Dynamic characteristics of magnetorheological fluid lubricated journal bearing and its application to rotor vibration control

Application of smart lubricants like magnetorheological (MR) fluids is always considered to be a promising field of realizing smart bearings with semi-active controllable capability. For bearings lubricated with MR fluid, the dynamic characteristics i.e. the stiffness and damping coefficients are important, while few studies have focused on this field. The present work adopts the Herschel-Bulkley model to describe the rheological behavior of MR fluid. The shearing-thinning effect incorporated in this model leads to different result compared to that from the Bingham model. Stiffness and damping coefficients of bearings lubricated with Newtonian fluid, Bingham fluid are calculated. Calculations show that shear-thinning effect has great influences on both static and dynamic characteristics of the journal bearing. Simulations of rotordynamics of a turbo-expander rotor with different bearing properties are performed to investigate the possibility of MR fluid as lubricants to control the behavior of rotor. Results show that MR fluids are applicable to change performances of the rotor system. Vibration amplitude suppression and critical speed alteration can be achieved by MR fluids

Sharing Patient Disease Data with Privacy Preservation

When patient data are shared for studying a specific disease, a privacy disclosure occurs as long as an individual is known to be in the shared data. Individuals in such specific disease data are thus subject to higher disclosure risk than those in datasets with different diseases. This problem has been overlooked in privacy research and practice. In this study, we analyze disclosure risks for this problem and identify appropriate risk measures. An efficient algorithm is developed for anonymizing the data. An experimental study is conducted to demonstrate the effectiveness of the proposed approach