Mechanical engineering is one of the important branches of engineering. Fluid dynamic is essential fields of study and research within mechanical engineering. Majority of engineering challenges directly or indirectly deals with the fluid dynamics. With development of numerical methods and the increase of computer power, we can simulate complex engineering problems with some degree of confidence. The combined field of engineering mathematics and fluid dynamics we generally call as Computational Fluid Dynamics (CFD). The present course focuses on CFD techniques and tools. The students will learn different tools and techniques used to simulate and to solve complex engineering problems through CFD.

Classic examples of CFD modelling and its applications are aerodynamic shape optimization of aircraft, landing gear, wind turbine blades, car, bridge, tall buildings. CFD tools are also used in the field of medicine to model blood flow through heart. CFD is not limited to mechanical engineering, it is applicable to almost all engineering branches and the medicine. Use of CFD enables to minimize the cost of the expensive experimental studies. Through CFD tools, we model the governing equations, including conservation of mass, momentum and energy. We can also model the turbulent characteristics of flow.

This course provides basic competence of important topics numerical modelling, which creates foundation for the advanced courses in subsequent years, specifically writing of master’s thesis using CFD tools. Some of the topics are introductory level, and others are at analysis, evaluate and critical reflection level. Following are the broad topics students will learn in this course. Detailed information on the depth of the topics will be given in the classroom.

1. Conservation of mass, momentum and energy equations with discretization techniques.
2. Introduction of CFD to solve engineering problems.
3. Basics of partial differential equations (PDEs) in fluid dynamics, spatial discretization methods, time discretization methods, stability related methods, solution verification and validation.
4. Introduction to turbulence modelling.
5. Selected cases in the field fluid dynamics, thermodynamics, heat transfer and turbomachinery.
6. Use of numerical tools to simulate the problems (software learning).

This course aims to increase student’s fundamental knowledge on numerical techniques, and create interest in solving engineering problems using CFD tools. This course also aims to develop skill (software learning) in CFD modelling, foster critical thinking on numerical accuracy and to reflect through verification and validation of the numerical results.

Competence

After the completion of the course the candidate will be able to…

1. use the knowledge of mathematical modelling techniques and carry out computational fluid dynamic analysis of engineering problems within mechanical engineering.
2. model and simulate the fluid flow related problems using available software tools.
3. use the knowledge of verification and validation techniques, and evaluate the quality of the mathematical model, and demonstrate the reliability of results.
4. communicate the results of modelled engineering problem through a scientific report and the presentations.

Skill

After the completion of the course the candidate will be able to…

1. prepare numerical model of real-life engineering case and simulate with certain assumptions and explain the results with some degree of confidence.
2. use the knowledge of the numerical methods, turbulence modelling, discretization schemes and boundary conditions, and select required parameters consciously to carry out the simulations.
3. classify and weigh between the complexities of real-life engineering cases and available computer resources. The candidate can make suitable judgement on required simplifications of the mathematical model and the consequences in terms of accuracy of the results.
4. solve simplified engineering problems related to fluid dynamics using finite difference method.
5. work in collaboratively in a group and make a scientific presentation, discuss numerical results, judge the quality of the results recognizing state-of-the-art in the field of computational fluid dynamics. In addition, the candidate will be able to document the work in a scientific report.

Knowledge

After the completion of the course the candidate…

1. can explain the conservation laws and describe in the context of computational fluid dynamics.
2. will be able to solve simplified fluid dynamic problem using the knowledge of partial differential equation.
3. has knowledge of finite difference and finite volume methods, and will be able to formulate the basic fluid dynamic related engineering problems through suitable programme and software.
4. can list the essential steps, governing laws, equations and methods used to carry out computational fluid dynamic analysis.
5. has knowledge of basic post-processing techniques of simulated problem and can show contours, streamlines and vectors.
6. has knowledge of software programme to model, and is trained to simulate the simplified fluid dynamic problems.
7. has knowledge of numerical errors and uncertainties and, the candidate can draw preliminary conclusion on the accuracy of the modelled engineering problems.

The candidate has knowledge of documentation of scientific results obtained through computational fluid dynamic analysis.

Learning methods are divided into several categories,

• collaborative learning in group,
• project base learning,
• problem base learning (case studies).

The very first lecture focuses on course specific information such as course structure, assignments, group work, assessment, expectations and learning outcome. It is desirable for all students to join the first lecture in this course. The second and subsequent lectures focus on course specific instructions and learning. This course is divided into two main segments: (1) regular lectures and (2) project work. During regular lectures, instructions on theoretical concepts and mathematical modelling will be given through lectures, presentations, group work and exercises. Second part of the semester will focus on applying the theoretical concepts and programming skills to the project work. The project work will be carried out using available programming tools and solving the problem. That includes creating geometry, mesh, prescribing boundary conditions, simulation and post-processing the results. The students will deliver the project presentation and report at the end of the semester.

We may use OpenFOAM and ParaView as a tool for the CFD simulations and post processing of the results. This course does not teach specifics of the OpenFOAM software. Essential information to carry out the basic CFD simulation using OpenFOAM will be given during the project work.