Partial Differential Equations - Modelling and ... - ResearchGate
Partial Differential Equations - Modelling and ... - ResearchGate
Partial Differential Equations - Modelling and ... - ResearchGate
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218 J. Hao et al.<br />
<strong>and</strong> solve for V n+5/6<br />
G<br />
<strong>and</strong> ω n+5/6 from<br />
⎧<br />
⎪⎨ 〈e i , u n+5/6 − V n+5/6 −−−−−→<br />
n+5/6<br />
G<br />
− ω G n+4/6 ⊥<br />
x 〉 n+4/6 B<br />
=0, for i =1, 2,<br />
h<br />
⎪⎩ 〈 −−−−−→<br />
G n+4/6 ⊥<br />
x , u n+5/6 − V n+5/6 −−−−−→<br />
n+5/6<br />
G<br />
− ω G n+4/6 ⊥<br />
x 〉 n+4/6 B<br />
=0.<br />
h<br />
(30)<br />
Step 7. Finally, take V n+1,0<br />
G<br />
= V n+5/6<br />
G<br />
<strong>and</strong> G n+1,0 = G n+4/6 . Then predict<br />
the final position <strong>and</strong> translation velocity as follows:<br />
For k =1,...,N,<br />
Call Adhesive Dynamics Algorithm,<br />
̂V n+1,k<br />
G<br />
= V n+1,k−1<br />
G<br />
+ F r (G n+1,k−1 )△t/2N, (31)<br />
Ĝ n+1,k = G n+1,k−1 +(̂V n+1,k<br />
G<br />
V n+1,k<br />
G<br />
= V n+1,k−1<br />
G<br />
G n+1,k = G n+1,k−1 +(V n+1,k<br />
G<br />
+ V n+1,k−1<br />
G<br />
)△t/4N, (32)<br />
+(F r (Ĝn+1,k )+F r (G n+1,k−1 ))△t/4N,<br />
(33)<br />
+ V n+1,k−1<br />
G<br />
)△t/4N, (34)<br />
enddo;<br />
<strong>and</strong> let V n+1<br />
G<br />
= Vn+1,N G<br />
, G n+1 = G n+1,N ; <strong>and</strong> set u n+1 = u n+5/6 ,<br />
ω n+1 = ω n+5/6 .<br />
In Algorithm 1, we have t n+s =(n + s)△t, W n+1<br />
g = W 0,h g 0,h(t n+1 ), Λ n+s<br />
0,h =<br />
Λ 0,h (t n+s ), B n+s<br />
h<br />
is the region occupied by the particle centered at G n+s ,<br />
<strong>and</strong> F r is the combination of a short range repulsion force which prevents the<br />
particle/particle <strong>and</strong> particle/wall penetration (see, e.g., [GPHJ99, GPH + 01])<br />
<strong>and</strong> the force obtained from the adhesive dynamics algorithm for the cell<br />
adhesion. Finally, α <strong>and</strong> β verify α + β =1;wehavechosenα =1<strong>and</strong>β =0<br />
in the numerical simulations discussed later.<br />
The degenerated quasi-Stokes problem (21) is solved by a preconditioned<br />
conjugate gradient method introduced in [GPP98], in which discrete elliptic<br />
problems from the preconditioning are solved by a matrix-free fast solver from<br />
FISHPAK by Adams et al. in [ASS80]. The advection problem (22) for the<br />
velocity field is solved by a wave-like equation method as in [DG97]. The<br />
problem (24) is a classical discrete elliptic problem which can be solved by<br />
the same matrix-free fast solver. To enforce the rigid body motion inside<br />
the region occupied by the particles, we have applied the conjugate gradient<br />
method discussed in [PG02, PG05].<br />
4 Numerical Results <strong>and</strong> Discussion<br />
We consider the detachment of 20 cells in shear flow as the test problem for<br />
cell adhesion model at the initial stage of the adhesion. The computational<br />
domain is Ω =(0, 23)×(0, 10) (unit: 10 µm). Cells have the shape of an ellipse,