Andrew_Mac_Guinness_12042854

Andrew Mac Guinness I.D.12042854 M.Eng. Research Project 2014/2015
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Characterisation of Wall Shear Stress Magnitude in Melt Electrowritten Tissue Engineering
Bone Graft Scaffolds and Design of Bioreactor Chamber Flow field
Andrew Mac Guinness and David Hoey
Department of Mechanical, Aeronautical and Biomedical Engineering
University of Limerick, Limerick, Ireland
Abstract
Investigations into researching tissue engineered bone scaffolds are being conducted to reduce issues with graft donor
availability and body rejection after implantation. In this paper idealised CAD modelled melt electrowritten bone graft
scaffolds and bioreactor chambers, were simulated using Computational Fluid Dynamics to estimate Wall Shear Stress
magnitudes and flow distribution throughout the scaffold. Wall Shear Stress plays an important role in creating an
environment in which cell differentiation can occur. This paper investigates how pore size and fibre diameter impact wall
shear stress generation. The results show that an increase in pore size and decrease in fibre diameter will decrease the Wall
Shear Stress magnitude when keeping the inlet fluid velocity constant. The results also show that introducing a baffle plate
between the scaffold and chamber inlet will reduce the gradient of the velocity profile, thus creating a more homogenous
inlet velocity across the surface of the scaffolds.
Keywords: Bone Scaffolds, Melt Electrospinning writing, CFD, Pore Size, Bioreactor Chamber.
1. Introduction
Orthopaedic surgeons are confronted daily with cases
where allografts and autografts are currently the best
course of treatment for their patients. These procedures,
while being effective in treating patients have their
limitations, such as availability of donor material and risk
of the host body rejecting the implanted graft. There are
three areas of study in bone tissue engineering; cells,
growth factors and scaffolds. This study investigates the
latter of the three and how to alleviate the problem of
donor availability while decreasing the risk of rejection.
This is achieved by seeding a polymeric scaffold with
cells from the host patent. Using the patient’s own cells
greatly reduces the risk that the bone graft will be
rejected.
Cell seeding is one of the fundamental steps in
creating a 3-D bone graft scaffold. Seeding is the means
by which to distribute cells throughout the scaffold prior
to culturing and implantation. To achieve a superior graft
quality there are two factors discussed in this paper, both
of which have to be taken into account when designing
and seeding the scaffold. Firstly, studies have shown that
mechanical stimulation must be present via a dynamic
flow regime when seeding the scaffold to avoid creating a
densely seeded layer of cells along the scaffold
extremities. Dense seeding blocks the supply of nutrients
to the core of the scaffold. Without a nutrient supply to
the centre of the scaffold, cells in that area become
necrotic and die. Secondly, during cell seeding it has been
discovered that little to no osteogenic differentiation can
be observed between scaffold and cell constructs without
the medium being exposed to mechanical stimulation
even with dexamethasone, which has been shown to
induce cell differentiation [1].
Perfusion bioreactors can provide the required mass
transport for the medium, increasing the penetration of
nutrients through the scaffold. Studies show that
osteogenic differentiation occurs in greater volume with
culturing cells that are exposed to fluid flow when
compared to cells exposed to static culture [2] [3]. Many
in vitro studies have concluded that fluid shear stress
directly affects osteogenic differentiation [4] [5].
However if the wall shear stress generated is too great,
then cell washout can occur. Since quantifying shear
stress directly from experimental methods are impossible
due to the small fibre and porosity size, Computational
Fluid Dynamics (CFD) is needed to simulate wall shear
stress to ensure that the shear stresses generated are
within the required range for bone cell differentiation.
Currently a melt electrowriting apparatus capable of
printing electrowritten scaffolds is being developed. The
research carried out in this paper coincides with the
projected capabilities of the printer.
There are two primary objectives of this study.
Firstly, to design a set of scaffold geometries that the 3-D
printer is capable of producing; simulate these scaffolds
using CFD to investigate the Wall Shear Stress (WSS)
and velocity profiles generated for each scaffold. These
results will be analysed to determine a preferred scaffold
design, taking into account: fibre diameter, pore size and
inlet velocity to the scaffold. Secondly, to design a
bioreactor chamber’s flow field and determine where to
place the scaffold within it. The chamber should be
designed in such a way so that the scaffolds face is
perpendicular to the flow and is exposed to a constant
velocity.
2. Literature review
2.1 Scaffold Design
When creating a 3-D scaffold Hutmacher states that
the following three characteristics should be observed: (1)
It# is# hereby# declared# that# this# report# is# entirely# my# own#
work,# unless# otherwise# stated,# and# that# all# sources# of#
information# have# been# properly# acknowledged# and#
referenced.# It# is# also# declared# that# this# report# has# not#
previously# been# submitted,# in# whole# or# in# part,# as# part#
fulfilment#of#any#module#assessment#requirement.#
#
Signed:##____________________## Date:# # _________##

