Gear design and analysis are fundamental aspects of mechanical engineering, particularly due to their extensive applications in industries such as automotive, aerospace, and marine. In power transmission systems, gears must meet strict performance requirements to ensure efficiency and durability. Recent advancements in materials science have led to increased research on composite materials in gear design, offering improved performance over conventional materials. This study examines the comparative effectiveness of contact and bending stress in pure HDPE spur gears versus HDPE reinforced with TiO 2 and SiO 2 composites. Using ANSYS Workbench, the contact and bending stresses between polymer gear pairs are analyzed through simulation, modeling their behavior under applied torque loads. The study provides a detailed three-dimensional analysis of gear tooth interactions, treating the contact between teeth as a dynamic engagement. Torque is applied to the driving gear under controlled loads, while the driven gear is constrained to facilitate an in-depth stress evaluation around the gear teeth. The results indicate that HDPE-TiO 2 -SiO 2 composite spur gears exhibit significantly improved performance in managing contact and bending stresses compared to pure HDPE gears, demonstrating their potential for enhanced durability and reliability in demanding applications
This study employs finite element analysis to evaluate the influence of office chair headrest curvature and inclination angle on head-headrest interaction. A computational model, incorporating the Ogden Foam constitutive model for the soft material, was developed. Results indicate that while headrest curvature and inclination have minimal impact on overall deformation, the inclination angle significantly affects stress distribution. Specifically, von Mises stress on the head decreases with increased long-side curvature.
This paper presents a method for synchronizing and merging point cloud data from two LiDAR sensors mounted on a vehicle to create a dense, machine-learning-compatible dataset. Two identical Ouster OS1 sensors (32×1024, 20 Hz) were tested in real traffic, and a synchronization algorithm was developed to align frames based on timestamp differences. The merged point clouds were organized into a 64×1024 matrix, with effective handling of missing data to ensure compatibility with neural networks. Computational performance was analyzed across processing steps, highlighting trade-offs between accuracy and speed. Results show that proper synchronization enables efficient sensor fusion, improving perception and robustness in autonomous driving.
This paper presents a workflow combining reverse engineering, topology optimization, and additive manufacturing. The method was applied to a motorcycle swingarm redesigned through 3D scanning, CAD reconstruction, and structural optimization. Finite element analysis and prototype testing confirmed over 25% weight reduction while maintaining stiffness. The workflow demonstrates applicability in automotive and aerospace engineering.
This study demonstrates the application of Complex Eigenvalue Analysis (CEA) to optimize a weighted bolt that targets unstable frequencies in a floating caliper brake assembly. A commercial automobile brake assembly undergoes experimental modal analysis, and a corresponding finite element model is developed. The experimental and analytical models are compared, and a modal assurance criterion matrix is established based on relevant modes. Mass modifications are implemented, and the results obtained are presented.
