Understanding CFD Simulation Process with Exampleslearncax.com /blog/2012/12/07/understanding-cf d-simulation-process-with-examples/

Ganesh Visavale

Having already explained the background & evolution of Computational Fluid Dynamics (CFD) in the earlier blogIntroduction to CFD, let us now try to understand the CFD simulation process with a few examples.

Computat ional Fluid Dynamics (CFD):

Def ining CFD : CFD is the science of predicting fluid flow, heat transfer, mass transfer, chemical reactions, and relatedphenomena by solving the mathematical equations which govern these processes using numerical methods (i.e., on acomputer). Thus it provides a qualitative and quantitative prediction of fluid flows by means of:

mathematical modeling (partial differential equations)

numerical methods (discretization and solution techniques)

software tools (solvers, pre- and postprocessing utilities)

Simulat ion Process:

To understand the simulation process and the steps involved in it let us consider an example of a flow through apipe bend. The figure below gives series of the steps that would be involved in its analysis. For a fluid flow through apipe bend we have the geometry built up, segregated into smaller fragments/ segments, called a mesh. With thismesh we actually define our probe-points where we want the analysis to be done. We then define the boundaryconditions to get a unique solution solving it with a computer. The results obtained gives us a lot of data along theseprobe points that are then post-processed with visualization tools to analyse the results.

Thus CFD process in overall is a 3 step procedure:

1. Pre Processing: This step consist of defining a geometry to define our domain of interest. The domain ofinterest is then divided into segments, called as mesh generation step and the problem is set-up defining theboundary conditions. Gridgen, CFD-GEOM, or ANSYS Workbench Environment & Modules, ANSYS ICEMCFD, TGrid etc., are some of the popular pre-processing softwares.

2. Solver : Once the problem is set-up defining the boundary conditions we solve it with the software on thecomputer, (can also be done by hand-calculations, but would take long time). We have different popular

commercial softwares available for this like Star-CD and Star CCM+ (CD-Adapco), FLUENT and CFX (ANSYS,Inc), GASP (Aerosoft, Inc), CFD++ (Metacomp Technologies) etc. Also there are free to use softwares likeOpenFOAM, CFL3D, Typhon, OVERFLOW, Wind-US etc, all with different capabilities. These softwares arecapable of solving the equations at every probe-point defined during the mesh generation step and also wecan include additional models as required by the physics. The numerical methods are also defined at the thisstage and we solve the whole problem.

3. Post-processing: Once we get the results as values at our probe points we analyse them by means of colorplots, contour plots, appropriate graphical representations & can generate reports. Tecplot 360, EnSight,FieldView, ParaView, ANSYS CFD-Post etc., are some of the popular post processing softwares.

How CFD Works ?

Now let us try to analyze a real life problem, with 2 examples discussed below.

Test Case: Fin-Tube Heat Exchanger

A Fin-Tube Heat ExchangerThe above image is of a fin- tube heatexchanger typically used for transferringheat in radiators in automobiles or inhousehold applications (in cold countrieswhere room heating is essential). In thiswe have cold/ hot fluid being pouredthrough these tubes and other fluid(air/water) flowing over the tubes.

Domain of Interest: Area between two finsNow looking at the geometry, it can be seen that the fin tube heat exchanger is a cascade of a large number of finsattached to the tubes and thus seems to be a complex problem. However in CFD analysis of the fintube heatexchanger, the problem can be simplified to a great extent by identifying our domain of interest and considering onlya small section of the it (as above). Simplifying assumptions are made in order to make the problem tractable (e.g.,in this case: steady-state, incompressible, inviscid, two-dimensional). Also for solving the problem we consider theconservation of mass, momentum and energy as is required in the study. In pre-processing step we take thegeometry and divide it into smaller fragments as in figure below, called meshing or the grid generation step.

Thus as the geometry is discretizedso are the equations (as above) ateach cell which on solving gives usthe values that is obtained in the formof colorful contour plots using thevisualization techniques that can giveus a very good insight to locate thehot- spots, recirculation, & deadzones. So its not only the qualitativedepiction of values that we generatebut also the quantitative data (fromfigure we can see temperature varyingfrom 464 K to 361 K) that can help usanalyze the overall flow phenomena.Also if you see the regions betweenthe fins as in figure below, it is clearthat there is rapid fall in temperaturefrom the base (hot region) to the topas is typically encountered with fluegases.

Water flow over a tube bank

Consider the analysis of a cascade of tubes placed inside a domain across which a fluid (water) is flowing. Theobjective here is to compute average pressure drop and heat transfer per tube row. So it is a physical system inwhich we have a complicated setup of several cascade of tubes. To start with, we shall not proceed to solve thereal problem but would try to simplify it taking a section for analysis, set-up the problem, first gain confidence over itand then if the computational resources are available and if time permits, proceed to implement on the real problem.

cascade

Assumptions

flow is two-dimensional, laminar, incompressible

flow approaching tube bank is steady with a known velocity

body forces due to gravity are negligible

flow is translationally periodic (i.e. geometry repeats itself)

As can be seen from the discretized geometry above, we have a fine mesh size at near the wall of the tubes andcoarser at the other regions, so as to resolve the boundary layer flow at these regions. We have a whole systembeing modeled as we set up the problem on a software for example, Fluent as in figure below. In the solver weimport the mesh, select the appropriate solver methodology, define operating conditions (no-slip, Qw or Tw atwalls), initialize and iterate to get a converged solution.

Once the problem is solved we can have results as in figure below. It shows contours of temperature around thetubes. As seen, the regions near the tube wall have re-circulation zones as a result of which there is a heat built- up

(red color) also shown by color variations. So we see that we can have a very nice depiction of real life situationthrough a simple 2-D analysis.Also you can analyse a case wherein you have flow over a singletube with a obstruction- free region ahead, as in figure below. Thefigure shows the analysis for a typical phenomena called vortexshedding typically encountered in cases of flow around tubesbecause of which a familiar process called the von Karmanvortices are generated. The tube encounters a lot of lift force thatis sinusoidal in nature. The plot of time versus lift force clearlyshows a sinusoidal nature in an analysis performed in ANSYSCFX.

Thus with a few real life problems we have tried to understand theCFD simulation process.

Coming up next : Why CFD project as your MS thesis can help you inlong term ?

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