COMPUTATIONAL FLUIDS DYNAMICS

Course Information
TitleΥΠΟΛΟΓΙΣΤΙΚΗ ΡΕΥΣΤΟΜΗΧΑΝΙΚΗ / COMPUTATIONAL FLUIDS DYNAMICS
Code355
FacultyEngineering
SchoolMechanical Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorKyriakos Yakinthos
CommonYes
StatusActive
Course ID20000359

Programme of Study: UPS of School of Mechanical Engineering

Registered students: 73
OrientationAttendance TypeSemesterYearECTS
EnergyCompulsory Course belonging to the selected specialization (Compulsory Specialization Course)1055

Class Information
Academic Year2018 – 2019
Class PeriodSpring
Faculty Instructors
Weekly Hours4
Class ID
600131085
Type of the Course
  • Background
  • Scientific Area
Course Category
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Erasmus
The course is also offered to exchange programme students.
Language of Instruction
  • Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Maths I, II, III Numerical Analysis and Programming Fluid Mechanics Advanced Fluid Mechanics Aerodynamics
Learning Outcomes
The students will be able to: 1. Know how to calculate the flow field development on/in bodies with the use of numerical techniques for the discretization of governing equations 2. Know how to use CFD packages for the
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Make decisions
  • Work autonomously
  • Work in teams
  • Work in an international context
  • Design and manage projects
Course Content (Syllabus)
1. Introduction. Error analysis. Essential algorithms for the solution of system of equations. Numerical integration. 2. Linear and non-linear differential equations. Classification of differential equations governing mass transport and heat transfer phenomena. Typical equations governing convection and diffusion problems. The "source term" concept. The importance of boundary conditions and initial conditions. 3. Discretization techniques of differential equations. Taylor expansion. Discretization of first and second order. Error analysis of discretized equations. 4. Finite differences technique. Solution of parabolic, elliptic and hyperbolic flow problems with the use of finite differences technique. Discretization techniques for compressible flow problems. 5. Control volume technique. Numerical integration on a control volume. Control volume techniques adapted for specific problems. The numerical scheme and the interpolation scheme on the control volume technique. The hybrid and the central scheme. Higher order numerical schemes. The SIMPLE and SIMPLEC pressure correction technique. 6. Elements from the grid generation and grid aspects. Classification of grids and grid quality. Transformation from the cartesian to the generalized curvilinear space. Transformation of the fluid flow and heat transfer cartesian equations to the generalized curvilinear forms. The Jacobi determinant. 7. Elements from vector programming. Management of vector units on the computer processor. Programming on a parallel environment for high performance computing. The MPI parallel programming protocol.
Keywords
CFD, linear and non-linear differential equations, convection, diffusion
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Description
Lectures: PowerPoint and video presentations Computer lab: Projects assigned to the students, focused on programming and CFD Communication: Announcements, various information on the eclass platform Personal communication by email
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures802.7
Project401.3
Written assigments270.9
Exams30.1
Total1505
Student Assessment
Description
Projects (70% of the final grade) Exams (30% of the final grade)
Student Assessment methods
  • Written Exam with Extended Answer Questions (Formative, Summative)
  • Written Assignment (Formative, Summative)
  • Oral Exams (Formative, Summative)
  • Written Exam with Problem Solving (Summative)
  • Labortatory Assignment (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Υπολογιστική Ρευστομηχανική, Γ. Μπεργελές, εκδ. Συμεών
Additional bibliography for study
Σημειώσεις Υπολογιστικής Ρευστομηχανικής Κ. Υάκινθος
Last Update
07-11-2016