Principal Research Engineer & UKRI Future Leaders Fellow · United Kingdom Atomic Energy Authority (UKAEA), Fusion Technology Division · Sheffield, UK · lloydcolinfletcher@gmail.com
Google Scholar · GitHub · ORCID
My research addresses the overarching question:
How do we qualify fusion materials and components for extreme and untestable environments?
I develop methods that link simulation and data-rich experiments so that engineering models can be validated and used to support real-world design and qualification decisions. My work centres on simulation-driven experimental design, validation and uncertainty quantification, scientific software, image-based measurement and data-rich experiments, with a particular focus on extracting maximum information from limited and expensive fusion-engineering test campaigns.
I currently lead a £3.2M integrated experimental–computational research programme through a UKRI Future Leaders Fellowship (FLF), developing new methodologies and open-source tools for digital design qualification.
- UKRI Future Leaders Fellow, Applied Materials Technology Group, Fusion Technology Division, UKAEA South Yorkshire · September 2024–present
- Principal Research Engineer, Applied Materials Technology Group, Fusion Technology Division, UKAEA South Yorkshire · February 2024–present
- Visiting Lecturer, Department of Materials Science & Engineering, University of Sheffield · August 2024–present
- Senior Research Engineer, Applied Materials Technology Group, Fusion Technology Division, UKAEA South Yorkshire · August 2021–September 2024
- Principal Investigator of a £3.2M UKRI Future Leaders Fellowship, leading a multidisciplinary programme of approximately 8–9 FTE, four co-funded doctoral studentships and annual Year in Industry placements.
- Built UKAEA South Yorkshire's component-validation and simulation-driven experimental-design capability from the ground up, establishing its integrated experimental–computational research group and embedding it in Virtual Qualification for Fusion and FUJUKEN, including collaboration with QST, Japan.
- Founded and led development of Pyvale and Riley, open-source platforms for virtual experimentation, imaging simulation and model validation; Pyvale was subsequently identified in an internal technology review as a distinctive technology for strategic investment.
- Established simulation-driven experimental design as a UKAEA core capability, with team members now supporting cross-divisional fusion programmes.
- Developed staff, careers and capability through successful promotion-in-post and chartership cases, fellowship and grant development, graduate training, and progression of placement students into doctoral research.
Principal Investigator — UKRI Future Leaders Fellowship · September 2024–August 2028 · UKRI award: £1.6M · Matched UKAEA contribution: £1.6M · Combined programme value: £3.2M · UKRI Gateway to Research — MR/Y015916/1
The fellowship develops a new Computer Aided Validation (CAV) methodology for determining when engineering simulations are sufficiently credible to support design and qualification decisions, while maximising the information obtained from limited, costly experiments.
- Develop and demonstrate simulation-driven experimental-design methods that maximise validation information while reducing the cost, time and risk of component experiments.
- Quantify and minimise measurement and experimental uncertainty through rigorous workflows linking simulation, measurement and model-validation metrics.
- Deliver Pyvale, a virtual engineering laboratory for optimising validation experiments before physical testing, and apply the methodology to increasingly complex fusion-engineering problems.
Technical leadership of an integrated experimental–computational programme including ~9 FTE of research staff time at UKAEA: 1 FTE Principal Research Engineer / Fellow; 3 FTE computational research engineers; 1 FTE Lead Research Engineer — experimental; 1 FTE Specialist Research Engineer — experimental; 2 FTE graduate research engineers; and 1 FTE Year in Industry student per year, alongside 4 co-funded PhD studentships.
The programme deliberately integrates experimental and computational researchers rather than separating experimental design, simulation and analysis into independent activities. Graduate researchers and placement students receive combined experimental/computational training in this methodology.
Imperial College London · University of Liverpool · University of Oxford · Swansea University · University of Sheffield
Pyvale v1.0, including Pyvale DIC 2D, and Riley; open-source experimental-design workflows; publications and preprints on DIC, experimental design and model validation; a probabilistic validation application for a major UKAEA component experiment; and supporting experimental, simulation and validation datasets.
