🤖 AI Summary
This study addresses the challenge posed by time-varying configurations in sliding beam systems, where conventional fixed modal coordinates become invalid and online-updated modal bases often suffer from semantic drift. To overcome this, the authors propose a global reduced-order basis method tailored for sliding beams: a unified low-dimensional basis is extracted via Proper Orthogonal Decomposition (POD) from a snapshot matrix of modal responses and embedded within a constrained multibody dynamics framework to accommodate continuous sliding motion. This approach preserves essential dynamic characteristics while eliminating inconsistencies in modal coordinate interpretation. Numerical simulations under highly flexible beam conditions, time-varying loads, and active sliding demonstrate approximately 90% reduction in computational time, with root-mean-square displacement errors maintained below 2%.
📝 Abstract
Model order reduction decreases the dimension of a mechanical system by introducing modal coordinates that retain important dynamic characteristics. Sliding beams, as found in telescopic structures, pose a fundamental challenge. Fixed modal coordinates fail to capture evolving system properties, and updating the modal basis during simulation causes modal coordinates to change meaning. The present work addresses this challenge by constructing a global reduction basis for a sliding beam. The global basis is constructed from snapshots in the form of modal matrices and compressed using proper orthogonal decomposition. Reduction is applied within a constraint multibody formalism with algebraically enforced constraints that permit continuous slider movement. The method is validated against an absolute nodal coordinate formulation of a sliding beam with a sliding joint. Different combinations of snapshot quantity and eigenmodes per snapshot are investigated and an error map is shown. A challenging test case involving a highly flexible beam subjected to time-dependent loading and slider movement demonstrates that the global reduction basis reduces computation time by approximately 90% while keeping the root-mean-square displacement error, introduced by the global reduction, below 2%.