A density-based fuzzy clustering technique for non-destructive detection of defects in materials

In non-destructive testing and evaluation of materials, defects contain visible aggregations of similar levels of brightness with large scale of correlation between them. In most cases, these brightnesses have no notable contrast relative to non-defect counterparts. However, the density and the size of the defect are visually the most notable features. In this paper, we have utilized human conception for classifying defects by the fusion of fuzzy clustering method and fuzzy logic rules based on the density and the size of the defect. The probability of detection and the probability of error are compared with the Bayes classifier. The proposed approach shows that there is less dependency between the variation of density and size of a defect and variations of noise density and distribution. Experimental images from eddy current, ultrasonic and radiography techniques are investigated. It is shown that the new approach reduces the noise and drift, leading to a better detection of defects.     

Efficient and mild synthesis of ortho-hydroxyaryl ketones catalyzed by zinc chloride under solvent-free condition and microwave irradiation

Preparation of ortho-hydroxyaryl ketones was regioselectively carried out from phenol and naphthol derivatives, in reaction with various organic acids by using a ZnCl₂ as catalyst, under microwave and solvent-free mild conditions. In this reaction, the products were obtained in very high yields and very short reaction times.     

Information processing in recovered depressed children and adolescents

Previous research into subjective probability estimates for negative events revealed that depressed children estimated events as equally likely to happen to themselves as to other children. In contrast, both controls and anxious children estimated that negative events were more likely to happen to others than to themselves. The present study followed up this finding by investigating the subjective probability judgements concerning future negative events generated by children and adolescents who have recovered from depression. Subjects generated probability estimates either for themselves or for other children for a range of negative events on a visual analogue scale. The results revealed that both recovered depressed and matched control groups estimated negative events as significantly more likely to happen to others than to themselves. It was also found that the recovered depressed subjects estimated that negative events were less likely overall, compared to the controls. These results are discussed in the context of the adult literature.     

Determining the optimum replacement policy for Holstein dairy herds in Iran

The objective of this study was to determine the optimum replacement policy for Holstein dairy herds in Iran using a dynamic programming model. Cows were described in terms of state variables that included milk production class, parity, pregnancy status, and month in milk with a 1-mo stage length. The objective function maximized the net present value of cows over a 15-yr planning horizon. Markov simulation was used to estimate expected herd dynamics under the optimal decision plan determined by dynamic programming. Stochastic elements included probabilities of pregnancy and abortion, production level, and involuntary culling. The optimum annual culling rate was estimated to be 31.4%, and cows had an expected herd life (time from first calving until culling) of 3.18 yr. High replacement cost and low carcass value resulted in only 2.87% voluntary culling (i.e., optimal model-based replacement). Assuming a heat detection rate of 0.4, cows averaged 2.8 services per lactation under the optimal policy. Sensitivity analyses were carried out to evaluate the effect of milk price, herd-average production, feed cost, heifer price, and carcass value on optimum replacement decisions. Herd-average production, replacement cost, and risk of involuntary culling were important factors affecting the optimal culling policy. Changes in the price of feed, calves, and milk and the probability of pregnancy had no considerable effect on the optimal policy considering the market situation in Iran during 2008.     

The simplest method for calculating energy output and Gurney velocity of explosives

Two correlations are introduced for calculating Gurney velocity as a useful parameter for thermochemical estimation of explosive energy output. For CaHbNcOd explosives, only the chemical composition of high explosive as well as its condensed or estimated gas phase heat of formation, which later is calculated by group additivity rules, is needed for calculating Gurney velocity. The introduced simple correlations in the present work may be applied to any explosive that contains the elements of carbon, hydrogen, nitrogen and oxygen with no difficulties at any loading density. There is no need to use any assumed decomposition reaction in present work. Gurney velocity are calculated for different pure and explosive formulations and compared with measured Gurney velocity at specified loading density. The results show that the agreement is good for present method as compared to previous correlations.     

Effect of ultrasound- and pulsed electric field-assisted enzymatic treatment on the recovery and quality of sunflower oil

The aim of this study was to evaluate the effect of cavitation and electroporation on enzymolysis extraction of sunflower oil. The optimum extraction conditions during 2 h under enzyme-assisted extraction (EAE) with a maximum oil yield of ≈23.70 ± 0.11% were as follows: cellulase/pectinase ratio 2:1, enzyme concentration 2%, pH 4.5, liquid/solid ratio 6:1 ml/g, and extraction temperature 40°C. Under the optimized enzymatic conditions, the application of ultrasound- (250 W) and pulsed electric field- (1.2 kV/cm; 52.4 kJ/kg) assisted enzymatic extraction for 30 min significantly increased the oil extraction yield by 91.1% and 18.6%, respectively, as compared with EAE.     

Coupled particle swarm optimization method with genetic algorithm for the static–dynamic performance of the magneto-electro-elastic nanosystem

As a first attempt, Fourier series expansion (FSE), particle swarm optimization (PSO), and genetic algorithm (GA) methods are coupled for analysis of the static–dynamic performance and propagated waves in the magneto-electro-elastic (MEE) nanoplate. The FSE method is presented for solving the motion equations of the MEE nanoplate. For increasing the performance of genetic algorithms for solving the problem, the particle swarm optimization technique is added as an operator of the GA. Accuracy, convergence, and applicability of the proposed mixed approach are shown in the results section. Also, we prove that for obtaining the convergence results of the PSO and GA, we should consider more than 16 iterations. Finally, it is shown that if designers consider the presented algorithm in their model, the results of phase velocity of the nanosystem will be increased by 27%. A useful suggestion is that there is a region the same as a trapezium in which there are no effects from magnetic and electric potential of the MEE face sheet on the phase velocity of the smart nanoplate, and the region will be bigger by increasing the wavenumber.

     

Rate of Methane Hydrate Formation in Presence of Tetra-n-Butylammonium Chloride and Tween 80: Application in Air Conditioning Systems

Theoretical Foundations of Chemical Engineering - Moderate hydrate forming conditions of tetra-n-butylammonium salts have made these compounds as attractive materials to store the cold in air...     

Study of the performance of dry methane reforming in a microchannel reactor using sputtered Ni/Al2O3 coating on stainless steel

In this study, a microchannel reactor was designed, its catalytic performance in dry methane reforming (DRM) was assessed, and the results were compared with those observed in a conventional fixed bed reactor. The catalyst was prepared in two forms, including catalyst pellets and catalyst-coated plate. The microchannel reactor had thin films of Ni/Al₂O₃ coated on stainless steel substrate via radio frequency (RF) magnetron sputtering method in various sputtering times. The fall-off rate of the catalyst-coated plates can be neglected after putting the plates under the high-temperature DRM reaction, due to the formation of firm active catalyst coatings. The performance of the samples was evaluated at different temperatures from 700 to 800 °C, at P = 1 atm, with a CH₄:CO₂ ratio of 1. The results of XRD showed that with increasing the sputtering time, there was an increase in crystallinity. As observed in FESEM images, the sample prepared with 5 min of sputtering was dense and uniform. The results of EDX not only proved the dispersion of the samples observed in XRD and FESEM analysis, but also verified the presence of the utilized elements. The temperature of 800 °C and the sample with 5 min sputtering time were selected as the optimum condition that provided the best performance. Catalytic performance was investigated in fixed bed reactor at the same GHSV; based on the results there were no significant conversions in the fixed bed reactor. The results of the stability test in the microchannel reactor showed a good performance during 30 h on stream. Therefore, Ni/Al₂O₃ thin films had a satisfactory performance in the designed microchannel. Our study shows that this type of reactor has many advantages in terms of performance, compactness, and economic concerns.