Plenary Speakers

Dr Jim Reed (EDF Energy)

Dr Jim Reed is Chief Graphite Engineer of EDF Energy Nuclear Operations and is one of the UK's leading specialists in nuclear graphite. He provides technical oversight, governance and independent assurance for the UK graphite programme, which supports the safe operation, inspection and life extension of the UK's Advanced Gas-cooled Reactors (AGRs).

Dr Reed has worked continuously in the UK nuclear industry since 1981, spanning the Central Electricity Generating Board, Nuclear Electric, British Energy and EDF Energy. He has more than 40 years of experience in graphite behaviour, reactor core assessment and safety case development. Before becoming Chief Graphite Engineer, he served for over 20 years as Group Head of Graphite and led the graphite research and assessment programme responsible for understanding reactor graphite behaviour from fundamental materials science through to whole-core structural performance.

Mathematical modelling is a key part of understanding the ageing and degradation of the graphite cores – which is a key component of the station lifetime.

Talk Title: Computational Analysis Supporting the Safe Operation of UK Nuclear Reactors covering the complete size range from atomic scale to whole structure some 10m across

Abstract

Computational modelling plays a central role in demonstrating the continued safe operation of AGR graphite cores. Advanced analysis methods are used to predict irradiation-induced changes in graphite behaviour, assess core distortion and component interaction, and forecast future reactor conditions throughout extended operating lifetimes. These models integrate material science, structural mechanics and whole-core behaviour and are benchmarked against reactor inspections and experimental evidence. The resulting assessments provide a key part of the safety case by supporting engineering judgement, quantifying margins, and demonstrating that the graphite core will continue to perform its safety functions throughout the planned operating life of the reactor.

Prof Silvia Budday (Friedrich-Alexander-Universität Erlangen-Nürnberg)

Silvia Budday, currently a Full Professor heading the Institute of Continuum Mechanics and Biomechanics (LKM) at Friedrich-Alexander-Universität Erlangen-Nürnberg, studied Mechanical Engineering at the Karlsruhe Institute of Technology (KIT). During her Master’s studies, she spent one year at Purdue University, Indiana, USA.

For her PhD on “The Role of Mechanics during Brain Development” at FAU, she received the GACM Best PhD Award (German Association for Computational Mechanics) 2017, the ECCOMAS Best PhD Award (European Community on Computational Methods in Applied Sciences), and the Bertha Benz-Prize from the Daimler und Benz Stiftung as a woman visionary pioneer in engineering. 

Since April 2019, she had been leading a research group in the Emmy Noether-Programme by the German Research Foundation (DFG) on BRAIn mechaNIcs ACross Scales (BRAINIACS). In 2021, she was awarded the Heinz Maier-Leibnitz-Prize by the DFG and BMBF and the Richard-von-Mises-Prize by the International Association of Applied Mathematics and Mechanics (GAMM). In 2023, she received an ERC Starting Grant for her project “Mechanics-augmented brain surgery (MAGERY)”. Her work focuses on experimental and computational soft tissue biomechanics with special emphasis on brain mechanics and the relationship between material properties, structure, and function. 

Talk Title: Computational modeling of brain mechanics in health and disease 

Abstract

The brain is one of our most complex organ systems. Despite decades of intense research, many fundamental processes and diseases are still not fully understood. While a large body of literature exists regarding the role of chemical signaling in regulating brain function, only more recently the important contribution of mechanical stimuli has been discovered. To fully understand brain development, homeostasis, and pathology, it is therefore key to explore mechanics as an important puzzle piece. This requires close interdisciplinary exchange as brain tissue is not only ultrasoft, biphasic, and highly heterogeneous, but also continuously changes its microstructural composition and architecture as well as its mechanical properties – in close relation to evolving brain function. Computational models based on nonlinear continuum mechanics can valuably complement experimental studies to systematically understand the mechanisms underlying mechanics-regulated biological and biomedical processes. In addition, they can allow for data transfer across species and scales, and eventually pave the way for personalized clinical predictions. Here, we present a pipeline combining experiments, microstructural analyses, continuum mechanics modelling and finite element simulations to predict how the brain develops or behaves during a surgical procedure. We highlight the great potential of mechanics-based diagnosis and treatment of neurological disorders and point towards open challenges that we still need to address before translation into the clinics becomes possible. 

