**For exclusive (professional) use of CFD with large amounts of mesh elements**

If we dedicate ourselves daily to develop simulations of CFD using any software (commercial or free) we need a good workstation that allows us long hours of work (computer on 24/7); in these cases we need a server processor for example Intel XEON or AMD EPYC (latest series), although they do not have a high frequency in GHz, these processors have a large bandwidth which allows avoiding “bottlenecks” (which happen with Ryzen processors or I7, I9) in simulations with large mesh elements, in addition these processors are prepared to be running continuously. It is ideal to install 02 processors on a single board because we can scale the performance. Regarding the graphics card is important to choose an Nvidia QUADRO, these cards are also designed to support long hours of work and also allow a better visualization of 3D objects, if you have that card we added an NVIDIA TESLA V100 have for sure that You will have the best worksation of the market. The costs of assembling one of these computers is very high.

2.** For CFD sharing with other Render applications, games, etc.**

If we develop simulations with mesh elements smaller than 8 MM and we use other softwares such as Blender, 3DMax, Autodesk Inventor, Solidworks where we need to render, we can select a Ryzen Threadripper processor or an i7 or i9, these processors are multi-threaded (multi-threaded) threading) which allows other tasks to be done in parallel, however this option does not serve to develop CFD simulations (in other blog we will explain why), these processors do not allow to scale (put 02 processors in a single board) although its great advantage in The high clock frequency, are very useful for simulations with few mesh elements. Regarding the graphics card we can select an NVIDIA QUADRO although with the NVIDIA Geforce RTX also work well, with the latter you can use your workstation for high-end games.

3.** For practice and learn CFD, making eventual use of the computer**

If you are starting in the world of CFD and do not want to invest too much you can opt for “economic” processors that will allow you to develop smaller simulations of 1MM mesh elements without problems, 4-core processors are more than enough with NVIDIA Geforce GTX video cards.

Here we share a video of an assembly of a workstation with a processor RYZEN Threadripper 2950x of 16 cores (32 threads) with an NVIDIA GEFORCE RTX 2060 video card.

]]>Therefore we decided to do a test with some forms of mesh elements and thus observe the variation of results and the calculation time that takes in each case. We use mesh elements in three dimensions with ANSYS CFX and ANSYS FLUENT (later we will do more tests with identical meshes using other CFD software).

We observe that the polyhedral mesh is the one that contains a smaller number of elements but a larger number of nodes, unlike the tetrahedral mesh, this as we will see in the following tables of results directly affects the calculation time.

For the created model, the elements in the polyhedral mesh are reduced to less than 50% compared to the tetrahedral mesh. The combination of a hexahedral and prism mesh is in an intermediate-term keeping their values of nodes and elements close.

**Case analyzed:**

Simulation of a phase (water) in a pipeline, with activation of energy using the k-epsilon turbulence model considering an inflation in the walls.

**Types of mesh:** Tetrahedral, Hex / Prism and Polyhedral

To observe the differences between the meshes you can see the following video:

**Results:**

We observe that the polyhedral mesh is the one that contains a smaller number of elements but a larger number of nodes, unlike the tetrahedral mesh, this as we will see in the following tables of results directly affects the calculation time.

For the created model, the elements in the polyhedral mesh are reduced to less than 50% compared to the tetrahedral mesh. The combination of the hexahedral and prismatic mesh is in an intermediate-term keeping their values of nodes and elements close.

The results of the physics of the problem (temperature and velocity) at the outlet of the pipe are very similar for all cases, however, the distribution of temperatures and speeds is slightly different in the polyhedral meshing, you can see the video again (shown above ) and see this point in more detail.

Regarding the difference between the software used (CFX and FLUENT) we note that CFX obtains results in smaller iterations (we did not modify the residues of the convergence, these default values were maintained for both software), however, the calculation time in CFX is much smaller with the tetrahedral mesh and the combination of hexahedral and prismatic; up to this point CFX for a great alternative to reduce computational time but the polyhedral mesh (which can only be generated in ANSYS FLUENT) decreases the calculation time radically.

