The port-Hamiltonian (pH) formalism provides a general framework for the modeling, analysis and control of complex dynamical systems. It generalizes classical Hamiltonian dynamics with respect to dissipative effects and formalizes the interaction between multiple open systems. In the present talk we deal with the pH modeling and space-time discretization of flexible multibody systems. In particular, the geometrically nonlinear Simo-Reissner beam model will be considered as representative structural component of a flexible multibody system. Starting with the pH formulation of the infinite-dimensional beam model the finite element discretization yields a corresponding semi-discrete formulation, retaining the pH structure. We will show that the energy-based pH approach opens new avenues to the design of structure-preserving discretizations in space and time. In particular, a new class of energy-momentum consistent schemes emanating from the pH formulation will be presented.

Peter Betsch is full professor of mechanics at the Karlsruhe Institute of Technology (KIT), Germany. His main research interests lie in the field of computational mechanics with focus on nonlinear structural and continuum mechanics, flexible multibody dynamics, coupled problems, finite element technology, optimal control, and inverse dynamics problems. In this connection, he is particularly interested in the design of structure-preserving numerical methods. He earned his Diploma degree in Aerospace Engineering from the University of Stuttgart in 1991, his Doctor degree from the University of Hanover in 1996 and, after a post-doc stay at the University of California at Berkeley in 1997, he finished his Habilitation degree at the University of Kaiserslautern in 2002. In 2003 he was appointed full professor of computational mechanics at the University of Siegen before he moved to KIT in 2013.

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Karin Nachbagauer is a Professor for Applied Mathematics at the University of Applied Sciences, Upper Austria, Campus Wels, Austria, and holds a position as visiting Research Professor as a Hans Fischer Fellow at the Institute for Advanced Studies of the Technical University of Munich (IAS-TUM). Her research focuses on the adjoint method for inverse problems in multibody dynamics, computational mechanics and human-robot interaction. She is the main developer of the FreeDyn multibody software which is used for research developments and in teaching of mechanical engineering and multibody systems. Karin Nachbagauer is also Principal Investigator at the Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich, and manages a research group on soft robotics at TUM and a research group on human-robot interaction at the University of Applied Science in Wels.

The flexibility and robustness of current robots is limited by their lack of understanding of their environment. For this reason, most robots operate in controlled environments. Machine learning can circumvent modeling problems but introduces new problems of generalizing from examples. How can robots acquire understanding (of structure, function, causality, etc.) that allows them to generalize from sparse experience? Motivated by shortcomings of current machine-learning methods, I will argue that "understanding" is a meaningful notion in AI that reaches beyond prediction and control. I will discuss examples of our recent work on learning visual relational concepts, extrapolation of learned movements beyond the training distribution, learning of symbolic concepts and rules, and structure-driven skill learning from sensorimotor experience. Our long-term objective is to improve abstraction, generalization, robustness, and ultimately explainability of robot perception and action.

Justus Piater is a Professor of computer science at the University of Innsbruck, Austria where he leads the Intelligent and Interactive Systems group. He earned his Ph.D. degree at the University of Massachusetts Amherst, USA, and was a visiting researcher at the Max Planck Institutes for Biological Cybernetics and for Intelligent Systems in Tübingen, Germany. His research interests focus on learning and inference in sensorimotor systems that was published in more than 200 papers, several of which have received best-paper awards. He is an ELLIS Fellow. At the University of Innsbruck he served as Dean of the Faculty of Mathematics, Computer Science and Physics and is the founding director of the Digital Science Center.

Non-smooth multibody dynamics is characterized by set-valued force laws and discontinuous impact-like events. It has significant applications across various fields, including robotics, automation, video games, virtual reality and aerospace, to name a few. These systems often involve impacts, friction and other discontinuities that challenge traditional smooth dynamics approaches. The non-smooth nature of these systems presents several challenges, such as the need for advanced numerical methods and computational tools to handle discontinuities and non-linearities, where variational inequalities (often in form of complementarity problems) must be solved at discrete time steps. Future perspectives in non-smooth dynamics research include the development of more efficient complementarity solvers for real-time applications, scalable parallel algorithms for large-scale problems such as granular flows, new time integration methods, more robust and efficient collision detection algorithms, and efficient support of deformable parts with contacts and self-contacts. Applications and practical examples will be discussed.

Alessandro Tasora is a Full Professor in Applied Mechanics at the University of Parma, Italy. Member of the ASME. His research focuses on multibody dynamics, computational non-smooth mechanics, vehicle dynamics and robotics. He is the author of the ProjectChrono software library, a popular multi-physics tool used in many research centers to implement multi-flexible-body simulations. Alessandro Tasora is also the Director of the Digital Dynamics Lab at the University of Parma and co-founder and member of the Board of SpaceGlass, and has been a key figure in several academic, editorial and research initiatives. He is coordinator of the Kinematics and Dynamics of Multibody Systems group of the AIMETA association, and he is member of the Editorial board of Multibody System Dynamics. He is Director of the International Multibody Summer School, an event that takes place yearly since 2016.

With the development of space technology, the demand for large space structures has increased, such as large space telescopes, satellite antennas and space stations. Due to their extremely large size and complex configuration, these structures must be constructed through modular deployment or on-orbit assembly. The flexible multibody dynamics simulation is a key tool, sometimes the only tool, for designing the dynamic characteristics of these structures because of the limitation of the ground experiments caused by gravity. In the framework of flexible multibody dynamics, this presentation first introduces our research team’s achievements in the dynamic modeling method for moving flexible bodies. Then, the contact dynamics modeling using the complementary method is described. After that, numerical algorithms, such as variational algorithms, parallelization algorithms developed for different cases are also presented. Finally, some applications, advancements, and experimental verifications are provided.

Qiang Tian is Professor at the Beijing Institute of Technology (BIT), China. In 2009, he received his PhD degree from Huazhong University of Science and Technology, China. From 2014 to 2015, he visited the University of Illinois at Chicago (UIC), US. He received China’s National Science Fund for Distinguished Young Scholars in 2021. He is currently an associate editor of Mechanism and Machine Theory and an editorial board member of Multibody System Dynamics.

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