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High porosity with high pore interconnectivity to allow
room for cell growth and consistent flow of nutrients and
metabolic waste; (2) The scaffold material should be both
biocompatible and bioresorbable with controllable
degradation rates that match cell growth; (3) Material
should consist of a suitable surface chemistry for cell
attachment, proliferation and differentiation [6]. The
research conducted in this paper will now focus on
Hutmachers first characteristic.
Previous studies conducted have analysed the effect
that unstructured/ irregular scaffold geometries have on
fluid flow. Micro Computed Tomography (µCT) scans of
scaffolds are digitised and simulated using commercial
CFD packages. The results show that the irregular pore
size, shape and poor interconnectivity of pores create a
heterogeneous distribution of flow. This leaved the
creation of a heterogeneous distribution of nutrients,
removal of metabolic waste and generation of WSS [7]
[8]. The simulations show that the fluid will always
choose the path of least resistance (i.e. the fluid will flow
through the larger pore size). Leaving areas of the
scaffold with smaller pores in danger of not generating
large enough values of WSS needed for osteogenic
differentiation by not receiving the nutrients needed for
cell growth. In comparison when studies are conducted on
uniform structured scaffolds with equal pore sizes, the
fluid is distributed equally across the scaffold, allowing
for a more uniform WSS distribution and homogenous
distribution of nutrients and waste removal [9]. Melchels
2011 paper demonstrated how varying the pore size
across a scaffold affects the fluid flow. In this study two
scaffolds where modelled and analysed. The first had an
isotropic pore size and the second had a gradient pore size
varying from 500µm at the centre to 250µm at the
circumference. The isotropic model exhibits similar
results to that modelled by Zhao and Mcnamara in that,
the constant pore size throughout the entirety of the
scaffold allows for the fluid to generate a uniform flow
and WSS distribution [10]. However the second scaffold
modelled has a gradient in the pore size. It can be seen
that, similar to Maes study the fluid tends to flow through
the larger pores again creating an uneven distribution of
WSS [10]. It is important to understand the optimum
stress values that induce osteogenic differentiation with a
range of WSS between 0.1-10mPa having been identified
as a range where bone cell differentiation occurs [9]. If
the WSS generated is greater than 10mPa, cell washout
can occur. Since quantifying shear stress directly from
experimental methods are impossible due to the small
fibre and pore size, CDF is needed to predict WSS to
ensure that the shear stresses generated are within the
required range for bone cell differentiation.
2.2 Bioreactor chamber design.
Two criteria for bioreactor chambers are; (1) The
chamber should have no areas of flow stagnation, as
stagnated flow can lead to a build-up of nutrients not
reaching the scaffold or a build-up of metabolic waste not
being removed from the chamber, further obstructing the
flow. (2) Have a uniform fluid velocity when the fluid
first interacts with the scaffold inside the chamber.
Multiple studies have indicated that when a scaffold
is exposed to stagnant flow nutrients cannot be delivered
or renewed [9] [7] [11]. A 2014 paper on biofabrication of
perfusion bioreactors demonstrates that both the inner
architecture and shape off the chamber affect the
perfusion of flow. It details 11 chambers that were
modelled in 2-D. The results showed that introducing
chamfered edges where the chamber diameter changes
eliminate areas of fluid stagnation.
2.3 Conclusion
From the literature it is clear that in order to obtain a
constant WSS across a scaffold, it has to be designed to
have a constant pore size. None of the papers studied
compared how solely changes in fibre diameter affect the
WSS generation. As previously stated the existence of
mechanical stimulation also affects WSS generation
therefore for each scaffold analysed, multiple simulations
will be run with incremental changes in the fluid velocity
to try and obtain an appropriate inlet velocity for each
scaffold.
3. Materials and Methods
3.1 Scaffold Geometry Creation
For ease of printing, the modelled scaffold geometry
consists of a fibre layup pattern of 00
-900
-00
, three
scaffolds modelled have a constant diameter of 16µm to
allow for direct comparison of results due to changes in
scaffold porosity. A further forth scaffold with a fibre
diameter of 11µm was modelled to analyse how the flow
reacted when faced with a smaller fibre diameter. A fibre
size of 11µm was modelled, as this is the lower limit of
the typical range of diameters commonly used in melt
electrowriting. For each of the scaffolds modelled, the
porosity remains constant throughout the entire volume of
the scaffold. For specifications on pore sizes of each
scaffold, see Table 1. As the fibres are layered in a
staggered pattern there are two ways that the pore size can
be measured. The first way is to view the scaffold through
the surfaces perpendicular to the direction on the fluid
flow; this is the apparent pore size. In this view the pore
appears to be square. The second method of measuring
the pore size is by viewing the scaffold along the length
of the fibre and measuring the distance between the fibres
in a row, this is the layer pore size. Figure 1A and 1B,
illustrates the difference between the apparent pore size
1A and the layer pore size 1B.
Table 1 Pore Sizes and Fibre Diameter for each
scaffold
Scaffold
Apparent
Pore Size
Layer
Pore Size
Fibre
Diameter
A 10µm 45µm 16µm
B 20µm 90µm 16µm
C 40 µm 180µm 16µm
D 20µm 85µm 11µm

