MS134 - Multiphysics-Driven Fracture & Damage Simulation: Bridging Scales and Fields

Organized by: L. Poh (National University of Singapore, Singapore), S. Natarajan (Indian Institute of Technology Madras, India), R. Peerlings (Eindhoven University of Technology, Netherlands), A. Menzel (TU Dortmund University, Germany) and H. Waisman (Columbia University, United States)
Keywords: Damage, Multiphysics, Fracture, Multiscale;
Understanding and predicting material failure in natural and engineered structures subjected to multiphysics loading conditions and under the influence of multiscale effects is of paramount importance. Traditional approaches to fracture and damage modelling often fall short when faced with real-world scenarios involving coupled physical phenomena - such as thermal gradients, chemical reactions, fluid-structure interactions, electromagnetic effects, to name a few, that interact with mechanical response. Furthermore, underlying microstructure plays a crucial role. As a result, multi-physics & multi-scale driven simulations have emerged as a critical framework to capture the interplay of these diverse processes. This evolving field aims to unify mechanical fracture mechanics with other physical systems, enabling more accurate and predictive models. Recent advances in computational power, numerical methods (XFEM, VEM, peridynamics, thick level set, lipfield, localised gradient damage model, phase-field models) and data-driven techniques are fuelling the progress in this domain. Moreover, integration of multiscale modeling allows researchers to link microstructural evolution with observable macroscopic failure, enhancing material design and preventive failures. The aim of this mini-symposium is twofold: (a) bring together experts from computational mechanics, material science and applied physics to explore the frontiers of fracture and damage modeling in multiphysics and multiscale environments and (b) identify key challenges, share novel computational methods and foster collaboration towards developing robust, reliable predictive numerical frameworks capable of addressing the complexity of real-world material and structures.