TY - INPR A1 - Schulz, Carsten A1 - Graneß, Henry A1 - Weinzierl, Stefan A1 - Nicklas, Johannes T1 - Eigenvalue perturbation in drivetrain analysis and optimization N2 - The optimization of the dynamic behavior of drive systems often involves targeted modifications of the system characteristics. Structural and parametric modifications are used to satisfy the constraints of the dynamic requirements. However, many optimizations are still achieved by intuition or parameter variations, even though more streamlined and easy-to-implement tools such as the eigenvalue perturbation method are available. In this article, the eigenvalue perturbation method in the form of an eigenvalue sensitivity analysis is used to efficiently optimize the dynamic behavior for two different use cases using different optimization measures. This paper demonstrates, how eigenvalue perturbation theory can efficiently optimize drivetrain dynamics by systematically modifying system parameters. Two case studies show how eigenvalue sensitivity analysis achieves targeted frequency shifts to avoid resonances: (1) adapting shaft stiffness and control parameters in a torsional drivetrain, and (2) optimizing structural modifications in a wind turbine bedplate. The study introduces the eigenvector tensor product as a weighting matrix, identifying key parameters for effective redesign. Compared to conventional parameter studies, this method enables precise control over system dynamics with minimal computational effort, making it highly applicable for vibration mitigation and drivetrain optimization. Y1 - 2025 U6 - https://doi.org/10.21203/rs.3.rs-6368754/v1 PB - Research Square Platform LLC ER - TY - INPR A1 - Vogl, Yannick A1 - Schulz, Carsten A1 - Schaeffer, Thomas A1 - Geiger, Benjamin T1 - Prediction of the wear behavior of a conveyor belt with flexible rollers N2 - This paper introduces a method to predict wear behavior in conveyor belt systems using a lumped mass modeling approach. While previous research has focused primarily on lateral belt walking, this study shifts attention to belt deformation and its associated wear. Both significantly affect system efficiency and component lifespan. The authors propose using local frictional power as a wear indicator, leveraging its direct relation to frictional work in established wear models. To validate the method, the study simulates a conveyor belt with three flexible rollers and a deformable belt modeled through rigid spheres connected by spring-damper elements. The authors quantify and visualize frictional power density across the belt width, distinguishing between running and transverse directions. The results demonstrate that the frictional power distribution depends heavily on discretization quality, particularly due to the polygon effect inherent in the lumped mass approach. A convergence analysis reveals a minimum discretization of nine sphere rows with 557 spheres per row to achieve reliable qualitative insights. This method enables researchers to evaluate wear distribution in flexible conveyor systems and adapt the approach for broader applications in multibody dynamics. Future work should refine discretization techniques and friction models to enhance quantitative accuracy. Y1 - 2025 U6 - https://doi.org/10.21203/rs.3.rs-6343500/v1 N1 - Der Aufsatz wurde peer-reviewed veröffentlicht und ist ebenfalls in diesem Repositorium verzeichnet unter: https://opus4.kobv.de/opus4-oth-regensburg/8489 PB - Research Square Platform LLC ER -