WEBVTT
00:15.840 --> 00:21.970
Welcome to lecture number 38 of this lecture
series on turbo machinery aerodynamics. We
00:21.970 --> 00:26.860
have come towards the end of this particular
lecture series, we have three more lectures
00:26.860 --> 00:32.840
left and we have decided that as we promised
in the first lecture that we are going devote
00:32.840 --> 00:38.680
these three lectures towards discussion on
some aspects of CFD or Computational Fluid
00:38.680 --> 00:45.300
Dynamics specific towards turbo machine flows.
We are assuming that you are aware of some
00:45.300 --> 00:52.290
of the basics of CFD and that you have had
a chance to understand the fundamental aspects
00:52.290 --> 00:58.200
involved in CFD. So, we are assuming that
this background information is available with
00:58.200 --> 01:04.199
you and with that assumption we are going
to discuss some of the aspects which hold
01:04.199 --> 01:11.199
the key towards using CFD as tool for design
as well as analysis of turbo machinery flows.
01:13.700 --> 01:20.100
CFD as we know is relatively young compared
to the other two methods of analysis which
01:20.100 --> 01:25.780
have been existing for a very long time now.
The other two methods being the theoretical
01:25.780 --> 01:31.700
analysis, methodology as well as the experimental
method which they of course, these have been
01:31.700 --> 01:38.700
around for several years now, and therefore
CFD in comparison to these methods have relatively
01:41.369 --> 01:48.369
very short span I would say may be last 25
to 30 years also. So, it is in the last 25
01:48.610 --> 01:55.610
to 30 years also, that there has been a tremendous
development in techniques or design analysis
01:57.000 --> 02:04.000
methods using a third approach which we now
know as Computational Fluid Dynamics or CFD.
02:04.170 --> 02:11.170
So, CFD is basically trying to solve the governing
equations of a flow using a computing technique
02:14.840 --> 02:21.840
using numerical techniques and that requires
that we identify the domain of interest and
02:22.140 --> 02:29.140
then decide which are the points on this flow
that we would like to solve and then that
02:29.349 --> 02:36.349
is considered to be taken as a representation
of the flow field itself. So, depending upon
02:36.519 --> 02:43.519
the number of points that we choose to analyze
you can get better and better solutions depending
02:43.590 --> 02:48.239
of course, upon a variety of other parameters
like the solver being used and so on.
02:48.239 --> 02:55.239
So, CFD though it is considered as a very
powerful tool in the design analysis and optimization
02:57.019 --> 03:03.829
loop which is a common loop that is used in
any design exercise that it is taken up, that
03:03.829 --> 03:10.739
there is a preliminary design then its goes
to as 1-D analysis and then 2-D and 3-D analysis
03:10.739 --> 03:17.739
and then it goes to an an optimization routine
and then finally a CFD detail CFD analysis
03:18.290 --> 03:23.280
and then this loop is kind of if required
from the CFD analysis to be find that the
03:23.280 --> 03:29.700
performance is not what we had intended then
the designers have to come back to some of
03:29.700 --> 03:36.700
the intermediate steps to correct those issues
and try and achieve the performance that the
03:37.370 --> 03:41.170
particular design exercise was intended for
.
03:41.170 --> 03:47.829
Traditionally these have always required the
design analysis and optimization loop always
03:47.829 --> 03:54.829
required an experimental validation of the
design itself. This is partly being replaced
03:58.109 --> 04:05.109
by Computational Fluid Dynamics, but as has
been as was initially thought that CFD is
04:05.659 --> 04:11.739
going to replace all numerical, all theoretical
and experimental techniques that is quite
04:11.739 --> 04:18.570
not true at least at that moment and few years
from now that I can for see, that experimental
04:18.570 --> 04:25.570
methods as well as analytical or theoretical
methods will continue to guide us or be the
04:26.670 --> 04:33.670
other two distinct analysis tool that will
continue to exist along with CFD.
04:34.630 --> 04:39.560
Of course, the importance and relevance of
CFD is continuously growing with more and
04:39.560 --> 04:46.560
more modifications and refinements that CFD
tools have had in the last several years and
04:47.340 --> 04:52.460
with the computing power that is available
which is also increasing at an at a very fast
04:52.460 --> 04:59.300
rate, CFD is definitely likely to be a very
powerful tool which will be used and it is
04:59.300 --> 05:06.120
continuously even now used and will continue
to be used even more in design analysis in
05:06.120 --> 05:10.690
general.
But our interest as in this course is on turbo
05:10.690 --> 05:17.690
machines and CFD of course, has been used
in turbo machine design analysis and optimization
05:18.150 --> 05:25.150
cycle, but there are certain very key challenges
which are still which which still need to
05:26.460 --> 05:33.129
be resolved. So, that CFD can be you know
taken as a very standard technique of design.
05:33.129 --> 05:37.949
Even though it is, but there are certain limitations
which are which is what we shall be discussing
05:37.949 --> 05:41.590
in today's lecture and possibly in next lecture
as well.
05:41.590 --> 05:48.590
We will continue with some of the issues associated
with CFD and those which are currently under
05:49.569 --> 05:55.720
revision in the sense that they need to be
revised and better methods of estimation of
05:55.720 --> 06:01.190
certain aspects need to be developed which
hopefully will happen in the coming years.
06:01.190 --> 06:07.190
Today's lecture we are going to devote towards
basically three aspects. CFD I will give a
06:07.190 --> 06:11.069
general introduction which I assume that you
already have, but I will nevertheless give
06:11.069 --> 06:18.069
you an introduction and overview of CFD then
we shall talk about grid generation and boundary
06:18.789 --> 06:23.000
conditions.
Grid generation is is still an issue with
06:23.000 --> 06:30.000
reference to CFD and of course, grid generation
in general if you talk to people who work
06:31.300 --> 06:38.289
in CFD they would admit that grid generation
continuous to be relatively challenging aspect
06:38.289 --> 06:42.930
because that something which is very much
dependent on the geometry that we are trying
06:42.930 --> 06:48.860
to solve. So, the more complex and intricate
the geometry the more difficult it is to generate
06:48.860 --> 06:55.860
grids for a particular geometry. In fact,
considerable amount of time is usually required
06:56.520 --> 07:01.580
for generating the grid for a very complex
geometry. For example, if one has to generate
07:01.580 --> 07:07.539
a geometry for a very complicated geometry
let us say like combustion chamber including
07:07.539 --> 07:12.229
all the holds and cooling holds which are
present on the combustion chamber or for that
07:12.229 --> 07:17.889
matter even a turbine blade which has all
the cooling holds and which need to be simulated
07:17.889 --> 07:21.349
using CFD.
So, generating grids for such geometries is
07:21.349 --> 07:27.889
extremely complicated and a tremendous amount
of time is required for developing grids which
07:27.889 --> 07:34.889
can accurately predict the performance and
and people all over the world researches are
07:36.860 --> 07:42.849
trying to develop automated tools which can
be used for generating a grid which in some
07:42.849 --> 07:48.870
form exist for relatively simpler geometries,
but for very complex geometries like with
07:48.870 --> 07:53.599
turbine blade cooling holds and combustion
chambers and all that it becomes a later tricky
07:53.599 --> 08:00.599
and we did not really have an automated grid
generation tool which can faithfully grid
08:01.539 --> 08:06.860
the such very intricate geometries and help
us in the analysis.
