Designer porous antibacterial membranes derived from thermally induced phase separation of PS/PVME blends decorated with an electrospun nanofiber scaffold

We report the development of porous membranes by thermally induced phase separation of a PS/PVME (polystyrene/polyvinylmethyl ether]) blend, which is a typical LCST mixture. The morphology of the membrane after etching out the PVME phase was characterized by scanning electron microscopy. To give the membrane an antibacterial surface, polystyrene (PS) and polyvinyl(methyl ether)]-alt-maleic anhydride (PVME-MAH) with silver nanoparticles (nAg) were electrospun on the membrane surface. Pure water flux was evaluated by using a cross-flow membrane setup. The microgrooved fibers changed the flux across the membrane depending on the surface properties. The antibacterial properties of the membrane were confirmed by the reduction in the colony count of E. coli. The SEM images show the disruption of the bacterial cell membrane and the antibacterial mechanism was discussed.

Numerical prediction of nozzle flow separation: Issue of turbulence modeling

Numerical simulation of separated flows in rocket nozzles is challenging because existing turbulence models are unable to predict it correctly. This paper addresses this issue with the Spalart-Allmaras and Shear Stress Transport (SST) eddy-viscosity models, which predict flow separation with moderate success. Their performances have been compared against experimental data for a conical and two contoured subscale nozzles. It is found that they fail to predict the separation location correctly, exhibiting sensitivity to the nozzle pressure ratio (NPR) and nozzle type. A careful assessment indicated how the model had to be tuned for better, consistent prediction. It is learnt that SST model's failure is caused by limiting of the shear stress inside boundary layer according to Bradshaw's assumption, and by over prediction of jet spreading rate. Accordingly, SST's coefficients were empirically modified to match the experimental wall pressure data. Results confirm that accurate RANS prediction of separation depends on the correct capture of the jet spreading rate, and that it is feasible over a wide range of NPRs by modified values of the diffusion coefficients in the turbulence model. (C) 2015 Elsevier Masson SAS. All rights reserved.

Numerical Simulation of Particle Separation in An Oil-Sand Separator

The gathering systems of crude oil are greatly endangered by the fine sand and soil in oil. Up to now , how to separate sand from the viscid oil is still a technical problem for oil production home or abroad. Recently , Institute of Mechanics in Chinese Academy of Sciences has developed a new type of oil-sand separator , which has been applied successfully in oil field in situ. In this paper, the numerical method of vortex-stream function is used to predict the liquid-solid separating course and the efficiency for this oil-sand separator. Results show that the viscosity and particle diameter have much influence on the particle motion. The calculating separating efficiency is compared with that of experiment and indicates that this method can be used to model the complex two-phase flow in the separator.

Multi-channel signal separation

The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

Bayesian separation and recovery of convolutively mixed autoregressive sources

In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.

Toughness Of Ni/Al2O3 Interfaces As Dependent On Micron-Scale Plasticity And Atomistic-Scale Separation

Ceramic/metal interfaces were studied that fail by atomistic separation accompanied by plastic dissipation in the metal. The macroscopic toughness of the specific Ni alloy/Al2O3 interface considered is typically on the order of ten times the atomistic work of separation in mode I and even higher if combinations of mode I and mode II act on the interface. Inputs to the computational model of interface toughness are: (i) strain gradient plasticity applied to the Ni alloy with a length parameter determined by an indentation test, and (ii) a potential characterizing mixed mode separation of the interface fit to atomistic results. The roles of the several length parameters in the strain gradient plasticity are determined for indentation and crack growth. One of the parameters is shown to be of dominant importance, thus establishing that indentation can be used to measure the relevant length parameter. Recent results for separation of Ni/Al2O3 interfaces computed by atomistic methods are reviewed, including a set of results computed for mixed mode separation. An approximate potential fit to these results is characterized by the work of separation, the peak separation stress for normal separation and the traction-displacement relation in pure shearing of the interface. With these inputs, the model for steady-state crack growth is used to compute the toughness of the interface under mode I and under the full range of mode mix. The effect of interface strength and the work of separation on macroscopic toughness is computed. Fundamental implications for plasticity-enhanced toughness emerge.

Effects of Mach number on turbulent separation behaviours induced by blunt fin

An experimental study of the interaction between shock wave and turbulent boundary layer induced by blunt fin has been carried out at M-infinity = 7.8 using oil flow visualization and simultaneous measurements of fluctuating wall pressure and heat transfer. This paper presents the effects of Mach number on turbulent separation behaviours induced by blunt fin.