Established UKAEA's component-validation capability at the South Yorkshire site, developing a hybrid experimental–computational group focused on data-rich experiments, simulation validation and experimental design.
Established the component-validation laboratory, associated computational infrastructure and an approximately 6 FTE team. Secured >£100k in initial imaging, experimental and computational equipment, and enabled a further ~£100k for electromagnetic-loading rigs and instrumentation through FUJUKEN. Developed integrated experimental, computational and validation-analysis methods and applied them through cross-divisional programmes with defined publication outputs.
Experimental data and capability have supported research with or by the University of Liverpool, University of Sheffield, University of York, Swansea University, Imperial College London and the University of Oxford, including PhD projects, internships and collaborative validation-method development.
Founder and Lead Developer · GitHub repository · Languages: Python, C++ · Licence: MIT
Pyvale is an open-source virtual engineering laboratory that transforms engineering simulations into virtual experiments, processes them through realistic measurement pipelines, and supports uncertainty-quantification and model-validation studies.
Pyvale Digital Image Correlation: Pyvale includes a dedicated high-performance two-dimensional Digital Image Correlation (DIC) engine combining a Python interface with performant compiled routines.
Key capabilities: multithreaded DIC; memory-efficient processing of extremely large experimental images; demonstrated processing of gigapixel-scale image pairs; performance from desktop workstations to automated and high-performance-computing workflows; and integration with Pyvale's wider virtual-experiment and validation workflow.
Pyvale DIC is already being used externally at the University of Manchester / Henry Royce Institute for analysis of very-high-resolution scanning-electron-microscope datasets.
Associated paper: J. Hirst, L. Sibson, A. Tayeb, B. Poole, M. Sampson, W. Bielajewa, M. Atkinson, A. Marsh, R. Spencer, R. Hamill, C. Hamelin, A. Harte and L. Fletcher, "PYVALE: A Fast, Scalable, Open-Source 2D Digital Image Correlation (DIC) Engine Capable of Handling Gigapixel Images."
arXiv:2601.12941, 2026. Under review in Experimental Mechanics.
Founder and Lead Developer · GitHub repository · Core implementation: Zig · Interface: C ABI / Cython / Python
Riley is a high-performance scientific rasterisation and camera-simulation framework for Digital Image Correlation uncertainty quantification and simulation-driven experimental design.
Key capabilities: rasterisation of linear and higher-order finite elements; scientific camera simulation including lens distortion and point-spread functions; supersampled image generation; high-order texture interpolation; DIC uncertainty-quantification workflows; data-oriented implementation; explicit SIMD vectorisation; and hierarchical CPU parallelisation.
Novel algorithms were developed for accurate rasterisation of higher-order finite elements while retaining high computational throughput.
A representative performance case processes a 5 MP stereo sequence comprising 64 frames per camera in approximately 2.7 seconds.
Riley is being developed as the high-performance rendering backend for Pyvale, enabling integrated workflows such as: FE model → Riley → Pyvale DIC → post-processing → inverse analysis / model validation
Associated paper: L. Fletcher, J. Hirst and W. Bielajewa, "Riley: A Computational Framework for Higher-Order Finite Element Image Synthesis Applied to Digital Image Correlation Uncertainty Quantification." engrXiv preprint, 2026. Under review in Engineering with Computers.
Current line-management responsibility spans staff from early-career engineers through to Lead Research Engineers: 2 × Lead Research Engineer, 1 × Senior Research Engineer and 3 × Research Engineers.
In addition to formal line management, I provide technical leadership and research mentorship across the full multidisciplinary Future Leaders Fellowship team.
- Mentored staff through UKAEA's graduate development scheme, two successful promotion-in-post processes, and CEng MIMechE professional registration.
- Mentor Grade G/H researchers and prospective Future Leaders Fellowship applicants on research ideas, fellowship and external-funding proposals, including Royal Academy of Engineering and UKRI opportunities.
