RADIAL FLOW HOLLOW FIBERREVERSE OSMOSIS: EXPERIMENTS AND THEORY

The performance of a hollow fiber reverse osmosis system is studied both theoretically and experimentally. Experiments were carried out for applied pressure ranging from 200 to 400 psig, feed rates varying from 75 to 380 cc/sec and for feed concentrations up to 34,000 ppm of sodium chloride.

A mathematical model is proposed to predict productivity, ϕ, and product concentration, θ_p. The model involves solving membrane transport equations simultaneously with the hydrodynamic equations. The solubility-diffusion-imperfection, or pore diffusion model, is used to describe solute and solvent transport across the membrane. The axial gradients of shell side concentration, neglected in previous investigations, are taken into account. The differential equations are solved numerically by the 4th Order Runge-Kutta method.

Predicted values of ϕ and θ_p agree within 8% and 17% respectively, with experimental data over the entire range of operating conditions. However, membrane transport coefficients were found to be concentration dependent.

An approximate analysis shows that the concentration polarization is negligible in present day hollow fiber systems.     

Deposition of hydroxyapatite coatings by axial plasma spraying: Influence of feedstock characteristics on coating microstructure,phase content and mechanical properties

Axial plasma spray is one of the thermal spray techniques to deposit multifunctional advanced coatings. The present work explores the use of this process to deposit thin, continuous, and adherent Ca₅ (PO₄)₃OH (hydroxyapatite, HAp) coatings and characterize its microstructure, phases, hardness and adhesion strength. Three different suspension-deposited HAp coatings were investigated and compared with powder-deposited HAp coating on a Ti6Al4V substrate. The effect of mean solute particle size and solid-loading in the suspension has been explored on the evolution of microstructure, phase content and mechanical properties of axial suspension plasma sprayed (ASPS) coatings. Phase-characterization has shown retention of hydroxyapatite phase and coating crystallinity in the deposited coatings, whereas the adhesion strength of the HAp coating decreased from ～40 MPa to ～13 MPa when bioglass was added to the feedstock material. The lower solid load content and lower mean solute particle size in the suspension were found to be beneficial in achieving porous, rougher, and well-adhering coatings. This work concludes that ASPS can potentially deposit thin HAp coatings (< 50 μm) with high adhesion strength.     

Comparative wear performance of titanium based coatings for automotive applications using exhaust gas recirculation

This paper reports tribological characterization of titanium based coatings ion bonded on steel balls for automotive applications using exhaust gas recirculation (EGR). It is well known that lubricating oil drawn from EGR operated engine is contaminated with soot and higher amounts of wear debris compared to non-EGR operated engine. In this study, steel balls coated with TiN, TiAlN and TiCN are investigated in both fresh lubricating oil and EGR stressed oil for a comparative assessment of their wear characteristics in two mediums. Normal load was applied on the samples, tested against a rotating cast iron disk, simulating ring-liner interaction. In each experiment, about one quarter of disk was dipped in the oil (a) to ensure the presence of a thin oil film on the disk-ball interface during the experiment, and (b) to avoid exposure of the worn surface to atmospheric air. The results reveal that the wear rates of the coatings based on the change in the scar diameters of the samples, tested in EGR oil was 2-4 times higher than that of fresh lubricating oil. It was found that despite lowest hardness, TiN coated samples showed smaller scar diameters than TiAlN and TiCN coated samples in both lubricating oil environments. A simple geometric model was used to calculate the thickness of the coating removed as a function of the test duration. Results show that TiN coatings last for 120 min in fresh oil as compared to 30 min in the EGR oil under normal loading, whereas TiAlN and TiCN coating last for 60 and 30 min respectively in fresh oil and wear out in 15 min in EGR oil.     

A compact dual band short ended metamaterial antenna with extended bandwidth

A compact dual‐band CPW–fed metamaterial inspired antenna using Composite Right/Left Handed (CRLH) resonant approach is presented in this article. The antenna is designed such that it can be operated in series resonant mode where resonance behavior is characterized by series LC parameters. Proposed antenna comprises two annular ring resonators connected with the signal patch intended to excite the higher order modes. This results extension of second band from 51.4% (f_c = 6.92 GHz) to 69.2% (f_c = 7.35 GHz). In addition to that proposed antenna shows compact nature with an electrical size of 0.14 λ₀ × 0.21 λ0 × 0.01 λ₀ at f₀ = 2.18 GHz. The antenna is operating over 2.14–2.23 GHz, 4.81–9.90 GHz with simulated peak gain of 0.66 and 4.44 dB, respectively. Simulated radiation efficiencies of proposed antenna are 69.8 and 94.1% throughout first and second band, respectively. To examine the resonance and radiation characteristics prototype is fabricated and measured. Observed experimental results are in good agreement with those simulated one. These characteristics makes this antenna is a good candidate for modern wireless communication systems such as Bluetooth, WLAN/Wi‐Fi band. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE 26:435–441, 2016.     