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Figure 1.A Figure 1.B
Apparent Pore size Layer Pore Size
To avoid meshing issues where the prism layers
would converge onto a single point, the interconnections
between the fibres were merged by a distance of 0.1
micron with a fillet of radius 0.5 microns, as shown in
Figure 2. Applying a fillet to the interconnections ensures
that the CFD meshing code will not try and converge on a
single point and return floating point errors.
Figure 2. Fillet on scaffold interconnections
3.2 Bioreactor Geometry Creation
To determine a suitable chamber in which to place
the scaffolds, multiple design iterations were modelled
and simulated. For the purpose of ease of comparison
between scaffolds, the inlet and outlet diameters of 2mm
and chamber diameter form 6mm to 8mm was applied
universally. These dimensions are based of Costa 2014
study as referenced in 2.2. The first aim of the chamber
design was to determine the inlet velocity required to
ensure that the fluid interacting with the scaffold equals
the velocity determined from the scaffold simulations.
The second aim was to try and optimise the velocity
profile so that the velocity gradient is minimal in the
region where the fluid interacts with the scaffold, thereby
inducing a uniform WSS.
3.3 Computational Fluid Dynamic Modelling
The simulations are performed with CFD software
Star CCM+ (9.02.005-R8) running on Window 7
operating system with an Intel Xeon W3530 2.80GHz and
18GB of RAM. To computationally estimate the WSS on
the fibres while the fluid undergoes mechanical
stimulation throughout it and to simulate each scaffold
and bioreactor chamber the flow field was discretised and
meshed using Polyhedral cells and Prism layers. Images
of generated meshes can be found in Appendix C. Table 2
depicts the mesh cell count for scaffold A,B,C and D.
Table 2. Comparison of Mesh Cell Count against the
Four Scaffolds
The scaffolds were modelled as cell free, rigid and
impermeable to reduce computation time required to
solve the simulation. Uniform velocity profiles were
applied to the inlet of each scaffold, see Table 3. The fluid
simulated is a blend of distilled water and 10% fetal
Bovine solution. It is modelled as a Newtonian fluid with
a density and viscosity of 1000kg/m3
and 1.45mPa.s
respectively at 370
C [9]. As the sub-scaffold modelled is a
section of a much larger scaffold, a slip condition was
applied to the outer wall of the flow field and a no-slip
condition applied to the scaffold fibres. The inlet and
outlet have velocity inlet and pressure outlets applied
respectively. The segregated solver was used to solve the
flow field with convergence taken at 1x10-4
. See
Appendix E for sample convergence graphic. To
determine the type of fluid flow, either laminar or
turbulent the Reynolds numbers (Re) was calculated using
Equation 1.
!" =
!"#!!!
!!(!!!!!)
(1)
Where l1 and l2 are the length and width of the rectangular pore
when looking perpendicular to the direction of flow. As shown in Figure
1A.
3.4 CFD Mesh Validation
Adequately meshing the flow field is critical to
obtaining accurate shear stress results along the walls of
the scaffold fibres. Generally increasing the cell count or
grid refinement, around the areas of interest allow for
more accurate results. However as the cell count increases
so will the computation time. A limit is approached
whereby increasing the grid refinement yields little
increase in result accuracy. To find the best compromise
between solution accuracy and computation time a Grid
Independence Study (GIS) must be conducted for each
new model. An example of a GIS for scaffold A can be
seen in Figure 3, here it can be seen that the maximum
WSS is plotted against cell number. WSS was chosen as
the comparable parameter due to its sensitivity changes in
the mesh. WSS is generated within the boundary layer of
the fluid, which is very sensitive to mesh changes because
gradient in the velocity profile is generated within this
region.
Figure 3. GIS of Scaffold A
Figure 3 shows that after 3.6 million cells the
fluctuation of maximum WSS is below 1%. This means
that any increase in cell numbers will increase
0.23
0.24
0.25
0.26
0.27
0 5 10 15
MaximumWallShear
Stress(mPa)
Cell Number (millions)
Scaffold Cell Number
A 3.6 Million
B 3.6 Million
C 7.0 Million
D 5.3 Million

4
computation time but will not increase the solution
accuracy. The macro created and used for generating the
grid independence study can be found in Appendix A.
4. Simulations Conducted
4.1 Scaffold Simulations
The following sub-section outlines the simulations
carried out during the research of this paper, Table 3. It
should be noted that as mentioned in section 3.3 a GIS
was carried out on each model before these simulations
could take place. The macro created and used for
generating a new velocity inlet once the solver converges
can be found in Appendix B. One Simulation of each
scaffold can be found in Appendix F.
Table 3. Velocities simulated for each scaffold
Velocity
(m/s)
Scaffold
A
Scaffold
B
Scaffold
C
Scaffold
D
0.02x10-4
0.03x10-4
0.04x10-4
0.05x10-4
0.06x10-4
0.07x10-4
0.08x10-4
-
0.09x10-4
0.1 x10-4
0.2 x10-4
0.3 x10-4
0.4 x10-4
4.2 Chamber Simulations
In total twenty different bioreactor chambers where
simulated, simulation files and results can be found on the
DVD in Appendix F-3. This paper outlines the results
from two chambers and illustrates the improvements
made over iterations of design between the first and latest
chamber design. Velocities ranging from 0.1x10-4
m/s to
0.3x10-4
m/s in 0.02x10-4
m/s intervals were simulated for
each chamber.
It can be observed that the inlet velocities are higher
for the chambers than the scaffolds with this being done
to allow for the retardation of the velocity as the chambers
diameter expands to accommodate the scaffold.
5. Results and Discussion
5.1 Validation of meshed models
Due to current instrumentation restrictions, gaining
results for WSS and fluid velocities from direct
measurement of scaffolds during experiments are
impossible due to scaffold architecture and size and there
is no method of definitively correlating simulated results
with actual measurements [7]. However there are methods
of ensuring that the simulation is set up in such a way that
the mesh will reduce the probability of an invalid
solution. Along with conducting a GIS, (see section 3.4)
there are also three meshing parameters that can be
checked according to the Star CCM+ User Guide. These
parameters of importance are Cell Skewness Angle, Face
Validity and Volume Change. Table 5, displays the
recommended value for each of the parameters as outlined
in the user manual and the recorded values of each for
scaffold A [10].
Table 4. Mesh Validation Checks
Parameter Recommendation Scaffold A
Skewness Angle < 85◦
9.6◦
Face Validity 0.5-1 0.91
Volume Change >1x10-5
2.5x10-4
5.2 Scaffolds
All four scaffold geometries were successfully
meshed and simulated with a range of velocity inlet
values as shown in Table 3, the results from these are
discussed in the following subsections. Results of WSS
are taken from a sub-region within the scaffold one pore
size smaller than the simulated volume. This is to
eliminate any abnormal results caused by the unrealistic
boundary that surrounds the scaffold where flow channels
can get closed off. The streamlines in Figure 4 show the
sub-region within scaffold B where the results are taken
from. The streamlines in this figure represent the velocity
of the fluid through the scaffold.
Figure 4.Velocity streamlines, Scaffold B
5.3 Scaffold Sub-section size validation
In order to run simulations with the computational
power provided (section 3.3), only sub-sections of
scaffolds could be simulated. The following validates that
the scaffold sub-sections are of a required size to
adequately analyse changes in scaffold pore size and fibre
diameter. As stated in section 2.1 the optimum range of
WSS generated between the fluid and the scaffold is
between 0.1mPa and 10mPa [9]. Figure 5 visually shows
the distribution of WSS across the entire scaffold.