- Led recruitment across internships, placements, graduate researchers, research engineers and senior roles; supervised interns who progressed to doctoral study or industry graduate roles.
- Mentored a Year in Industry student through to an Oxford PhD that I now co-fund and co-supervise; currently supervise two further placement students.
- Developing Experimental Design Engineer role descriptions and progression routes for computational and hybrid experimental–computational researchers.
Imperial College London: An Active-Learning Optimisation Framework for Experimental Design & Simulation of Fusion Breeder Blankets · Academic lead: Dr Andrew Duncan · Student: Sean Shite · Start: September 2026 · Role: Industrial co-supervisor / co-funder
Imperial College London: Smart Image-Based Sensor Array Optimisation for Fusion Simulation Validation · Academic lead: Dr Andrew Duncan · Student: Lucas Pigott · Start: September 2025 · Role: Industrial co-supervisor / co-funder
Swansea University: Validation and Uncertainty Quantification of Digital Twins · Academic lead: Prof. Perumal Nithiarasu · Student: Offer Made · Start: October 2026 · Role: Industrial co-supervisor
University of Oxford: Specimen Geometry Optimisation for Multi-Axial Testing Using Parametric Optimisation and Modern ML Ideation · Academic lead: Prof. Clive Siviour · Student: Lorna Sibson · Start: September 2026 · Role: Industrial co-supervisor / co-funder
University of Liverpool: Multi-Physics Simulation Validation for Fusion · Academic lead: Dr Ksenija Dvurecenska · Student: Rushayva Naidu · Start: September 2025 · Role: Industrial co-funder
Swansea University: Ray-Tracing Simulations for DIC Uncertainty Quantification for Immersed Fluid–Structure Interaction Problems in Fusion Components · Academic lead: Prof. Hari Arora · Student: Michael Darcy · Completed: August 2026 · Role: Industrial co-supervisor
University of Southampton: Panagiota Tavianatou — Primary supervision, inverse identification methods for extracting multiple mechanical properties of bone from data-rich experiments; Jared Van Blitterswyk — Co-supervision, high-strain-rate testing and image-based identification of composite properties; Sam Parry — Co-supervision, high-strain-rate testing of composite materials using image-based inertial methods.
Colorado School of Mines: Andrew Matejunas — Co-supervision with Dr Leslie Lamberson, high-strain-rate experimental methods for viscoelastic constitutive identification.
Materials Science & Engineering · August 2024–present
Develop and deliver teaching in fusion materials, structural integrity, engineering validation, verification, validation and uncertainty quantification, and experimental design.
University of Liverpool — 4th-Year Engineering: Structural Integrity; University of Sheffield — 4th-Year Advanced Nuclear Systems; Fusion Power CDT — Research Communication; Fusion Engineering CDT — Fusion Engineering Qualification. Each is one 2-hour invited lecture/workshop annually.
All teaching material is developed independently.
Lecturer for second-year Structural Analysis, teaching approximately 400 mechanical and aerospace engineering students; developed a new laboratory format enabling individual interaction with experimental equipment under COVID restrictions; tutor in first-year engineering statics; and supervisor of undergraduate and Master's research projects.
Lecturing: Materials; Aerospace Structural Analysis and Design. Tutoring: Materials; Object-Oriented Programming in C++; Programming for Engineers; Engineering Design and Communication; Stress Analysis and Design; Finite Element Analysis; Fracture Mechanics.
Student evaluation scores for Aerospace Structural Analysis and Design improved from 5.8/7 to 6.3/7 during the three years in which I taught the course.
- 2024–2028 — Principal Investigator: UKRI Future Leaders Fellowship · A Computer Aided Validation Framework for Digital Design Qualification · £3.2M (£1.6M UKRI + £1.6M matched UKAEA support) · UKRI Gateway to Research — MR/Y015916/1. A further 1 FTE/year of UKAEA effort is leveraged from aligned programmes.