08:06.860 --> 08:13.860
So, CFD as I was saying is considered is now
considered a standard third approach which
08:14.550 --> 08:19.389
comes in the design analysis optimization
cycle. The other two approaches as I mentioned
08:19.389 --> 08:25.520
being the experimental approach as well as
the theoretical approach. CFD definitely is
08:25.520 --> 08:31.490
a third approach and is increasingly being
used by designers in their design analysis
08:31.490 --> 08:37.030
cycle.
CFD has always been intended and will continue
08:37.030 --> 08:44.030
to be intended to complement theory and experiments.
It is not meant to replace either of them
08:44.090 --> 08:51.090
will which is unfortunately very rather large
misconception amongst people that CFD is something
08:52.560 --> 08:58.500
which can replace experiments and theory and
I do not think that is going to happen anywhere
08:58.500 --> 09:05.190
in the future. CFD is going to compliment
theory and experiments as third approach and
09:05.190 --> 09:09.390
would of course, be increasingly used by designers
all up the world.
09:09.390 --> 09:15.880
And CFD is also very common research tool
in the sense that there is lot of design exercises
09:15.880 --> 09:21.340
which involve lot of research to be carried
out on let us say optimization or a new design
09:21.340 --> 09:28.340
to be developed through certain modifications
of the shape or any other method that involves
09:29.980 --> 09:36.220
a lot of research exercise to be carried out.
CFD is definitely a very strong contender
09:36.220 --> 09:40.000
for one of the research tools which can be
used for such an analysis.
09:40.000 --> 09:45.800
So, CFD is to summarize a few points and I
was talking about CFD; obviously, is a very
09:45.800 --> 09:52.260
powerful analytic tool and is a third approach
for analysis besides experiments and theory.
09:52.260 --> 09:59.230
CFD compliments very well theory and experiments
and is primarily not intended to replace any
09:59.230 --> 10:05.620
of these and off let CFD is very commonly
used to research tool and it is definitely
10:05.620 --> 10:11.890
recognized as a dependable research tool for
a variety of flow applications accepting a
10:11.890 --> 10:18.890
few cases where CFD is still struggling to
kind of predict the performance very well.
10:19.070 --> 10:25.570
For example, in compressor stall surge prediction
that is something which CFD is not really
10:25.570 --> 10:31.990
in a position to predict well and that is
where some of these experimental or analytical
10:31.990 --> 10:36.950
tools will still need to be used for such
complex flow scenarios.
10:36.950 --> 10:43.950
Now, let me quickly take you to the different
methods or levels of CFD analysis that could
10:44.960 --> 10:51.960
be carried out. So, one could carry out very
simple fast simulations or one could carry
10:53.120 --> 10:59.950
out very detailed and analysis of a particular
flow field that it trying to simulate and
10:59.950 --> 11:05.510
that depends upon the requirement, whether
we really need it is very such high and computations
11:05.510 --> 11:10.220
to be carried out which obviously requires
a lot of time as well as effort and, and therefore
11:10.220 --> 11:17.220
money or can simple calculations using CFD
help us in understanding the the design methodology
11:17.930 --> 11:24.170
and whether the basic design works or not.
So, based on this one could either have very
11:24.170 --> 11:30.360
simple Euler based solution which is a potential
flow solution which could again be 2-D or
11:30.360 --> 11:36.790
3-D or one could go for one level higher we
could go to 2-Dimensional or axisymmetric
11:36.790 --> 11:43.790
Navier-Stokes solution with of course, certain
approximations or one could go for a 3-D Navier-Stokes
11:44.080 --> 11:50.680
solution, one could either have a Reynolds
Averaged Navier-Stokes - RANS as it is called
11:50.680 --> 11:56.360
that is truncated form of Navier-Stokes equation
using Reynolds Averaging or one could go for
11:56.360 --> 12:03.360
an Unsteady RANS that is also called URANS
- Unsteady Reynolds Averaged Navier-Stokes.
12:04.390 --> 12:10.990
Another level higher is what is known as Large
Eddy Simulation which is something which is
12:10.990 --> 12:17.990
much more involved in complicated than URANS
or RANS. Large Eddy Simulation involves simulating
12:19.500 --> 12:25.410
the larger Eddies and computing the smaller
Eddies directly. Larger Eddy Simulation; obviously,
12:25.410 --> 12:32.410
requires much higher computational power as
compare to RANS or for that matter any other
12:35.440 --> 12:40.190
Navier any other form of solution and the
ultimate aim of course, is to get what is
12:40.190 --> 12:46.300
known as a direct numerical simulations or
DNS. Direct Numerical Simulation is something
12:46.300 --> 12:51.820
which is used well which could be eventually
I would say few years from now may be could
12:51.820 --> 12:56.730
be used for complex flow scenarios like the
turbo machines. Currently this is simply being
12:56.730 --> 13:01.900
respective to very simple flow fields like
flow path circular cylinders and flow passes
13:01.900 --> 13:08.040
an airfoil and so on.
DNS involves use of the Navier-Stokes the
13:08.040 --> 13:13.370
3-D Navier-Stokes equation in its original
form without any approximations. Unlike in
13:13.370 --> 13:20.120
RANS where there are certain approximations
for example, turbulence is modeled in in RANS,
13:20.120 --> 13:25.750
DNS does not require any turbulence modeling,
and therefore that is considered to be the
13:25.750 --> 13:32.750
most accurate most possible accurate numerical
solution of a flow field, but; obviously,
13:33.260 --> 13:40.260
this requires a huge amount of memory and
also DNS is directly a function of the Reynolds
13:40.830 --> 13:46.550
number. Higher the Reynolds number the more
are the number of cells that will be required
13:46.550 --> 13:53.550
for for us to develop a DNS solution. DNS
in fact, is proportional to Reynolds number
13:54.140 --> 13:58.410
square which means if we are looking at a
Reynolds number, the number of nodes required
13:58.410 --> 14:03.730
for DNS is square of the Reynolds number itself
almost the square of the Reynolds number.
14:03.730 --> 14:08.330
So, if you are looking at a Reynolds number
which is let us say in typical turbo turbine
14:08.330 --> 14:14.680
or compressor flows could be easily in ten
to the power 5 or 6. So, square of that is
14:14.680 --> 14:21.680
10 rise to 10 or 10 rise to 12. That is the
amount of nodes or elements or discretized
14:22.800 --> 14:29.770
elements which we will we required for us
to develop DNS solutions.
