Symmetry in FEA is great, as it reduces the size of the task. This, in turn, shortens the computing time. Computing time is still a big issue, especially when you run complex models. Without a doubt, this is why using symmetry in FEA is so popular. There is a catch to this, however, as you make some assumptions while defining symmetry. Those assumptions may lead to incomplete outcomes of your analysis.

What is symmetry in FEA

Simply put symmetry is a set of boundary conditions that make part of your model work as if you have modeled the whole model.

This is almost always explained in a classical example of a beam loaded with 2 forces:

Symmetry in FEA - a classical example

You can clearly see here, that the model is symmetric, which means that if you split it in half (as shown with the axis) you get 2 mirror images. Such cases allow for use of symmetry, and definition of it can be derived simply by observation.

You can notice that in the middle of the deformed shape there will be no rotation at all, but it moved downward along the symmetry line/plane. This is enough to see, that symmetry boundary conditions will look like this:

Symmetry in FEA - classical example with BC

With such definition, you can simply solve half of your model, and the outcomes will be correct! This is a great benefit of symmetry, as it can greatly reduce model size.

Where is the catch?

Of course, there must be something, as the title suggested right? What I was silent about before is, that in the example above not only the model and loads were symmetric. Also, the outcome was!

This is an issue that can be easily overlooked. Symmetry in FEA will always produce a symmetric outcome, simply because well… it’s symmetry!

At first sight it may seem that this is not an issue. After all, if I have a symmetric model, with symmetric loads and boundary conditions the outcome must be symmetric right? Unfortunately, that is not always the case! The fact that in a lot of cases it is true, makes this even easier to forget!

If you analyze vibrations, buckling or any other analysis that may produce a unsymmetrical outcome, you should especially remember about this!

Small example

I will show you how this problem works on another well-known problem: Euler’s case!

We will use Linear Bifurcation Analysis (LBA) to calculate eigenvalues of the problem. After some simple modeling, I was able to obtain first 5 eigenvalues of the beam:

You can easily notice, that the task is actually symmetric. So now let’s reduce it, to see what will happen:

Notice, that forms 2 and 4 from the full model is “gone”. The values for the forms I got are correct, and correspond with the forms I got in the first model. However, some of the forms are not there at all!

Take a closer look on Forms 2 and 4 from the first model. They are not symmetric! In fact, they are antisymmetric which is possible to get in symmetric models.

This is why symmetry in FEA may be dangerous:

It will show the correct answers, but will hide from you some forms of buckling or vibrations etc. Biggest problems appear if you miss something that is important, like that vibration frequency that you were seeking or buckling form you were not able to counteract.

Last few words

As you can see, from time to time, symmetry can work against you. But this doesn’t change the fact that it is an awesome tool, that should be used whenever possible.

Just be aware of its limitations, and you will do just fine!

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