- 2023 — Principal Investigator: UKAEA Internal Funding — Technologies for Component Qualification · 4.2 FTE staff resource plus £53k capital/consumables.
- 2022 — Principal Investigator: UKAEA Internal Funding — Image-Based Component Validation of In-Vessel Components · 2 FTE staff resource plus £20k capital/consumables.
- 2019 — Principal Investigator: EPSRC Vacation Bursary · £3k stipend plus £300 consumables for an undergraduate research project.
- 2018–2021 — Principal Investigator: Leverhulme Early Career Research Fellowship · Imaging Impact: Image-Based Methods for Dynamically Testing Bone · £82k.
- 2017–2019 — Co-Investigator: US Air Force Office of Scientific Research / EOARD · Novel photomechanics approaches to determine the intra- and inter-laminar properties of composites at high rates of strain · US$125k.
- Professional roles: National Committee Member, British Society for Strain Measurement; Industrial Advisory Board Member, Materials Engineering, University of Sheffield; and contributor to the International Digital Image Correlation Society Stereo DIC Challenge.
- Review and mentoring: peer reviewer for UKRI Future Leaders Fellowship applications and journals including Experimental Mechanics, Strain and Journal of Dynamic Behavior of Materials; internal mentor and proposal reviewer for fellowship and external-funding applicants.
- Strategic contribution: promotion-in-post panels across UKAEA's Materials, Integrated Engineering and Computing Divisions; Fusion Technology Division Landscape and Technology Strategy Review panel; and programme development for cross-divisional Virtual Qualification activities.
- Chartered Engineer and Member of the Institution of Mechanical Engineers (CEng, MIMechE).
2026: Invited Research Seminar, Department of Engineering Science, University of Oxford (invited by Dr Aaron Graham). 2025: Invited Presentation, Henry Royce Institute CDT Student Conference. Recurring: invited teaching at the University of Sheffield, University of Liverpool, Fusion Power CDT and Fusion Engineering CDT.
Earlier invited seminars and lectures are retained in previous full CV records.
26. R. Spencer, L. Fletcher, R. Hamill, C. Hamelin and A. Harte,
"Design of a Materials Testing 2.0 Creep Test Using the Virtual Fields Method and Open Source Tools."
Experimental Mechanics, 2026.
DOI: 10.1007/s11340-026-01360-9
25. J. T. Horne-Jones, M. Baxter, A. Tayeb, L. Fletcher, J. Paterson, S. Biggs-Fox and A. Harte,
"Towards Virtual Qualification in Nuclear Fusion: Demonstrating Probabilistic Model Validation on a High Heat Flux Component."
arXiv:2605.11886, 2026. Submitted to ASME Journal of Verification, Validation and Uncertainty Quantification.
24. J. Hirst, L. Sibson, A. Tayeb, B. Poole, M. Sampson, W. Bielajewa, M. Atkinson, A. Marsh, R. Spencer, R. Hamill, C. Hamelin, A. Harte and L. Fletcher,
"PYVALE: A Fast, Scalable, Open-Source 2D Digital Image Correlation (DIC) Engine Capable of Handling Gigapixel Images."
arXiv:2601.12941, 2026. Under review in Experimental Mechanics.
23. L. Fletcher, J. Hirst and W. Bielajewa,
"Riley: A Computational Framework for Higher-Order Finite Element Image Synthesis Applied to Digital Image Correlation Uncertainty Quantification."
engrXiv preprint, 2026. Under review in Engineering with Computers.
22. A. Tayeb, L. Fletcher, M. Gorley, A. Harte and C. Hamelin,
"Image-Based Deformation Measurements of Fusion Divertor Armour Under High Heat Flux Loading."
The Journal of Strain Analysis for Engineering Design, 61(4), 267–283, 2026.
DOI: 10.1177/03093247251414309
21. L. Fletcher and F. Pierron,
"Analysing the High Strain Rate Behaviour of Cortical Bone with the Image-Based Inertial Impact (IBII) Test."
