Virtual prototyping is crucial in modern product development cycles as it is used to reduce development cost and time. The development of digital twins of production equipments is the key to achieve automation but requires significant scientific advances in digital models guaranteeing accurate physical behavior. In particular, highly slender flexible structures are often the critical components that hamper the full automation.

Current engineering software tools achieve good performance with flexible components for small deformations, but they struggle with highly flexible structures which are of high importance for example in medical applications. Their mechanical response is complex and occurs at different spatial and temporal scales.

With this minisymposium we want to address the interplay between the newest digital tools including neural networks and the mechanical and geometric modelling of highly flexible slender and multi-body systems. We want to discuss challenges and opportunities of AI tools in this field of engineering, mathematical guarantees of correct mechanical behaviour in traditional and in neural networks approximations, and the vast unexploited potential in industrial applications.

The minisymposum will include talks on new AI tools as well as more traditional digital approaches relevant for solving these scientific and industrial challenges. We will discuss a variety of engineering problems and applications within the field of highly flexible slender structures, including scientific computing and geometric numerical approaches (analysis and algorithms) and the physically sound integration of deep learning methodologies.