Drag constant, flow regimes, CFD

In summary, OpenFoam may be able to approximate drag constants for bullets over the range of k_M=0.5(0.3)-5.0, but it is a bit complicated and may not be accurate. It would be possible to construct an experiment to measure drag constants for various shapes and velocities, but lacks accuracy due to the lack of knowledge of fluid dynamics.
  • #1
tuoni
61
0
In my effort of approximating drag constants for bullets, I have come across the McDrag program, by Robert L. McCoy. The disadvantage is that it approximates drag constants based on a few predefined shapes and a drag model (e.g. G1, G7), limiting it to only the simplest of bullets.

Fully fledged CFD is beyond my level of knowledge and skill, but some level of CFD would probably be very useful, and certainly better than McDrag alone. I have been reading NASA's Beginner's Guide to Aeronautics (http://www.grc.nasa.gov/WWW/K-12/airplane/guided.htm) and other sources to learn of the various sources of drag in different flow regimes.

Only the nonthermodynamic drag constant is of interest and below Mach constant 0.5 (or maybe even as low as 0.3) and above 5.0, the nonthermodynamic drag constant can be assumed to be constant.

From what I have learned, the important sources of drag are:
  • friction drag (skin friction)
  • pressure drag (form drag)
    • incompressible flow
    • compressible flow
  • wave drag

Friction drag is determined by the boundary layer, viscous properties of the medium, and the wetted surface. Pressure drag is due to the pressure gradient over the body, arising from the fluid flow around the body. In compressible flow the change in mass density must be taken into account. Wave drag is due to the generation of shock waves over the body.

For radially symmetrical projectiles (bullets), and with a very narrow field of required CFD, would it still be impractical/difficult to create a lean and efficient program to approximate drag constants of bullets over the range k_M=0.5(0.3)-5.0?

Or would I ultimately resort to third-party, naughtily complex, messy, and bloated libraries/toolsets to accomplish my goal?
 
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  • #2
If I recall correctly, CFD is not very good at calculating drag, usually being around 30% off experimental values. It could give you a starting point though.

I've been working with an opensource CFD program called OpenFoam for a couple of weeks, but it's a bit complicated and it's taking a while to figure it out (it's not really GUI based). Another is Code-Saturn which could als give you some results. Problem with CFD is that is very much trash in is trash out. If you don't know what you're doing, the results can look nice, but mean nothing.

Any chance of doing your own experiments?
 
  • #3
I would love to construct a small "wind tunnel" of my own, and conduct expirments to empirically determine the drag constant of various shapes at various velocities. If I understood it correctly, using the Reynolds constant:

Mach 0.3-5.0 (approx. 102-1700 m/s) in standard atmosphere, T=288.15 K, ρ=1.225 kg/m^3, μ=1.812e-5 Pa·s;

using an enlarged scale model of a bullet (200 mm long);

is equal to 0.765-12.749 m/s in water, T=288.15 K, ρ=999 kg/m^3, μ=1.108e-3 Pa·s.

There are also plenty of diagrams depicting the drag constant of a sphere over Reynolds and Mach constant which would be used to calibrate the experiment. This means it could *MAYBE* be possible to construct such an experiment.

However, I don't know quite enough about fluid dynamics to truly know if this would really work, if the similarity parameter is correct...? What about wave drag? The velocity of sound differs in air and water...

The next problem would be how to compile the data...once I have drag constants for various shapes and have created empirical algorithms for it...how do I combine a cylinder with a tangent nose? I doubt it's possible to just add them together.
 

1. What is drag constant and how does it affect an object's movement?

Drag constant, also known as drag coefficient, is a dimensionless quantity that represents the air resistance experienced by an object moving through a fluid. It is dependent on the shape, size, and surface properties of the object, as well as the speed and density of the fluid. A higher drag constant means that the object experiences more air resistance, resulting in a slower movement.

2. What are the different flow regimes and how do they impact fluid dynamics?

Flow regimes refer to the different patterns of fluid flow that can occur, depending on the conditions and characteristics of the fluid. The most common flow regimes are laminar, turbulent, and transitional. Laminar flow is smooth and orderly, while turbulent flow is chaotic and unpredictable. Transitional flow occurs when there is a mix of both laminar and turbulent flow. These flow regimes have a significant impact on the behavior of fluids, such as their resistance to flow and mixing capabilities.

3. How is Computational Fluid Dynamics (CFD) used in scientific research?

CFD is a simulation technique that uses numerical methods to solve and analyze fluid flow and heat transfer problems. It is widely used in scientific research to study complex fluid dynamics phenomena, such as aerodynamics, hydrodynamics, and heat transfer. CFD allows scientists to conduct virtual experiments and analyze the effects of different parameters on fluid behavior, without the need for physical prototypes or testing.

4. What are the limitations of using CFD in fluid dynamics research?

While CFD has revolutionized the field of fluid dynamics, it does have some limitations. One major limitation is the accuracy of the results, as they are highly dependent on the assumptions and simplifications made in the simulation. Additionally, CFD requires powerful computing resources and can be time-consuming, making it impractical for certain applications. It is important for scientists to carefully validate and verify their CFD simulations to ensure accurate results.

5. Can CFD be used to model any type of fluid flow?

CFD can be used to model a wide range of fluid flow phenomena, including incompressible and compressible flows, single and multiphase flows, and laminar and turbulent flows. However, there are certain limitations and challenges in modeling complex flows, such as those involving free surface or highly viscous fluids. In these cases, other numerical methods or physical experiments may be necessary to accurately capture the behavior of the fluid.

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