5
Figure 5. WSS along the surface of fibres, Scaffold B
Using visualisation techniques, the data presented, while
being visually striking, appears to be cluttered making
comparison between simulations hard. Line probes are
used to organise the WSS results. A line probe was placed
at the same point on each scaffold; a representative of this
line probe, shown in Figure 6 highlights the position of
the probe coloured in purple. The result from this probe of
WSS can be viewed in Figure 7.
Figure 6. Position of Line Probe, Scaffold B
Figure 7 show graphically the WSS generated along
the length of one fibre within scaffold B, each data line
represents a velocity inlet, Table 3. Similar graphs were
produced for the Scaffold’s A, C and D, these can be
found in Appendix D.
The two red horizontal lines represent the maximum
and minimum WSS 10-0.1mPa respectively, for the
optimum range of cell differentiation as outlined by Zhao
[9]. The fluctuation of WSS along the x-axis is due to the
fibres upstream in the flow, obstructing the fluid retarding
and accelerating it unevenly. While the fluid velocity
fluctuates, the structured fibre lay-up means that the
velocity change throughout the scaffold is repeatable and
therefore predictable. It can be seen in Figure 8 that the
velocity of the fluid fluctuates in a repeating cycle
throughout the length and width of the scaffold.
Figure 8. Illustrating Repeating Velocity Pattern,
Scaffold B
Therefore an assumption can be made that if the inlet
velocity to the scaffold is constant throughout the entire
inlet and the scaffold lay-up is repeating throughout its
entirety then the results gained should be repeated
everywhere else along the scaffold. This repeatability of
flow along with Maes et al’s recommendation of scaffolds
with homogenous pore sizes, that the sub-section should
be minimum five to six times the average pore size,
validates that the scaffold sub-sections simulated in this
project are of a sufficient size to be a representative of a
full scaffold [7].
5.4 Comparison of WSS generation due to Pore Size
Scaffolds A, B and C are compared in this section,
and as stated in Table 1, the fibre lay-up and fibre
diameters are constant. However the pore size doubles
between A to B and B to C. All three scaffolds were
simulated with multiple velocity inlet rates, and graphs
displaying multiple inlet velocities for each scaffold can
be found in Appendix D. Line probes were placed on the
scaffolds as described in section 5.3, Figure 6. The results
show for a constant inlet velocity that, as the pore size
increases the WSS produced decreases. This means that
the inlet velocity to the scaffold can be increased without
exceeding the 10mPa WSS limit. Increasing the velocity
allows more nutrients to be delivered throughout the
scaffold and metabolic waste can be removed quicker,
reducing the risk of cells becoming necrotic. This is
illustrated in Figures 9A,B and C, where distance along
the fibre is plotted against WSS for a velocity inlet of
5x10-5
m/s for all three scaffolds, As with Figure 7 the
horizontal red lines represent the maximum and minimum
desired WSS. It should be noted that the valleys in WSS
0#
0.002#
0.004#
0.006#
0.008#
0.01#
0.012#
0# 0.00005# 0.0001# 0.00015# 0.0002# 0.00025# 0.0003#
Wall$Shear$Stress$(mPa)$
Distance$along$Fibre$(m)$
Figure 7. Graph of WSS generated along Line Probe
for varying Inlet Velocities, Scaffold B

6
along the graph are where there is a fibre directly above
the data line, obstructing the flow.
Figure 9. WSS Vs. Distance along Fibre
Velocity inlet= 5x10-5
m/s,(A) Scaffold A, (B) Scaffold
B, (C) Scaffold C.
When comparing these graphs it can be noted that as
well as a drop in WSS as pore size increases there is also
a drop in fluctuation in WSS between each scaffold.
There is a 55% drop in maximum WSS between scaffold
A and B, and a further drop of 56% between scaffold B
and C. This is due to the fibres having less of an impact of
impeding the fluid through the scaffold. With scaffold A,
the fluid had to flow through a pore size of 10 microns,
comparing that to scaffold C where the same volume of
fluid now flows through a pore size of 40 microns, the
Venturi effect created by the pore size is decreased,
creating a more uniform velocity distribution
perpendicular to the flow.
Due to the decrease in WSS with increase in pore
size, there is no one-inlet velocity for all scaffolds that
will generate the same WSS for all scaffolds. Therefore
for each scaffold there is an optimum velocity that is a
compromise between generating WSS profiles within the
desired range of between 0.1-10mPa while ensuring the
fastest delivery of nutrients and removal of waste. Table 6
details the optimum inlet velocity to achieve maximum
nutrient delivery and waste removal without generating
WSS outside of the recommended range.
Table 5. Optimum Inlet Velocity for each Scaffold
Scaffolds Velocity Inlet
Scaffold A 4 x10-6
m/s
Scaffold B 1 x10-5
m/s
Scaffold C 2 x10-5
m/s
5.5 Comparison of WSS generation due to Fibre Diameter
When investigating the effect changing the fibre
diameter has on WSS, Scaffold’s B and D are compared.
These two scaffolds are chosen for comparison, as their
fibre lay-up and pore sizes are almost identical. As stated
in Table 6 the optimum inlet velocity for scaffold B was
found to be 1 x10-4
m/s. For comparing the effect of fibre
diameter on WSS generation the inlet velocity graphed in
Figure 10A,B below is 1 x10-5
m/s for both scaffold B,
Figure 10A and scaffold D, Figure 10B. As the graphs
show there is a drop in maximum WSS from 0.0103mPa
to 0.00931mPa. This calculates to a 10.7% reduction in
WSS when the fibre diameter is reduced by 5µm.
Figure 10. WSS Vs. Distance along Fibre,
Velocity inlet= 1x10-5
m/s.(A) Scaffold B, (B) Scaffold D
To establish a link between WSS generation and fibre
diameter, more simulations should be run with scaffolds
of different fibre diameters. Unfortunately due to
computation resource two scaffolds could be analysed.
5.6 Comparison with Literature
Results of structured scaffolds exist in literature;
these studies were used as benchmarks to help confirm
the validity of the mesh models and physics conditions.
The results generated in this study are of the same
magnitude as the results found in the literature. The result
of Zhao et al. show only 75% of their scaffolds create
conditions necessary for osteogenic differentiation to
occur. However the scaffolds modelled, while being
structured with a constant pore size throughout, was
modelled with a square fibre cross section [9]. The square
cross section was likely chosen to reduce meshing and
solver computation time at the expense of real scaffold
0#
0.005#
0.01#
0.015#
0# 0.00005# 0.0001# 0.00015# 0.0002#
Wall$Shear$Stress$
(mPa)$$
Distance$along$ﬁbre$(m)$
0#
0.002#
0.004#
0.006#
0.008#
0.01#
0.012#
0# 0.0001# 0.0002# 0.0003# 0.0004#
Wall$Shear$Stress$
(mPa)$
0#
0.005#
0.01#
0.015#
H0.0008#H0.0006#H0.0004#H0.0002#0#
Wall$Shear$Stress$
(mPa)$
0#
0.005#
0.01#
0.015#
0# 0.0001# 0.0002# 0.0003# 0.0004#
Wall$Shear$Stress$
(mPa)$
0#
0.005#
0.01#
0.015#
H0.0004#H0.0002#0#
Wall$Shear$Stress$
(mPa)$
9A
9B
9C
10B
10A

