The turbulence model can make a big difference in your simulation. There are many turbulence models around. It becomes a tough job to select one out of them.
There is no perfect turbulence model. It all depends on several parameters like Reynold's number, whether the flow is separated, pressure gradients, boundary layer thikness and so on. In this answer, brief information about a few popular models is given along with pros and cons and potential applications. However, interested users can see this excellent NASA website and references therein to know more about turbulence modeling.
A) ONE EQUATION MODEL:
1. Spalart-Allmaras
This model solves for one additional variable for Spalart-Allmaras viscosity. According to a NASA document, there are many modifications in this model targeted for specific purposes.
Pros: Less memory intensive, Very robust, fast convergence
Cons: Not suitable for separated flow, free shear layers, decaying turbulence, complex internal flows
Uses: Computations in boundary layers, entire flowfield if mild or no separation, aerospace and automobile applications, for initial computations before going to higher model, compressible flow computations
Applicability to your case: a good candidate for reducing simulation time. You can predict the drag fairly well with this model. However, if you are interested in knowing the flow separation region, this model will not give highly accurate results.
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B) TWO-EQUATIONS MODELS:
- $k$-$\epsilon$ turbulence model:
A general purpose model. This model solves for kinetic energy ($k$) and turbulent dissipation ($\epsilon$). The equations for this models can be found at this cfd-online page. This model requires wall functions to be computed for the implementation. Suitable only for fully turbulent flows.
Pros: simple to implement, fast convergence, predicts the flows in many practical cases, good for external aerodynamics
Cons: Not suitable for axi-symmetric jets, vortex flows and strong separation. Very low sensitivity for the adverse pressure gradients, difficult to start (need initialization with Spalart-Allmaras), not suitable for near wall applications
Uses: Suitable for initial iterations, good for external flows around complex geometries, good for shear layers and free non wall bounded flows
Applicability in your case: Although this model is good for external bluff body computation, it is suitable only for turbulent flows. Since the velocities are low, flow is going to experience transition from laminar to turbulent (max $Re = 1.98*10^6$ using this calculator). You might benefit better with a variant like realizable $k$-$\epsilon$ model.
2. $k$-$\omega$ turbulence model:
Solves for $k$ and turbulence frequency $\omega$. Gives better results for near wall flows. Predicts transition (although early sometimes). Quite sensitive to the initial guess and hence initial few iterations are performed with $k$-$\epsilon$ model. This article gives near wall treatment for this model.
Pros: Excellent for boundary layers, works in adverse pressure gradient, works for strong separated flows, jets and free shear layers
Cons: Time required for convergence is more, memory intensive, Requires mesh resolution near the wall, predicts early and excessive separation
Uses: Internal flows, Pipe flows, Jet flows, vortices
Applicability in your case: Not completely suitable for your case since the boundary layer values depend strongly on free stream $\omega$. This requires a very fine grid to resolve and hence long computation time. Also it does not account for the transport of turbulent shear stress.
3. $k$-$\omega$ SST
Best of both worlds! This model has a blending function which uses $k$-$\omega$ near the wall and $k$-$\epsilon$ in the free stream. It does not use wall functions.
All the variants of this model can be found at this NASA page.
Pros: Accounts for turbulent shear stress while giving all the benefits of $k$-$\omega$ model, Highly accurate prediction of separation and transition, Very good free stream as well as boundary layer results
Cons: Not suitable for free shear and vortex flows as much as standard $k$-$\omega$, Not suitable for jet flows, Requires fine mesh resolution near walls
Uses: External aerodynamics, separated flows, Boundary layers and adverse pressure gradients
Applicability in your case: Highly applicable. If you want better results, use a variant of sst model which uses $k$-$\epsilon$ RNG or realizable model away from the walls
So which model is most appropriate?
My guess would be $k$-$\omega$ SST model.
Since it will give better transition, separation and works even under adverse pressure gradients, you will get better skin friction drag. At the same time, it works well away from the walls, which will give you good pressure drag and hence parasitic drag. You will get better flow visualization. You can very well use the Spalart-Allmaras model, but if you see this study, you will notice how much difference the SST model makes.
And don't take my word for it. A report on 'Aerodynamic Analysis and Drag Coefficient Evaluation of Time-Trial Bicycle Riders ' uses the SST model. This paper compares all the turbulence models results for cyclist aerodynamics and arrives at a conclusion that the SST model gives the best overall results. I am citing these results because Reynold's number wise and dimensions wise, a bicycle goes most closer to your case, for which tons of studies are available.
However, if time is limited in your case, go for Spalart-Allmaras model. You can also go for RNG $k$-$\epsilon$ or realizable $k$-$\epsilon$ in that case. However, this study of a bicycle wheel shows, S-A model gives better results than $k$-$\epsilon$ (this is very much geometry specific, different model might work for your geometry). If you have all the time in the world, conduct studies using SST and epsilon model and publish your comparison so others might also benefit from it.
If you have better computational resources, go for LES. But I feel it is not called for in this case and it might not be appropriate. I do not have experience with LES, so can't comment.
Some interesting resources:
The FOAM house: If you want to learn OpenFOAM step by step
Recent advances on the numerical modeling of turbulent flows
Lectures in Turbulence for the $21^{st}$ century - highly recommended reading if you wish to understand turbulence
Turbulence Models and Their Application to Complex Flows
All the best!
Cheers!