14:29.770 --> 14:36.600
Now, one could also have CFD analysis which
could be either steady or unsteady as I was
14:36.600 --> 14:42.230
saying, one could have RANS solutions or one
could have unsteady RANS solutions. One may
14:42.230 --> 14:47.380
also have is the flow requirement is such
that the Mach numbers are very low. One might
14:47.380 --> 14:53.350
stick to an incompressible CFD analysis or
if one is dealing with higher Mach numbers
14:53.350 --> 14:59.030
then that is basically a compressible solution
that we need to look at.
14:59.030 --> 15:03.580
If the Reynolds numbers are very low it could
be either laminar flow solution or if it is
15:03.580 --> 15:08.420
high Reynolds numbers flow, then we need to
go a turbulent flow simulation. One may be
15:08.420 --> 15:12.710
also dealing with internal flow or external
flow. In turbo machines, generally the flow
15:12.710 --> 15:17.300
field that we are trying to simulate are internal
flows, but if you looking at let us say a
15:17.300 --> 15:23.170
simple airfoil or a blade shape without considering
the casing and all that then that could be
15:23.170 --> 15:28.660
considered like an external flow stimulation,
but in general turbo machine flows are internal
15:28.660 --> 15:32.920
flows simulations that we carrying out.
So, these are different methodologies that
15:32.920 --> 15:39.920
are available for a designer to choose from
and try to apply some of these methods in
15:39.990 --> 15:46.990
or incorporate these methods in his design
exercise and depending upon the level of accuracy
15:47.910 --> 15:54.910
that is required from the simulations the
designer may choose for either a simple 2-D
15:55.060 --> 16:02.060
Euler solution or a 2-D Navier-Stoke solution
or one could go for a 3-D RANS solutions and
16:04.170 --> 16:10.700
possibly when an LES depending upon the computer
power that is available, but not a really
16:10.700 --> 16:16.690
a DNS at this moment we are not really at
a stage where we can use DNS for full a scale,
16:16.690 --> 16:23.220
let us say compressor flow simulation or even
a turbine flow simulation we are not really
16:23.220 --> 16:28.930
up to that level, but hopefully in the next
few years we should be able to develop techniques
16:28.930 --> 16:35.930
which can be or develop computing power which
can be used for using DNS for our numerical
16:36.380 --> 16:42.390
simulations.
So, DNS is likely to be depending upon other
16:42.390 --> 16:47.340
developments which might take place and which
probably requires much less computing power.
16:47.340 --> 16:54.340
DNS could possibly be the ultimate aim of
CFD user or a CFD researcher where one can
16:57.020 --> 17:03.750
use DNS in flow field simulations and capture
the entire range of scales that are there
17:03.750 --> 17:10.750
in a turbulent flow. For example, if you are
aware of turbulence and turbulent flow situations
17:10.809 --> 17:17.089
then we know that in turbulent flow energy
dissipation is taking place through Eddies
17:17.089 --> 17:22.279
which are which which break down into smaller
Eddies and eventually dissipates the energy
17:22.279 --> 17:28.250
and the smallest scale through which energy
is dissipated is known as the kolmogorov scale
17:28.250 --> 17:32.379
and it has scales in length, time as well
as velocity.
17:32.379 --> 17:38.220
So, these are there are several ranges of
these scales which are there through which
17:38.220 --> 17:45.220
energy is dissipated and in large Eddy simulation,
we try to compute this smaller Eddies properly
17:45.860 --> 17:50.629
and simulate using certain approximation the
larger Eddies and that is why it is called
17:50.629 --> 17:57.370
large Eddy simulation and since we are simulating
larger Eddies there is and there is scope
17:57.370 --> 18:02.679
for some approximation that is coming in which
is why earlier results though or much better
18:02.679 --> 18:08.990
than RANS solutions, they are still not the
final or the correct solutions.
18:08.990 --> 18:12.610
Well it is correct in the sense, that it depends
upon the level of accuracy are we looking
18:12.610 --> 18:18.039
at where as if you look at DNS there are no
such simulation or approximations that are
18:18.039 --> 18:23.350
taking place it is computely it is completely
simulating or calculating all these scales
18:23.350 --> 18:30.350
present in a turbulent flow which means that
to be able to capture the smallest scale from
18:30.519 --> 18:37.519
smallest scale to the largest scale that many
number of grids or nodes are required where
18:37.519 --> 18:42.669
all the governing equations can be solved
and that is why it is called direct numerical
18:42.669 --> 18:49.669
simulations which does not involve any approximation.
Currently the most commonly used 3-D analysis
18:51.110 --> 18:56.610
tool is the RANS or Reynolds Averaged either
in the steady mode or Unsteady RANS that is
18:56.610 --> 19:01.110
URANS.
But the only issue, one of the issues which
19:01.110 --> 19:08.110
RANS or URANS has is in the computation of
turbulence because we as such at the moment
19:10.059 --> 19:17.059
do not really have turbulence model or a model
which can simulate the turbulence in the right
19:20.070 --> 19:26.860
way. There are several turbulence models which
are available and designer has to choose among
19:26.860 --> 19:31.169
these set of turbulence models which are available
depending upon the applications. So, there
19:31.169 --> 19:35.879
is no model which can be set to be universal
and can be used in all applications their
19:35.879 --> 19:41.129
application depended and that is one of the
limitations that modern day CFD has when it
19:41.129 --> 19:48.129
comes to computing turbulent flow. Now, I
mentioned that the governing equations are
19:49.610 --> 19:54.600
the once which are being computed or solved
over a flow field.
19:54.600 --> 19:59.960
Let us take a quick look at what are the different
governing equations that are been solved in
19:59.960 --> 20:05.009
a particular in a typical CFD simulation.
I am sure you would be aware of this, but
20:05.009 --> 20:10.039
this is just to recap fundamentals.
So, CFD basically involves solving the governing
20:10.039 --> 20:16.919
equations of fluid flow conservation of mass,
conservation of momentum, conservation of
20:16.919 --> 20:23.620
energy. One would also be using equation of
state and the species conservation in case
20:23.620 --> 20:29.759
it is a reacting flow. For example, in a turbine
flow one as there are hot gases which are
20:29.759 --> 20:36.519
present in a turbine flow and so, one may
also be required to use the species conservation
20:36.519 --> 20:42.779
equation because one would like to ensure
that the species in terms of all the constituents
20:42.779 --> 20:46.899
of the hot gases are conserved as it passes
through the turbine.
20:46.899 --> 20:51.899
So, these are the governing equations that
I am sure you are aware of and depending upon
20:51.899 --> 20:56.620
the application some of them may or may not
be use. For example, species conservation
20:56.620 --> 21:00.980
may not really be used for a compressor flow
at least the initial stages of a compressor
21:00.980 --> 21:06.450
flow where the temperatures are not very high,
one would not expect any combustion or any
21:06.450 --> 21:11.490
reaction taking place.