7
geometry representation. Despite the difference in
geometry the results obtained follow the same trends as
theirs. Literature has concluded that WSS is highly
dependent on pore size, there are cases similar to this
study where and increase in pores size has seen a decrease
in WSS. This has been the case with Maes et al. For the
same inlet velocity, when the pore size was doubled from
275µm to 645µm the resulting WSS almost halved. This
compares favourably with the results obtained with
scaffold A, B and C.
To date there has yet to be any published data on
solely analysing the effect fibre diameter has on WSS
magnitude, therefore comparison with literature is not
possible.
Since there are many variables in each simulation that
has to be considered, such as; velocity inlet magnitudes,
scaffold architecture, fluid properties, scaffold material
and manufacturing process. Caution should be observed
when comparing results with other authors work.
5.7 Bioreactor Chambers
Controlling the flow within chambers and scaffolds is
essential to create the correct conditions for bone cell
differentiation. The goal of the chamber design is to
create a homogenous laminar flow field.
Copies of all simulated chamber designs can be found
in the accompanying DVD found in Appendix F-3. The
first chamber and chamber 20 are discussed in this
section. The chambers overall dimensions were decided
upon after reviewing literature on bioreactor chamber
design, these dimensions were detailed in section 2.2 of
this report. Chamber 1 is designed from the findings of
Costa et al., who conducted 2-D simulations of Bioreactor
chambers [12]. Costa describes that in order to ensure
controlled flow rates throughout a chamber, the fluid
should flow vertically up. This would ensure that the fluid
would not be accelerated due to gravity. The change in
diameter of the chamber should be gradual, not sharp
steps. Creating a chamber with steps will generate areas
of backpressure and create swirling or stagnated flow
[12]. This will eventually generate a build-up of sediment,
further reducing the effectiveness on the chamber.
Chamber 20 is the result of incremental changes in the
chamber design in an effort to eliminate swirling and
stagnated flow.
5.8 Bioreactor configurations
5.8.1 Chamber 1
Figure 11A, 11B depicts the velocity profile of the
fluid inside chamber 1 without a scaffold in place. It can
be seen that while the chamfers help avoid areas of fluid
stagnation; the velocity profile across the chamber is
parabolic in shape. When the fluid interacts with the
scaffold the parabolic shape of the velocity profile will
create a heterogeneous distribution of WSS generation,
with WSS being highest at the centre of the scaffold
gradually reducing as the fluid velocity reduces near the
walls of the bioreactor.
Figure 11.
(A) Plane section displaying velocity profile of fluid
through Chamber 1.
(B) Graph of fluid velocity through centre of Chamber
1.
5.8.2 Chamber 20
Chamber 20 is the most recent and successful
chamber simulated to date, Figure 12 depicts a velocity
profile generated. The velocity profile is plotted from the
centre of the chamber to the external walls. There is a
noticeable difference in the shape of the velocity profile
between Figure 11B and Figure 12. A baffle plate is
inserted between the chamber inlet and the scaffold; this
causes the flatter velocity profile. The baffle obstructs the
flow, slowing the fluid in the centre of the chamber,
giving a more uniform velocity distribution through the
chamber where the scaffold is placed.
Figure 12. Velocity profile Chamber 20,
Inlet velocity 1.2x10-5
m/s.
Figure 12 shows the more even distribution of fluid
velocity though the chamber. It also outlines the effect the
0#
0.0000005#
0.000001#
0.0000015#
0.000002#
H0.006# H0.004# H0.002# 0# 0.002# 0.004# 0.006#
Velocity$(m/s)$
Distance$through$centre$of$chamber$(m)$
0#
0.000002#
0.000004#
0.000006#
0.000008#
0.00001#
0.000012#
H0.003#H0.002#H0.001#0#
Velocity(m/s)$
Distance$from$centre$fo$chamber$to$wall$
(m)$
A
B

