Parameter Interval Uncertainty Analysis of Internal Resonance of Rotating Porous Shaft–Disk–Blade Assemblies Reinforced by Graphene Nanoplatelets

This paper conducts a parameter interval uncertainty analysis of the internal resonance of a rotating porous shaft–disk–blade assembly reinforced by graphene nanoplatelets (GPLs). The nanocomposite rotating assembly is considered to be composed of a porous metal matrix and graphene nanoplatelet (GPL) reinforcement material. Effective material properties are obtained by using the rule of mixture and the Halpin–Tsai micromechanical model. The modeling and internal resonance analysis of a rotating shaft–disk–blade assembly are carried out based on the finite element method. Moreover, based on the Chebyshev polynomial approximation method, the parameter interval uncertainty analysis of the rotating assembly is conducted. The effects of the uncertainties of the GPL length-to-width ratio, porosity coefficient and GPL length-to-thickness ratio are investigated in detail. The present analysis procedure can give an interval estimation of the vibration behavior of porous shaft–disk–blade rotors reinforced with graphene nanoplatelets (GPLs).

Blade Sorting Method for Unbalance Minimization of an Aeroengine Concentric Rotor

This paper proposes a blade sorting method based on the cloud adaptive genetic algorithm (CAGA), which is used to optimize the unbalanced of asymmetric rotor of aero-engine. Firstly, by analyzing the unbalance of the arrangement caused by the deviation of the mass moment of the blade, and considering the concentricity of the disk, an optimization model of the unbalanced amount of the blade assembly was established. Secondly, the selection operator, crossover operator, and mutation operator of the algorithm were designed, and the cloud adaptive genetic algorithm was used to optimize the assembly unbalance. Thirdly, the mass moments of a group of aero-engine blades were weighed using a moment scale (MW0), and the blade mass moment distribution and assembly unbalance under the six blade arrangements were analyzed. Finally, by setting different disk concentricity, the corresponding blade arrangement and the final rotor unbalance were obtained. Through analysis, it was found that the unbalance of GA is at least 57.5% optimized relative to the weight sorted, sorting type 2, sorting type 4, and sorting-1/4 skip method, and the unbalance optimized by the CAGA is 95.7% optimized relative to GA. In the case of different initial concentricity of the disk, the effective algorithm accuracy is still maintained, which proves the effectiveness of the method for the arrangement of asymmetric rotor blades. This method establishes an effective asymmetric rotor blade arrangement model, uses the cloud adaptive genetic algorithm to sort the blade assembly, and effectively reduces the unbalanced amount of the asymmetric rotor.

Magnetic Coupling for a 10 kW Tidal Current Turbine: Design and Small Scale Experiments

This paper presents a coupling design that improves water tightness of a marine current turbine (MCT). The coupling is numerically analyzed and incorporated into the design of an MCT from a previous study. The performance of the MCT with the magnetic coupling is compared to the previous results in small scale turbine experiments. The results show that the new design is water tight and has lower mechanical losses when compared with previous results. The new turbine has increased maximum power output (from 116 W to 122 W) and hydrodynamic coefficient of power (Previously 0.45 to 0.46). Using these results, the coupling design is scaled for a 10 kW MCT and further analyzed by finite element analysis. The results obtained show that the magnetic coupling is capable of withstanding the combined weight of the hub and blade assembly. The results in this study will be used for developing a prototype for deployment in real seas.

Rotor Balancing with Turbine Blade Assembly Using Ant Colony Optimization for Aero-Engine Applications

The purpose of this paper is to present a novel turbine balancing using Ant Colony Optimization method. Results are compared against well known optimization methods available at open literature. With the new approach, turbine blade set can be separated in to two blade sets as heavy and light blades. This approach makes possible the application of Ant Colony Optimization methodology. ACO methodology is compared with Steepest Descent and Exchange Heuristic methods using nine different initial blade placements. And results are presented. Performance of the three evaluated methods is affected by the initial blade placement. Exchange Heuristics method was quick and provided good results in most of the cases. Ant colony optimization was able find better results than the Steepest Descent method. The approach of separating blades into two sets decreased the solution time of Steepest Descent algorithm. Ant colony optimization method can be used for turbine blade assembly and balancing for aircraft gas turbine applications. This approach is used for the first time in this area and not seen at the open literature.

Design and Strength Analysis of Curved-Root Concept for Compressor Rotor Blade in Gas Turbine

The motivation of the article is fatigue and fretting issue of the compressor rotor blades and disks. These phenomena can be caused by high contact pressures leading to fretting occurring on contact faces in the lock (blade-disk connection, attachment of the blade to the disk). Additionally, geometrical notches and high cyclic loading can initiate cracks and lead to engine failures. The paper presents finite element static and modal analyses of the axial compressor 3rd rotor stage (disk and blades) of the K-15 turbine engine. The analyses were performed for the original trapezoidal/dovetail lock geometry and its two modifications (new lock concepts) to optimize the stress state of the disk-blade assembly. The cyclic symmetry formulation was used to reduce modelling and computational effort.

Fracture Failure Mechanisms of Long Single PA6 Fibers

The present study investigates the failure mechanisms of industrial fiber materials, using a custom designed fiber cutting performance test bench. The fracture morphologies of single PA6 fibers are examined by scanning electron microscopy. The analysis reveals that fiber cutting can be distinguished according to four distinct stages of fiber failure represented by shearing, cutting, brittle fracture, and tensile failure, which are the result of different mechanisms active during the processes of crack initiation, extension and fracture. The results of fractographic analysis are further verified by an analysis of the blade assembly speed with respect to time over the entire fracture failure process based on high-speed camera data. The results of fractographic analysis and blade assembly speed are fully consistent.