Search

A rod fastened rotor (RFR), which contains serial disks, rods (or a rod), and a torque tube, is the main form of heavy duty gas turbines and light duty aero engines. The roughness of the interface is the main parameter affecting the bending stiffness of RFR, and the jumpiness of the disks is the intuitive representation of the unbalance of the rotor. In this paper, a multi-optimization algorithm, NSGA-Ⅱ, was used to improve the vibration behavior of the RFR-bearing system. First, the quantitative relation between the bending stiffness of the rotor and the roughness of the interface was set up by combining the Persson contact theory and the Greenwood–Williamson model, and the nondimensional bending stiffness (NS) was proposed as the optimization objective of roughness. Then, the optimization objective of the jumpiness of the disk, (A + B), was rendered based on the minimum unbalance force. Finally, the multi-optimization on the roughness and jumpiness of the RFR was carried out, and the vibration behavior was improved greatly. In addition, this multi-optimization method was applied to a practical RFR, and the experimental results showed that the vibration amplitude was reduced by about 82%. The work in this paper can provide the guidance for vibration reduction of the rotor system. [ABSTRACT FROM AUTHOR]

Probabilistic fasteners are known to provide strong attachment onto their respective surfaces. Examples are Velcro® and the "3M dual lock" system. However, these systems typically only function using specific counter surfaces and are often destructive to other surfaces such as fabrics. Moreover, the design parameters to optimize their functionality are not obvious. Here, we present a surface patterned with soft micrometric features inspired by the mushroom shape showing a nondestructive mechanical interlocking and thus attachment to fabrics. We provide a scalable experimental approach to prepare these surfaces and quantify the attachment strength with rheometric and video-based analysis. In these "probabilistic fasteners," we find that higher feature densities result in higher attachment force; however, the individual feature strength is higher on a low feature density surface. We interpret our results via a load-sharing principle common in fiber bundle models. Our work provides new handles for tuning the mechanical attachment properties of soft patterned surfaces that can be used in various applications including soft robotics. [ABSTRACT FROM AUTHOR]