So, in non-reacting flows the use of species
21:11.490 --> 21:17.710
conservation does not make any sense. So,
one need not use species conservation. So,
21:17.710 --> 21:22.519
these are the governing equations that have
been solved in CFD analysis and then how do
21:22.519 --> 21:28.169
you solve these governing equations. So, there
are S series of steps of which are followed
21:28.169 --> 21:35.169
in typical CFD analysis and basically the
step begins with identification of what you
21:36.159 --> 21:41.840
need to simulate. For example, if you need
to simulate a compressor flow or flow field
21:41.840 --> 21:48.009
around a compressor blade, one needs to define
the domains or boundaries of this particular
21:48.009 --> 21:52.340
flow field that you are simulating.
So, in a compressor blade let us say we are
21:52.340 --> 21:58.480
simulating only one blade of a compressor,
then one needs to define what are the bounds
21:58.480 --> 22:05.480
or limits around the compressor blade where
we need to compute we also need to keep in
22:05.549 --> 22:10.240
mind a few things that the domains are not
too close to the surface because that would
22:10.240 --> 22:15.409
not hel[p]- give us the chance to compute
all the flow physics present. It cannot be
22:15.409 --> 22:20.120
too far away because that will increase your
computing time. So, one needs to have an optimum
22:20.120 --> 22:27.120
domain and that is the first step of any simulation
to identify the domain or boundaries of the
22:27.330 --> 22:32.070
simulation.
The second step is to discretize the domain
22:32.070 --> 22:39.070
itself that is you would need to determine
the number of points in the domain at which
22:39.850 --> 22:44.899
the solutions or or the governing equations
are solved. So, all these discretisation is
22:44.899 --> 22:50.710
probably the second step after defining the
geometry and the domain, one would need to
22:50.710 --> 22:51.960
discretize the domain.
22:51.960 --> 22:56.590
Discretisation would involved basically a
machine or gridding the geometry by defining
22:56.590 --> 23:03.590
points various points on the geometry and
then the those points are where the governing
23:04.710 --> 23:11.509
equation would be solved and so, discretisation
could be either in the space domain or even
23:11.509 --> 23:15.789
in the time domain. One could discretize in
one definitely needs to discretize in time
23:15.789 --> 23:22.789
well in space, one may also need to discretize
in time if you are looking at unsteady solution
23:25.240 --> 23:31.039
that is if it is a time marching solution
there is also a discretisation in time domain
23:31.039 --> 23:35.409
that is after how many times steps that we
need to proceed and find out the solutions
23:35.409 --> 23:41.950
for the next time step.
Once you discretize the domain, the next step
23:41.950 --> 23:48.950
is to define the boundary conditions that
is you need to define the conditions at the
23:49.029 --> 23:55.850
boundary because that is there the simulations
would begin and then and the simulations or
23:55.850 --> 24:02.850
the solver would maintain the boundary conditions
that one is defining. Subsequently we solve
24:03.629 --> 24:09.110
the appropriate governing equations at these
discretize points and once the solving is
24:09.110 --> 24:15.929
done through a series of iterations and once
the iterations have converged as per the convergence
24:15.929 --> 24:22.279
criteria that is been specified, one can post
process and analyze the converge solution.
24:22.279 --> 24:29.279
So, these are the series of steps that one
would follow in a standard CFD solution this
24:29.619 --> 24:33.129
is of course, independent of what you are
trying to simulate whether it is flow pass
24:33.129 --> 24:38.749
cylinder whether it is flow passed an aircraft
or flow passed in airfoil or flow passed a
24:38.749 --> 24:44.110
compressor blade, the steps that are required
to be followed are identical in all these
24:44.110 --> 24:48.820
cases. The governing equations are more or
less identical, boundary conditions are different,
24:48.820 --> 24:55.529
the geometry is of course, different. So,
as we are discussing about turbo machinery
24:55.529 --> 25:00.749
flows why is it that turbo machinery is very
difficult to simulate as I have mentioned
25:00.749 --> 25:05.970
in the beginning there are lot of challenges
associated with simulating turbo machinery
25:05.970 --> 25:08.690
flows.
So, there are a few issues which are associated
25:08.690 --> 25:14.019
with turbo machinery flows and probably specific
primarily turbo machinery flows which makes
25:14.019 --> 25:18.580
simulating turbo machine flow quite complicated
and challenging task.
25:18.580 --> 25:25.249
Now turbo machinery involves; obviously, very
complex shear flows which involves shear layers
25:25.249 --> 25:30.629
on rotating surfaces on the blades. Shear
layers on which are developing on the curved
25:30.629 --> 25:35.159
surfaces again on the blades, one may have
separated flows which could be because of
25:35.159 --> 25:39.649
shock and boundary layer interaction or corner
separation or during stall. Shock boundary
25:39.649 --> 25:43.970
layer interaction being when it is transonic
case.
25:43.970 --> 25:50.970
Turbo machinery flows also involves swirling
flows, because the flow exiting a set of rotor
25:51.419 --> 25:58.249
rotor blades are swirling and there are vortices
involved in such flows and you also have interacting
25:58.249 --> 26:03.580
boundary layers between the blade surface
and the casing or blade surface and the and
26:03.580 --> 26:09.710
the hub surface and end wall boundary layers
and so on. So, all these put together make
26:09.710 --> 26:16.710
turbo machinery flows extremely complicated
and it is not possible to simplify this problem
26:20.049 --> 26:24.119
one can of course, simplify, but with the
loss of accuracy.
26:24.119 --> 26:28.259
For example, if you have to really simulate
a turbo machinery flow let us say compressor
26:28.259 --> 26:34.360
flow, one cannot simply do a two dimensional
Euler analysis and estimate the performance.
26:34.360 --> 26:39.929
One could at a as a starting point, but it
will no no way give us the exact performance
26:39.929 --> 26:46.179
because Euler of course, solution does not
give you the losses and if you go for a 2-D
26:46.179 --> 26:52.159
NS solution Navier- Stoke solution, one would
miss out on a variety of losses like the 3-D
26:52.159 --> 26:58.289
losses which are involved. So, one needs to
do a 3-D Navier-Stoke solution to be able
26:58.289 --> 27:05.289
to estimate the performance in the right way,
and therefore to be able to generate a 3-D
27:07.840 --> 27:12.259
Navier-Stoke solution one needs to understand
the complexities that are involved in this
27:12.259 --> 27:17.419
solution. Now there are a lot of challenges
as I have mentioned in turbo machinery CFD
27:17.419 --> 27:21.100
starting from grid generation.
So, grid generation itself is a challenge
27:21.100 --> 27:27.139
because the geometry can be quite complex
we have blades which could be twisted and
27:27.139 --> 27:33.230
which could have different curvatures has
lot of radii at the leading edge and trailing
27:33.230 --> 27:38.509
edge and at the junction between the blade
and the hub surface all these make the geometry
27:38.509 --> 27:39.980
extremely complicated.
27:39.980 --> 27:46.980
So, grid generation is an extremely involved
process in turbomachinery flows plus the fact
27:48.080 --> 27:53.649
that we also have a rotating domain. The rotor
blades are rotating and the rotating flow
27:53.649 --> 27:58.559
goes into the stator and which is stationary.
So, how do how do you actually take this into
27:58.559 --> 28:05.559
account how do factor the fact that there
is a rotating domain which is present in turbo
28:06.499 --> 28:11.039
machinery flows.
