2.5.3. Post-Processing

So, after the solution is solved, there is post processing, is after the results are obtained, we have to show it graphically or we have to find some values we have to interpret those results that we got in most of the cases plotting the results is termed as post processing.

Post-processing refers to the actions taken after computational fluid dynamics (CFD) simulations are completed. This phase involves analyzing and visualizing the results of the simulation. The primary goal of post-processing is to interpret the computed data and present it in a way that makes it understandable. This often includes creating graphs, charts, or animations that depict how the fluid behaves under various conditions. Without post-processing, the raw data generated by CFD simulations would be challenging to interpret and use effectively.

Imagine you just baked a cake using a new recipe, and now you want to share it with your friends. Simply showing them the ingredients isn't enough; you need to cut a slice, present it nicely on a plate, and maybe even describe the flavor. Post-processing in CFD is similar; it's about taking the numerical results and making them presentable and meaningful, allowing observers to 'taste' the results of the simulations.

Defining the geometry and the discretization of the domain, these 2 things are called preprocessing. So, something that you have to do before the calculation can begin in the computer, all right. And the post processing is something that you have to do after the calculations have something to be done with the results after calculations have finished whereas preprocessing steps to be completed before the calculation can begin on computer.

Preprocessing and post-processing are two essential phases in the CFD workflow. Preprocessing involves preparing the model for simulation. It includes defining the geometry of the flow, creating a mesh (discretization of the domain), and setting up initial and boundary conditions. This preparation is crucial for ensuring that the simulation reflects the real-world scenario accurately. On the other hand, post-processing is focused on analyzing the results after the simulation has been run. This step is about creating visual representations of the data, such as velocity fields, pressure distributions, and other relevant metrics to help understand the flow patterns.

Think of a scientist conducting an experiment. Before starting, they must prepare the equipment (preprocessing) by gathering materials and calibrating instruments. After the experiment concludes, they analyze the results, perhaps creating graphs or reports to summarize findings (post-processing). Just like in science, both stages are crucial for a successful CFD analysis.

So now as we said that the first step is defining the geometry. So, this step includes the creation of a CAD model what is CAD computer aided design. So, you use some software is are there are even tools available within the computational fluid dynamics models where you can define the geometry or derive for example, suppose for example, there is a tank right and there is a pier. And you have to and this is open no I am just drawing it in 2d assume it is 3d and flow is coming through this right.

Defining the geometry is a critical step in both preprocessing and post-processing of CFD. It involves creating a detailed Computer-Aided Design (CAD) model that accurately represents the physical system being studied. This model defines the shape, size, and boundaries of the domain where fluid flow will be analyzed. The geometry directly impacts how the flow is simulated and, consequently, how the results are interpreted in the post-processing phase. Accurate geometry ensures that the fluid interactions and flows are modeled appropriately, which is essential for reliable analysis.

Consider an architect designing a building. They create detailed blueprints that outline the dimensions and layout of each room. Without these blueprints, the construction workers wouldn't know how to build the building accurately. Similarly, in CFD, the geometry acts as the blueprint for the simulation, dictating how the fluid will behave around the obstacles and structures defined in the model.

So, the second step was discretization of the domain. So, this process is known as grid generation or mesh generation. So, the process this particular process of discretization involves developing a set of algebraic equations based on discrete points in the flow domain to be used in place of partial differential equations.

Discretization of the domain, often referred to as grid or mesh generation, is an essential step in preparing the model for CFD analysis. During this phase, the continuous domain of fluid flow is divided into smaller, manageable elements or cells. Each cell will represent a specific portion of the flow, and the governing equations will be solved over these discrete points. This allows for the approximation of complex flow phenomena by breaking it down into simpler, solvable parts.

Think of discretization as slicing a pizza into pieces. A whole pizza represents a continuous domain, but when you slice it up, each piece becomes easier to handle, and you can distribute it to different people for consumption. In CFD, discretizing the flow domain allows us to tackle complicated flows piece by piece, improving our ability to analyze and understand the behavior of the fluid.

So, the most common discretization techniques available for the numerical solution of partial differential equations are the finite difference method, finite element method, and finite volume method. So, we will go into small details of this, so that you have a broader idea.

There are three prevalent techniques for discretization when working with partial differential equations in CFD: the finite difference method, the finite element method, and the finite volume method. Each method has its unique approach to breaking down equations into solvable algebraic forms. The finite difference method approximates derivatives using discrete points, while the finite element method divides the domain into smaller elements and derives equations for each element. The finite volume method, on the other hand, focuses on the integral form of the equations over discrete volumes, which is favorable for conservation laws. Understanding these techniques allows engineers to select the most appropriate method based on their specific fluid dynamics problems.

Imagine you are trying to compute the speed of a river. You could either measure the speed at various discrete locations along the river (finite difference), use sections of the river to see how much water flows past a certain point (finite volume), or create little sections of the riverbed and calculate the speed for each section as a whole (finite element). Each provides valuable insights, and choosing the right method depends on the scenario you are studying.

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