Welcome to Fluid Dynamics with Python in ICT Summer School 2022. On this course, we will learn the fundamental of fluid dynamics as well as Python programming. In addition, we will also learn Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow.
This course introduces the fundamentals of fluid dynamics and its practices with Python. The participating students learn the government equations for fluid flow and how to compute them by using jupyterLab. Specifically, the following study aims and competencies are highlighted in this course;
- to increase knowledge about the fundamentals of fluid dynamics
- to increase knowledge about the governing equations for fluid flow
- to calculate some simplified 2-D fluid flow fields using computational fluid dynamics and jupyterLab.
- to calculate the wind flows in the simplified 2-D city areas using actual map data and meteorological data.
- to acquire Python programming skills for fluid flow calculations
Participating students have basic mathematics, such as linear algebra, vector and matrix operations, linear combination, basic multivariate calculus, partial differential equation, etc. The students preferably have basic programming skills in Python.
- About this lecture
- Goal of this lecture
- How to implement fluid dynamics program on jupyterLab/colab
- Mathmatical expressions on jupyterLab
- Variables / Arrays / Libraries / Assigning array variables
- How to visualize results of fluid flow calculations
- What is fluid flow (fluid dynamics)?
- Pressure
- Experiment; Try to take out an item in the bottle without water leakage
- Torricellian vaccum
- Mercury column/Water column
- Pascal's principle
- Types of fluids
- Experiment; Stirring two kinds of fluid
- Ideal fluid
- Real fluid
- Newtonian fluid
- non-Newtonian fluid
- Types of fluid flow
- Experiment; Try to control a falling ball
- Laminar flow/Trubulent flow
- Reynolds number
- Basis of fluid flow (Bernolli's theorem)
- Experiment; Snowman
- Basis of Bernoulli's theorem
- Spouting flow from a hole at the bottom of a barrel
- Intravenous drip
- Experiment; Spouting flow
- How to measure fluid flow velocity: Pitot tube
- Simple particle image velocimetory
- Governing equations of fluid flow
- 1-D heat transfer (How to solve partial differential equation)
- Explicit scheme / Implicit scheme / Semi-implicit scheme
- Solving discretized diffusion equation by using spreadsheet software
- One-dimensional diffusion equation
- Linear and non-linear convection equations
- Laplace equation / Poisson equation
- Cavity flow
- Channel flow
- How to obtain geographic (map) data
- How to obtain real meteorological data
- Wind flows in simplified 2-D city areas
- Independent research by using fluid dynamics simulation
Daily exercises on the course are worth 50%, and reports about fluid dynamics simulation (python programming) are worth 50%.
Daily exercises on the course are worth 50%, and reports about fluid dynamics simulation (python programming) are worth 50%.
A computer with the following software is necessary: Office software (i.e., MS Office, Apple Keynote/Numbers/Pages, Libre Office) and a web browser that can execute "google colaboratory" on it. Slides, exercise handouts, and jupyterLab examples will be provided in sessions.
The student advisor will recommend optional programme components for each student based on their individual study plan.
These lecture materials refers to "CFD Python: the 12 steps to Navier-Stokes equation.", Journal of Open Source Education, 1(9), 21 (2018) https://doi.org/10.21105/jose.00021 by Barba, Lorena A., and Forsyth, Gilbert F.