8
baffle plate has on creating a more homogenous velocity
distribution.
Figure 13. Velocity distribution through Chamber 20,
Inlet velocity 1.2x10-5
m/s
Simulations were ran and analysed to determine the
correct inlet velocity for chamber 20 that would generate
the required velocities at the scaffold’s interface. Table 7
details the chamber inlet velocity’s required for scaffold
A, B and C.
Table 6. Inlet velocity for Chamber 20 for each
scaffold
Scaffold Chamber 20 Velocity Inlet
Scaffold A 4.2 x10-6
m/s
Scaffold B 1.2 x10-5
m/s
Scaffold C 2.3 x10-5
m/s
Scaffold D 1 x10-5
m/s
5.9 Position of scaffold within chamber
Line probes where placed every 0.5mm along the
length of the chamber and measurements of velocity
distribution were recorded and plotted. The results
determined when using chamber 20, that the scaffold
should be placed in the chamber 2mm above the baffle
plate. This is to allow the fluid to settle and distribute
evenly after being disturbed from flowing through the
baffle. Figure 14 depicts five velocity profile plots
measured from chamber 20. The graph shows that the
flattest velocity profile can be found 2mm after the fluid
exits the baffle plate.
Figure 14. Velocity Profile of fluid in Chamber 20
after fluid passes through baffle plate.
6. Limitations of simulations
Due to the length of the project and computational
resources available, there are limitations to what was
capable of being performed during this research. As
mentioned full scaffolds could not be modelled, therefore
simulations could not be run where a scaffold is placed
inside a chamber. This is partly why both the scaffold and
chamber were modelled and analysed separately.
Currently no mathematical model exists to simulate
cell growth inside a scaffold. This means that it is not
possible to model how pore size will shrink with cell
growth. However, these limitations are not considered to
be relevant as the research was conducted to achieve good
starting conditions for testing.
7. Conclusions
7.1 Scaffold conclusions
• A set of four sub-sections of scaffolds capable of
being printed by means of a Melt Electrowriter were
modelled and simulated.
• Appropriate flow conditions were developed to allow
for affective seeding of each scaffold designed.
• The WSS generated on each scaffold for multiple
fluid velocities was obtained.
• WSS magnitude was found to be highly dependent on
scaffold pore size. Results show that when doubling
the pore size, a reduction in WSS in the order of 50%
is achieved. However, this study has shown that pore
size is not the only factor in WSS magnitude.
• As the pore size increases the magnitude in WSS
fluctuation decreases.
• Fibre diameter affects WSS magnitude. This study
shows that WSS magnitude dropped 10% when the
fibre diameter was decreased by 5µm.
7.2 Chamber conclusions
• A Bioreactor chamber was developed for the seeding
of bone tissue engineering scaffolds and designed to
eliminate areas of flow stagnation and reduce the
fluid velocity gradient along its cross section.
• Simulations show that placing a baffle plate between
the expansion of the chamber and the scaffold will
reduce the variation in velocity across the chamber.
• Results show that the most suitable chamber
simulated is chamber twenty, with the scaffold placed
2mm away from the trailing edge of the baffle plate.
7.3 Scaffold/ Chamber Configuration
• From the scaffolds and chambers simulated the best
configuration would be Scaffold D placed in
Chamber 20, 2mm above the baffle plate with an
inlet velocity of 1 x10-5
m/s.
8. Recommendations for future work
More research should be conducted on the effect of
fibre diameter; the two simulations completed, are not
enough to understand how fibre diameter affects the fluid
flow. A Fluid Structure Interaction (FSI) study should be
conducted to assess the scaffolds deformation behaviour
when fluid at the velocities recommended in this paper,
pass through the scaffold. The FSI could assess if there is
a link between pore size and scaffold stiffness.
0.E+00#
2.EH06#
4.EH06#
6.EH06#
8.EH06#
1.EH05#
1.EH05#
1.EH05#
H0.003#H0.002#H0.001#0#
Velocity$(m/s)$
Distance$from$centre$of$chamber$to$wall$
(m)$
1mm#
2mm#
5mm#
7mm#
8mm#

