2D Drops Benchmark

This benchmark has been proposed and realised by [Hysing]. It allows us to verify our level set code, our Navier-Stokes solver and how they couple together.

Computer codes, used for the acquisition of results, are from [Doyeux], with the use of [Chabannes]'s Navier-Stokes code.

1. Problem Description

We want to simulate the rising of a 2D bubble in a Newtonian fluid. The bubble, made of a specific fluid, is placed into a second one, with a higher density. Like this, the bubble, due to its lowest density and by the action of gravity, rises.

The equations used to define fluid bubble rising in an other are the Navier-Stokes for the fluid and the advection one for the level set method. As for the bubble rising, two forces are defined :

  • The gravity force : fg=ρϕg

  • The surface tension force : fst=Γσκn

We denote Ω×]0,3] the interest domain with Ω=(0,1)×(0,2). Ω can be decompose into Ω1, the domain outside the bubble and Ω2 the domain inside the bubble and Γ the interface between these two.

2D Bubble Geo
Figure 1. Geometry used in 2D Bubble Benchmark

Durig this benchmark, we will study two different cases : the first one with a ellipsoidal bubble and the second one with a squirted bubble.

1.1. Boundary conditions

  • On the lateral walls, we imposed slip conditions

un=0t(u+tu)n=0
  • On the horizontal walls, no slip conditions are imposed : u=0

1.2. Initial conditions

In order to let the bubble rise, its density must be inferior to the density of the exterior fluid, so ρ1>ρ2

2. Inputs

The following table displays the various fixed and variables parameters of this test-case.

Table 1. Fixed and Variable Input Parameters
Name Description Nominal Value Units

g

gravity acceleration

(0,0.98)

m/s2

l

length domain

1

m

h

height domain

2

m

r

bubble radius

0.25

m

Bc

bubble center

(0.5,0.5)

m

3. Outputs

In the first place, the quantities we want to measure are Xc the position of the center of the mass of the bubble, the velocity of the center of the mass Uc and the circularity c, define as the ratio between the perimeter of a circle and the perimeter of the bubble. They can be expressed by

Xc=Ω2xΩ21=Ωx(1Hε(ϕ))Ω(1Hε(ϕ))
Uc=Ω2uΩ21=Ωu(1Hε(ϕ))Ω(1Hε(ϕ))
c=(4πΩ21)12Γ1=(4πΩ(1Hε(ϕ)))12Ωδε(ϕ)

After that, we interest us to quantitative points for comparison as cmin, the minimum of the circularity and tcmin, the time needed to obtain this minimum, ucmax and tucmax the maximum velocity and the time to attain it, or yc(t=3) the position of the bubble at the final time step. We add a second maximum velocity umax and ucmax2 and its time tucmax2 for the second test on the squirted bubble.

4. Discretization

This is the parameters associate to the two cases, which interest us here.

Case

ρ1

ρ2

μ1

μ2

σ

Re

E0

ellipsoidal bubble (1)

1000

100

10

1

24.5

35

10

squirted bubble (2)

1000

1

10

0.1

1.96

35

125

5. Implementation

6. Results

6.1. Test 1

6.2. Test 2

We describe the different quantitative results for the two studied cases.

Table 2. Results comparison between benchmark values and our results for the ellipsoidal case

h

cmin

tcmin

ucmax

tucmax

yc(t=3)

lower bound

0.9011

1.8750

0.2417

0.9213

1.0799

upper bound

0.9013

1.9041

0.2421

0.9313

1.0817

0.02

0.8981

1.925

0.2400

0.9280

1.0787

0.01

0.8999

1.9

0.2410

0.9252

1.0812

0.00875

0.89998

1.9

0.2410

0.9259

1.0814

0.0075

0.9001

1.9

0.2412

0.9251

1.0812

0.00625

0.8981

1.9

0.2412

0.9248

1.0815

Table 3. Results comparison between benchmark values and our results for the squirted case

h

cmin

tcmin

ucmax1

tucmax1

ucmax2

tucmax2

yc(t=3)

lower bound

0.4647

2.4004

0.2502

0.7281

0.2393

1.9844

1.1249

upper bound

0.5869

3.0000

0.2524

0.7332

0.2440

2.0705

1.1380

0.02

0.4744

2.995

0.2464

0.7529

0.2207

1.8319

1.0810

0.01

0.4642

2.995

0.2493

0.7559

0.2315

1.8522

1.1012

0.00875

0.4629

2.995

0.2494

0.7565

0.2324

1.8622

1.1047

0.0075

0.4646

2.995

0.2495

0.7574

0.2333

1.8739

1.1111

0.00625

0.4616

2.995

0.2496

0.7574

0.2341

1.8828

1.1186

6.3. Conclusion

7. Bibliography

References for this benchmark
  • [Hysing] S. Hysing, S. Turek, D. Kuzmin, N. Parolini, E. Burman, S. Ganesan, and L. Tobiska, Quantitative benchmark computations of two-dimensional bubble dynamics, International Journal for Numerical Methods in Fluids, 2009.

  • [Chabannes] V. Chabannes, Vers la simulation numérique des écoulements sanguins, Équations aux dérivées partielles. PhD thesis, Université de Grenoble, 2013.

  • [Doyeux] V. Doyeux, Modélisation et simulation de systèmes multi-fluides, Application aux écoulements sanguins, PhD thesis, Université de Grenoble, 2014.