Embedded Files
The UKACM 2026 School will focus on Advanced Computational Methods in Engineering, including large deformation analysis, data-driven multi-scale analysis and high-fidelity simulation.
Alessandro Franci is an Associate Professor at the Universitat Politècnica de Catalunya (UPC) in Barcelona, Spain, and an Associate Research Professor at the International Centre for Numerical Methods in Engineering (CIMNE), also in Barcelona. He is an expert in numerical methods and computational mechanics, with research focused on the numerical simulation of Newtonian and non-Newtonian free-surface flows, fluid–structure interaction, thermally coupled problems, and granular media.
Franci obtained both his Bachelor's and Master's degrees in Civil Engineering from the Politecnico di Milano, Italy, and completed his PhD in Structural Analysis at UPC in 2015. His doctoral thesis received the SEMNI Prize, awarded by the Spanish Society of Numerical Methods in Engineering to the best PhD thesis in Numerical Methods in Spain, and the PIONEER Prize, awarded by the Agency of Catalan Research Centres (CERCA).
He has served on the Scientific Committee and organized multiple symposia for several conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Franci co-chaired the PARTICLES - ECCOMAS conference in Milan in 2023 and in Barcelona in 2025. He is also the director of the Particles Course, an ECCOMAS advanced course designed to provide an overview of the theory and applications of the most widely used particle methods.
Course Description
Course Description
Topic: The Particle Finite Element Method: A Powerful Tool For Simulating Large-Deformation Problems
The Particle Finite Element Method (PFEM) has emerged as a robust and versatile numerical technique for tackling challenging problems involving large deformations, free surface flows, and fluid-structure interaction phenomena. By combining the advantages of particle-based and mesh-based methods, PFEM enables accurate tracking of evolving geometries and interfaces without the limitations of mesh distortion commonly encountered in standard finite element methods. This talk provides a comprehensive introduction to the fundamental concepts of PFEM, followed by its application to a range of complex engineering problems. Particular emphasis will be placed on the simulation of major natural hazards, such as landslides and landslides-generated wave events.
Kostas Karapiperis is an Assistant Professor at EPFL, where he directs the Data-Driven Mechanics Laboratory (LMD). His research is focused on the intersection of mechanics of materials and data science, with applications ranging from geomechanics to structural mechanics. Prior to EPFL, he worked as a Postdoctoral Researcher and Lecturer at the Department of Mechanical and Process Engineering of ETH Zürich, supported by a Marie Skłodowska-Curie Fellowship. He received his PhD in Applied Mechanics and a Minor in Applied Mathematics from the California Institute of Technology (U.S.A), following his MSc in Civil Engineering at the University of California, Davis (U.S.A), and his BSc also in Civil Engineering at the National Technical University of Athens, Greece.
Course Description
Topic: Data-driven multiscale modeling
Topic: Data-driven multiscale modeling
Multiscale modeling is a key tool in computational mechanics, enabling the prediction of material behavior by leveraging information from lower scales, when conventional constitutive models are insufficient. However, multiscale methods often suffer from high computational cost and complexity. In this lecture, we showcase recent advances in data-driven and learning-based methods and discuss how they can help address these challenges. We emphasize on linking microstructural features to macroscopic properties, combining simulations with experimental data, while incorporating physics and thermodynamics to enhance the models' robustness and generalization capabilities. Applications are drawn from real problems involving the prediction of the nonlinear behavior of geomaterials and structural materials. The lecture focuses on practical understanding of the methods, while also discussing their current limitations.
Liang Yang is a Lecturer at Cranfield University and the founder of Voxshell, a Cranfield spin-out company leading the entrepreneurial pathway in computational engineering. His academic research focuses on the development of computational models for complex multiphysics problems, including fluid dynamics, solid mechanics, and thermal transport.
Before joining Cranfield, Liang worked as PDRA at City, University of London, and Imperial College London. He earned his PhD in Computational Mechanics from Swansea University, and holds dual MSc degrees in Computational Mechanics from Swansea University and the Universitat Politècnica de Catalunya (UPC).
Course Description
Topic: The Future of Generative Design: Bridging Implicit Geometry and Simulation
Topic: The Future of Generative Design: Bridging Implicit Geometry and Simulation
Generative design is undergoing a fundamental shift—from traditional boundary-based modeling to implicit representations that enable greater geometric complexity, automation, and performance. This talk explores the emerging computational pipeline that links implicit geometry generation directly to high-fidelity simulation, enabling robust analysis of fluid, solid, and radiation phenomena within a single unified framework.
I will present recent advances in geometry creation using signed distance fields, followed by novel mesh generation techniques that preserve fidelity while ensuring solver compatibility. A key focus will be on how these meshes feed into scalable solvers for fluid dynamics, structural mechanics, and radiation transport, enabling accurate, multiphysics analysis for highly complex parts. By bridging generative design and simulation, this workflow reduces human intervention, improves robustness, and accelerates iteration cycles—unlocking new opportunities for advanced manufacturing and high-performance engineering. Generative design is undergoing a fundamental shift—from traditional boundary-based modeling to implicit representations that enable greater geometric complexity, automation, and performance. This talk explores the emerging computational pipeline that links implicit geometry generation directly to high-fidelity simulation, enabling robust analysis of fluid, solid, and radiation phenomena within a single unified framework.
Page updated
Google Sites
Report abuse