Experimental investigation of particle distribution in a flow through a stenosed artery

The particle distribution of a dilute solid-liquid suspension through a stenosed arterial geometry was investigated. Particle image velocimetry (PIV) was used to determine the velocity as well as to acquire the flow images. The light intensity scattered by particles was evaluated to determine the particle distribution. Flow separation exists where the flow emerges from the stenosis throat. From the PIV images, the particle density distribution exhibited differing non-uniform characteristics which vary with flow rate, particle size and particle concentration. At low flow rates, a particle-free layer is formed. As the flow rate is increased, particles accumulate in concentric recirculation orbits within the downstream vortex. Particles with larger size and higher concentration tend to accumulate more towards the center of the vortex.     

Thermodynamic and NMR investigations on the adsorption mechanism of puerarin with oligo‐β‐cyclodextrin‐coupled polystyrene‐based matrix

BACKGROUND: Adsorption of puerarin on native resin polystyrene (PS) and oligo‐β‐cyclodextrin‐coupled matrix (PS‐CDP) was studied for interactions between the adsorbents and the adsorbates. The sorption mechanism on PS‐CDP was investigated using the isosteric heat approach and nuclear magnetic resonance (NMR) spectroscopy. RESULTS: The equilibrium adsorption data of puerarin on the two matrices PS and PS‐CDP (polystyrene‐based matrix before and after coupling by oligo‐β‐cyclodextrin) in the temperature range 288–318 K were well fitted to the Freundlich adsorption isotherm model. The energetic heterogeneity of the media was observed based on the result that the values of isosteric enthalpy were quantitatively correlated with the fractional loading of puerarin adsorption. The more heterogeneous surface of PS‐CDP compared with PS was attributed to the complexation between puerarin and β‐cyclodextrin (β‐CD). NMR studies validated the formation of an inclusion complex puerarin/β‐CD. CONCLUSION: Thermodynamic and NMR studies confirmed that multi‐interaction cooperatively governed the isolation of puerarin from aqueous solution on PS‐CDP matrix. Copyright © 2009 Society of Chemical Industry     

Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for an instantaneous reactive and active current (I_d-I_q) and power theory (Pq0) in SIMULINK. To prevent the degradation effect of disturbances on the system's performance, PS0-PI is applied in the inner loop which generate a required dc link-voltage. Additionally, a comparative analysis of both techniques has been presented to evaluate and validate the performance under balanced load conditions. The presented result concludes that the Adaptive Fuzzy PI controller performs better due to the non-linearity and robustness of the system. Therefore, the gains taken from a tuning of the PSO based PI controller optimized with Fuzzy Logic Controller (FLC) are optimal that will detect reactive power and harmonics much faster and accurately. The proposed hybrid technique minimizes distortion by selecting appropriate switching pulses for VSI (Voltage Source Inverter), and thus the simulation has been taken in SIMULINK/MATLAB. The proposed technique gives better tracking performance and robustness for reactive power compensation and harmonics mitigation. As a result of the comparison, it can be concluded that the PSO-based Adaptive Fuzzy PI system produces accurate results with the lower THD and a power factor closer to unity than other techniques.     

Pollution source identification using a coupled diffusion model with a genetic algorithm

A new approach for the source quantification has been developed on the basis of real air pollutant hourly concentrations of SO₂, measured by three monitoring stations, during 9 h, around a group of three industrial sources. This inverse problem has been solved by coupling a direct model of diffusion (Pasquill’s Gaussian model) with a genetic algorithm, to search solutions leading to a minimum error between model outputs and measurements. The inversion performance depends on the relationship between the wind field and the configuration sources–receptors: good results are obtained when the monitoring stations are downwind from the sources, and in these cases, the order of magnitude of emissions is retrieved, sometimes with less than 10% error for at least two sources; there are some configurations (wind direction versus source and receptor locations) which do not permit to restore emissions. The latter situations reveal the need to conceive a specific network of sensors, taking into account the source locations and the most frequent weather patterns.     

