Data-Centric Engineering is delighted to partner with Institute of Physics (IOP) workshop on Physics Enhancing Machine Learning in Applied Solid Mechanics.
This event aims to demonstrate advanced techniques and industrial applications showcasing recent progress in this area, and the strengths and limitations of using physics knowledge to enhance Machine Learning strategies in applied solid mechanics. Contributions of particular interest are those that focus on how physics domain knowledge and the availability of a causal physics-based model enable one to move from accurate-but-wrong predictions, to explainable and interpretable inferences fully exploiting machine learning techniques in applied solid mechanics.
This special collection gathers together articles deriving from the event. Articles accepted into the workshop are given the option of submitting a fully developed research paper to DCE, which undergoes the standard DCE peer review process. Articles are published as soon as ready. Those published to date are below, but further content from both 2022 and 2023 editions of the workshop will follow shortly.
Guest Editors:
- Alice Cicirello (University of Cambridge)
- Zack Xuereb Conti (The Alan Turing Institute)