In this series of 5 videos, I will show you how to generate and simulate a 2D Axi-symmetric Transducer Design with OnScale.

## Transducer Design Part 1 – Introduction

What is a transducer and what kind of results you can obtain from such an FEA simulation with OnScale?

**That’s what I am talking about in this introduction video:**

A transducer is an electronic device which transforms one type of energy into another type of energy.

A multilayer transducer like the one in this article belongs to the family of the piezoelectric acoustic transducers, which are special transducers which transform an initial electric input signal into an acoustic wave.

Such transducers are used heavily in sonar, medical imaging, NDE (Non-Destructive Engineering) and signal processing systems.

**Note about OnScale Algorithms and Time Domain FEA Simulation:**

- OnScale uses a mixed Nonlinear Transient explicit/implicit algorithm which performs a direct time integration of the 2D or 3D electro-mechanical equations.
- This special time domain method increases a lot the speed at which such 2D or 3D piezoelectric model can be calculated while maintaining a very good level of results accuracy.

## Transducer Design Part 2 – Material and Geometry

In this second part of the Multilayer Transducer Design Tutorial with OnScale, I will show you:

- How to assign material from the material database
- How to setup the polarization of your piezoelectric layer
- How to generate each geometry layer using the Primitive Shapes in Designer

**Note: **The geometry looks like rectangles, but actually this model is an Axi-symmetric model, so you should vizualise the model as if it was rotated around an axis.

This transducer is very simple, it composed of 3 main components:

- A Piezoelectric disc which is here set up as the material CTS 3203HD (pmt3) with is a soft type of PZT of the PZT5H Family.
- A Backing Layer back20 which is Tungsten loaded Epoxy
- A Matching at the top in Vantico HY1300/CY1301 (hard) which is some kind of special epoxy.

**What is a matching layer?**

The purpose of the matching layer is to maximize the transmission of the ultrasound waves from the PZT to the water.

There is a big gap between the impedance of the PZT and the impedance of the water. The matching layer makes the transition smoother to avoid the reflection of the acoustic waves. Think about the ultrasound gel used by doctors between the probe and the skin when they do an ultrasound scan.

## Transducer Design Part 3 – Electrodes, BCs, Mesh and Extrapolation Output

In this 3rd part of the Multi-layer Transducer Design Tutorial with OnScale, I’ll show you:

- How to set up the drive function
- How to create the electrodes
- How to set up the mesh size and how to use keypoints for that
- How to set up the boundary conditions of the domain
- How to set up the analysis time
- How to define the output you want and in particular, the maximum acoustic pressure and the extrapolation boundary

The drive function is a time distribution which is assigned to the electrode. It will determine the kind of pulse of voltage sent into your model

In OnScale, the most often used drive function is the Ricker Wavelet:

It is a very convenient time function to use, because it frequency domain, this function has a rather broad frequency band. Allowing you to analyze the entire response to a broad band of frequencies in one go.

For example, a Ricker Wavelet defined with a Drive Frequency of 1GHz will provide in frequency domain a distribution like this:

The Frequency band here goes from 0 Hz to around 2 GHz.

**How about doing all that in Frequency domain directly?**

If we wanted to simulate that in frequency domain, we would need to define a sampling frequency and simulate a huge number of frequencies to get the same response.

## Transducer Design Part 4 – Running the simulation on the cloud

In this part 4 of the Multilayer transducer Design with OnScale, I will show you:

- How to upload you simulation on the cloud
- How to run and download your results
- How to open those results in the post-process module

OnScale can run simulation both on your local computer (like most traditional FEA software) or on the cloud.

The advantage of using the cloud to calculate is threefold:

- You can run hundreds of simulation studies at the same time with minor variations and understand quickly your design space.
- You can run big models that simply wouldn’t run on a local computer
- It frees your local PC from heavy calculation which run in the cloud while you can do something else at the same time.

OnScale uses currently Amazon AWS for its Cloud Integration so all the security of your data is backed up by Amazon Systems.

## Transducer Design Part 5 – Results Post processing – Directivity – TVR

In this part 5 of the multilayer transducer design with OnScale, I will show you:

- How to check the Time history and Field data calculated results
- How to use the extrapolation toolkit to check the extrapolated data
- How to visualize the directivity (Beam Radial Plot)
- How to visualize the Transmit Sensitivity (TVR)

If you are still wondering how to understand Post-processing OnScale Results, I have another article here which goes in depth on that aspect.

The results we can get here from this simulation are:

- The various electrical time history curves such as the voltage, charge and current discharge of the electrodes according to time
- Then, by doing a simple Post-processing FFT (Fast Fourier Transform), you can calculate the Impedance and the Admittance of this transducer.
- Finally it is possible to calculate all kind of other KPIs such as the directivity (called also Radial Beam Plot) or the Transmit Sensitivity (TVR) using OnScale Extrapolation Toolkit.

**Interested in other ways to post-process your results?**

OnScale allows several ways to post-process your results: Scripting (Review Scripts or Python), directly vizualization with Matlab or with Paraview.

## Where can I find this model and detailed step-by-step tutorial?

The full step-by-step tutorial is also available here

The Model all set up is the 2D_Transducer.jfp available here

That’s all for today, I hope this article was useful to you!

If you like the blog and what I write, please share it with your friends of colleagues on Social Networks such as Linkedin or Facebook.

Thank you!

**Cyprien “Tranducing the Knowledge to your Brain” Rusu**

**PS:** I wanted to put a cool picture of me with the Eiffel Tower for a change, because why not? I am French after all…

## Want to continue to learn useful stuffs?

Check this article where I show you how to make the model you just built parametric:

[…] In this video, I will start from the multilayer transducer model that I described in depth in this article. […]