From 3D Image Data to Fusion Energy: Interview with Dr Llion Evans

Posted on 10 August 2018 by Rebekah Dixon

Last month we conducted our first ever ‘Twitterview’ with Dr Llion Evans of Swansea University. A ‘Twitterview’ is exactly what it says on the tin: an interview on Twitter. #Twitterview

We asked Llion questions about himself, his work, and the impact it can have, as well as any challenges he faces. All his answers had to fit into the 140/280 characters in a tweet.

Our conversation, which took place completely on Twitter, discussed everything from virtual qualification, image-based modelling from industrial CT (Computed Tomography) data to fusion energy, and much more.

Missed it? Or want to read it again? Either see the entire Twitterview as it originally appeared on Twitter, or see below for the questions and answers.

What's your job?

I’ve just started a new position as an EPSRC Manufacturing Research Fellow at the Zienkiewicz Centre in Swansea University In this role I’m leading a 5-year research project to look at using #ImageBasedModelling in the manufacturing sector to perform #VirtualQualification.

Zienkiewicz Centre in Swansea University (Courtesy: Swansea University)

What’s ‘virtual qualification’?

Essentially, it’s a process where we create digital replicas of manufactured components that are micro-scale accurate which we test in a computer instead of a lab. This is done by converting X-ray CT images into ultra-high resolution simulations.

Divertor monoblock component and digital replica (Courtesy: Llion Evans)

What’s the value in doing that?

The aim is to reduce or even replace physical testing which can be time consuming and expensive. Because virtual testing includes micro-features simulate what we actually manufacture rather than just what we designed (there’s often a significant difference).

(Courtesy: Llion Evans)

How did you end up in your current role?

Previously I worked at Culham Fusion Energy Centre using #ImageBasedModelling to investigate designs for the first fusion device planned to generate electricity. I loved that job but wanted to develop the technique more, which I can do as an EPSRC fellow.

Computer-generated cutaway image of JET during a plasma experiment (Courtesy: EFDA JET)

Fusion energy, that’s pretty exciting!

Definitely, as you can imagine at Culham Fusion Energy Centre we’re always pushing everything to the limit. So, having increased accuracy through #ImageBasedModelling is invaluable in realizing the goal of making it a commercial reality.

ITER Divertor (Courtesy: ITER Organization)

How does Simpleware software help your work?

The CT scan gets our component from the real to the digital world. Then Synopsys Simpleware is a key stage in the workflow to get from our 3D X-ray images to ultra-high resolution engineering simulations.

Detail of reconstructed mesh of divertor monoblock (Courtesy: Llion Evans)

How long have been using Simpleware software?

I started using Synopsys Simpleware as a PhD student at The University of Manchester's School of Materials  ‏in The University of Manchester almost 10 years ago now! It’s been great to see how it’s developed over time, I’m impressed how each year new features are added which increase its usefulness.

Has the software enabled you to overcome any specific problems?

We found a small region of debonding that kept occurring in the heat exchange component. By creating an #ImageBasedModel with Simpleware software we were able to quantify its impact on performance and optimise use of the component.

Analysis of divertor monoblock tile created from an X-ray tomography image (Courtesy: Llion Evans)

Have there been any challenges?

Yes, because Synopsys Simpleware allows us to model at resolutions much higher than normal, the simulation software we’d typically use struggled to cope. But we’ve been able to use ParaFEM and Kitware ParaView to get around this.

What kind of response have you had from the industrial sector?

When industrial contacts see what the technique’s capable of they’re extremely keen to look at applications, but there isn’t enough info out there how to go about this. We’ve identified this as a barrier to adoption so we’re establishing a new forum to address this.

Swansea University Bay Campus (Courtesy: Swansea University)

What can we expect to see?

Firstly, there’s the Image-Based Finite Element Method for Industry event (IBFEM-4i) this September. We’ll have a 2-day training course then a 2-day workshop open to industry and academia. For those interested in joining us please go to

What do you hope to achieve with your EPSRC fellowship?

#ImageBasedModelling is great for R&D but takes a too much time for routine use on the factory floor for every component. We’re going to look at how we can use #MachineLearning to automate and scale-up the process for the manufacturing sector, as shown in this video. Learn more about EPSRC 

What impact do you predict the outcome of your fellowship will have?

In the short-term we aim to demonstrate that automated #VirtualQualification can be used on whole batch of Fusion Energy components to predict the performance of each part individually.

(Courtesy: Culham Centre for Fusion Energy)

In the long-term we want to establish #VirtualQualification as an invaluable tool for manufacturing. And see it used in #SmartFactories to reduce environmental footprint by reducing wastage.

(Courtesy: Llion Evans)

Thank you Llion Evans for an interesting chat about your current work - looking forward to seeing more developments in this project! We hope everyone else enjoyed hearing about all your work as much as we did!

If you wanted to find out more about Llion and his work, he will be at the Image Based Finite Element Method (IBFEM) event this September in Swansea, where Simpleware Director, Philippe Young will be giving a talk. Go to IBSim-4i 2018 for more information.

If you have any questions, or would be interested in doing a twitter view, please email us on




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