Besides this the flow in turbo machine is
28:11.039 --> 28:17.720
three-dimensional, it is highly unsteady,
it is turbulent, extremely complex shear flows
28:17.720 --> 28:24.720
as I have mentioned in previous class a previous
slide. Capturing all these different effects
28:24.799 --> 28:31.799
and and also viscous effects and put together
how do you actually simulate all these using
28:32.869 --> 28:38.379
let us say Reynolds Averaged Navier-Stoke
equation, because there is certain as I mentioned
28:38.379 --> 28:44.259
the flow is also turbulent higher turbulent.
In fact so, turbulence modeling becomes a
28:44.259 --> 28:50.989
very challenging task in most of these turbo
machineries CFD's. So, how do how does a designer
28:50.989 --> 28:57.239
or an analyst who is trying to work out performance
of a turbo machine take these factors into
28:57.239 --> 29:03.059
account because the flow is extremely a complex.
And if you also look at the performance of
29:03.059 --> 29:09.889
some of the components like let us say the
fan of turbo fan engine. The fan blades tends
29:09.889 --> 29:16.100
to deflect and vibrate under the loads the
aero dynamic loads and that vibration can
29:16.100 --> 29:21.600
also induce an effect on the flow and then
there is a back effect on the structure itself.
29:21.600 --> 29:26.869
So, there is a very strong fluid-structure
coupling and it is also referred to as aero
29:26.869 --> 29:32.730
elasticity. So, that is yet another aspect
that is quite challenging to simulate and
29:32.730 --> 29:38.840
how do you simulate aero elastic effects in
some these components like a fan blade. So,
29:38.840 --> 29:45.840
fluid-structure interaction is also important
which means that CFD also needs to be complimenting
29:46.480 --> 29:53.480
other analytical tools like finite element
methods which are used for structural analysis.
29:54.330 --> 30:01.179
So, if you look at turbo machinery CFD we
have a few options available, we could go
30:01.179 --> 30:08.179
for 2D analysis as I said 2D or you could
for a quasi 3D or even a full 3D analysis.
30:08.559 --> 30:15.049
A two dimensional analysis could be used on
a conceptual design phase where one does not
30:15.049 --> 30:22.009
want to spend lot of time on 3 analysis because
he would like to first freeze your design
30:22.009 --> 30:29.009
and look at whether the design is is conceptually
feasible. Well these have been used in in
30:30.220 --> 30:37.220
a reasonably reasonably accurate way for let
us say long blades where in two dimensional
30:37.889 --> 30:43.610
effects can be fairly well simulated. For
example, in the LP turbines the last stages
30:43.610 --> 30:50.119
of a turbine. If you are not really looking
at a very simplistic solution, one can go
30:50.119 --> 30:56.399
for a quasi 3D analysis where in the area
of the flow path changes which means it is
30:56.399 --> 31:02.539
not necessarily 3D, but it is no longer 2D
as well and one can add an extra source terms
31:02.539 --> 31:07.769
for acceleration or deceleration or the boundary
layer growth as a result of area change.
31:07.769 --> 31:12.659
One could actually go for a 3D simulation
which is of late being very commonly used
31:12.659 --> 31:18.649
where of course, one requires to simulate
the true geometry, it can simulate secondary
31:18.649 --> 31:24.690
flows shock locations and interactions of
end wall boundary layers and so on and so,
31:24.690 --> 31:30.179
3D simulations are usually used towards the
end of the design face where we have sort
31:30.179 --> 31:37.179
of arrived at reasonably good design geometry.
One could also go for a transient or stationary
31:37.950 --> 31:42.739
simulations. Stationary simulations are usually
or steady simulations usually are more common.
31:42.739 --> 31:47.909
Transient simulations, one can interact one
can actually compute the flow unsteadiness
31:47.909 --> 31:53.450
vortex shedding interaction of wake with rotors
and so on. So, these are simulations which
31:53.450 --> 32:00.179
will require a transient CFD run to be carried
out. So, these are the different options that
32:00.179 --> 32:07.179
a designer has when it comes to trying to
simulate a CFD solution. One could also use
32:08.259 --> 32:14.649
different types of solvers as I mentioned,
one could go for an Euler solver or one could
32:14.649 --> 32:21.649
go with a RANS or URANS, LES or probably DNS
sometime in the future.
32:21.909 --> 32:28.809
So, what I will take up now are 2 distinct
aspects of the solution procedure which are
32:28.809 --> 32:35.129
very important aspects of the whole CFD simulation
itself. So, we will begin witH-grid generation
32:35.129 --> 32:40.309
or mesh generation we will discuss different
types of grids or meshes which are used in
32:40.309 --> 32:47.239
CFD simulations applied for turbo machinery
blades. We will then discuss about boundary
32:47.239 --> 32:49.789
conditions in some detail.
32:49.789 --> 32:56.789
Now grid is the discretisation or grids are
used for basically discretizing the domain
32:59.009 --> 33:03.980
and there are different types of grids or
meshes which are available and which can be
33:03.980 --> 33:10.980
used. These can basically be classified as
structured grids, unstructured grids and hybrid
33:11.440 --> 33:15.909
grids.
For a structure grids are primarily more suited
33:15.909 --> 33:22.909
for relatively well-defined geometries, but
they are more difficult to generate, but it
33:23.289 --> 33:29.359
is possible for us to control the near-wall
clustering of the cells very well. That is
33:29.359 --> 33:34.899
because, one can change the near-wall number
of cells very close to the wall in a much
33:34.899 --> 33:40.200
better way using near-wall clustering and
it is possible it is gives us more flexibility
33:40.200 --> 33:46.629
and control over the size of grids. At the
same time, structured grids require less number
33:46.629 --> 33:53.629
of well less memory power. The only issue
is that it is more difficult to generate and
33:53.830 --> 33:59.850
when the geometry is very complex, structured
grids may not be very easy to generate.
33:59.850 --> 34:05.369
Unstructured girds on the other hand are intended
primarily for complex geometries, they are
34:05.369 --> 34:11.100
easier to generate it and very easy to automate
as well, but the major disadvantage is we
34:11.100 --> 34:16.750
do not really have a control over the near-wall
clustering, we do have some control, but not
34:16.750 --> 34:23.750
as much as control as we have in the case
of structured grids. So, a designer would
34:23.800 --> 34:26.560
often want to use structured grids for his
analysis.
34:26.560 --> 34:31.490
Let us take a look at both of one example
of both of these different types of grids.
34:31.490 --> 34:37.390
So, this is a typical structured grid and
as you can see there is a certain amount of
34:37.390 --> 34:44.390
structuring and you can define the grids in
certain manner and it is not random. Structured
34:44.910 --> 34:49.780
girds are usually used with multiple blocks
and I will explain what is blocks and topology
34:49.780 --> 34:56.590
little later, but you can see they are distinct
where is one block here around the blade,
34:56.590 --> 35:01.590
there is another block here, there are blocks
here as well. So, this is what is known as
35:01.590 --> 35:06.390
a multi block structured grid.
