Rayleigh–Taylor and Richtmyer-Meshkov instability induced flow, turbulence, and mixing. II

Failure diagnosis using deep belief learning based health state classification

A review on data-driven fault severity assessment in rolling bearings

DEM/CFD-DEM Modelling of Non-spherical Particulate Systems: Theoretical Developments and Applications

A summary of fault modelling and predictive health monitoring of rolling element bearings

Condition monitoring is the process of monitoring a condition parameter in machinery, so that a significant change is indicative of a developing failure. The use of conditional monitoring allows maintenance to be scheduled, or other actions taken to avoid the consequences of failure before it actually occurs.

Vibration-Based Condition Monitoring

In this paper, a new mechanism of flow instability and turbulence transition is proposed for wall bounded shear flows. It is stated that the total energy gradient in the transverse direction and that in the streamwise direction of the main flow dominate the disturbance amplification or decay. Thus, they determine the critical condition of instability initiation and flow transition under given initial disturbance. A new dimensionless parameter K for characterizing flow instability is proposed which is expressed as the ratio of the energy gradients in the two directions for the flow without energy input or output. It is suggested that flow instability should first occur at the position of K max which may be the most dangerous position. This speculation is confirmed by Nishioka et al.'s experimental data. Comparison with experimental data for plane Poiseuille flow and pipe Poiseuille flow indicates that the proposed idea is really valid. It is found that the turbulence transition takes place at a critical value of K max of about 385 for both plane Poiseuille flow and pipe Poiseuille flow, below which no turbulence will occur regardless the disturbance. More studies show that the theory is also valid for plane Couette flows which holds a critical value of K max of about 370.

Mechanism of flow instability and transition to turbulence

Instability of Taylor-Couette flow between concentric rotating cylinders

A parallel unstructured finite volume method (FVM) is developed and implemented under a distributed computing environment through the parallel virtual machine (PVM) libraries, and is used to simulate the channel flow of the Oldroyd-B fluid past a circular cylinder. Differing from our previous work [11, 12] , a discrete elastic viscous split stress (DEVSS) formulation together with an independent interpolation of the vorticity (DEVSS- ω ) is proposed in this paper. This method has almost the same stability behavior as the elastic viscous split stress (EVSS) formulation, and is suitable for complex constitutive models. To further improve the stability at high Deborah numbers, we combine the idea of the discrete adaptive elastic viscous split stress (DAVSS) formulation [7] with the independent interpolation of the vorticity to arrive at the DAVSS- ω method. The numerical implementation is based on the unstructured FVM method and the semi-implicit method for pressure-linked equations revised (SIMPLER) algorithm. The parallelization of the program is implemented by a domain decomposition strategy and using PVM software libraries. The results are compared with those by the EVSS, DEVSS, and the plain Oldroyd-B formulation (without splitting the stress). It is found that the drag coefficient first decreases and then increases with the De number, for a channel half width to cylinder radius ratio of h / R  = 2. It is also confirmed that the drag enhancement at high Deborah number is due to the increasing extension effect in the regions near the front and the rear stagnation points.

Hua-Shu Dou

Papers

Vibration-Based Condition Monitoring

Mechanism of flow instability and transition to turbulence

Instability of Taylor-Couette flow between concentric rotating cylinders

The flow of an Oldroyd-B fluid past a cylinder in a channel: adaptive viscosity vorticity (DAVSS-ω) formulation

Numerical prediction and similarity study of pressure fluctuation in a prototype Kaplan turbine and the model turbine