Real Parts Tested Virtually

Llion Evans

Dr Llion Marc Evans leads the Image-Based Simulation (IBSim) group at the Zienkiewicz Centre for Computational Engineering, College of Engineering, Swansea University. Llion holds an EPSRC Manufacturing Research Fellowship 2018-2023 (EP/R012091/1), is working group executive member and CoI for the EPSRC Collaborative Computational Projects in Tomographic Imaging (EP/T026677/1).

Area of expertise and interest

He has worked in the field of image-based simulation and non-destructive evaluation (NDE) for over ten years. His main research interests are IBSim using the finite element method (FEM) and its application in high-value manufacturing (HVM). This work focusses on industrial application and scale-up of IBSim for Virtual Qualification.

Emrah Sozumert

Dr Emrah Sozumert is a postdoctoral researcher at the Zienkiewicz Centre for Computational Engineering at Swansea University. He is currently working on Inline virtual qualification from 3D X-ray imaging for high-value manufacturing funded by EPSRC (2020-2023). He was awarded a Ph.D. degree by Wolfson School of Mechanical, Electrical and Manufacturing Engineering at Loughborough University. His Ph.D. research was on multi-scale modelling of polymeric nonwovens, financially supported by Loughborough and North Carolina State Universities. His research interests are image-based modelling, finite-element method, random fibrous networks.

Area of expertise and interest

In his current project, he designs and manufactures heat exchange components with controlled defects for benchmark tests.  Later, the components are digitised with X-ray tomography to then be tested in both the laboratory and using part-specific simulations under the extreme thermal conditions of a fusion energy device.

Salahudeen Mohamed

Dr Salahudeen Mohamed is a EUROfusion Engineering fellow (2020-2022) at the Zienkiewicz Centre for Computational Engineering, College of Engineering, Swansea University. He has broad experience in using numerical models for solving fluid and structural dynamics problems in various engineering applications. His current work is focussed on prediction of the changes in engineering properties of fusion power plant component materials due to the hostile radiation conditions.

Area of expertise and interest

As a EUROfusion engineering fellow, his project theme is about the development of a robust concurrent multi-scale model for studying the irradiation hardening induced by the defects within components of fusion device. In particular, hardening phenomenon will be assessed at different length scales starting from micro-scale to macro-scale from which mechanical behaviour of the components of fusion reactor design is predicted and evaluated over its lifetime at high neutron irradiated loads.

Ben Thorpe

Originally from West Yorkshire, Ben studied his undergraduate in Physics and masters in Solid state physics at the University of Hull from 2009-2013. He then went on to undertake his PhD at Swansea University from 2015-2019. He then went on to work as a Research Software engineer at the Swansea Academy of Advanced Computing (SA2C) before moving to IBSim in October 2021.

Area of expertise and interest

His PhD was in Spintronics, specifically the simulation of electrical polarized spin injection and spin transport in realistic III-V and Si/Ge nano-scale electronic devices. With the aim of creating a so called hybrid spin transistor. During his time at SA2C he developed his skills in programming for HPC and collaborated on several projects with a number of academic groups across the university. Most notably working with the Welsh Technical advisory group performing simulations for tracking the spread of Covid-19 in Wales. Which were then used to inform Welsh government policy during the pandemic. His current work at IBSim involves performing “as manufactured” image based simulations of 3D printed metal parts. Using X-ray CT imaging and machine learning.

Students

Rhydian Lewis

Rhydian Lewis is a PhD student at Swansea University under the supervision of Dr Llion Evans. His research is in collaboration with the UK Atomic Energy Authority (UKAEA) to maximise the impact of a testing facility through coupling experimental and simulation data. The aim is to couple use Machine Learning (ML) with computational models to maximise insight of experimental facilities. Rhydian completed his bachelor’s degree in Mathematics and its Applications in Cardiff University in 2014 and a master’s degree in Aerospace Engineering at Swansea University in 2018 before joining the IBSim group at the start of 2019.

Area of expertise and interest

Computation modelling has long been a cornerstone of the engineering workflow. While its use has been key to developments in several industries, only a small fraction of the data recorded is used to steer decision making. In the age of big data and ML it is now possible to turn a much larger fraction of the data into invaluable information.

The ‘Heat by Induction to Verify Extremes’ (HIVE) facility at UKAEA is used to test components under the extreme environments experienced in a fusion device. Collecting data from a virtual twin of HIVE and applying to ML algorithms ensures a more efficient testing regime. This can be achieved in a number of ways, such as optimising the experimental parameters, discovering inverse solutions & optimised sensor placement for model validation.

Alex Cornell-Thorne

Alex Cornell-Thorne is a PhD student at Swansea University under the supervision of Dr Llion Evans. His research project, “The effects of length scales and data resolution on image-based simulation”, is in collaboration with The Manufacturing Technology Centre (The MTC). He completed his Physics BSc at the University of Keele in 2019 where he found an affinity for computational modelling and data analysis as tools for scientifically based research and development.

Area of expertise and interest

As volumetric scanning methods, e.g. X-Ray Computed Tomography (XCT), and computing power improve, image-based simulation (IBSim) geometries can be generated at increasingly fine resolutions. This primary goal of this research is to quantify the impact of increasing image resolution on the IBSim method with a particular focus on the relation between feature sizes, how this relates to the material’s granular scale and the finite element sizes used.

Additionally, this project is investigating how increased data impacts the IBSim workflow (e.g. computational expense and imaging time) and aims to produce ‘best practice’ guidelines for achieving a balance between data resolution, results accuracy and time costs

Prakhar Sharma

Prakhar Sharma is a PhD student at Swansea University under the supervision of Prof Perumal Nithiarasu, Dr Llion Evans and Dr Michelle Tindall (UKAEA). His research is in collaboration with the UK Atomic Energy Authority (UKAEA) to understand the thermo-mechanical behaviour of fusion components inside a fusion reactor. The aim is to develop forward and inverse machine learning approaches to deliver new digital twin models.

Prakhar completed his bachelor’s degree in Civil Engineering at Dr APJ Abdul Kalam Technical University in 2019 and his master’s in Computational Mechanics at Swansea University in 2021.

Area of expertise and interest

He has worked in the field of data-driven system identification. Specifically, obtaining the governing PDE from sparse observation data. Currently, he is using Physics-informed neural networks to solve stiff-PDEs.

Alumni

Llion Evans

Dr Llion Marc Evans leads the Image-Based Simulation (IBSim) group at the Zienkiewicz Centre for Computational Engineering, College of Engineering, Swansea University. Llion holds an EPSRC Manufacturing Research Fellowship 2018-2023 (EP/R012091/1), is working group executive member and CoI for the EPSRC Collaborative Computational Projects in Tomographic Imaging (EP/T026677/1).

Area of expertise and interest

He has worked in the field of image-based simulation and non-destructive evaluation (NDE) for over ten years. His main research interests are IBSim using the finite element method (FEM) and its application in high-value manufacturing (HVM). This work focusses on industrial application and scale-up of IBSim for Virtual Qualification.

Partners and Collaborators

The ZCCE IBSim Group partners with an increasingly wide range of organisations to undertake world-leading research. We’re grateful to our collaborators for backing us with their finance, time and resources. Through working with us they’re supporting us towards our aim to transform component qualification by replacing costly and time-consuming experimental methods with an inline ‘virtual’ methodology that scales-up for high-value manufacturing.