Journal of Dynamic Behavior of Materials, 11, 562–583, 2025.
DOI: 10.1007/s40870-025-00478-6
20. R. Spencer, L. Fletcher, M. Gorley, C. Hamelin and A. Harte,
"Robust Assessment of Post-Localisation Hardening Behaviour in Eurofer97 using Inverse Finite Element Methods."
Strain, 2024.
19. E. J. Muttio, W. G. Dettmer, J. Clarke, D. Perić, Z. Ren and L. Fletcher,
"A supervised parallel optimisation framework for metaheuristic algorithms."
Swarm and Evolutionary Computation, 84, 101445, 2024.
DOI: 10.1016/j.swevo.2023.101445
18. C. B. Burson-Thomas, T. J. Harvey, L. Fletcher, R. Wellman, F. Pierron and R. J. K. Wood,
"Investigating high-speed liquid impingement with full-field measurements."
Proceedings of the Royal Society A, 479, 20230023, 2023.
DOI: 10.1098/rspa.2023.0023
17. L. R. Humphrey, A. J. Dubas, L. Fletcher and A. Davis,
"Machine learning techniques for sequential learning engineering design optimisation."
Plasma Physics and Controlled Fusion, 66, 025002, 2023.
DOI: 10.1088/1361-6587/ad11fb
16. T. R. Barrett, M. Bamford, B. Chuilon, T. Deighan, P. Efthymiou, L. Fletcher, M. Gorley, T. Grant, T. Hall, D. Horsley, M. Kovari and M. Tindall,
"The CHIMERA facility development programme."
Fusion Engineering and Design, 194, 113689, 2023.
DOI: 10.1016/j.fusengdes.2023.113689
15. L. Fletcher, F. Davis, S. Dreuilhe, A. Marek and F. Pierron,
"High strain rate elasto-plasticity identification using the image-based inertial impact test (IBII) — Part 1: Error quantification."
Strain, 57, e12374, 2021.
DOI: 10.1111/str.12374
14. L. Fletcher, F. Davis, S. Dreuilhe, A. Marek and F. Pierron,
"High strain rate elasto-plasticity identification using the image-based inertial impact test (IBII) — Part 2: Experimental validation."
Strain, 57, e12375, 2021.
DOI: 10.1111/str.12375
13. S. Parry, L. Fletcher and F. Pierron,
"The Off-Axis IBII Test for Composites."
Journal of Dynamic Behavior of Materials, 7, 127–155, 2021.
DOI: 10.1007/s40870-020-00271-7
12. J. Van Blitterswyk, L. Fletcher and F. Pierron,
"Investigation of the 2D assumption in the image-based inertial impact test."
Strain, 57, e12369, 2021.
DOI: 10.1111/str.12369
11. J. Van Blitterswyk, L. Fletcher and F. Pierron,
"Image-Based Inertial Impact Tests for Measuring the Interlaminar Shear Moduli of Composites."
Journal of Dynamic Behavior of Materials, 6, 373–398, 2020.
DOI: 10.1007/s40870-020-00258-4
10. L. Fletcher and F. Pierron,
"The Image-Based Inertial Release (IBIR) Test: A New High Strain Rate Test for Stiffness Strain-Rate Sensitivity Identification."
Experimental Mechanics, 60, 493–508, 2020.
DOI: 10.1007/s11340-019-00580-6
9. T. Fourest, P. Bouda, L. Fletcher, D. Notta-Cuvier, E. Markiewicz, F. Pierron and B. Langrand,
"Image-Based Inertial Impact Test for Characterisation of Strain Rate Dependency of Ti6Al4V Titanium Alloy."
Experimental Mechanics, 60, 235–248, 2020.
DOI: 10.1007/s11340-019-00559-3
8. F. Pierron and L. Fletcher,
"Generalized stress–strain curves for IBII tests on isotropic and orthotropic materials."
