Life science special report 161215 IY opt

LIFE SCIENCES VIRTUAL ABDOMINAL AORTIC ANEURYSM
PRE-PROCESSING
Different mesh topologies and
grid refinements were assessed
(Figure 3) using STAR-CCM+. These
were based on polyhedral, nonconformal
hexahedral and tetrahedral
elements, all with boundary layer
extrusion to accurately calculate
the velocity gradient near the walls
of the vessel. For the sensitivity
analysis of the grid, the verification
procedure proposed by Roache [1]
was followed. The mesh size varied
from 300,000 to roughly 1,400,000
cells. In addition, the influence of
the boundary layer was taken into
account by comparing the solutions
obtained with various dimensions of
prisms layer, as shown on Figure 4.
FIGURE 4: Prism layer infl uence
investigation
SOLVING
The physics and the solver setups had
to be determined in order to automate
the solving process. Two different
types of fluids were compared to
model the behavior of the blood: (a) a
simple Newtonian fluid with standard
properties and (b) a non-Newtonian
fluid with Power-law rheology. The
influence of the time step and number
of inner iterations was assessed
using the same systematic approach
as adopted for the mesh study.
While keeping the physics and the
solver parameters unchanged,
different numerical schemes
were tested and compared:
• Solvers: segregated (S), coupled
implicit (Ci) and coupled explicit (Ce)
• Pressure/velocity coupling: first-order
and second-order upwind convection
schemes (pv1 and pv2 respectively)
• Temporal discretization: first-order
and second-order upwind convection
scheme (t1 and t2 respectively)
Figure 5 shows a comparison of OSI
values computed with the different
numerical schemes. In Figure 6,
the time history for the benchmark
model and the final average
value of the velocity magnitude
inside the vessel are reported.
POST-PROCESSING
To visualize the numerical solution, scalar
plots that show the variations of a number
of parameters were drawn on the surface
and inside the vessel. Furthermore, by
exporting the solution-in-time, it was
possible to integrate the Wall Shear Stress
(WSS) components and compute the
hemodynamic risk indices. Figure 7 shows
a sample of post-processing images.
FIGURE 3: Example of grid topology.
A: tetrahedral based; B: polyhedral
based; C: hexahedral based.
The investigation about grid
generation led to the definition of
a discretization strategy which is
suitable to represent the physics as
realistically as possible.
CONCLUSION
This study assessed how the choice of
grid, solver models and features of the
fl uid (blood) affects the computation
of some specifi c parameters (such as
pressure, fl uid velocity, tension and
stress state of the vessel) in the case
of an abdominal aortic aneurysm. The
investigation about grid generation
led to the defi nition of a discretization
strategy which is suitable to represent
the physics as realistically as possible.
Non-conformal hexahedral grids allow
the representation of the phenomenon
FIGURE 5: Oscillatory Shear Index (OSI)
computed using different numerical schemes
with fewer numerical discretization errors
than the other non-structural grids; as a
consequence, the use of a polyhedral or
tetrahedral mesh implies a more refi ned
grid and therefore a higher number
of cells, which in turn requires more
computational time and resources . It is
also necessary to have a good resolution
of the boundary layer to compute the
WSS accurately. For the solving phase,
a suitable time step and number of
inner iterations, numerical scheme
and fl uid rheology were extracted as
parameters for the automation process.
6 SPECIAL REPORT