Toolbox is available at CFD Toolbox. 
We implement the benchmark proposed by Turek and Hron, on the behavior of drag and lift forces of a flow around an object composed by a pole and a bar, see Figure [imggeometry1].
The software and the numerical results were initially obtained from Vincent Chabannes.
This benchmark is linked to the Turek Hron CSM and Turek Hron FSI benchmarks. 
We consider a 2D model representative of a laminar incompressible flow around an obstacle. The flow domain, named \(\Omega_f\), is contained into the rectangle \( \lbrack 0,2.5 \rbrack \times \lbrack 0,0.41 \rbrack \). It is characterised, in particular, by its dynamic viscosity \(\mu_f\) and by its density \(\rho_f\). In this case, the fluid material we used is glycerine.
In order to describe the flow, the incompressible NavierStokes model is chosen for this case, define by the conservation of momentum equation and the conservation of mass equation. At them, we add the material constitutive equation, that help us to define \(\boldsymbol{\sigma}_f\)
The goal of this benchmark is to study the behavior of lift forces \(F_L\) and drag forces \(F_D\), with three different fluid dynamics applied on the obstacle, i.e on \(\Gamma_{obst}\), we made rigid by setting specific structure parameters. To simulate these cases, different mean inflow velocities, and thus different Reynolds numbers, will be used.
We set
on \(\Gamma_{in}\), an inflow Dirichlet condition : \( \boldsymbol{u}_f=(v_{in},0) \)
on \(\Gamma_{wall}\) and \(\Gamma_{obst}\), a homogeneous Dirichlet condition : \( \boldsymbol{u}_f=\boldsymbol{0} \)
on \(\Gamma_{out}\), a Neumann condition : \( \boldsymbol{\sigma}_f\boldsymbol{ n }_f=\boldsymbol{0} \)
We use a parabolic velocity profile, in order to describe the flow inlet by \( \Gamma_{in} \), which can be express by
\[ v_{cst} = 1.5 \bar{U} \frac{4}{0.1681} y \left(0.41y\right) \] 
where \(\bar{U}\) is the mean inflow velocity.
However, we want to impose a progressive increase of this velocity profile. That’s why we define
\[ v_{in} = \left\{ \begin{aligned} & v_{cst} \frac{1\cos\left( \frac{\pi}{2} t \right) }{2} \quad & \text{ if } t < 2 \\ & v_{cst} \quad & \text{ otherwise } \end{aligned} \right. \] 
With t the time.
Moreover, in this case, there is no source term, so \(f_f\equiv 0\).
The following table displays the various fixed and variables parameters of this testcase.
Name  Description  Nominal Value  Units  

\(l\) 
elastic structure length 
\(0.35\) 
\(m\) 

\(h\) 
elastic structure height 
\(0.02\) 
\(m\) 

\(r\) 
cylinder radius 
\(0.05\) 
\(m\) 

\(C\) 
cylinder center coordinates 
\((0.2,0.2)\) 
\(m\) 

\(\nu_f\) 
kinematic viscosity 
\(1\times 10^{3}\) 
\(m^2/s\) 

\(\mu_f\) 
dynamic viscosity 
\(1\) 
\(kg/(m \times s)\) 

\(\rho_f\) 
density 
\(1000\) 
\(kg/m^3\) 

\(f_f\) 
source term 
0 
\(kg/(m^3 \times s)\) 

\(\bar{U}\) 
characteristic inflow velocity 

\(m/s\) 
As defined above, the goal of this benchmark is to measure the drag and lift forces, \(F_D\) and \(F_L\), to control the fluid solver behavior. They can be obtain from
\[ (F_D,F_L)=\int_{\Gamma_{obst}}\boldsymbol{\sigma}_f \boldsymbol{ n }_f \] 
where \(\boldsymbol{n}_f\) the outer unit normal vector from \(\partial \Omega_f\).
To realize these tests, we made the choice to used \(P_N\)\(P_{N1}\) TaylorHood finite elements, described by Chabannes, to discretize space. With the time discretization, we use BDF, for Backward Differentation Formulation, schemes at different orders \(q\).
Here are the different solvers ( linear and nonlinear ) used during results acquisition.
type 
gmres 
relative tolerance 
1e13 
max iteration 
1000 
reuse preconditioner 
false 
relative tolerance 
1e8 
steps tolerance 
1e8 
max iteration 
CFD1/CFD2 : 100  CFD3 : 50 
max iteration with reuse 
CFD1/CFD2 : 100  CFD3 : 50 
reuse jacobian 
false 
reuse jacobian rebuild at first Newton step 
true 
relative tolerance 
1e5 
max iteration 
1000 
max iteration with reuse 
CFD1/CFD2 : 100  CFD3 : 1000 
reuse preconditioner 
false 
reuse preconditioner rebuild at first Newton step 
false 
type 
lu 
package 
mumps 
The configuration files are in toolboxes/fluid/TurekHron
. The different cases are implemented in the corresponding .cfg
files e.g. cfd1.cfg
, cfd2.cfg
and cfd3.cfg
.
The command line in feelpptoolboxes docker reads
$ mpirun np 4 /usr/local/bin/feelpp_toolbox_fluid_2d configfile cfd1.cfg
The result files are then stored by default in
feel/applications/models/fluid/TurekHron/"case_name"/"velocity_space""pression_space""Geometric_order"/"processor_used"
For example, for CFD2 case executed on \(12\) processors, with a \(P_2\) velocity approximation space, a \(P_1\) pressure approximation space and a geometric order of \(1\), the path is
feel/toolboxes/fluid/TurekHron/cfd2/P2P1G1/np_12
Here are results from the different cases studied in this benchmark.
\(\mathbf{N_{geo}}\)  \(\mathbf{N_{elt}}\)  \(\mathbf{N_{dof}}\)  Drag  Lift 

