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报告内容摘要：
    As membrane processes operate, rejected substances in the feed accumulate near the feed side of the membrane and then form concentration polarisation. Concentration polarisation increases resistance to filtration, which in return requires higher pressures in order to maintain a constant flux or leads to lower filtration productivity. Additionally, the build-upon the surface of the membrane may result in membrane fouling, which decreases system performance, requires cleaning and decreases membrane life. A conventional method to deal with concentration polarisation is to increase flow speed to cause channel-wide turbulence. Since concentration polarisation only occurs in the vicinity of the membrane surface where velocity is normally very low, inducing turbulence throughout the channel is not an efficient method for reducing concentration polarisation.
    This project proposes an activation scheme for improving the mixing in the boundary layer of pressure-driven membrane systems and thereby increasing the productivity of membrane systems. Through application of an external electric field, a flow of ions in the vicinity of the membrane surface will be generated, creating simultaneous electro-osmotic flow that should reduce the concentration polarization on the membrane surface. An optimal control problem is formulated and solved to determine the waveform of the control action required to produce an electric field that can effectively increase mixing in the vicinity of the membrane surface with improved energy efficiency. A mixing index in terms of a measure of spatial gradients of the perturbation velocities is used to describe the mixing caused by both length stretching and vortices. The efficacy of the proposed control   is validated by Computational Fluid Dynamics (CFD) simulations. In addition, a linearized model is used and discretized for analysing the frequency property of the system in order to obtain an optimal waveform of the input voltage. PIV experiments will be shown at the presentation.
    The non-uniformity of the electric field causes complicated interactions between regions within the channel. For this reason, a partition based model is developed to describe the input voltage and the concentration gradients of the electro-osmotic flow. The response data for this model is obtained from transient simulations using CFD software. The input signal used in CFD simulations for modeling purposes is a uniform slip velocity localized to a single partition, which corresponds to electric field at the location. The output from the CFD simulation is the average salt gradient perpendicular to the membrane surface at the membrane surface, which is chosen as a measure of the extent of concentration polarization. The relationship between the responses of partitions and the inputs from a single partition is identified as a linear system model. System identification techniques are used to find the type of models for both local and non-local responses. The relationship is then used to generalize the responses so that they can be tailored to a range of cross-flow velocities as well as for arbitrarily sized and distributed non-overlapping partitions. In addition, this method can be generalized to the case where there are spacers installed in the channel and hence enabling the feedback control system development for this case.

报告人简介：
Dr. Hua Ouyang received his degree in Engineering Mechanics from Hunan University, China and M.S. degree in General Mechanics and Foundation of Mechanics from Peking University, China in 2000 and 2003, respectively. He received his first Ph.D. degree in Industrial Electronics in 2007 from the University of Glamorgan, UK and his second Ph.D. degree in Electrical Engineering in 2011 from the University of New South Wales at the Australian Defence Force Academy. From 2007-2011, he worked as a research assistant at UNSW (ADFA). Now, he is a postdoctoral research fellow in the School of Chemical Engineering, University of New South Wales, Sydney. His research interests include robust control and filtering, networked control systems and modelling and control of nonlinear system.