2025 (Current Year) Faculty Courses School of Engineering Department of Mechanical Engineering Graduate major in Mechanical Engineering
Computational Fluid Dynamics
- Academic unit or major
- Graduate major in Mechanical Engineering
- Instructor(s)
- Ryo Onishi / Satoshi Ii / Feng Xiao
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Thu
- Class
- -
- Course Code
- MEC.F431
- Number of credits
- 100
- Course offered
- 2025
- Offered quarter
- 1Q
- Syllabus updated
- Apr 2, 2025
- Language
- English
Syllabus
Course overview and goals
Computational fluid dynamics is an essential and advanced tool to solve fluid mechanic problems in scientific and engineering researches. In this course, you will learn the numerical methods and stills to solve the governing equations of fluid mechanics, based on the basic knowledge of fluid mechanics and numerical analysis you have acquired in the undergraduate studies.
Course description and aims
The lectures will cover the fundamental numerical approaches to solve compressible and incompressible flows, as well as well other advanced topics. Students are expected to learn not only the knowledge about the numerical methods but also skills to develop computer codes through practice.
Keywords
Incompressible flow, compressible flow, numerical analysis, discretization scheme, turbulence model, parallel computing, computer simulation, programming, biophysical flows
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Students will learn the governing equations of fluid mechanics, and then discretization methods, discrete equations, typical solution methods for compressible and incompressible flows. They also learn new developments in the field of computational fluid dynamics, such as biophysical flows, turbulence modeling, high-performance computing and data-driven approach.
Exercises will be made in class as needed. The class will be held in person, but may be held via zoom (lectures ＃5&6). Collaboration tools will be used in those zoom classes.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Introduction, governing equations of fluid dynamics, fundamentals of discretization methods | Basic equations for fluid dynamics, discretization methods (finite difference, finite volume methods, time-integration method) |
| Class 2 | Properties of discrete equations, numerical methods for hyperbolic equation (scalar) | Properties of discrete equations (consistency, stability, convergency), conservative scheme for scalar advection equation (numerical conservation, numerical flux, total variation diminishing) |
| Class 3 | Numerical methods for hyperbolic equations (system) and application to biophysical flows | Hyperbolic system (Euler equations, flux splitting, approximate Riemann solver), One-dimensional model for blood flow |
| Class 4 | MAC and SMAC methods for incompressible flows | Pressure-projection based numerical methods for incompressible flows |
| Class 5 | Turbulence modeling and environmental fluid simulation (zoom) | Turbulence models(DNS/LES/RANS), numerical models and simulations for environmental flows |
| Class 6 | Parallel computing of environmental and engineering flows (zoom) | Parallel computing, high performance computing, large scale simulations of environmental and engineering flows |
| Class 7 | Introduction of AI for CFD | Data-driven fluid dynamics, AI, Machine learning, physics-informed neural network |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
not specified
Reference books, course materials, etc.
1. Anderson, J.D., Computational Fluid Dynamics - The Basics with Applications; McGraw-Hill, Inc. 1995
2. Hirsch C., Volume 1&2, Numerical Computational of Internal and External Flows; John Wiley & Sons, 2001
3. Ferziger, J.H. and Peric, M., Computational Methods for Fluid Dynamics; Springer, 1999
4. 藤井孝蔵、立川智章：「Pythonで学ぶ流体力学の数値計算法」、オーム社、2020年（in Japanese）
5. 肖鋒，長崎孝夫：「数値流体解析の基礎 - Visual C++とgnuplotによる圧縮性・非圧縮性流体解析」，コロナ社，2020年(in Japanese)
Evaluation methods and criteria
The evaluation will be based on reports, exercises and quizzes.
Related courses
- MEC.F201 ： Fundamentals of Fluid Mechanics
- MEC.F211 ： Practical Fluid Mechanics
- MEC.B222 ： Fundamentals of computational mechanics
- MEC.F331 ： Advanced Fluid Mechanics
Prerequisites
It is desirable to have the knowledge on fundamentals of thermo-fluid dynamics and numerical analysis
Other
Exercises using laptops (Google colab) may be conducted. Advance notice will be given.