Efficient mixing of viscoelastic fluids in a microchannel at low Reynolds number

In this paper, we examined mixing of various two-fluid flows in a silicon/glass microchannel based on the competition of dominant forces in a flow field, namely viscous/elastic, viscous/viscous and viscous/inertial. Experiments were performed over a range of Deborah and Reynolds numbers (0.36 < De < 278, 0.005 < Re < 24.2). Fluorescent dye and microshperes were used to characterize the flow kinematics. Employing abrupt convergent/divergent channel geometry, we achieved efficient mixing of two-dissimilar viscoelastic fluids at very low Reynolds number. Enhanced mixing was achieved through elastically induced flow instability at negligible diffusion and inertial effects (i.e. enormous Peclet and Elasticity numbers). This viscoelastic mixing was achieved over a short effective mixing length and relatively fast flow velocities.     

An Effective Technique for Subpixel Image Registration Under Noisy Conditions

This paper proposes an effective higher order statistics method to address subpixel image registration. Conventional power spectrum-based techniques employ second-order statistics to estimate subpixel translation between two images. They are, however, susceptible to noise, thereby leading to significant performance deterioration in low signal-to-noise ratio environments or in the presence of cross-correlated channel noise. In view of this, we propose a bispectrum-based approach to alleviate this difficulty. The new method utilizes the characteristics of bispectrum to suppress Gaussian noise. It develops a phase relationship between the image pair and estimates the subpixel translation by solving a set of nonlinear equations. Experimental results show that the proposed technique provides performance improvement over conventional power-spectrum-based methods under different noise levels and conditions.     

An MDD-based generalized arc consistency algorithm for positive and negative table constraints and some global constraints

A table constraint is explicitly represented as its set of solutions or non-solutions. This ad hoc (or extensional) representation may require space exponential to the arity of the constraint, making enforcing GAC expensive. In this paper, we address the space and time inefficiencies simultaneously by presenting the mddc constraint. mddc is a global constraint that represents its (non-)solutions with a multi-valued decision diagram (MDD). The MDD-based representation has the advantage that it can be exponentially smaller than a table. The associated GAC algorithm (called mddc) has time complexity linear to the size of the MDD, and achieves full incrementality in constant time. In addition, we show how to convert a positive or negative table constraint into an mddc constraint in time linear to the size of the table. Our experiments on structured problems, car sequencing and still-life, show that mddc is also a fast GAC algorithm for some global constraints such as sequence and regular. We also show that mddc is faster than the state-of-the-art generic GAC algorithms in Gent et al. (2007), Lecoutre and Szymanek (2006), Lhomme and Régin (2005) for table constraint.     

Parametric Sequence Alignment with Constraints

Approximate matching techniques based on string alignment are important tools for investigating similarities between strings, such as those representing DNA and protein sequences. We propose a constraint based approach for parametric sequence alignment which allows for more general string alignment queries where the alignment cost can itself be parameterized as a query with some initial constraints. Thus, the costs need not be fixed in a parametric alignment query unlike the case in normal alignment. The basic dynamic programming string edit distance algorithm is generalized to a naive algorithm which uses inequalities to represent the alignment score. The naive algorithm is rather costly and the remainder of the paper develops an improvement which prunes alternatives where it can and approximates the alternatives otherwise. This reduces the number of inequalities significantly and strengthens the constraint representation with equalities. We present some preliminary results using parametric alignment on some general alignment queries.     

The performance of superhydrophobic and superoleophilic carbon nanotube meshes in water–oil filtration

Vertically-aligned multi-walled carbon nanotubes (CNTs) were grown on stainless steel (SS) mesh by thermal chemical vapor deposition with a diffusion barrier of Al₂O₃ film. These three-dimensional porous structures (SS-CNT meshes) were found to be superhydrophobic and superoleophilic. Water advancing contact angles of 145–150° were determined for these SS-CNT meshes in air and oil (gasoline, isooctane). Oil, on the other hand, completely wet the SS-CNT meshes. This combined superhydrophobic and superoleophilic property repelled water while allowed the permeation of oil. Filtration tests demonstrated efficiencies better than 80% of these SS-CNT meshes as the filtration membranes of the water-in-oil emulsions. We have conducted quantitative analysis on the diameters of the oil droplets in both the feed emulsion and the filtrate. Then, we have evaluated the issue of water blockage and possible way to improve the filtration efficiency. Finally, the filtration and blockage mechanisms are proposed.     

Clear model fluids to emulate the rheological properties of thickened digested sludge

Optimising flow processes in wastewater treatment plants requires that designers and operators take into account the flow properties of the sludge. Moreover, due to increasingly more stringent conditions on final disposal avenues such as landfill, composting, incineration etc., practitioners need to produce safer sludge in smaller quantities. Anaerobic digestion is a key treatment process for solids treatment and pathogen reduction. Due to the inherent opacity of sludge, it is impossible to visualise the mixing and flow patterns inside an anaerobic digester. Therefore, choosing an appropriate transparent model fluid which can mimic the rheological behaviour of sludge is imperative for visualisation of the hydrodynamic functioning of an anaerobic digester.Digested sludge is a complex material with time dependent non-Newtonian thixotropic characteristics. In steady state, it can be modelled by a basic power-law. However, for short-time processes the Herschel-Bulkley model can be used to model liquid-like properties.The objective of this study was to identify transparent model fluids which will mimic the behaviour of real sludge. A comparison of three model fluids, Carboxymethyl Cellulose (CMC), Carbopol gel and Laponite clay revealed that these fluids could each model certain aspects of sludge behaviour. It is concluded that the rheological behaviour of sludge can be modelled using CMC in steady state flow at high shear rates, Carbopol gel for short-time flow processes and Laponite clay suspension where time dependence is dominant.     

Laser ablation and growth of Si and Ge

In this work, we investigated the laser ablation and deposition of Si and Ge at room temperature in vacuum by employing nanosecond lasers of 248 nm, 355 nm, 532 nm and 1064 nm. Time-integrated optical emission spectra were obtained for neutrals and ionized Ge and Si species in the plasma at laser fluences from 0.5 to 11 J/cm². The deposited films were characterized by using Raman spectroscopy, scanning electron microscopy and atomic force microscopy. Amorphous Si and Ge films, micron-sized crystalline droplets and nano-sized particles were deposited. The results suggested that ionized species in the plasma promote the process of subsurface implantation for both Si and Ge films while large droplets were produced from the superheated and melted layer of the target. The dependence of the properties of the materials on laser wavelength and fluence were discussed.