Therefore from this small test, we can give some scopes as seen.

- The elements of the mesh are those that define the dependence of the calculation time.
- The polyhedral meshing gives a shorter calculation time compared to other mesh types.
- The physical results of the polyhedral mesh are similar to the other mesh types analyzed in this test.

**Recommendations**

- To know the error of the results, it is necessary to validate the simulation with an experimental test that allows us to know what type of mesh is the most appropriate.
- We can not conclude with this test that one software is faster than another, this has only been a case in a single phase, it is likely that by adding more variables or changing the turbulence model, the results obtained will vary.

Hoping that these results can be helpful, we invite you to subscribe to our YouTube channel: CFD.NINJA where you will find varied information and CFD tutorials.

If you want to know how to generate a polyhedral mesh you can see this tutorial:

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Certainly, the question has no handle, I have always believed that all software is good (considering that they have the same simulation capabilities) and those who are wrong are us, the users. This led me to perform a simulation of a rectangular weir in ANSYS CFX and OpenFOAM considering the same mesh, identical border conditions and the same number of processors; and here are the results, watch the video.

The simulation times are very similar, the flow behavior is almost the same (I used the K-Epsilon turbulence model), to say that one CFD software is better than another is an error. Although many opt for ANSYS, Flow 3D, Abaqus, etc. for various reasons such as; more information, recognized support, lots of tutorials, varied training, etc. The high licensing costs make it not feasible to develop medium and small-scale projects, for that reason I am starting to love OpenFOAM because there is something that makes it unique compared to all commercial software, it is that OpenFOAM is free. You will tell me but OpenFOAM is more difficult to learn, it is true, and that is why the pleasure of obtaining the results is much more rewarding.

]]>Source: NASA

During the late 1920s and into the 1930s, the NACA developed a series of thoroughly tested airfoils and devised a numerical designation for each airfoil — a four digit number that represented the airfoil section’s critical geometric properties. By 1929, Langley had developed this system to the point where the numbering system was complemented by an airfoil cross-section, and the complete catalog of 78 airfoils appeared in the NACA’s annual report for 1933. Engineers could quickly see the peculiarities of each airfoil shape, and the numerical designator (“NACA 2415,” for instance) specified camber lines, maximum thickness, and special nose features. These figures and shapes transmitted the sort of information to engineers that allowed them to select specific airfoils for desired performance characteristics of specific aircraft.

You can review these tutorials using ANSYS CFX and ANSYS FLUENT

- ANSYS CFX – NACA 4412 – Unstructured Mesh
- ANSYS CFX – NACA 4412 – Structured Mesh
- ANSYS CFX – NACA 0012 with angle of attack
- ANSYS FLUENT – NACA 4412 – Unstructured Mesh

Recent airfoil data for both flight and ‘wind~tunnel tests have been collected and correlated insofar as possible. The flight data consist largely of drag measurements made by the wake survey method. Most of~he data on airfoil section characteristics were obtained in the Langley two-dimension allow turbulence pressure tunnel. Detail data necessary for the application of NACA 6~series airfoils to wing design are presented in supplementary figures, together with recent data for the NACA 00-, 14-, 24-, 44-, and 230-series airfoils. The general methods used to derive the basic thickness forms jor NACA 6- and 7 -series airfoils and their corresponding pressure distributions are presented. Data and methods are given for rapidly obtaining the approximate pressure distributions For NACA four digit, five-digit, 6-, and 7-series airfoils. The report includes an analysis of the lift, drag, pitching moment, and critical speed characteristics of the airfoils, together with a discussion of the effects of surface conditions. Data on high-lift devices are presented. Problems associated with lateral – control devices, leading-edge air intakes, and interference are briefly discussed. The data indicate that the effects of surface condition on the lift and drag characteristics are at least as large as the effects of the airfoil shape and must be considered in airfoil selection and the prediction of wing characteristics. Airfoils permuting extensive laminar flow, such as the NACA 6-series airfoils, have much lower drag coefficients at high speed and cruising lift coefficients than earlier types of airfoils if, and only if, the wing surfaces are suffic1~ently smooth and fair. The NACA 6-scries airfoils also have favorable critical-speed characterIstics and do not appear to present 1Lnu8ual problems associated with the applicatIon of high-lift and lateral – control devices.

