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Course detail
FSI-MVPAcad. year: 2026/2027
The course introduces students to modern Computational Fluid Dynamics (CFD) as a key tool in contemporary engineering. It integrates the physical principles of fluid flow, numerical methods, and the practical use of commercial CFD software to enable students to build reliable simulations, interpret them correctly, and apply them in the design and optimization of fluid systems and energy technologies. Emphasis is placed on understanding the relationships between flow physics, numerical approaches, turbulence modelling, and mesh quality, as well as on the verification and validation of obtained results. Upon completion, students will have the competencies required for qualified and responsible use of CFD in industrial and research practice, particularly in fluid engineering, energy systems, and computational simulations for sustainable energy.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
Knowledge of basic equations of fluid flow and fluid mechanics principles..
Rules for evaluation and completion of the course
The final grade is based on the evaluation of projects assigned throughout the semester (4–5 individual and team projects) and a written examination in CFD theory. The overall grade follows the ECTS point scale.
All reports and outputs are prepared in English.
Attendance is recorded; any (limited) absences are handled individually.
Aims
The course offers a comprehensive introduction to computational fluid dynamics (CFD) and to the numerical solution of the governing flow equations, with a particular focus on the finite volume method. Students acquire both the theoretical background and practical skills necessary for qualified work with CFD software – from mesh generation and the selection of appropriate physical and turbulence models to the correct interpretation and validation of simulation results.
The course also introduces the fundamentals of multiphase flow modelling, flow in rotating domains, and the use of optimization methods in the design of fluid machinery. A substantial part of the instruction is carried out through individual and team projects using the commercial CFD software ANSYS Fluent.
Study aids
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
specialization FLI , 1 year of study, summer semester, compulsory
Lecture
Teacher / Lecturer
Syllabus
1. The role of computational modelling (CFD) in the design of fluid machinery; advantages and limitations of computational modelling. Massively parallel computations, HPC, GPU computing. Motivational examples of CFD applications.
2. Basic differential equations of fluid mechanics; mathematical classification of these equations; the necessity of numerical solution. Approaches to discretizing partial differential equations (finite differences, finite elements, finite volumes).
3. The finite volume method. Application of the finite volume method to 1D and 2D diffusion problems. Solution of systems of equations.
4. Convection–diffusion problems, numerical interpolation schemes. Convergence (definition, practical assessment), convergence acceleration.
5. Momentum equations, the SIMPLE algorithm. Unsteady problems. Explicit and implicit schemes, stability conditions (CFL), selection of time step.
6. Computational meshes: types, quality metrics, adaptation. Flow in rotating reference frames (multiple reference frame, mixing plane, sliding mesh).
7. Turbulence (physical description, phenomenology, transition to turbulence), options for computational modelling of turbulent flow.
8. Statistical analysis, Reynolds equations, turbulent stresses, the closure problem, Boussinesq hypothesis.
9. Turbulence models (zero-, one-, and two-equation models; Reynolds stress models). Large Eddy Simulation (LES). Direct Numerical Simulation (DNS). Advanced turbulence models (scale-resolved and hybrid approaches), data-driven turbulence models.
10. Near-wall modelling (wall functions, two-layer approach). Validation, verification, computational uncertainties. “Best practice” recommendations.
11. Multiphase flow (Euler vs. Lagrange, Volume of Fluid, mixture model, cavitation).
12. Shape optimization of fluid components. Geometry parametrization, definition of the objective function, coupling with CFD, scripting. Principles of selected optimization methods. Reduced-order models, digital twins.
13. Integration of CFD in development and research. Demonstration on a real example of a fluid machine or component (including a presentation by a practising researcher).
Computer-assisted exercise
1. Project 1: Computational modeling and experimental visualization of selected flow phenomenon.
2.-4. Acquainting with flow simulation process (preprocessor + solver + postprocessor). Application in Ansys Fluent environment. Basics of geometry modeling (SpaceClaim, Ansys Modeler) and mesh building (Ansys Mesh, Fluent Meshing)
Project 2 : setting up a script for postprocessing
6.-7. Project 3: Industrial project
8.-11. Project 4 : Industrial project
12.-13. Project 5: Shape optimization in CFD environment