In this course, turbulence, turbulent transports and turbulent combustion are lectured from fundamentals to applications. Based on the knowledge of turbulence, cutting-edge passive and active control methods for turbulent flows and combustion are studied.
Turbulence, on one hand, enhances heat and mass transfers and, on the other, increases undesirable friction drag and sound noise and so on. Hence, proper controls of turbulence are key to effective utilization of energy in a wide range of fluid machinery, ships and airplanes etc. Students will study fundamentals of turbulence, turbulent heat and mass transfers, turbulent combustion. Furthermore students will learn about passive and active control methods of turbulent flows and experience the evolvement of smart control technologies for turbulence to controls of heat and mass transfer and also combustion.
By the end of this course, students will be able to:
1) Explain the fundamental theory of turbulence in ideal turbulent fields
2) Choose turbulent models in computational fluid dynamics simulation
3) Apply control methods for turbulence to practical engineering problems.
Turbulence, fine scale structure of turbulence, RANS, LES, boundary layer separation, drag, pressure, friction, pipe flows, airplanes, combustion, energy, environment
✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
The course is taught in lecture style. Exercise problems will be assigned. Required learning should be completed outside of the classroom for preparation and review purposes.
Course schedule | Required learning | |
---|---|---|
Class 1 | Technologies for effective energy utilization and turbulence controls | Understand impact of technologies for effective energy utilization to environmental problems and requirement of turbulent controls |
Class 2 | Turbulence statistics | Understand turbulence statistics in ideal turbulence fields, self-similarity, Reynolds stress, turbulent kinetic energy, energy dissipation rate |
Class 3 | Intermittency and theory of turbulence | Understand intermittency and intermittent factor, two-point correlation, scales of turbulence, turbulence structures |
Class 4 | Turbulence models | Understand RANS(Reynolds averaged Navier-Stokes equation), large eddy simulation,energy transfer, turbulence models |
Class 5 | Passive control of turbulence | Understand classification of control approaches, control of turbulent boundary layer, surface modifications, control based on turbulence characteristic scales |
Class 6 | Active control of turbulence | Understand sensors and actuators for active control, identification and control of large scale vortical structures, low-frequency control |
Class 7 | Control of turbulent heat and mass transfers, Controls of combustion | Understand turbulence structures near wall and controls for them, trade-off between friction drag reduction and enhancement of heat and mass transfers. Understand turbulent flame structures, combustion instabilities and benefits/ challenges in combustion controls. |
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.
Materials will be provided if they are required.
U. Frish, "Turbulence", Cambridge University Press, (1995),
S. Pope, "Turbulent Flows", Cambridge University Press, (2000)
Students' knowledge of basic physics of turbulence, controls of turbulent flows, heat and mass transfers and combustion will be assessed.
Final report 70%, exercise problems 30%.
Students are expected to have successfully completed Thermodynamics (Mechanical Engineering) (MEC.E201.R), Heat Transfer (MEC.E311.A), Energy Conversion (MEC.E331.E), Fundamentals of Fluid Mechanics (MEC.F201.R), Practical Fluid Mechanics (MEC.F211.A), Advanced Fluid Mechanics (MEC.F331.E), Partial Differential Equations (MEC.B213.A), Vector Analysis (MEC.B214.A) , Probability Theory and Statistics (MEC.B231.E), Fundamentals of Signal Processing (MEC.B331.E), Modeling and Control Theory (MEC.I312.A) or have equivalent knowledge.