9
Acknowledgements
I would like to acknowledge my supervisor Dr. David Hoey for outlining my thesis and keeping me from straying
outside the project scope. I would also like to thank Kian Eichholz for outlining the capabilities of the melt electrowriter,
which in turn determined the scaffolds to be simulated.
References
[1] H.L. Holtarf, J.A. Jansen, and A.G. Mikos, "Flow
perfusion culture induces the osteoblastic
differentiation of marrow stromal cell-scaffold
constructs in the absence of dexamethasone,"
Journal of Biomedical Materials Research , vol. Part
A, no. 72A, pp. 326-334, 2005.
[2] AS Goldstein, TM Juarez, D Helmke, MC Gustin,
and AG Mikos, "Effect of convection on osteoblastic
cell growth and function in biodegradable polymer
foam scaffold," Biomaterials, vol. 22, no. 11, pp.
1279-1288, 2001.
[3] MJ Jaasma, NA Plunkett, and FJ O'Brien, "Design
and validation of a dynamic flow perfusion
bioreactor for the use with compliant tissue
engineering scaffolds," J Biotechnol, vol. 133, no. 4,
pp. 490-496, 2008.
[4] S. Scaglione et al., "effects of fluid and calcium
phosphate coating on human bone marrow stromal
cells cultured in a defined 2D model system,"
Journal of Biomedical Materials Research, vol. Part
A, no. 86A, pp. 411-419, 2008.
[5] M.R. Kreke, L.A. sharp, Y.W. Lee, and A.S.
Goldstein, "Effect of intermittent shear stress on
mechanotransductive signaling and osteoblatic
differentiation of bone marrow stromal cells," Tissue
Engineering, vol. Part A, no. 14, pp. 529-537, 2008.
[6] Dietmar W. Hutmacher, "Scaffolds in tissue
engineeringbone and cartilage," Biomaterials, vol.
21, pp. 2529-2543, 2000.
[7] F. Maes et al., "Computational models for wall shear
stress estimation in scaffolds; A comparative study
of two complete geometries," Journal of
Biomechanics, vol. 45, pp. 1586-1592, 2012.
[8] Frederic Maes, Peter Van Ransbeeck, Hans Van
Oosterwyck, and Pascal Verdonck, "Modeling Fluid
Flow Through Irregular Scaffolds for perfusion
Bioreactors," Biotechnology and Bioengineering,
vol. 103, no. 3, pp. 621-630, June 2009.
[9] Feihu Zhao, Ted J. Vaughan, and Laoise M.
Mcnamara, "Multiscale fluid-structure interaction
modelling to determine the mechanical stimulation
of bone cells in a tissue engineered scaffold,"
Biomech Model Mechanobiol, June 2014.
[10] Ferry P.W. Melchels et al., "The influence of the
scaffold design on the distribution of adhering cells
after perfusion cell seeding," Biomaterials, vol. 32,
pp. 2878-2884, 2011.
[11] Blaise Porter, Roger Zauel, Harlan Stockman, Robert
Guldberg, and David Fyhrie, "3-D Computational
Modeling of Media Flow Through Scaffolds in a
perfusion Bioreactor," horunal of Biomechanics, vol.
38, pp. 543-549, 2005.
[12] Star CCM+, "Star CCM+ User Guide," in Star
CCM+ User Guide Version 9.02.: CD-adapco, pp.
2235-2240.
[13] Pedro F Costa et al., "Biofabricarion of customized
bone grafts by combination of additive
manufacturing and bioreactor knowhow,"
Biofabrication, vol. 6, 2014.

Appendix A
A-1
APPENDIX A (Grid Independence Macro)
Simulation Tip
If using either macro from Appendix A or B, ensure that all line probes, x-y plots, scalar scenes, plane sections etc. are
set up in the first simulation that the macro is run from. This will ensure that when each simulation is opened for analysis
that time is not wasted reapplying all the post processing required to obtain the data required.
// STAR-CCM+ macro: Rename_Mesh3.java
// Written by STAR-CCM+ 9.02.005
package macro;
import java.util.*;
import star.common.*;
import star.base.neo.*;
import star.meshing.*;
public class Rename_Mesh3 extends StarMacro {
public void execute() {
execute0();
// C:WorkAreaAndrew Masters research dont deleteChamber 1GIS_Start.sim
execute1();
// C:WorkAreaAndrew Masters research dont deleteChamber 1GIS_1.sim
execute2();
// C:WorkAreaAndrew Masters research dont deleteChamber 1GIS_1.sim
execute3();
// C:WorkAreaAndrew Masters research dont deleteChamber 1GIS_.8.sim
execute4();
// C:WorkAreaAndrew Masters research dont deleteChamber 1GIS_.8.sim
}
private void execute0() {
Simulation simulation_0 =
getActiveSimulation();
simulation_0.saveState(resolvePath("C:WorkAreaAndrew Masters research dont deleteChamber
1GIS_Start.sim"));
}
1GIS_1.sim"));
}
Solution solution_0 =
simulation_0.getSolution();
solution_0.clearSolution();
AutoMeshOperation autoMeshOperation_0 =
((AutoMeshOperation) simulation_0.get(MeshOperationManager.class).getObject("Automated Mesh"));
autoMeshOperation_0.getDefaultValues().get(BaseSize.class).setValue(1);
MeshPipelineController meshPipelineController_0 =
simulation_0.get(MeshPipelineController.class);
meshPipelineController_0.generateVolumeMesh();
simulation_0.getSimulationIterator().run();
1GIS_1.sim"));
}
1GIS_.8.sim"));

Appendix A
A-2
}
Solution solution_0 =
simulation_0.getSolution();
solution_0.clearSolution();
AutoMeshOperation autoMeshOperation_0 =
((AutoMeshOperation) simulation_0.get(MeshOperationManager.class).getObject("Automated Mesh"));
autoMeshOperation_0.getDefaultValues().get(BaseSize.class).setValue(0.8);
MeshPipelineController meshPipelineController_0 =
simulation_0.get(MeshPipelineController.class);
meshPipelineController_0.generateVolumeMesh();
1GIS_.8.sim"));
}
}

Appendix B
B-1
APPENDIX B (Velocity Change Macro)
// STAR-CCM+ macro: Change_Velocity_macro_2.java
// Written by STAR-CCM+ 9.02.005
package macro;
import java.util.*;
import star.common.*;
import star.base.neo.*;
import star.flow.*;
public class Change_Velocity_macro_2 extends StarMacro {
public void execute() {
execute0();
// C:WorkAreaAndrew Masters research dont delete700_Mesh_Change0.05.sim
execute1();
execute2();
execute3();
}
simulation_0.saveState(resolvePath("C:WorkAreaAndrew Masters research dont
delete700_Mesh_Change0.05.sim"));
}
Region region_0 =
simulation_0.getRegionManager().getRegion("Subtract");
Boundary boundary_0 =
region_0.getBoundaryManager().getBoundary("inlet");
VelocityMagnitudeProfile velocityMagnitudeProfile_0 =
boundary_0.getValues().get(VelocityMagnitudeProfile.class);
velocityMagnitudeProfile_0.getMethod(ConstantScalarProfileMethod.class).getQuantity().setValue(0.05E-4);
delete700_Mesh_Change0.05_simfin.sim"));
}
delete700_Mesh_Change0.06.sim"));
}
Simulation simulation_0
Region region_0 =
simulation_0.getRegionManager().getRegion("Subtract");
Boundary boundary_0 =
region_0.getBoundaryManager().getBoundary("inlet");
VelocityMagnitudeProfile velocityMagnitudeProfile_0 =
boundary_0.getValues().get(VelocityMagnitudeProfile.class);
velocityMagnitudeProfile_0.getMethod(ConstantScalarProfileMethod.class).getQuantity().setValue(0.06E-4);
delete700_Mesh_Change0.06_simfin.sim"));
}