Journal of Dynamic Behavior of Materials, 5, 180–193, 2019.
DOI: 10.1007/s40870-019-00197-9
7. L. Fletcher, J. Van-Blitterswyk and F. Pierron,
"A novel image-based inertial impact test (IBII) for the transverse properties of composites at high strain rates."
Journal of Dynamic Behavior of Materials, 5, 65–92, 2019.
DOI: 10.1007/s40870-019-00186-y
6. L. Fletcher and F. Pierron,
"An image-based inertial impact (IBII) test for tungsten carbide cermets."
Journal of Dynamic Behavior of Materials, 4, 481–504, 2018.
DOI: 10.1007/s40870-018-0172-4
5. J. Van-Blitterswyk, L. Fletcher and F. Pierron,
"Image-based inertial impact test for composite interlaminar tensile properties."
Journal of Dynamic Behavior of Materials, 4, 543–572, 2018.
DOI: 10.1007/s40870-018-0175-1
4. J. Van-Blitterswyk, L. Fletcher and F. Pierron,
"Characterisation of the Interlaminar Properties of Composites at High Strain Rates: A Review."
Advanced Experimental Mechanics, 2, 3–28, 2017.
DOI: 10.11395/aem.2.0_3
3. M. V. Nguyen, J. Codrington, L. Fletcher, C. W. Dreyer and W. J. Sampson,
"Influence of cortical bone thickness on miniscrew microcrack formation."
American Journal of Orthodontics and Dentofacial Orthopedics, 152, 301–311, 2017.
DOI: 10.1016/j.ajodo.2016.12.028
2. M. V. Nguyen, J. Codrington, L. Fletcher, C. W. Dreyer and W. J. Sampson,
"The influence of miniscrew insertion torque."
European Journal of Orthodontics, 2017.
DOI: 10.1093/ejo/cjx026
1. L. Fletcher, J. Codrington and I. Parkinson,
"Effects of fatigue induced damage on the longitudinal fracture resistance of cortical bone."
Journal of Materials Science: Materials in Medicine, 25, 1661–1670, 2014.
DOI: 10.1007/s10856-014-5213-5
L. Fletcher, J. Van-Blitterswyk and F. Pierron,
A Manual for Conducting Image-Based Inertial Impact (IBII) Tests.
University of Southampton, 2019.
DOI: 10.5258/SOTON/P0015
Open-source software: Pyvale, including Pyvale DIC, for virtual experimentation and Digital Image Correlation; and Riley for high-performance scientific rasterisation and camera simulation.
Research and teaching in structural and experimental mechanics; primary and co-supervision of doctoral and undergraduate researchers; and attracted £28k industrial consultancy from JRM Engineering on behalf of Subaru, Japan, applying image-based dynamic-test methods to carbon-fibre composites.
Imaging Impact: Image-Based Methods for Dynamically Testing Bone — independent ~£82k fellowship developing image-based mechanical tests for identifying the dynamic properties of bone.
Developed new high-strain-rate materials-testing methods using ultra-high-speed imaging and inverse identification.
Developed methods for composites, ceramics, adhesives, polymers and metals; created open workflows linking finite-element simulation, experimental design, imaging and inverse analysis; collaborated with Solvay and the US Army Research Laboratory; and produced an open-access methodology manual.
International collaborative project investigating fracture mechanisms in an ovine osteoporosis model.
Experimental characterisation of a bio-adhesive derived from frog protein.
Thesis: Fatigue-Fracture Interaction Mechanisms in Cortical Bone.
Experimental and numerical investigation of fatigue-induced degradation of cortical-bone fracture resistance and associated hierarchical toughening mechanisms.
Bachelor of Engineering — First Class Honours, Mechanical and Aerospace Engineering, University of Adelaide · 2008–2011
Honours project: Contribution of the Organic and Inorganic Constituents to the Fracture Resistance of Cortical Bone.
© Lloyd Fletcher. The contents of this CV are provided for reference and may not be reproduced or redistributed without permission.