]]>**Author: ***Bjorn Sjodin is VP of Product Management for COMSOL Inc.*

**How would you define the finite-element method?**

The finite-element method is a computational method that subdivides a CAD model into very small but finite-sized elements of geometrically simple shapes. The collection of all these simple shapes constitutes the so-called finite-element mesh.

The next step is to take a system of field equations, mathematically represented by partial differential equations (PDEs) that describe the physics you are interested in, and formulate these equations for each element. This is handled by approximating the fields within each element as a simple function, such as a linear or quadratic polynomial, with a finite number of degrees of freedom (DOFs). This gives an approximate local description of the physics by a set of simple linear (but sometimes nonlinear) equations. When the contributions from all elements are assembled you end up with a large sparse matrix equation system that can be solved by any of a number of well-known sparse matrix solvers.

The type of solver used depends on the original physics, since each type of physics gives its unique imprint on the structure of the matrix. To speed things up, this structure is exploited by using a tailored numerical method. A method may be suitable for structural mechanics but not for electromagnetics, and vice versa. Historically, the method was first applied to structural analysis. Over the last ten years or so, it has been realized that the finite element method is also suitable for a large class of multi-physics problems.

**How would you define the finite-difference method?**

The finite-difference method is the most direct approach to discretizing partial differential equations. You consider a point in space where you take the continuum representation of the equations and replace it with a set of discrete equations, called finite-difference equations. The finite-difference method is typically defined on a regular grid and this fact can be used for very efficient solution methods. The method is therefore not usually used for irregular CAD geometries, but more often for rectangular or block-shaped models.

There is a connection with the finite-element method: Certain formulations of the finite-element method defined on a regular grid are identical to a finite-difference method on the same grid. Regular grids can often be used in meteorological, seismological, and astrophysical simulations, for example.

**How would you define finite-volume method?**

The finite-volume method is similar to the finite-element method in that the CAD model is first divided into very small but finite-sized elements of geometrically simple shapes. Apart from this, the finite-volume method is very different from the finite-element method, beginning with the concept of elements, which are instead referred to as cells.

The finite-volume method is based on the fact that many physical laws are conservation laws—what goes into one cell on one side needs to leave the same cell on another side. Following this idea, you end up with a formulation that consists of flux conservation equations defined in an averaged sense over the cells. Historically, this method has been very successful in solving fluid flow problems

**What are the major differences between the three methods?**

Each method is quite similar in that it represents a systematic numerical method for solving PDEs. One important difference is the ease of implementation. A common opinion is that the finite-difference method is the easiest to implement and the finite-element method the most difficult. One reason for this may be that the finite-element method requires quite sophisticated mathematics for its formulation.

**Finite-Element Method: Advantages and Disadvantages**

One reason for the finite element method’s success in multi-physics analysis is that it is a very general method. Solving the resulting equation systems are the same or very similar to well-known and efficient methods used for structural and electromagnetics analysis. Another reason for the method’s success is that it makes it easy to “increase the order of the elements” so that the physics fields can be approximated very accurately. This typically corresponds to locally approximating the physics fields with polynomials of “higher order,” such as second- and third-degree polynomials, or higher. This technique is often critical, for example, in the case of accurate stress analysis.

If we consider the example of stress analysis, it is quite common that there are important stress concentrations close to some of the corners of a mechanical part. In this case, the finite-element method allows for two different ways of increasing the accuracy of the solution around this corner. One way is to increase the order of the elements, as described earlier. Another method is to locally refine the mesh close to that corner; the element density increases locally. The finer the mesh (i.e., more elements), the more accurate approximation one gets for the stress field around the corner of interest. Both techniques are used in finite-element software and are frequently made automatic from the user’s perspective. This is known as “adaptive mesh refinement.”

