Course detail
Computational Fluid Dynamics
FSI-MVP-A Acad. year: 2021/2022 Summer semester
Computational fluid dynamics (CFD) is one of the three pillars of modern fluid dynamics (theoretical fluid dynamics, experimental fluid dynamics, CFD). Spreading of the CFD codes into practice requires acquainting with methods of numerical solution of fluid flow. Their knowledge is necessary for correct evaluation of the computational simulation results and qualified usage of CFD software for fluid machines and systems design.
Supervisor
Department
Learning outcomes of the course unit
Student will get acquinted with principles of numerical solution of fluid flow and with optimization methods for fluid machines and elements design. Student will obtain skills of work with particular CFD code (Fluent).
Prerequisites
Knowledge of basic equations of fluid flow, basics of work with PC.
Planned learning activities and teaching methods
The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.
Assesment methods and criteria linked to learning outcomes
Oral and written part, evaluation of the project reports. Overall grading according to ECTS scale.
Language of instruction
English
Aims
Aquainting with principles of computational fluid dynamics, gaining knowledge for practical work with CFD software.
Specification of controlled education, way of implementation and compensation for absences
Attendance is recorded, limited absence is judged individually. 4 project reports.
The study programmes with the given course
Programme N-ENG-A: Mechanical Engineering, Master's
branch ---: no specialisation, 6 credits, compulsory-optional
Type of course unit
Lecture
39 hours, optionally
Teacher / Lecturer
Syllabus
1. Role of CFD in design of fluid machines, advantages and limitations of computational modeling. Motivating presentation of CFD applications.
2. Basic differential equations of fluid mechanics, mathematical classification of these equations, necessity of numerical solution.
3. Approaches to discretization of partial differential equations (finite differences, volumes, elements). Finite volume method (FVM).
4. Application of FVM to 1D and 2D diffusion. Solution of the systém of equations. Convergence.
5. Unsteady problem. Explicit, implicit scheme.
6. Advection – diffusion problem, algorithm SIMPLE.
7. Flow in rotating frame of reference (multiple reference frame, mixing plane, sliding mesh), multiphase flow – basic principles.
8. Turbulence, possibilities of computational solution. Statistical analysis. Reynolds equations. Turbulent stress tensor. Problem of the equation systém closure. Boussinesque hypothesis.
9. Turbulence models (zero, one, two equation models, Reynolds stress model). Large eddy simulation. Direct numerical simulation.
10. Near wall modeling (wall functions, two layer approach). Visualization in CFD environment.
11. Shape optimization of fluid elements, Geometry parametrization, objective function definition, interconnecting of optimization and CFD.
12. Principles of some optimization methods.
13. Integration of CFD in CAE (Computer Aided Engineering) environment. Presentation on the real example of fluid machine or element (together with presentation of the research engineer from industry).
Computer-assisted exercise
26 hours, compulsory
Teacher / Lecturer
Syllabus
1. Acquiting with computational modeling process (preprocessor + solver + postprocessor)
2. – 4. Rotationally symmetrical laminar pipe flow. Comparison of numerical analytical solution. Computational grid building, boundary conditions assigning, preparation of the computational model for solution in the code Fluent, evaluation, writing report for every team
6.-.7. Numerical solution of 1D diffusion problem (arbitrary programming language of spreadshhet)
8.-11. Planar flow through axial blade cascade. Individual teams will compute different flow rates and angles of the cascade. Results will be presented in report.
12.-13. Optimization code of selected optimization method.