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MECENG 106 Notes: Fluid Dynamics
Fall 2024
By Aathreya Kadambi
Expanding on Lectures by Professor Phil Marcus
This fall Iβm taking a fluid dynamics class by Professor Phil Marcus at Berkeley! Coincidentally, I actually was really interested in his research on Jupyterβs red spot and these related problems in freshman year, although I ended up going down a different road for a while. Excited to learn fluid dynamics.
Chapter 1: Hydrostatics
Story 1: Dimensions
Relevant lectures: Lecture 1
The lecture notes have anything you need to succeed. You are also strongly recommended to work in teams on the homework. Homework are combination of graded and self-graded. Feel free to go to any discussion section.
When you write down equations, you should keep track of the dimensions of the quanities in the equation. If you are taking the or of something, it better be dimensionless.
Dimensional analysis is very important. In fact, people were able to find the energy in the atomic bomb (which was a well-kept secret) based on the speed of the shock wave.
Dimensions are things like length, time, mass, etc.. It is important to distinguish these things from units, which we use to measure these dimensions.
Remark. Iβll leave out the examples and discussion of dimensional analysis and units and things like that, since one can find good treatment of that subject in practically any thick science textbook. One thing I will mention is that apparently thereβs actually a unit of temperature called βRankineβ. Iβve never seen that before.
Story 2: Properties of Fluids
Relevant lectures: Lectures 1, 2
Our properties are going to be functions of space and time: and . Here are some important properties:
The following properties live in .
- Temperature: .
- Mass Density: . It has dimensions in MLT units.
- Pressure: . It has dimensions in MLT units.
- Velocity: . It has dimensions .
Remark. Notice how we are treating these quantities in a continuum. I was thinking about it, and I guess this means in terms of temperature for example, we can treat each particle or molecule as a Dirac function, and the temperature in a region is the expected value of the temperature in that region when one integrates. That feels somewhat nice because it gives this intutiion of temperature over a region being looking at space in a lower resolution.
In fluid dynamics, we will write the ideal gas law as:
In physics we generally use the form . So what is the relationship between these two forms? In physics one has to look up the molecular weights and stuff, and in MechE, we have to look up individual gas constants for each gas.
Ideal gas equation of state:
Story 3: Viscosity
Viscosity is about roughly how well things flow. Physically, it is a diffusion coefficient of momentum.
In fluid dynamics, we have so called boundary conditions. For a Newtonian fluid, the boundary conditions are that the fluid at any surface in the direction that is parallel to the surface must move at the same velocity as the surface. This is called the no-slip boundary condition. The zeroness of momentum diffuses into the middle so that for honey, where that diffusion would happen very quickly for example, the momentum in the middle will also be close to zero. For water on the other hand, the momentum in the middle might be high even if the momentum at the surface is zero.
So far what we have discussed is called the kinematic viscosity. There is another viscosity called dynamic viscosity, which satisfies From now on, will refer to kinematic viscosity. There is a dimensionless quantity called the Reynoldβs number, defined: where we are using brackets here to indicate βcharacteristic valuesβ. When , we call it laminar, when it is we call it turbulent, and in between this, we call it transitional.
For 3D flows, it is extremely difficult to make calculations in the transitional region without approximations. Thatβs why you need to take MECENG 106, because that is one of the hardest places to calculate flows.
Example. Consider water out of a tap. The characteristic volume and length are and , and the viscosity is . As such,
Remark. You can compute the transition point for smoke flowing up, when it transitions through different types of flow. Why do we define the Reynoldβs number like that?
Story 4: Pressure
Relevant Lectures: Lecture 2
Consider an area. This vector has normal inward vector. We might write: so that the integral is A question is, if we change our orientation, then do we get a different force or something? It turns out that the magnitude is independent.
We will show this in the static case, namely where
Now letβs imagine a little piece of swiss cheese (proceeds to draw an inclined plane with angle theta).
Chapter 2: Go with the Flow
Story 1: Towards Continuity and Conservation
In the following, weβre going to pretend we know some information: the density (a distribution on representing mass), (an idea of flux), and (another distribution on representing creation/destruction of mass).
Consider any fixed region (volume) , and imagine filled with a fluid. The density of this fluid is given by . Then we can obtain a fwe quantities directly:
- Total Mass of Fluid in Container: (summing up the density function)
- Time Rate of Change of Total Mass of Fluid in Container:
- Flux Through The Boundary/Surface (Rate of transport of mass from outside to inside):
- is defined so that is the time rate at which mass passes through the surface element
Then we find that the change in the total mass of the region can only change when mass is created or destroyed within the region, or when it flows in through the boundary. This gives us: and since this holds for all regions , we find that
Story 2: Mass and Momentum Go with the Flow
We theorize that mass βgoes with the flowβ in the sense that, as Professor Marcus puts it, βtransport of mass in a fluid is due to the fluid velocityβ. Mathematically,
In general, if we make the assumption that a quantity βgoes with the flowβ and know the density of the quantitiy, we can write an expression for and get an appropriate continuity or conservation law. Another important example is momentum. In the case of momentum, the density is something like βmass times velocityβ. Since velocity is a vector quantity though, and we want a scalar density field, we instead choose a particular direction called the βaccounting directionβ, which we will use to study momentum flow in that direction. If we take a certain direction , and write , then we can take the scalar density field , and end up with the expression:
Now if we simplify this equation and also use the conservation of mass equation from before, we can actually simplify this into the form:
We actually have a special name for the operator: it is called the Lagrangian time derivative, or the material or advective or convective derivative. This is kind of like the total time derivative from the perspective of someone who is moving, taking their motion into account via chain rule. A Lagrangian particle is a particle which βgoes with the flowβ, so the Lagrangian derivative is the rate of change in time as observed by a Lagrangian particle.
To summarize, the Euler equation and continuity equation can be written:
Story 3: Vorticity and Bernoulliβs Theorem
We call the curl of the velocity vector field vorticity: . This satisfies the following identity:
Now there are a few important definitions:
- Streamline: a continuous curve tangent to everywhere
- Cannot be visualized in an experiment
- Pathline: path of a particle that βgoes with the flowβ
- When velocity is independent of time, pathlines and streamlines are the same
- Streakline: path created by a bunch of particles released at every time up to a certain point
Finally, we can discover Bernoulliβs equation by dotting our expression with and noting that , and considering the case of a steady flow so that :
Remark. In what we have done so far, we have not accounted for viscous effects. As such, we should be wary of applying Bernoulliβs equation or Eulerβs equation to situations where viscous effects matter.
Story 4: Energy and the Breakdown of Bernoulli
Remark. This story is motivated by my trauma from midterm 2. I knowingly used Bernoulli in a place it probably wasnβt applicable to avoid the possible pains and time stress of a control volume approach, but to my horror and demise, this wasnβt a valid approximation.
At the time, my deluded justification was that for a propeller, there should be points in time where air above and below the propeller are connected spatially (there isnβt a propeller fan in the way) although to be fair they are always connected spatially. I used this idea of path connectedness to justify having a streamline and applying Bernoulli. After all, streamlines are curves that are at all points tangent to the velocity field, so there should be some time where we can find a streamline there, when the propeller isnβt in the way. Yeahβ¦ I was a fool and got cooked on that midterm as a result.
So in this story, we will learn from my mistakes and learn where the ideas of Bernoulli functions break down.
