Section all recorded, and the results were compared

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Last updated: May 19, 2019

Section A: Introductionto CFDExistenceof modern technologies had eased the application of science for humans. Withprogression of computational performance, Computational Fluid Dynamics (CFD)software was introduced to the modern society to study on flow of fluid withoutany physical subject to be tested on. This software was implemented to a widevariety of industries which includes automotive, aerospace, astrophysics,chemical manufacturing and power generators. Before the introduction of CFD,researchers had to rely solely on their knowledge of mathematics and fluidmechanics to estimate an outcome of fluid flows.

While the software is of aidto modern society, CFD would need a computer to process its simulation and dataretrieval of the desired simulation. Therefore, a substantial amount ofcomputational performance was needed to ensure the data was processed quicklyand accurately to meet current industries standard of efficiency.CFDsoftware is a tool where knowledge of fluid mechanics, mathematics and computerscience were applied in simulating a fluid flow motion.

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These motions arederived by mathematical equations and represented in computer programminglanguage only readable by computers. The results were then converted to quantifiabledata that is displayed in readable human language. During the simulation inCFD, all progress was predicted using numerical data as from derivation fromall available mathematical equations in fluid dynamic flow.Whilefluid is solved in mathematical solutions, there are still fundamental stepsrequired to be obeyed.

(Fawehinmi et al., 2005). There are threemethods in this problem solving through Experimental, Analytical andComputational solving where data are validated. Back when there is nocomputational aid such as CFD, Experimental solving uses a more tedioustechnique which is to build a scaled down replica model representing the realobject of study and the flow properties are to be measured and recorded. Thistechnique is frequently used, where experimental data were all recorded, andthe results were compared to theoretical values derived from mathematicalequations from fluid dynamics. It is different from Analytical solving asanalytical does not require any physical model to obtain theoretical data.

Themethod involved for analytical is by comparing measurements of the desired objectof study in mathematical modelling to related equations from equations of fluiddynamics. But Analytical solving applies to a limited number of simplified flowgeometries. There were recorded errors from the above methods of solving whichleads to search for improvement in error reduction while accurately obtainresults subjected to fluid dynamics. Throughyears of testing and perfecting, CFD software is now able to display resultsaccurately while having little to no error. It applies to any fluid flow, be itsimple or complex fluid flow.

With such accuracy, computational solving methodhad to be ideal choice of studying fluid flow problems as the results were morereliable albeit the other methods, Experimental and Analytical solving approachwere still being used. Fluidflows are controlled and influenced by partial differential equations that isrepresented by laws of Conservation of Mass, Momentum and Energy. CFD uses theabove governing equations and below represented by following Navier-Stokes equationsbased from conservation laws:a)     Conservationof Mass (from continuity equation)  b)     Conservationof Momentum (from Momentum equation)  Where;  i:    Local change of timeii:   Momentum convectioniii:  Surface forceiv:  Molecular-dependent momentum exchange(diffusion)v:   Mass force c)     Conservationof Energy (from Energy equation)   Where;i:    Local energy change with timeii:   Convection termiii:  Pressure workiv:  Heat flux (diffusion)v:   Irreversible transfer of mechanical energy intoheatWhen all theconservation equations were applied to Navier-Stokes equation, the followingsimplified general form is formed:  SinceCFD was used due to its high efficiency and low risks, it also improves safetywhile saving on production costs. An example would be the use of wind tunnel todetermine efficiency of a car model cutting through the air (fluid flow) willincrease costs in Research and Development sector of a company. By using CFD asthe base to study fluid flow on the desired model, less electricity would beused on simulation compared to a physical wind tunnel. Costs of material willalso be saved since no models were needed and changes to the car model toimprove efficiency and performance can be done without wastage of anymaterials. Besides that, CFD was also to be used in ensure minimal losses inpiping by simulating the pipe designs with different angles to reduce losses atbends of pipe, attachment of valves, taper and other pipe attachments. (Gabryjonczyk, 2013).

Therefore, this CFD software can solve many fluid problems, preventing designfailure while ensuring safety of its design for prototype or production models. Hereis the order of the process of CFD software based from the 5th slideof (Choudhary, 2015):  Figure 1: Flow chart ofComputational Fluid Dynamics Thecycle of CFD is not that complex to understand to begin with as it all beginswith the problem related to fluid where humans tend to solve from theirknowledge of Fluid Mechanics. This data is then brought into Navier-StokesEquations to determine the nature of the flow.

This data is then translatedinto Discretized Form as a computer only understood programming language. Inthis form, the computer can analyse and compute the entered data, Grid by Gridfor each mesh on the model. After the meshing process, simulation is executedto show every result obtained from fluid flow. The results are then convertedfrom programming language to human language for quantifying and displayed foruser to compare and analyse the data. 

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