Drag prediction benchmarks
Hello,
Does anyone know of any basic drag prediction benchmarks? I have been tasked with demonstrating the effectiveness of the commercial code we use for predicting drag over sections of aircraft, in particular helicopter engine intakes. I was hoping to do a benchmark problem or two to get some experience and check I am getting good results before tackling the real thing. All comments will be gratefully received. Althea 
Re: Drag prediction benchmarks
(1). Ask the vendor of the software you are using to provide some examples where the skin friction is computed. (2). Some codes can give good solution of pressure distributions but not accurate wall skin friction or heat transfer. (3). It is a hard problem, and if the vendor can handle it, they will definitely say so.

Re: Drag prediction benchmarks
Hi Althea: A good reference that is used by a lot in the aeronautics industry is a report titled National Advisory Committee for Aeronautics. I think it was published by NASA in 1945 under report no 824. You can buy a copy from them directly.

Re: Drag prediction benchmarks
Let me give you some thumb rule about drag in respect to boundary layer thickness. The thicker is the boundary layer thickness on the surface of the flow of interest, the higher is the drag and vice versa. Again, the higher is the boundary layer thinkness of the flow of interest, the lower is the amount of heat transfer from the surface to another medium (explained by me in IC engine earliar).
Now let us consider the aspects of dimples in a gulf ball. Due to dimples in a ball, boundary layer thickness tends to go inside the dimples reducing boundary layer thickness as well as augmenting turbulence on the surface of the ball. Thus the dimples reduce drag in a ball. So the software you are using must be able to handle and calculate the boundary layer thickness of the flow of interest for drag prediction. Let me come back again in predicting the drag on the surface of a car (underhood as well as the painted body). If the surface area is increased then drag will also increase. This is obvious. But think of how smart an engineer has to be to increase surface area (to improve underhood heat transfer as well as make the car more spacious to sit comfortably inside) and at the same time reduce drag to improve fuel economy. Don't you think it is design optimization? 
Re: Drag prediction benchmarks
Sorry, boundary layer (not boundary layer thickness) tends to go inside the dimples reducing its thickness.

Re: Drag prediction benchmarks
You need to be more specific about what kind of engine you are talking about before we can give you some concepts to start your evaluations.

Re: Drag prediction benchmarks
There is one "dragbenchmark" which probably could help you:
Schaefer M. and Turek, S.: Benchmark computations of laminar flow around cylinder, in Hirschel (Edt.): Flow Simulation with HighPerformance Computers II, Notes on Numerical Fluid Mechanics, Vol 52, Vieweg 1996, p. 547566 The basic idea is to compute the drag and lift coefficient for a cylinder within a 2D or 3D channel with different mass flow. There is a stationary test at Re=20 and there are two instationary tests at Re=100 (one "quasistationary" with constant mass flow and annother with timevarying mass flow). The problem has been computed by many different codes  so the results can be trusted :). There is also a conference paper about a combined experimental (LDV, PIV) and numerical investigation for the same problem, giving local timedependent velocities at some positions within the vortex street behind the cylinder: Stenzel, O. und C. Lund. Laser Doppler Velocimetry (LDV) and Particle Image Velocimetry (PIV) Measurements of the Time Dependent Flow behind a Circular Cylinder and Comparison with Results Obtained by Numerical Simulation. In: Proceedings of the 9th International Symposium on Applications of Laser Techniques to Fluid Mechanics. Lisbon, Portugal. 1998: 2.4.12.4.8 Hope this of interest for you Chris 
Re: Drag prediction benchmarks
That is completely wrong. Dimples reduce the drag by triggering transition from a laminar to a turbulent boundary layer. A turbulent boundary layer stays attached to the surface longer and thus gives a smaller wake thereby reducing the pressure drag. The friction drag is higher in a turbulent boundary layer. However, this effect is secondary.

Re: Drag prediction benchmarks
A turbulent boundary layer stays attached to the surface longer if the boundary layer thickness is thinner therefore augmenting turbulence. How does it sound? Turbulence is a complex phenomenon. I am also now trying to understand about turbulence but lot of things I myself don't understand. So I would not be surprised if I am mistaken.

Re: Drag prediction benchmarks
i guess you could also try comparing your code to results obtained from exact solutions such as Blasius boundary layer solution etc. a book on viscous flow/boundary layers wouls probably have these results.

Re: Drag prediction benchmarks
Of course you could use any exact solution to check to results of your code.
There are however not many analytical solutions to viscous timedependent flow within a somewhat complex geometry (compared with a rectangular box a cylinder in a channel is rather "complex"). Furthermore, many analytical solutions present a somewhat "simple" flow field. Again, compared with a taylorvortex (as an example), a karman vortex street is rather "complex". The benchmarktest I mentioned is very valueable because the flow field is both timedependent and complex. With the mass flow itself changing as a function of time you have a really complex instationary flow. 
Re: Drag prediction benchmarks
sorry i had meant to reply to althea's post not yours. although i think these analytyical solution would be her best first step

Re: Drag prediction benchmarks
Drag can be reduced significantly (about 30%  50%) by blowing out or sucking in (by drilling small holes on the solid surface) turbulent flows. This technology can be applied to reduce drag on helicopters, low speed aircrafts, automobiles etc. The controlling system can be designed just like a computer chess game. If a person makes a move, the computer choosing better possibilities makes a move to balance the game or stay in better position. As the level of the game goes up from 1 to 9, the computer takes longer time to make decisions because of increasing the number of better possibilities. In the same way, as the speed of the aircraft, helicopter or automobile changes, drag also changes. In order to minimize drag, turbulent flows over the surface needs to be controlled to obtain optimum design.

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