Prof Patrick E. Farrell (University of Oxford) 

Patrick Farrell is a Professor in the numerical analysis group at the University of Oxford, and a visiting professor in the faculty of mathematics and physics at Charles University in Prague. His research interests are in the numerical solution of partial differential equations arising in physics and chemistry. He is also employed as a specialist consultant at the UK Atomic Energy Authority.

He obtained his bachelor’s degree in mathematics from the University of Galway, and his doctorate from Imperial College London in 2010. His doctoral thesis won the Roger Owen prize from the UK Association for Computational Mechanics and the Janet Watson prize from Imperial.

He has been awarded an EPSRC Early Career Research Fellowship (2013-2018), the 2015 Wilkinson Prize for Numerical Software, second place in the 2015 Leslie Fox Prize in Numerical Analysis, the 2020 Charles Broyden Prize in optimisation, a 2021 Whitehead Prize from the London Mathematical Society, and the 2025 SIAM Germund Dahlquist Prize. In 2026 he was elected a Fellow of the Society for Industrial and Applied Mathematics. He gave an invited section lecture at the International Congress of Mathematicians in 2026.

Talk Title: Enforcing conservation laws and dissipation inequalities numerically via auxiliary variables 

Abstract

Initial-value problems for ordinary and partial differential equations often possess conservation laws (e.g. for energy) and dissipation inequalities (e.g. for entropy). Standard discretisation methods, such as many Runge-Kutta and multistep schemes, usually do not preserve these structural properties. In this talk, we present a general strategy for simultaneously enforcing multiple conservation laws and dissipation inequalities in the numerical solution of initial-value problems. The key idea is to systematically modify a starting discretisation so that the continuous arguments establishing conservation and dissipation carry over to the discrete level. Each conservation law or dissipation inequality is represented by an associated test function; we introduce auxiliary variables for the projections of these test functions onto a discrete test set, and modify the equation to use these new variables. We demonstrate this strategy by applying it to Hamiltonian ordinary and partial differential equations, geometric flows, the incompressible and compressible Navier-Stokes equations, and a viscoelastic model. In each case, the strategy yields discretisations with new and useful properties. In several cases, preserving conservation and/or dissipation laws appears to offer considerable qualitative advantages over preserving other structures, such as symplecticity.

Dr Ted O'Hare (Arup) - UKACM 2025 Roger Owen Prize

Dr Ted O’Hare is a geotechnical engineer at Arup and a researcher in computational geomechanics. His research focuses on robust simulation methods for large-deformation geotechnics, nonlinear continuum modelling, and the mechanics of failure in geomaterials. He completed his PhD in Computational Mechanics at Durham University in 2025, investigating strain localisation using generalised continuum modelling and the Material Point Method (MPM). His doctoral research received the 2025 UKACM Roger Owen Prize, and he was runner-up for the 2026 ALERT Geomaterials Ioannis Vardoulakis PhD Prize. Following a brief postdoctoral position at Durham University investigating drag-anchor embedment using the MPM, he joined Arup in April 2026, where he applies numerical modelling to energy, infrastructure and offshore design projects and research. 

Talk Title: Capturing Localised Failure in Geomaterials Beyond the Classical Continuum 

Abstract

Strain localisation is a fundamental mechanism of failure in geomaterials, but its numerical modelling presents significant challenges. In conventional continuum formulations, the onset of strain-softening leads to pathological mesh dependence, undermining the reliability of computational predictions. Mesh-based techniques can also break down under the large deformations associated with geotechnical failure events.

This talk presents a nonlinear micropolar (Cosserat) approach to modelling strain localisation in geomaterials. By incorporating independent grain-scale microrotations and intrinsic length scales, micropolar continuum theory provides a physically motivated framework for capturing localised deformation beyond the limitations of classical continua. The approach is implemented within the Material Point Method, combining finite-strain elastoplastic continuum modelling with a numerical framework suited to problems involving large deformation. The talk will introduce the underlying theory and its computational implementation, before presenting numerical examples demonstrating its application to strain localisation in geomaterials. Particular attention will be given to the relationship between constitutive length scales and numerical resolution, as well as the predicted structure of localised deformation and its post-peak evolution.