Heterogeneous photocatalytic degradation of 4-chlorophenol by immobilization of cobalt tetrasulphophthalocyanine onto MCM-41

The photocatalytic activity of cobalt tetrasulphophthalocyanine immobilized onto MCM-41 was investigated for photocatalytic degradation of 4-chlorophenol (4-CP) in aqueous solutions. Immobilization of cobalt tetrasulphophthalocyanine complex to the walls of MCM-41 was performed by pre-anchorage of 3-(aminopropyl)-triethoxysilane (APTES) onto MCM-41 via post-synthesis method. X-ray diffraction, nitrogen physisorption, diffuse reflectance spectroscopy, energy-dispersive X-ray and FT-IR methods were used to characterize the product. Photocatalytic efficiency of the prepared photocatalyst for degradation of 4-CP was tested under illumination of UV-A and visible light. The reaction intermediates were identified by gas chromatography-mass spectrometry (GC-MS) technique.     

State estimator condition number analysis

This paper develops formulas for the condition number of the state estimation problem as a function of the different types and number of measurements. We present empirical results using the IEEE RTS-96 and IEEE 118 bus systems that validate the formulas     

Experimental investigation of effect of palmitic acid as inhibitor on particle size of asphaltenes flocs using imaging techniques

In this article, the effect of one well-known inhibitor namely palmitic acid is investigated on particle size distribution of asphaltenes by imaging techniques. Pure asphaltene is extracted from crude oil to prepare Heptol (n-heptane+toluene) solutions of suspended asphaltenes. Different concentrations of inhibitors are then added to the solution. Afterward, image analysis of microscopic photos is used to determine the particle size distribution of asphaltene flocs in the presence of inhibitors. Average particle size of asphaltene and fractal structure of aggregates are also investigated; results show that the compaction of asphaltenes flocs is correlated with concentration of inhibitor. However, no significant relationship was observed between surface roughness of flocs and inhibitor concentration.     

Detailed modeling of the evaporation and thermal decomposition of urea‐water solution in SCR systems

This work is aimed to develop a multicomponent evaporation model for droplets of urea‐water solution (UWS) and a thermal decomposition model of urea for automotive exhausts by using the selective catalytic reduction systems. In the multicomponent evaporation model, the influence of urea on the UWS evaporation is taken into account using a nonrandom two‐liquid activity model. The thermal decomposition model is based on a semidetailed kinetic scheme accounting not only for the production of ammonia (NH₃) and isocyanic acid but also for the formation of heavier solid by‐products (biuret, cyanuric acid, and ammelide). This kinetics model has been validated against gaseous data as well as solid‐phase concentration profiles obtained by Lundstroem et al. (2009) and Schaber et al. (2004). Both models have been implemented in IFP‐C3D industrial software to simulate UWS droplet evaporation and decomposition as well as the formation of solid by‐products. It has been shown that the presence of the urea solute has a small influence on the water evaporation rate, but its effect on the UWS temperature is significant. In addition, the contributions of hydrolysis and thermolysis to urea decomposition have been assessed. Finally, the impacts of the heating rate as well as gas‐phase chemistry on urea decomposition pathways have been studied in detail. It has been shown that reducing the heating rate of the UWS causes the extent of the polymerization to decrease because of the higher activation energy. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

State estimation distributed processing [for power systems]

This paper presents an application of a parallel algorithm to power systems state estimation. The authors apply the auxiliary problem principle to develop a distributed state estimator, demonstrating its performance on the Electric Reliability Council of Texas (ERCOT) and the Southwest Power Pool (SPP) systems     

Evaluation of driver drowsiness using respiration analysis by thermal imaging on a driving simulator

In this paper, a new non-intrusive driver drowsiness detection method is introduced based on respiration analysis using facial thermal imaging. Drowsiness is the cause of many driving accidents all over the world. Drivers’ respiration system undergoes significant changes from wakefulness to drowsiness and can be used to detect drowsiness. Current respiration measurement methods are intrusive and uncomfortable making respiration the least measured vital sign during driving. In this paper, a new method is presented based on facial thermal imaging to analyze drivers’ respiration signal non-intrusively. Thirty subjects are tested in a car simulator. They are fully awake at the beginning and experience drowsiness during the tests. The mean and the standard deviation of the respiration rate and the inspiration-to-expiration time ratio are extracted from the subjects’ respiration signal. To detect drowsiness, the Support Vector Machine (SVM) and the K-Nearest Neighbor (KNN) classifiers are used. The Observer Rating of Drowsiness method is used for scoring the drowsiness level and validating the proposed method. The performance and the results of both methods are presented and compared. The results indicate that drowsiness can be detected with the accuracy of 90%, sensitivity of 92%, specificity of 85%, and precision of 91%.

     

Estimating the Bubble Point Pressure and Formation Volume Factor of Oil Using Artificial Neural Networks

The phase performance of hydrocarbons is a very complicated behavior that hydrocarbons show at the time of phase change or when they remain in a particular phase. Process design is almost impossible without a good understanding of this behavior. Artificial Neural Networks have been widely utilized for engineering applications during the last two decades. Two models are presented for the prediction of the bubble point pressure and the oil formation volume factor for hydrocarbon mixtures using the Artificial Neural Networks (ANNs) approach. For this purpose, five‐layer neural networks were designed and trained using 106 experimental data points. After the training step, 9 experimental data points were also used for the model evaluation step and as a reliability check. The output of the models for both the training and predicted data are compared with the empirical equations of Standing, Glaso and Marhoun. It is concluded that the ANNs approach has an excellent capability for these purposes compared to the conventional methods.     

A successive boundary element model for investigation of sloshing frequencies in axisymmetric multi baffled containers

This study presents a developed successive Boundary Element Method to determine the symmetric and antisymmetric sloshing natural frequencies and mode shapes for multi baffled axisymmetric containers with arbitrary geometries. The developed fluid model is based on the Laplace equation and Green's theorem. The governing equations of fluid dynamic and free surface boundary condition are also applied to proposed model. A zoning method is presented to model arbitrary arrangement of baffles in multi baffled axisymmetric tanks. The influence of each zone on neighboring zones is applied by introducing interface influence matrix which correlates the velocity potential of interfaces to their flux. By discretizing the flow boundaries, the integral equation governed on the boundary is formulated into a general matrix eigenvalue problem. The proposed method has a considerable effect on decreasing computational cost and a good accuracy in determining the sloshing natural frequencies. The obtained results for different types of container based on the application of the presented study are validated in comparison with the literature and very good agreement is achieved. Finally, the effect of baffle parameters on the sloshing natural frequencies was investigated and some conclusions are outlined.     

Chemical and microbiological stability and sensorial properties of traditional Iranian butter incorporated with pomegranate peel extract

In this study, the antioxidant activity of pomegranate peel extract (PPE) and its potential effect on the chemical and microbiological stability of traditional butter was investigated. The PPE having total phenol content of 327.48 ± 1.43 mg gallic acid equivalent/g showed significantly greater (64.34 ± 0.32%) radical scavenging activity than butylated hydroxy toluene. Butter treated with PPE had significantly lower levels of peroxide value, free fatty acids, Totox, Schaal value and microbial population. The work concluded that PPE could be an excellent natural source of antimicrobial and antioxidant substances, which can be used for traditional butter preservation.     

An Inverse Modeling Approach to Calibrate Parameters for a Drainage Model with Two Optimization Algorithms on Homogeneous/Heterogeneous Soil

Water Resources Management - Due to the time and spatial limitations of subsurface drainage pilots, simulation models have been extensively applied for evaluating these systems. Since the accuracy...