Another advantage with the finite-element method, which is particularly important for multi-physics analysis, is that you can combine different kinds of functions that approximate the solution within each element. This is called mixed formulations. This is important, for example, in the case of electromagnetic heating. The physics and mathematics require one type of function for the electromagnetic field and another type of function for heat transfer; they both need to be tightly coupled to get an accurate solution and for the solution to converge. Mixed formulations are straightforward to handle the finite-element method, but difficult or impossible with other methods.

The benefits with both the finite-element method and the finite-volume method are that curved and irregular CAD geometries are handled in a natural way.

However, the mathematics behind the finite-element method is quite advanced and thus the method requires mathematical expertise for its implementation. Implementations of finite-difference and finite-volume methods are comparatively straightforward.

For certain time-dependent simulations, one needs to use so-called explicit solvers for reasons of efficiency. Implementing such solver techniques is more difficult for the finite-element method than for the finite-difference and finite-volume methods. However, this has successfully been commercialized in some cases, such as in crash simulations.

**Finite-Difference Method: Advantages and Disadvantages**

The finite-difference method is defined dimension per dimension; this makes it easy to increase the “element order” to get higher-order accuracy. If you can fit the simulation in a rectangular or box-shaped geometry using a regular grid, efficient implementations are much easier than for finite-element and finite-volume methods. Regular grids are useful for very-large-scale simulations on supercomputers often used in, as mentioned before, meteorological, seismological, and astrophysical simulations.

With the finite-difference method, you may easily run into problems handling curved boundaries for the purpose of defining the boundary conditions. Boundary conditions are needed to truncate the computational domain. They represent communication with the surrounding world, which is the part that you do not want included in your simulation. If one can overcome the boundary-condition problem on curved boundaries, the method gives very efficient and high quality results.

For computations that need high accuracy, the extra effort in making boundary-fitted meshes and the associated complications of such meshes for the implementation may be worth it. Examples include Formula 1 car computational-fluid-dynamic (CFD) simulations and space-shuttle CFD simulations. The finite-difference method is more difficult to use for handling material discontinuities. In addition, it does not lend itself for local grid refinement or anything similar to “adaptive mesh refinement.” This may be needed to resolve local rapid variations in solutions such as around a corner of a complex shape, as described earlier.

**Finite-Volume Method: Advantages and Disadvantages**

The finite-volume method is a natural choice for CFD problems, since the partial differential equations you have to solve for CFD are conservation laws. However, both finite differences and finite elements can also be used for CFD. Efficient technology for CFD with the finite-element method has become increasingly popular over the last 10 to 15 years. Techniques for CFD with the finite-difference and finite-volume method have been known and used much longer.

The finite-volume method’s strength is that it only needs to do flux evaluation for the cell boundaries. This also holds for nonlinear problems, which makes it extra powerful for robust handling of (nonlinear) conservation laws appearing in transport problems.

The local accuracy of the finite-volume method, such as close to a corner of interest, can be increased by refining the mesh around that corner, similar to the finite-element method. However, the functions that approximate the solution when using the finite-volume method cannot be easily made of higher order. This is a disadvantage of the finite-volume method compared to the finite-element and finite-difference methods.

**What are the major examples of each?**

*Finite-element method:* All kinds of structural analysis, heat transfer, chemical engineering, electromagnetics (including electrostatics, magnetostatics, low-frequency electromagnetics, and frequency-domain high-frequency electromagnetic waves), multi-physics, and CFD.

*Finite-difference method:* Weather calculations, astrophysics, seismology, physical realism in computer graphics, and special effects.

*Finite-volume method:* CFD, heat transfer, and chemical engineering.

**Which method is most commonly used in today’s analytic and simulation software?**

All of these methods are frequently used today in commercial software, as well as in academic environments. The finite-element method is usually most taxing on a computer system, but it depends on the type of analysis.