Reference Turek and Hron 
14.29 
1.119 

1 
9874 
45533 (\(P_2/P_1\)) 
14.217 
1.116 
1 
38094 
173608 (\(P_2/P_1\)) 
14.253 
1.120 
1 
59586 
270867 (\(P_2/P_1\)) 
14.262 
1.119 
2 
7026 
78758 (\(P_3/P_2\)) 
14.263 
1.121 
2 
59650 
660518 (\(P_3/P_2\)) 
14.278 
1.119 
3 
7026 
146057 (\(P_4/P_3\)) 
14.270 
1.120 
3 
59650 
1228831 (\(P_4/P_3\)) 
14.280 
1.119 
All the files used for this case can be found in this rep [geo file, config file, json file]
\(\mathbf{N_{geo}}\)  \(\mathbf{N_{elt}}\)  \(\mathbf{N_{dof}}\)  Drag  Lift 

Reference Turek and Hron 
136.7 
10.53 

1 
7020 
32510 (\(P_2/P_1\)) 
135.33 
10.364 
1 
38094 
173608 (\(P_2/P_1\)) 
136.39 
10.537 
1 
59586 
270867 (\(P_2/P_1\)) 
136.49 
10.531 
2 
7026 
78758 (\(P_3/P_2\)) 
136.67 
10.548 
2 
59650 
660518 (\(P_3/P_2\)) 
136.66 
10.532 
3 
7026 
146057 (\(P_4/P_3\)) 
136.65 
10.539 
3 
59650 
1228831 (\(P_4/P_3\)) 
136.66 
10.533 
All the files used for this case can be found in this rep [geo file, config file, json file]
As CFD3 is timedependent ( from BDF use ), results will be expressed as
\[ mean ± amplitude [frequency] \] 
where
mean is the average of the min and max values at the last period of oscillations.
\[ mean=\frac{1}{2}(max+min) \] 
amplitude is the difference of the max and the min at the last oscillation.
\[ amplitude=\frac{1}{2}(maxmin) \] 
frequency can be obtain by Fourier analysis on periodic data and retrieve the lowest frequency or by the following formula, if we know the period time T.
\[ frequency=\frac{1}{T} \] 
\(\mathbf{\Delta t}\)  \(\mathbf{N_{geo}}\)  \(\mathbf{N_{elt}}\)  \(\mathbf{N_{dof}}\)  \(\mathbf{N_{bdf}}\)  Drag  Lift 

0.005 
Reference Turek and Hron 
439.45 ± 5.6183[4.3956] 
−11.893 ± 437.81[4.3956] 
0.01 
1 
8042 
37514 (\(P_2/P_1\)) 
2 
437.47 ± 5.3750[4.3457] 
9.786 ± 437.54[4.3457] 
2 
2334 
26706 (\(P_3/P_2\)) 
2 
439.27 ± 5.1620[4.3457] 
8.887 ± 429.06[4.3457] 

2 
7970 
89790 (\(P_2/P_2\)) 
2 
439.56 ± 5.2335[4.3457] 
11.719 ± 425.81[4.3457] 
0.005 
1 
3509 
39843\((P_3/P_2)\) 
2 
438.24 ± 5.5375[4.3945] 
11.024 ± 433.90[4.3945] 
1 
8042 
90582 (\(P_3/P_2\)) 
2 
439.25 ± 5.6130[4.3945] 
10.988 ± 437.70[4.3945] 

2 
2334 
26706 (\(P_3/P_2\)) 
2 
439.49 ± 5.5985[4.3945] 
10.534 ± 441.02[4.3945] 

2 
7970 
89790 (\(P_3/P_2\)) 
2 
439.71 ± 5.6410[4.3945] 
11.375 ± 438.37[4.3945] 

3 
3499 
73440 (\(P_4/P_3\)) 
3 
439.93 ± 5.8072[4.3945] 
14.511 ± 440.96[4.3945] 

4 
2314 
78168 (\(P_5/P_4\)) 
2 
439.66 ± 5.6412[4.3945] 
11.329 ± 438.93[4.3945] 
0.002 
2 
7942 
89482 (\(P_3/P_2)\) 
2 
439.81 ± 5.7370[4.3945] 
13.730 ± 439.30[4.3945] 
3 
2340 
49389 (\(P_4/P_3\)) 
2 
440.03 ± 5.7321[4.3945] 
13.250 ± 439.64[4.3945] 

3 
2334 
49266 (\(P_4/P_3\)) 
3 
440.06 ± 5.7773[4.3945] 
14.092 ± 440.07[4.3945] 
All the files used for this case can be found in this rep [geo file, config file, json file].
Add a section on geometrical order. 
The reference results, Turek and Hron, have been obtained with a time step \(\Delta t=0.05\). When we compare our results, with the same step and \(\mathrm{BDF}_2\), we observe that they are in accordance with the reference results.
With a larger \(\Delta t\), a discrepancy is observed, in particular for the drag force. It can also be seen at the same time step, with a higher order \(\mathrm{BDF}_n\) ( e.g. \(\mathrm{BDF}_3\) ). This suggests that the couple \(\Delta t=0.05\) and \(\mathrm{BDF}_2\) isn’t enough accurate.
[TurekHron] S. Turek and J. Hron, Proposal for numerical benchmarking of fluidstructure interaction between an elastic object and laminar incompressible flow, Lecture Notes in Computational Science and Engineering, 2006.
[Chabannes] Vincent Chabannes, Vers la simulation numérique des écoulements sanguins, Équations aux dérivées partielles [math.AP], Universitée de Grenoble, 2013.