This article summarizes published journal articles on planetary and epicyclic gear dynamics and vibration. Research in this field has increased dramatically over the past two decades. The wide range of research topics demonstrates the technical challenges of understanding and predicting planetary gear dynamics and vibration. The research in this review includes mathematical models, vibration mode properties, dynamic response predictions including nonlinearities and time-varying mesh stiffness fluctuations, the effects of elastic compliance, and gyroscopic effects, among other topics. Practical aspects are also included, for example, planet load sharing, planet phasing, tooth surface modifications, and characteristics of measured vibration response.

A Review of Planetary and Epicyclic Gear Dynamics and Vibrations Research

The band structure, the density of states and optical absorption properties of Cu-doped ZnO were studied by the first-principles generalized gradient approximation plane-wave pseudopotential method based on density functional theory. For the Zn1-xCuxO (x = 0, x = 0.0278, x = 0.0417) original structure, geometric optimization and energy calculations were performed and compared with experimental results. With increasing Cu concentration, the band gap of the Zn1-xCuxO decreased due to the shift of the conduction band. Since the impurity level was introduced after Cu doping, the conduction band was moved downwards. Additionally, it was shown that the insertion of a Cu atom leads to a red shift of the optical absorption edge, which was consistent with the experimental results.

https://www.mdpi.com/1996-1944/12/1/196/pdf

Cu-Doped ZnO Electronic Structure and Optical Properties Studied by First-Principles Calculations and Experiments

Nonlinear torsional vibrations of a wind turbine gearbox

This review summarizes state-of-the-art progress in the molecular dynamics (MD) simulation of the novel thermal properties of graphene. The novel thermal properties of graphene, which include anisotropic thermal conductivity, decoupled phonon thermal transport, thermal rectification and tunable interfacial thermal conductance, have attracted enormous interest in the development of next-generation nano-devices. Molecular dynamics simulation is one of the main approaches in numerical simulation of the novel thermal properties of graphene. In this paper, the widely used potentials of MD for modeling the novel thermal properties of graphene are described first. Then MD simulations of anisotropic thermal conductivity, decoupled phonon thermal transport, thermal rectification and tunable interfacial thermal conductance are discussed. Finally, the paper concludes with highlights on both the current status and future directions of the MD simulation of the novel thermal properties of graphene.

A comprehensive review on the molecular dynamics simulation of the novel thermal properties of graphene

An Intelligent Prognostic System for Gear Performance Degradation Assessment and Remaining Useful Life Estimation

First-principle study of optical properties of (N, Ga) codoped ZnO

During the process of mechanism kinematic structure enumeration, isomorphism identification of graphs is an important and complicated problem. The problem is known to be a NP-complete problem. In this paper, according to the mechanism kinematic chain isomorphism identification criteria, a highly efficient hybrid genetic algorithm model is proposed for isomorphism identification. The model method is coupled with genetic algorithm, optimal choice, and optimal crossover operation. It shows a quick convergence rate of the late operation and can avoid convergence to local optimum. Simulation results show that the hybrid algorithm is more rapid and effective compared with simple genetic algorithm and the improved neural network algorithm.

An Improved Genetic Algorithm Approach on Mechanism Kinematic Structure Enumeration with Intelligent Manufacturing

Surface sliding simulation in micro-gear train for adhesion problem and tribology design by using molecular dynamics model

In intelligent mechanism design, isomorphism identification of mechanism kinematic chains (IIMKC) is aimed at avoiding repeated mechanism design and is proved to be an NP-complete problem. In this paper, kinematic chains are represented by graphs. An improved hybrid immune algorithm, which integrates the clonal selection immune algorithm with genetic algorithm and the local search algorithm, is proposed to solve IIMKC problem. Moreover, the novel saving and updating operator is proposed to save the best antibodies and maintain a diverse repertoire of antibodies for improving performance of clonal selection. In addition, the pseudo-crossover operator is introduced to enhance the efficiency of genetic algorithm. Simulation results validate the high efficiency and robustness of the hybrid immune algorithm.

An improved hybrid immune algorithm for mechanism kinematic chain isomorphism identification in intelligent design

This article investigates the vibration response of a planetary gear train under excitations of both deterministic and random loads. A lumped parameter model has been used in this investigation and the random excitations are represented by white noise. One version of the stochastic Newmark algorithms is employed to solve for both sample path response and the statistics of the response. The mean and the variance for all state variables are obtained through the same algorithm. The effects of three different levels of noise on the statistics are compared against each other. [DOI: 10.1115/1.4023053]

Ping Yang

Papers

First-principle study of optical properties of (N, Ga) codoped ZnO

An Improved Genetic Algorithm Approach on Mechanism Kinematic Structure Enumeration with Intelligent Manufacturing

Surface sliding simulation in micro-gear train for adhesion problem and tribology design by using molecular dynamics model

An improved hybrid immune algorithm for mechanism kinematic chain isomorphism identification in intelligent design

Random Vibration Analysis of Planetary Gear Trains