Real Parts Tested Virtually

Projects

Current Projects

Inline virtual qualification from 3D X-ray imaging for high-value manufacturing

EPSRC Manufacturing Research Fellowship (2018-2023)

https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/R012091/1

The aim of this research programme is to transform component qualification by replacing costly and time-consuming experimental methods with an inline ‘virtual’ methodology that scales-up for high-value manufacturing.

By creating micro-scale accurate models of components from 3D X-ray imaging to simulate under in-service conditions allows determining whether each part is fit for purpose without the need for costly and time-consuming experimental methods. This part-specific modelling improves simulation accuracy by accounting for deviations from design (tolerancing, micro-cracks, pores etc.). Because current methodology to use part-specific simulation for virtual qualification requires significant human interaction, which is a barrier for scalability, it is not used in any impactful way in manufacturing. Therefore, achieving this through successful automation of the technique by applying state-of-the-art 3D image processing and machine learning methods to deliver a new software tool for use in manufacturing is key this fellowship’s aim.

This research programme has these main objectives:

  1. To make the use of part-specific simulation feasible for many components and therefore production line manufacturing. This includes investigating automation techniques to integrate the various stages of IBSim. We are developing a set of software tools that aim to replace intensive manual interaction with an automated workflow supported with machine learning algorithms.
  2. To establish image-based simulation as a technique that has reproducible outcomes. This will be achieved by producing simulation-experiment calibration benchmarks based on industry-standard techniques for measuring thermomechanical material properties. All of the datasets (XCT, simulation, experimental) are being made freely available (open-access) to download in order for others to verify the IBSim workflows we’re developing and to test their own.
  3. To demonstrate the capabilities of automated ‘virtual qualification’ to predict part-specific performance on a batch of components for the first time. This will be achieved with a case study to demonstrate part-specific prediction of thermomechanical performance of heat exchange components manufactured to include controlled ‘defects’. This activity is being undertaken in partnership with UK Atomic Energy Authority (UKAEA) using the HIVE testing apparatus.
  4. To establish an active IBSim users’ and developers’ community that will facilitate wider adoption of image-based simulation as a non-destructive evaluation (NDE) tool. This will be achieved through training, support and by creating a network to discuss the cutting-edge developments in the field. The culmination of these activities is the annual IBSim-4i event hosted by the group.

This research programme is in collaboration with Airbus Defence & Space, Diamond Light Source, The MTC, Nikon Metrology, Synopsys, TWI, UKAEA and the University of Manchester.

CCPi Tomographic Imaging (Tomographic Imaging: UK Collaborative Computational Projects)

EPSRC CCP Networking Grant (2020-2025)

https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/T026677/1

The Collaborative Computational Project in (CCPi) Tomographic Imaging aims to provide the UK tomography community with a toolbox of algorithms that increases the quality and level of information that can be extracted by computed tomography. This EPSRC funded initiative is chaired by Prof Philip Withers (University of Manchester), Dr Llion Evans is a co-investigator (CoI) on the grant (2020-2025) and exec member of the working group. The ZCCE IBSim group will work with the CCPi Tomographic Imaging network by supporting several activities.

  • Development of open-source workflows for using the Core Imaging Library (CIL) with industrial applications, particularly IBSim.
  • Establish “CT benchmarks”: with links to the emerging ISO standards carefully designed benchmark CT datasets verified by different methods such as laser scanning for test, comparison and standardization of methods and workflows
  • Seek to expand links from academic tomography community to industrial users in terms of needs and applications, methods and software.
  • Develop an open-source toolkit for public engagement with XCT data.

Integration of Effects of Neutron Irradiation on Material Properties into FEM Virtual Tokamak Reactor framework

EUROfusion Engineering Grant (2020-2022)

Dr Salahudeen Mohamed is leading a EUROfusion project, funded by Horizon 2020, to investigate “Integration of Effects of Neutron Irradiation on Material Properties into FEM Virtual Tokamak Reactor framework” (2020-2022, EEG-2020/29).

The aim of the project is to develop a capability for predicting the changes in engineering properties of fusion power plant component materials at different lifecycle stage due to defects induced by neutron irradiation. The developed capability will better enable engineers to design efficient fusion device components.

The project’s main objectives are:

  1. To identify the microstructural defects in the irradiated components from electron microscopy for image-guided simulations.
  2. To establish a link between microstructural defects and macroscopic material properties using multi-scale in-house codes. To validate computational results obtained from the simulations through comparison with experimental data and to use this capability to assess the impact on the mechanical behaviour of components.
  3. To optimise the developed multi-scale code so that simulations complete in a timeframe making its use feasible and valuable within the iterative R&D cycle.

Past Projects

Image-based simulation of W-interlayer-CuCrZr joining region in DEMO water-cooled divertor monoblocks using X-ray and neutron tomography data

EUROfusion Research Fellowship (2015-2017)

The ITER divertor design is for an all tungsten (W) design, which is in-line with current expectations for DEMO. Joining of W and CuCrZr has proven problematic due to poor adhesion and a large mismatch of thermal expansion coefficients. To give a variety of potential manufacturing defects this work proposes to use IBSim to investigate a range of differing joining techniques (e.g. brazing or hot isostatic/radial pressing) being developed by partners such as Politecnico di Torino and Karlsruhe Institute of Technology (KIT).

In contrast to carbon, tungsten is a high attenuator of X-rays. Until recently laboratory X-ray sources were ill-equipped to image samples with dimensions of practical value due to low penetration. Using a novel high-powered CT scanner Dr Evans has recently successfully imaged tungsten pipes (11 mm diameter, 1.5 mm thick) with a 10 μm resolution, adequate for such a study. The material interfaces would be imaged by joining W, interlayer, and CuCrZr concentric pipes rather than manufacturing ‘full’ monoblocks. This would remove the bulk of the W, thus minimising the X-ray attenuation path. The interlayer constituent is the area under most development, ITER/DEMO relevant solutions will be examined in this work.

ParaFEM will be used to analyse the impact of joining techniques on thermal conductivity and stresses. This will directly support the current ‘PPPT Water Cooled Divertor’ work package, led by T. Barrett at CCFE, which performs mechanical analysis of novel divertor designs for DEMO using FE modelling. The best performers (i.e. lowest thermal stresses at a given high heat flux) will be used to produce ‘full monoblock’ samples to be imaged using neutron tomography at ISIS, UK (under a pre-existing agreement) with additional beam-time available at Technische Universität München, Germany. Although neutron tomography does not suffer the attenuation difficulties associated with X-rays, its resolution is lower. This will be used to observe whether significant variations between the ‘region of interest’ and ‘full’ samples exist due to the manufacturing process and quantify their impact.

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