Appendix C
C-1
APPENDIX C (Images of Scaffold and Chamber Meshes)
Figure C1-A, Plane section of Scaffold B mesh through flow field.
C1-B, Zoom in of mesh refinement around area of interest, Scaffold fibres.
C1-C, Zoom in of mesh refinement detailing Prism Layers around fibres to resolve near wall flows
B
C
A

Appendix C
C-2
Figure C2-A Mesh on outer wall of Chamber 20
C2-B Zoom in on mesh refinement around area of interest, Baffle plate.
A B

Appendix D
D-1
APPENDIX D (Wall Shear Stress Vs. Distance along fibre, for varying Inlet Velocities)
Figure D- 1 Varying Inlet Velocity Scaffold A
Figure D- 2 Varying Inlet Velocity Scaffold B
0#
0.02#
0.04#
0.06#
0.08#
0.1#
0.12#
0# 0.00002# 0.00004# 0.00006# 0.00008# 0.0001# 0.00012# 0.00014# 0.00016# 0.00018# 0.0002#
Wall$Shear$Stress$(mPa)$$
Distance$along$ﬁber$(m)$
1x10^H5m/s#
2x10^H5m/s#
3x10^H5m/s#
4x10^H5m/s#
5x10^H5m/s#
5x10^H6m/s#
Minimum#WSS#
Maximum#WSS#
2x10^H6m/s#
3x10^H6m/s#
4x10^H6m/s#
6x10^H6m/s#
7x10^H6m/s#
8x10^H6m/s#
9x10^H6m/s#
0#
0.002#
0.004#
0.006#
0.008#
0.01#
0.012#
0# 0.00005# 0.0001# 0.00015# 0.0002# 0.00025# 0.0003# 0.00035# 0.0004#
1x10^H5#m/s#
6x10^H6#m/s#
7x10^H6#m/s#
8x10^H6#m/s#
9x10^H6#m/s#
Maximum#
Minimum#

Appendix D
D-2
Figure D- 3Varying Inlet velocity Scaffold C
Figure D- 4Varying Inlet velocity Scaffold D
0#
0.005#
0.01#
0.015#
0.02#
0.025#
0.03#
0.035#
0.04#
H0.00045#H0.0004#H0.00035#H0.0003#H0.00025#H0.0002#H0.00015#H0.0001#H0.00005#0#0.00005#
DIstance$along$ﬁbre(m)$
0.1x10^H5#m/s#
0.2x10^H5#m/s#
0.3x10^H5#m/s#
0.4x10^H5#m/s#
0.5x10^H6#m/s#
0.6x10^H6#m/s#
0.7x10^H6#m/s#
Maximum#
Minimum#
0.8x10^H6#m/s#

Appendix E
E-1
Appendix E (Sample Convergence Graph)
0.000001$
0.00001$
0.0001$
0.001$
0.01$
0.1$
1$
0$ 500$ 1000$ 1500$ 2000$
Residuals)
Itera-on)
Con*nuity$
X0Momentum$
Y0Momentum$
Z0Momentum$

Appendix F
F-1
Appendix F (DVD of Scaffold simulations)

Appendix F
F-2
Appendix F (DVD of Scaffold simulations Continued)

Appendix F
F-3
Appendix F (DVD of Chamber Simulations)

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Characterisation of Wall Shear Stress Magnitude in Melt
Electrowritten Tissue Engineering Bone Graft Scaffolds and
Design of Bioreactor Chamber Flow field
ORIGINALITY REPORT
PRIMARY SOURCES
Brindley, D., K. Moorthy, J.-H. Lee, C. Mason,
H.-W. Kim, and I. Wall. "Bioprocess Forces
and Their Impact on Cell Behavior:
Implications for Bone Regeneration Therapy",
Journal of Tissue Engineering, 2011.
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Submitted to University of Sheffield
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download.star-russian-conference.ru
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novel flow-perfusion bioreactor supports 3D
dynamic cell culture.(Research Article)
(Report)", Journal of Biomedicine and
Biotechnology, Annual 2009 Issue
Publication
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Internet Source
Kramschuster, Adam, and Lih-Sheng Turng.
"Fabrication of Tissue Engineering
Scaffolds", Handbook of Biopolymers and
Biodegradable Plastics, 2013.
Publication
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Student Paper
Nie, Lei, Jinping Suo, Peng Zou, and Shuibin
Feng. "Preparation and Properties of Biphasic
Calcium Phosphate Scaffolds Multiply
Coated with HA/PLLA Nanocomposites for
Bone Tissue Engineering Applications",
Journal of Nanomaterials, 2012.
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engineering: in vitro bioactivity & antibacterial
activity", Frontiers of Materials Science in
China, 06/2008
Publication
J. Brandon Dixon. "Lymph Flow, Shear
Stress, and Lymphocyte Velocity in Rat
Mesenteric Prenodal Lymphatics",
Microcirculation, 10/1/2006
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properties and cell cultural response of
polycaprolactone scaffolds designed and
fabricated via fused deposition modeling",
Journal of Biomedical Materials Research,
05/2001
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Shoukri, M.. "On the thermal analysis of
pressure tube/calandria tube contact in
CANDU reactors", Nuclear Engineering and
Design, 19871002
Publication
Hamman, K.D.. "A CFD simulation process
for fast reactor fuel assemblies", Nuclear
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dipping process", Australian Journal of Crop
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