35:06.390 --> 35:12.240
And this is a typical unstructured gird and
you can see that the grids are not in a particular
35:12.240 --> 35:17.800
fashion. And they are relatively random and
this is a typical example of an unstructured
35:17.800 --> 35:22.580
grid. These are unstructured grids you can
see that immediately that not very easy to
35:22.580 --> 35:29.580
control the clustering around the blades where
you would like to simulate the boundary layers
35:30.220 --> 35:31.050
as well.
35:31.050 --> 35:38.050
So, let us start with the structured grid
multi-block and these are multi-blocks are
35:39.440 --> 35:45.330
used if we need to simulate curved surfaces.
So, generating a structured grid without multiple
35:45.330 --> 35:50.570
on a single block is very difficult it is
not really possible without having multiple
35:50.570 --> 35:57.570
blocks around the curved surface and the in
order to define multiple blocks on the curved
35:59.770 --> 36:06.770
surface one needs to define what is known
as a grid topology and grid topology also
36:07.180 --> 36:12.770
is to it is should ensure that the grid topology
will basically remain the same from the hub
36:12.770 --> 36:17.040
to tip and so, that grid topology should be
able to account for the variations in the
36:17.040 --> 36:24.040
blade shape from all the way from hub to tip.
So in a multi block structured grid, one needs
36:24.260 --> 36:31.260
to first identify and develop the topology
of the grid on the surface and then generate
36:32.420 --> 36:38.370
the grids within each of these blocks and
at the interface of these topologies or interface
36:38.370 --> 36:43.840
of these different blocks the number of cells
will have to be the same usually the same
36:43.840 --> 36:48.130
and of course, in some solvers they dO-grid
generators, they also give us a provision
36:48.130 --> 36:54.270
for having variable number of mesh points
at the interface. So, then adjacent blocks
36:54.270 --> 36:59.130
need not necessarily have the same number
of cells, but usually it is a practice used
36:59.130 --> 37:04.180
to maintain the same number of cells across
the blocks adjacent blocks.
37:04.180 --> 37:10.920
So, when you develop these number of discrete
number of blocks of around a surface, one
37:10.920 --> 37:17.030
can actually control the number of elements
in each of these blocks and that is the main
37:17.030 --> 37:21.750
flexibility which a structured grid provides
over an unstructured grid.
37:21.750 --> 37:27.770
So, if you look at grid topology it is basically
a structure of blocks that axis a frame work
37:27.770 --> 37:32.660
for for measuring the mesh elements. So, you
have to generate mesh, one needs a structure
37:32.660 --> 37:38.120
into which the meshes can be placed or grids
can be placed. The blocks are basically laid
37:38.120 --> 37:44.350
out without any gaps so; obviously, and shared
edges are and corners are possible blocks
37:44.350 --> 37:50.550
contain primarily the same number of elements
along each side. Topology usually does not
37:50.550 --> 37:54.530
change from hub to tip as I mentioned one
needs to maintain the same topology from hub
37:54.530 --> 38:01.530
to tip and one can edit the topology on 2-D
layers from hub to tip which means that if
38:01.840 --> 38:08.050
you change it on any of these surface it will
basically be applied all over from hub to
38:08.050 --> 38:12.300
the tip section.
The number of blocks will also determine the
38:12.300 --> 38:17.580
skewness of the grid elements that is if you
use lesser number of blocks, if you do not
38:17.580 --> 38:23.530
have any blocks at all and try to generate
a structured grid then what would happen is
38:23.530 --> 38:28.670
the regions with where there is a very sharp
change in the slope or curvatures the mesh
38:28.670 --> 38:35.640
or the grid becomes extremely skewed and such
a skewness can lead to lot of issues in convergence
38:35.640 --> 38:40.830
of the solution or accuracy of the solution
itself and that is why multiple block are
38:40.830 --> 38:47.380
anyway required for curved surfaces and use
of multiple blocks will give us a lot more
38:47.380 --> 38:53.550
flexibility in terms of the mesh or grid management
around the surface.
38:53.550 --> 38:58.960
So, let us look at what are the different
types of topology schemes that one can use
38:58.960 --> 39:04.970
let us start with the O-grid. O-grid is usually
used around the blade by forming a continuous
39:04.970 --> 39:11.030
loop around a surface and it gives us very
good boundary layer resolution because it
39:11.030 --> 39:16.640
is around the blade surface that we would
really be like interested in capturing the
39:16.640 --> 39:22.330
boundary layer and the viscous loss effects.
O-grid gives good control over y plus values
39:22.330 --> 39:27.730
that needs to be tightly monitored as you
are aware, y plus refers to the nearest element
39:27.730 --> 39:33.790
to the surface and to be able to simulate
the boundary layers very well one needs to
39:33.790 --> 39:40.600
have very low values of y plus. O-grid gives
us a very good control over the y plus and
39:40.600 --> 39:44.570
O- grid also provides near orthogonal elements
of the blades.
39:44.570 --> 39:50.350
Now, let us look at a one of the O-grid topology.
So, this is an O-grid that you can see around
39:50.350 --> 39:56.130
the blade all along the blade there is a set
of elements which have been demarcated as
39:56.130 --> 40:02.530
you can see the close up of this leading edge
of the blade, you can see that this is basically
40:02.530 --> 40:09.030
the O-grid which demarcates the grid around
the blade from rest of the blades.
40:09.030 --> 40:16.030
So, there is clear cut demarcation here and
that is possible because of the O-grid that
40:16.510 --> 40:23.510
is usually developed around the blade surface.
So, this is the basic O-grid topology.
40:26.180 --> 40:30.310
Now there are other forms of topologies which
I have shall discuss now there are J-grid,
40:30.310 --> 40:36.500
H-grid, C-grid and L-grid. J-grid is usually
used near the leading and trailing edges and
40:36.500 --> 40:40.730
it usually wraps up in opposite directions
at leading and trailing edges. On the other
40:40.730 --> 40:46.540
hand, H-grid tends to complete the meshing
by adding some blocks in an unstructured manner
40:46.540 --> 40:50.370
that is towards the leading or trailing edge
one may have some elements of unstructured
40:50.370 --> 40:55.920
blocks. The structured blocks usually extend
from upstream of the leading edge, downstream
40:55.920 --> 41:01.020
of the trailing edge and between blades and
periodic surfaces and you may have certain
41:01.020 --> 41:07.520
elements of unstructured blocks which the
H-grid will develop for us.
41:07.520 --> 41:13.550
These are two examples of typical J-grid and
H-grid topologies and why is it called J-grid
41:13.550 --> 41:20.550
because you can see that this resembles a
J and that is why there is a set of elements
41:21.050 --> 41:28.050
which are resembling the symbol J. So, you
can see a J here, this way and the J as I
41:29.260 --> 41:34.350
mentioned would be in opposite orientation.
So, at the trailing edge it is in this direction.
41:34.350 --> 41:40.320
So, this is a typical J-grid topology and
on the right hand side you have an H-grid
41:40.320 --> 41:46.100
topology.