]]>We invite you to see the sales chart in this link: CFD Beginners – ANSYS

**AN**alysis **SYS**tem, known as ANSYS was founded in 1970 by Dr. John Swanson, who worked at the Westinghouse Nuclear Laboratories in Pittsburgh, he was responsible for the nuclear reactor and developed computer codes for obtaining the efforts in the rotor.

He subsequently left his work to continue developing his code with the help of some colleagues, however ANSYS did not start as a CFD software, but started as a CAE software, and since 2003 begins with the acquisition of important Softwares such as CFX- 4 (later called CFX), and it is at that moment that he begins his adventure with the CFD; **Years later begins what was perhaps the greatest rivalry in the world of computational fluid dynamics; CFX vs FLUENT**, they were rivals, it was a classic, Real Madrid vs Barcelona, Brazil vs Argentina, USA vs USSR or whatever you want …

In those years I used FLUENT, it was spectacular !!!, we could even say that FLUENT had some advantage, until in 2006 the unexpected happened, ANSYS bought FLUENT for the sum of 630 million dollars, this generated the beginning of an Empire of the CFD, perhaps we can compare ANSYS with CD-ADAPCO and ABAQUS, which are also giant companies of the sector although I doubt have their magnitude.

ANSYS has many diehard fans (I consider myself one of them) and also its few detractors (as in any software), but the great advantage that ANSYS has over its competitors is the way it has integrated its programs so that they can interact with each other within Of a single environment through the Workbench; Allowing us to use, for example, FSI (fluid-structure interaction), parameterization, optimization, compare results in CFX and FLUENT, etc.

ANSYS has among its programs:

**ANSYS CFX** – Computational Fluid Dynamics

**ANSYS FLUENT** – Computational Fluid Dynamics

**ANSYS MECHANICAL** – Structural Analysis

**ANSYS MESHING** – Mesh Generator

**DESIGN MODELER** – CAD Software

**SPACECLAIM** – CAD Software

**ANSYS AIM** – Multiphysics simulation

**ANSYS AUTODYN** – Explicit software for analysis of extreme loads

These are some programs, there are much more, here I want to make a quote; The ANSYS MESHING is perhaps the best mesh generator of the market, only surpassed by the ICEM (Oh! Surprise, also of ANSYS).

But this story does not have a dream ending, because ANSYS is also one of the most expensive software on the market, so they have made available the student and academic world a free version, which has certain limitations of mesh and use of colors ( For the parallel simulation), in this web you will be able to download:

Soon we will develop tutorials in ANSYS, please do not forget to subscribe to our youtube channel:

Here are some examples of what can be done at ANSYS: Hydraulics

]]>In this tutorial we have installed Ubuntu 16.04, but if you use Ubuntu 14 you can also follow the same steps.

Now we are ready for our first tutorial

]]>Changing the operating system to learn OpenFOAM is difficult, so there is a way to use OpenFOAM on Windows by installing a virtual disk, it is an easy and safe way to use OpenFOAM.

In this video, we show you the procedure of the installation and in our next post, we will teach you how to install it.

However, if you are a fan of free software and want to work with OpenFOAM purely, we recommend you change your operating system to Linux.

It is important to emphasize that despite being the same software, both have small differences in their code, which are not fully compatible with each other.

You can visit both websites and download the one of your preference.

**CFD Direct**

http://openfoam.org/

**ESI Group**

http://openfoam.com/

In this Post we have developed a simulation of a simple thermal analysis testing both softwares for the same mesh and we have obtained the following results:

**ANSYS CFX**

**Solution in 24 iterations**

** Computed time: 12 seconds**

**ANSYS FLUENT**

**Solution in 3 iterations**

** Computed time: 3 seconds**

Although in this case, ANSYS FLUENT was faster, we can not say that will always be so. It is possible that in other conditions or in other types of simulations the opposite happens.

We invite you to make your own tests and comment your results, you can also try other software.

Please see the video

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