Multiresolution approach for multiple human detection using moments and local binary patterns

Human detection is a central problem in development of any surveillance application. In this study, we present a simple and efficient, multi-resolution gray scale invariant approach for multiple human detection. The multiresolution is important for objects of different size and gray scale invariance is important due to uneven illumination and within-class variability. The proposed method is based on integration of central moments upon multi-resolution gray scale invariant local binary patterns operator. Since, the local binary patterns operator is invariant against different resolutions of space scale and monotonic change in gray scale, therefore the proposed method is robust in terms of variations in space scale as well as gray scale. Another advantage is high computational accuracy of the method due to use of moment operator which enhances the efficiency of the proposed method. Moreover, the proposed method is simple, as these operations can be performed within a few steps in a small neighborhood and a lookup table. The proposed method is tested on multiple human images and experimentally found appropriate for multiple human detection. The proposed method has been evaluated over two datasets, one is our own created dataset and the other is standard INRIA human detection dataset. Experimental results obtained from the proposed method demonstrate that better discrimination can be achieved for human and non-human objects in real scenes.     

The dark side of information technology use

A large body of research has considered the positive aspects of information technology (IT) use. However, emerging research and practice commentary is beginning to focus on complex and often alarming ways in which use of IT affects organisational and social life. This Special Issue focuses on these ‘dark’ effects of IT use.     

Microalgae growth for nutrient recovery from sludge liquor and production of renewable bioenergy

Proof-of-concept has been demonstrated for a process that will utilize nutrients from sludge liquor, natural light, and CO2 from biogas to grow microalgae at wastewater treatment plants. This process will reduce the impact of returning side-streams to the head of the plant. The produced algae will be fed to anaerobic digesters for increased biogas production. Dewatering of anaerobically digested sludge in centrifuges produces reject water with extremely low transmittance of light. A pretreatment procedure was developed that improved light transmittance for reject water from the FREVAR, Norway, wastewater treatment plant from 0.1% T to 77% T (670 nm, 1 cm path). Chlorella sp. microalgae were found to be suitable for growth in this pre-treated reject water. Typical nitrogen removal was 80-90 g N/kg TSS of produced microalgae. The microalgae were successfully harvested by chemically assisted flocculation followed by straining through a 33 microm sieve cloth, achieving up to 99% recovery. Harvested algae were anaerobically co-digested with wastewater sludge. The specific methane gas production (mL CH4/g VS fed) for the algae varied from less than 65% to 90% of the specific methane gas production for the wastewater sludge, depending on digester temperature, retention time and pre-treatment of the algae biomass.     

Multi-objective reactive power market clearing in competitive electricity market using HFMOEA

This paper presents an application of a hybrid fuzzy multi-objective evolutionary algorithm (HFMOEA) for solving a highly constraint, mixed integer type, complex multi-objective reactive power market clearing (RPMC) problem for the competitive electricity market environment. In HFMOEA based multi-objective optimization approach, based on the output of a fuzzy logic controller crossover and mutation probabilities are varied dynamically. It enhances stochastic search capabilities of HFMOEA. In multi-objective RPMC optimization framework, two objective functions namely the total payment function (TPF) for reactive power support from generators and synchronous condensers and the total real transmission loss (TRTL) are minimized simultaneously for clearing the reactive power market. The proposed HFMOEA based multi-objective RPMC scheme is tested on a standard IEEE 24 bus reliability test system and its performance is compared with five other multi-objective evolutionary techniques such as MOPBIL, NSGA-II, UPS-EMOA and SPEA-2 and a new extended form of NSGA (ENSGA-II). Applying all these six evolutionary techniques, a detailed statistical analysis using T-test and boxplots is carried out on three performance metrics (spacing, spread and hypervolume) data for RPMC problem. The obtained simulation results confirm the overall superiority of HFMOEA to generate better Pareto-optimal solutions with higher convergence rate as compared to above mentioned algorithms. Further, TPF and TRTL values corresponding to the best compromise solutions are obtained using said multi-objective evolutionary techniques. These values are compared with one another to take better market clearing decisions in competitive electricity environment.     

Graphical models for interactive POMDPs: representations and solutions

We develop new graphical representations for the problem of sequential decision making in partially observable multiagent environments, as formalized by interactive partially observable Markov decision processes (I-POMDPs). The graphical models called interactive influence diagrams (I-IDs) and their dynamic counterparts, interactive dynamic influence diagrams (I-DIDs), seek to explicitly model the structure that is often present in real-world problems by decomposing the situation into chance and decision variables, and the dependencies between the variables. I-DIDs generalize DIDs, which may be viewed as graphical representations of POMDPs, to multiagent settings in the same way that I-POMDPs generalize POMDPs. I-DIDs may be used to compute the policy of an agent given its belief as the agent acts and observes in a setting that is populated by other interacting agents. Using several examples, we show how I-IDs and I-DIDs may be applied and demonstrate their usefulness. We also show how the models may be solved using the standard algorithms that are applicable to DIDs. Solving I-DIDs exactly involves knowing the solutions of possible models of the other agents. The space of models grows exponentially with the number of time steps. We present a method of solving I-DIDs approximately by limiting the number of other agents’ candidate models at each time step to a constant. We do this by clustering models that are likely to be behaviorally equivalent and selecting a representative set from the clusters. We discuss the error bound of the approximation technique and demonstrate its empirical performance.