Uncertainty modeling and robust minimax LQR control of multivariable nonlinear systems with application to hypersonic flight

For a class of multi‐input and multi‐output nonlinear uncertainty systems, a novel approach to design a nonlinear controller using minimax linear quadratic regulator (LQR) control is proposed. The proposed method combines a feedback linearization method with the robust minimax LQR approach in the presence of time‐varying uncertain parameters. The uncertainties, which are assumed to satisfy a certain integral quadratic constraint condition, do not necessarily satisfy a generalized matching condition. The procedure consists of feedback linearization of the nominal model and linearization of the remaining nonlinear uncertain terms with respect to each individual uncertainty at a local operating point. This two‐stage linearization process, followed by a robust minimax LQR control design, provides a robustly stable closed loop system. To demonstrate the effectiveness of the proposed approach, an application study is provided for a flight control problem of an air‐breathing hypersonic flight vehicle (AHFV), where the outputs to be controlled are the longitudinal velocity and altitude, and the control variables are the throttle setting and elevator deflection. The proposed method is used to derive a linearized uncertainty model for the longitudinal motion dynamics of the AHFV first, and then a robust minimax LQR controller is designed, which is based on this uncertainty model. The controller is synthesized considering seven uncertain aerodynamic and inertial parameters. The stability and performance of the synthesized controller is evaluated numerically via single scenario simulations for particular cruise conditions as well as a Monte‐Carlo type simulation based on numerous cases. It is observed that the control scheme proposed in this paper performs better, especially from the aspect of robustness to large ranges of uncertainties, than some controller design schemes previously published in the literature. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Fuzzy logic-based pre-classifier for tropical wood species recognition system

Classifying tropical wood species poses a considerable economic challenge and failure to classify the wood species accurately can have significant effects on timber industries. The problem of wood recognition is compounded with the nonlinearities of the features among the similar wood species. Besides that, large wood databases presented a problem of large processing time especially for online wood recognition system. In view of these problems, we propose the use of fuzzy logic-based pre-classifier as a means of treating uncertainty to improve the classification accuracy of tropical wood recognition system. The pre-classifier serve as a clustering mechanism for the large database simplifying the classification process making it more efficient. The use of the fuzzy logic-based pre-classifier has managed to increase the accuracy of the wood recognition system by 4 % and reduce the processing time for training and testing by more than 75 % and 26 % respectively.     

Supervised Multi‐Rejector of Periodic Disturbances for Nonlinear Systems Using Decoupled State Multimodel

In this paper, a multi‐rejector of periodic disturbances is proposed for discrete‐time nonlinear systems represented by a decoupled state multimodel. We report a decoupled state multimodel repetitive‐predictive control based on a supervised algorithm to ensure reference trajectory tracking and periodic disturbances rejection. Partial predictors associated to the local controllers make the best choice of the most valid partial controller that meets the desired closed loop performances. The effectiveness of the supervised multi‐rejector is shown via a simulation example. The obtained results are satisfactory and show a good rejection of periodic disturbances and reference trajectory tracking.     

On colloid-chemical properties of some polymer composites

The influence of the vibrowave action on the properties of some disperse systems used in the textile industry has been considered. It has been noted that excitation of nonlinear oscillation in the audio band under resonant conditions leads to an increase in the degree of dispersion of distributed systems and an increase in their colloid stability. __________ Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 79, No. 1, pp. 133–138, January–February, 2006.     

Recent Advances in Poly (Amide-B-Ethylene) Based Membranes for Carbon Dioxide (CO2) Capture: A Review

Polyamide-b-ethylene (Pebax) is a promising material for membrane-based gas separation application with excellent CO₂ capturing potential. Pebax is a rubbery elastomer which offers good mechanical support with its hard crystalline phase and excellent gas transport through its amorphous polyether phase. This review article includes recent advances in Pebax based membrane synthesis, solvent selection for membrane synthesis, compatible fillers with Pebax matrix and the improved gas separation performance of the prepared membranes. The literature review shows that Pebax based membranes are a good candidate for separation of CO₂ from flue gases and can be used for commercial applications.