Computationally efficient solution of population balance models incorporating nucleation, growth and coagulation: application to emulsion polymerization

A computationally efficient solution technique is presented for population balance models accounting for nucleation, growth and coagulation (aggregation) (with extensions for breakage). In contrast to earlier techniques, this technique is not based on approximating the population balance equation, but is based on employing individual rates of nucleation, growth and coagulation to update the PSD in a hierarchical framework. The method is comprised of two steps. The first step is the calculation of the rates of nucleation, growth and coagulation by solving an appropriate system of equations. This information is then used in the second step to update the PSD. The method effectively decomposes the fast and the slow kinetics, thereby eliminating the stiffness in the solution. In solving the coagulation kernel, a semi-analytical solution strategy is adapted, which substantially reduces the computational requirement, but also ensures the consistency of properties such as the number and mass of particles.     

Graph-based quadratic optimization: A fast evolutionary approach

Quadratic optimization lies at the very heart of many structural pattern recognition and computer vision problems, such as graph matching, object recognition, image segmentation, etc., and it is therefore of crucial importance to devise algorithmic solutions that are both efficient and effective. As it turns out, a large class of quadratic optimization problems can be formulated in terms of so-called “standard quadratic programs” (StQPs), which ask for finding the extrema of a quadratic polynomial over the standard simplex. Computationally, the standard approach for attacking this class of problems is to use replicator dynamics, a well-known family of algorithms from evolutionary game theory inspired by Darwinian selection processes. Despite their effectiveness in finding good solutions in a variety of applications, however, replicator dynamics suffer from being computationally expensive, as they require a number of operations per step which grows quadratically with the dimensionality of the problem being solved. In order to avoid this drawback, in this paper we propose a new population game dynamics (InImDyn) which is motivated by the analogy with infection and immunization processes within a population of “players.” We prove that the evolution of our dynamics is governed by a quadratic Lyapunov function, representing the average population payoff, which strictly increases along non-constant trajectories and that local solutions of StQPs are asymptotically stable (i.e., attractive) points. Each step of InImDyn is shown to have a linear time/space complexity, thereby allowing us to use it as a more efficient alternative to standard approaches for solving StQPs and related optimization problems. Indeed, we demonstrate experimentally that InImDyn is orders of magnitude faster than, and as accurate as, replicator dynamics on various applications ranging from tree matching to image registration, matching and segmentation.     

Electrochemical investigations on amorphous Fe-base alloys for alkaline water electrolysis

In this work different amorphous melt-spun Fe-alloys (Fe₈₂B₁₈, Fe₈₀Si₁₀B₁₀, Fe₆₀Co₂₀Si₁₀B₁₀) were investigated as cathode materials for the alkaline electrolysis of water. In particular, the influence of cobalt as well as the metalloids boron and silicon on the activity for the hydrogen evolution reaction (HER) was studied in 1 M KOH at 298 K using cyclic voltammetric, galvanostatic and polarization techniques. The electrocatalytic activity was evaluated in the view of the overpotential. It was found that cyclic voltammetric techniques can be used to activate the melt-spun Fe-alloys strongly. Different cyclic voltammetric activation procedures are discussed and the influence of the sweep rate and the potential window on the HER activity was elucidated. The experimental data indicate that the addition of metalloids and, most importantly, of cobalt improves the HER activity of the materials. Thus, the overpotential can be reduced by 200 mV compared to polycrystalline Ni.     

Solid-state production of esterase using fish processing wastes by Bacillus altitudinis AP-MSU

The bacterium Bacillus altitudinis AP-MSU, able to produce esterase was isolated from the gut of marine fish Sardinella longiceps. The esterase production was investigated in solid-state fermentation experiment using various fish processing waste meal. Among the tested fish processing wastes, red grouper waste emerged as the best source for higher esterase production. The suitable surfactant and triglyceride identified to increase the lipase production was neem oil. Effect of individual carbon and nitrogen sources supplementation on esterase production revealed that fructose and peptone aided the higher esterase production than the other tested carbon and nitrogen sources. The suitable concentration of sodium chloride for higher esterase production was at 5%. Effect of surfactants and trace elements on esterase production showed that Tween 20 and zinc sulphate, respectively produced maximum amount of esterase. The effect of physical parameters on lipase production revealed that 50 °C temperature and pH 7–8 were optimum for higher esterase production. Statistical optimization with Plackett–Burman design showed that neem oil, NaCl and fructose were found to be the most predictive factors for esterase production by this strain.     