So, H is resembling the letter H and so, this
41:46.100 --> 41:52.790
is basically an H-grid topology and as I mentioned
H-grid topology may lead to some amount of
41:52.790 --> 41:58.590
unstructured elements towards the leading
edge and trailing edges on account of the
41:58.590 --> 42:04.770
topology itself. So, if you had introduced
yet another block here that would become a
42:04.770 --> 42:11.650
J-grid and then you may not require this unstructured
block which are present here and all these
42:11.650 --> 42:16.300
are in conjunction with an O-grid, you can
see the O-grid right around the blade in both
42:16.300 --> 42:23.010
J-grid as well as H-grid topology, one can
see the O-grid right along the blade surface.
42:23.010 --> 42:29.910
So, most these topologies are usually used
in conjunction with an O-grid topology because
42:29.910 --> 42:35.460
O-grid is some which gives you control over
the boundary layer resolution or the grids
42:35.460 --> 42:40.930
around blade surface which is where the boundary
layer is one would like to capture that to
42:40.930 --> 42:46.040
the best possible extent and so, O-grid gives
you the flexibility.
42:46.040 --> 42:52.370
There are other forms of grids which are also
sometimes used the C-grid or the L-grid and
42:52.370 --> 42:57.490
irrespective of what gird is been used whether
it is J-grid, O-gird, C-grid or L-grid. There
42:57.490 --> 43:03.260
are all used in conjunction with an O-grid
for good resolution of the boundary layer
43:03.260 --> 43:10.260
and it is also necessary that resolve the
leading and trailing edges very well, because
43:10.430 --> 43:15.990
the leading and trailing edges one has a very
sharp in a let us say high speed compressor
43:15.990 --> 43:20.510
blades the leading and trailing edges can
be relatively quite sharp at a radius radii
43:20.510 --> 43:25.570
at leading and trailing edges could be very
small resolving these edges are very important
43:25.570 --> 43:31.330
because performance of the whole compressor
is a function also a function of the leading
43:31.330 --> 43:36.060
and trailing edge radii.
Now, irrespective of what kind of grid we
43:36.060 --> 43:43.060
use or which application is to be used for
one needs to establish that the grids or the
43:43.410 --> 43:48.380
solutions that you get from the computations
are independent of the grid sizes that is
43:48.380 --> 43:53.580
if you use 1 million cells or 10 million cells
is there is a difference in solutions then
43:53.580 --> 43:59.200
which one do you believe one would want to
believe which has more number of cells. So,
43:59.200 --> 44:06.200
it is a common practice now standard practice
now to establish the grid-insensitivity or
44:06.200 --> 44:11.640
grid-independence of any simulation.
So, one needs to demonstrate that as you change
44:11.640 --> 44:16.980
the number of grids from certain number to
the double that number or half the number,
44:16.980 --> 44:22.100
the number of the depending upon how many
numbers you have changed the solution should
44:22.100 --> 44:28.080
not be dependent on the number of grids that
you are using, and therefore one would of
44:28.080 --> 44:33.060
course, like to optimize between number of
cells used and the best possible solution
44:33.060 --> 44:39.020
and that is where one would want to do a grid
sensitivity analysis and establish that the
44:39.020 --> 44:45.860
number of grids you are using for analysis
is optimum and the solution for that particular
44:45.860 --> 44:52.860
number of grids and anything above that would
remain the same. So, one needs to establish
44:53.070 --> 44:57.880
grid-independence irrespective of what kind
of topology are you using.
44:57.880 --> 45:03.980
And let us take a look at 2 other grid topologies
the L-grid and C-grid. This is the L-grid
45:03.980 --> 45:10.610
topology very similar to a J-grid, but just
that in a J-grid one had a section here and
45:10.610 --> 45:16.150
this is basically the L-grid topology that
you can see and this is a typical C-grid topology
45:16.150 --> 45:21.200
you can see that unlike the multi-block here
multiple number of blocks here you have only
45:21.200 --> 45:27.550
2 blocks which have been provided and this
is the typical C shape that you get and that
45:27.550 --> 45:32.220
is why it is called a C-grid topology.
So, which topology to use basically depends
45:32.220 --> 45:37.030
upon the application and there are certain
standard thumb rules which are available which
45:37.030 --> 45:43.050
can help an analyst making a decision on which
kind of topology that he needs to use for
45:43.050 --> 45:50.050
his application. So, I did not understood
some elements of grid and grid generation.
45:50.080 --> 45:55.760
Let us look at the other aspect of starting
the simulation that is basically the boundary
45:55.760 --> 46:01.790
conditions. Boundary conditions are; obviously,
extremely important for a particular solution
46:01.790 --> 46:08.280
and its accuracy because the solution primarily
depends upon what kind of boundary conditions
46:08.280 --> 46:11.660
you are setting.
So, depending upon a different set of boundary
46:11.660 --> 46:18.250
conditions the solutions can entirely be different.
For example, if you look at a compressor operation,
46:18.250 --> 46:24.600
if you set the design boundary conditions
right one can get the design operating conditions
46:24.600 --> 46:28.700
or simulations for that operating conditions,
but if you get the design operating or the
46:28.700 --> 46:34.460
boundary conditions which lead towards compressors.
So, as then the solutions are entirely different
46:34.460 --> 46:39.100
from what it should have been, and therefore
to get the correct flow physics and to be
46:39.100 --> 46:45.670
able to make sense out of the simulations
one needs to ensure that the boundary conditions
46:45.670 --> 46:47.840
are set correctly.
46:47.840 --> 46:53.960
So, basically boundary conditions are essential
in capturing the flow physics correctly and
46:53.960 --> 46:58.440
appropriately and; obviously, the quality
of the solution that you get is a very strong
46:58.440 --> 47:04.490
function of the boundary condition itself.
In a turbo machinery flow, there are of the
47:04.490 --> 47:10.610
4 distinct types of boundaries that one would
encounter. The inlet boundary from which the
47:10.610 --> 47:16.970
flow begins or initiates, the exit boundary
that is at the outlet of the flow domain,
47:16.970 --> 47:23.970
periodic boundary on 2 sides of the domain
and walls or surfaces which could be the blades
47:24.270 --> 47:26.800
could be the hub or the casing.
47:26.800 --> 47:33.310
So, this is the typical flow domain with the
boundaries I have shown. This is compressor
47:33.310 --> 47:38.800
blade here we have a low speed compressor
blade the flow enters through the blade domain
47:38.800 --> 47:43.200
and here we have seen relating only one blade
and since all the blades are identical we
47:43.200 --> 47:47.510
will have to set what are known as the periodic
boundary conditions.
47:47.510 --> 47:52.040
So, this is the inlet domain that you can
see here as the inlet, this is the hub surface
47:52.040 --> 47:59.040
of the of the blade and this is the shroud
of the tip. The flow enters through the domain
48:00.070 --> 48:06.030
here and then it exits through the outlet
which is shown here in an orange and this
48:06.030 --> 48:11.550
is known as the outlet domain and on the sides
of the blade we have what is known as periodic
48:11.550 --> 48:16.480
boundary conditions which means that whatever
happens here will be a reflection of what
48:16.480 --> 48:23.480
should he happening even if they work in number
of other blades it around it and the periodic
48:23.950 --> 48:29.290
boundary walls will depend upon the number
of blades basically depending upon the solidity
48:29.290 --> 48:33.520
itself, if you have more number of blades
then these boundaries would come closure.
48:33.520 --> 48:38.640
In this particular domain, this is the domain
which rotates and these are the 2 domain that
48:38.640 --> 48:43.260
is the inlet and outlet domains are the one
which are stationary. The rotor domain is
48:43.260 --> 48:45.060
the one which rotates.
48:45.060 --> 48:51.330
So, if you have to set inlet boundary conditions
it; obviously, depend upon the application
48:51.330 --> 48:57.440
itself which depends upon the flow conditions
whether it is incompressible or compressible,
48:57.440 --> 49:04.040
the most commonly used boundary condition
for the inlet is this a set of predefined
49:04.040 --> 49:10.010
total pressure at the inlet, total temperature
and the velocity components or profile at
49:10.010 --> 49:13.720
the inlet.
So, this is most commonly used form of inlet
49:13.720 --> 49:19.960
boundary conditions which are applied in a
standard CFD solution for compressor or turbine
49:19.960 --> 49:24.130
flows. There are other forms of specifying
boundary conditions it could be velocity inlet
49:24.130 --> 49:30.280
which if it is very low speed in compressible
flow, one might even want to specify just
49:30.280 --> 49:37.280
velocity inlets or a mass flow inlet and there
are these are not generally used because there
49:37.690 --> 49:43.210
are lot of limitations with specifying this
as compared to the total pressure, total temperature
49:43.210 --> 49:50.210
velocity components because that is specifying
velocity or mass flow rate alone is too simplistic
49:51.540 --> 49:56.650
boundary condition to be applied which probably
is or simple two-dimensional analysis if you
49:56.650 --> 50:03.650
one would carrying out that, but not generally
used for series serious high and CFD dissimulations.
50:05.500 --> 50:09.980
Similarly at the exit, one needs to specify
a set of boundary conditions.
50:09.980 --> 50:13.940
Now here again there are different ways of
specifying boundary conditions, most commonly
50:13.940 --> 50:20.260
used are either static pressure which can
for a given inlet pressure give you a certain
50:20.260 --> 50:25.000
amount of mass flow rate. The other boundary
condition that one could use is mass flow
50:25.000 --> 50:31.550
rate itself and for low speed incompressible
flows whether you specify a static pressure
50:31.550 --> 50:36.490
or mass flow rate the results are not going
to be highly different and they are not very
50:36.490 --> 50:41.720
sensitive to this boundary condition, but
for high speed compressible flows specifying
50:41.720 --> 50:47.130
static pressure at the exit is the standard
practice and one would and also it this is
50:47.130 --> 50:52.730
a common practice even now used for low speeds
simulations it has been sort of establish
50:52.730 --> 50:58.380
that a specifying static pressure is probably
a better way of defining mass flow rate at
50:58.380 --> 51:04.800
the exit of the domain. So, one could specify
either static pressure at the exit or just
51:04.800 --> 51:08.340
the mass flow rate itself
51:08.340 --> 51:13.670
and but I say I mentioned for low speed incompressible
flow it should not really matter whether you
51:13.670 --> 51:20.670
are specifying static pressure or mass flow
rate and it is also possible that one can
51:21.280 --> 51:26.690
specify a static pressure distribution at
the exit rather than just an average static
51:26.690 --> 51:32.420
pressure, one may also want to be a little
more accurate, one can simulate a static pressure
51:32.420 --> 51:35.640
distribution as well at the exit.
51:35.640 --> 51:41.240
Now, for single passage simulation like the
one I have just showed periodic boundaries
51:41.240 --> 51:47.640
are used for simulating the effect of a blade
row and it is necessary that one appropriately
51:47.640 --> 51:54.640
chooses this domain, so that periodic or periodicity
is indeed valid. And on the surfaces like
51:55.120 --> 52:01.770
the blade or the hub or the shroud it the
standard boundary conditions like no-slip
52:01.770 --> 52:07.660
and adiabatic conditions are used.
But if you look at a turbine flow which has
52:07.660 --> 52:14.660
hot gases present if you are also simulating
the hot gases effect in a turbine flow instead
52:14.660 --> 52:20.090
of adiabatic condition one may replace that
with a constant heat flux condition . So,
52:20.090 --> 52:25.550
these are the two periodic conditions that
I mentioned and selecting this is very important
52:25.550 --> 52:30.880
because this basically represents the solidity
of the compressor itself and it simulates
52:30.880 --> 52:37.650
the curvature on either sides of the blades.
So, these are the different types of boundary
52:37.650 --> 52:43.360
conditions that one can simulate, one can
actually one needs to specify at the inlet
52:43.360 --> 52:50.360
exit and the side walls and surfaces to be
able to simulate the performance and flow
52:51.150 --> 52:57.760
conditions and flow physics run correctly.
So, let me now quickly recap our discussion
52:57.760 --> 53:04.760
in today's lecture and we had a very quick
discussion on CFD in general, this is as I
53:06.140 --> 53:11.080
mentioned in the beginning this assuming that
you have some knowledge of CFD already and
53:11.080 --> 53:16.630
so, we are trying to look at CFD in general,
but we are trying to understand aspects of
53:16.630 --> 53:23.630
CFD in in the context of turbo machine flows
and in that context I mentioned about two
53:23.740 --> 53:29.410
distinct aspects today that is the challenges
involved in grid generation to which I also
53:29.410 --> 53:36.380
explained the different types of grids that
are possible for a turbomachinery blade simulation
53:36.380 --> 53:42.010
and the key challenges involved in grid generation.
Subsequently we also discussed about boundary
53:42.010 --> 53:47.180
conditions and the right way of setting boundary
condition for turbo machinery flow simulations.
53:47.180 --> 53:52.340
So, we will continue discussion on some of
these aspects in next the couple of lectures
53:52.340 --> 53:57.760
as well in the next lecture I intend to introduce
a few other challenges which are involved
53:57.760 --> 54:04.760
in turbo machinery flow simulation to do with
basically the turbulence modeling and associated
54:04.800 --> 54:09.220
problems are shown with turbulence modeling
and why is it necessary that we use the right
54:09.220 --> 54:15.810
model for a set of problems that we are trying
to analyze. So, we will take up a few of these
54:15.810 --> 54:21.810
aspects in the next two lectures that we would
going to have on CFD as applied for turbo
54:21.810 --> 54:28.050
machinery flows and next lecture we will take
up some more challenges which are specific
54:28.050 --> 54:34.330
for turbo machinery CFD. So, we will take
up some of these topics for discussion in
54:34.330 --> 54:37.170
the next lecture which would be lecture number
39.