Comparative study on the heat transfer performance of micro-grooved anodized thermosyphon with R134a,R600a and R717 for low-temperature applications

Journal of Mechanical Science and Technology - A comparative heat transfer performance of an internally grooved anodized thermosyphon with eco-friendly refrigerants is presented in this study....     

Distance metric-based time-efficient fuzzy algorithm for abnormal magnetic resonance brain image segmentation

Image segmentation is one of the significant computational applications of the biomedical field. Automated computational methodologies are highly preferred for medical image segmentation since these techniques are immune to human perception error. Artificial intelligence (AI)-based techniques are often used for this process since they are superior to other automated techniques in terms of accuracy and convergence time period. Fuzzy systems hold a significant position among the AI techniques because of their high accuracy. Even though these systems are exceptionally accurate, the time period required for convergence is exceedingly high. In this work, a novel distance metric-based fuzzy C-means (FCM) algorithm is proposed to tackle the low-convergence-rate problem of the conventional fuzzy systems. This modified approach involves the concept of distance-based dimensionality reduction of the input vector space that substantially reduces the iterative time period of the conventional FCM algorithm. The effectiveness of the modified FCM algorithm is explored in the context of magnetic resonance brain tumor image segmentation. Experimental results show promising results for the proposed approach in terms of convergence time period and segmentation efficiency. Thus, this algorithm proves to be highly feasible for time-oriented real-time applications.     

A pattern based PSO approach for block matching in motion estimation

Block matching motion estimation is a popular method in developing video coding applications. A new algorithm has been proposed for reducing the number of search points using a pattern based particle swarm optimization (PSO) for motion estimation. The conventional particle swarm optimization has been modified to provide accurate solutions in motion estimation problems. This leads to very low computational cost and good estimation accuracy. Due to the center biased nature of the videos, the proposed approach uses an initial pattern to speed up the convergence of the algorithm. Simulation results show that improvements over other fast block matching motion estimation algorithms could be achieved with 31%～63% of search point reduction, without degradation of image quality.     

Probing first-order spatial coherence of a Bose-Einstein condensate

Abstract

We probe the spatial coherence properties of a magnetically trapped Bose gas. Two matter wave beams are extracted from two spatially separated regions of the trap and overlap outside the trapping region. The visibility of the resulting interference pattern measures the phase coherence between the regions of extraction. By varying the spatial separation between the two regions the first-order spatial correlation function of the trapped Bose gas can be measured. The location of the minima of the interference pattern is reproducible, which experimentally confirms that the trapped Bose-Einstein condensate is not fragmented into individual condensates.     

Power Quality Enhancement Using Linear Quadratic Regulator Based Current-controlled Voltage Source Inverter for the Grid Integrated Renewable Energy System

This paper presents an optimal control strategy using linear quadratic regulator (LQR) applied in current-controlled voltage source inverter (CCVSI) to control the real and reactive power flow between the renewable energy system (RES) and the grid. It also compensates harmonic current components drawn by the load from the grid terminal. A simplified equivalent circuit is used to develop the reduced order state space model of the three-phase grid connected renewable energy system. This makes the analysis and design of control law simpler by reducing the number of weighing variables used in LQR. The extension real–reactive power (p–q) method implemented in a–b–c frame is used to generate the reference current for controlling the real and reactive power to the grid to minimize the total harmonic distortion (THD) and to achieve unity power factor (UPF) operation at the grid side. The stated technique makes the grid current sinusoidal even under unbalanced grid voltages and the harmonic distortion factors are well within the IEEE limits. The system is simulated under changes in the real power fed from RES to the grid for both balanced and unbalanced grid conditions. The simulation results are validated by the experimental results.