Fluid Flow and Mixing in Non-Isothermal Water Model of Continuous Casting Tundish

Fluid flow and mixing of molten steel in a twin-slab-strand continuous casting tundish were investigated using a mixing model under non-isothermal conditions.This model led to a set of ordinary differential equations that were solved with a Runge-Kutta algorithm.Steady state water modeling was carried out under non-isothermal conditions.Experimental data obtained from the water model were used to calibrate the mixing model.Owing to the presence of a mixed convection in the non-isothermal conditions,a channelizing flow would be created in the fluid inside the tundish.A mixing model was designed that was capable of predicting RTD（residence time distribution）curves for different cases in non-isothermal conditions.The relationship between RTD parameters and the Tu（tundish Richardson number）was obtained for various cases under non-isothermal conditions.The results show that the RTD parameters were completely different under isothermal and non-isothermal conditions.The comparison of the RTD curves between the isothermal and non-isothermal conditions presents that the extent of mixing in the tundish in non-isothermal conditions is lower than the mixing extent in isothermal conditions.     

One-pot synthesis of hematite-alumina hollow sphere composite by ultrasonic spray pyrolysis technique with high adsorption capacity toward PAHs

A hybrid nanocomposite of alumina and hematite was synthesized by ultrasonic spray pyrolysis technique. The study of microscopic images, mapping analysis, and XRD patterns revealed that the Al₂O₃ – Fe₂O₃ nanocomposite was composed of separated spherical particles with a thin layer ball-shaped structure that metal oxides are uniformly distributed in the wall of hollow sphere particles, led to a coherent and monotonous construction. A series of coefficients of equilibrium sorption of polycyclic aromatic hydrocarbons (PAHs) as hazardous materials were measured on the prepared composite material in a batch technique. The free or pure Al₂O₃ or Fe₂O₃ showed negligible removal efficiency for the mentioned analytes. The various significant variables, such as initial analyte concentration, solution pH, adsorbent dose, and contact time to remove analyte, were studied in the aqueous solutions. Adsorption data were modeled to Langmuir, Freundlich, and Temkin isotherms, and a good correlation found in the case of Langmuir isotherm and adsorption capacity for anthracene, phenanthrene, and naphthalene were 370, 333, and 322 mg g^?1, respectively. Investigation of the kinetic models proved a pseudo-second-order, and the prepared adsorbent can be reused more than 7 times without a significant decrease of adsorption performance.     

A polar-based guided multi-objective evolutionary algorithm to search for optimal solutions interested by decision-makers in a logistics network design problem

In practical multi-objective optimization problems, respective decision-makers might be interested in some optimal solutions that have objective values closer to their specified values. Guided multi-objective evolutionary algorithms (guided MOEAs) have been significantly used to guide their evolutionary search direction toward these optimal solutions using by decision makers. However, most guided MOEAs need to be iteratively and interactively evaluated and then guided by decision-makers through re-formulating or re-weighting objectives, and it might negatively affect the algorithms performance. In this paper, a novel guided MOEA that uses a dynamic polar-based region around a particular point in objective space is proposed. Based on the region, new selection operations are designed such that the algorithm can guide the evolutionary search toward optimal solutions that are close to the particular point in objective space without the iterative and interactive efforts. The proposed guided MOEA is tested on the multi-criteria decision-making problem of flexible logistics network design with different desired points. Experimental results show that the proposed guided MOEA outperforms two most effective guided and non-guided MOEAs, R-NSGA-II and NSGA-II.     

Effects of high pressure treatment on glycolytic enzymes of Lactococcus lactis subsp. lactis,Streptococcus thermophilus and Lactobacillus acidophilus

High pressure processing (HPP) reduces the glycolytic activity of lactic acid bacteria (LAB) and provides a means to control further production of acidic metabolites in fermented dairy products during storage. However, there is limited information on the effects of HPP on specific enzymes of dairy starter bacteria responsible for the metabolism of lactose. The aim of this study was to determine pressure-induced inactivation of glycolytic enzymes in Lactococcus lactis subsp. lactis C10, Streptococcus thermophilus TS1 and Lactobacillus acidophilus 2400. Cultures were grown for 16 h in M17 or MRS broth containing 5% (w/v) lactose at pH 6.5 (maintained by addition of 10 M NaOH). The cells were harvested by centrifugation, washed and resuspended in 100 mM phosphate buffer (pH 6.5) and pressure-treated at 300 and 600 MPa (≤ 22 °C, 5 min). The ability of pressure-treated resting cells of Lactococcus, incubated with 5% (w/v) lactose at 30 °C, to ferment lactose was evaluated by determining titratable acidity (TA) during incubation. The activities of phospho-β-galactosidase (P-β-gal), β-galactosidase (β-gal) and lactate dehydrogenase (LDH) were determined in cell-free extracts of untreated and pressure-treated cells. Resting cells of Lactococcus treated at 600 MPa had a substantially lower rate of acidification than the controls and those treated at 300 MPa. Both P-β-gal and β-gal were significantly inactivated (p < 0.01) in the starter cultures treated at 300 or 600 MPa. The LDH in Lactococcus and Lactobacillus was highly resistant to pressure treatment at 300 MPa. In contrast, the LDH in Streptococcus was almost completely inactivated at ≥ 300 MPa.Industrial relevanceContinuing production of acidic metabolites in fermented dairy products during storage can be a technological challenge that adversely affects product quality. The current study demonstrates that high pressure processing (HPP) offers the potential of controlling this problem by inactivation of glycolytic enzymes in various mesophilic and thermophilic starter cultures. The findings of this research will assist in establishing optimised operating parameters for HPP treatment of cultured products to extend shelf-life, by reducing acid production during storage.     

Effectiveness of Zataria multiflora Boiss essential oil and grape seed extract impregnated chitosan film on ready-to-eat mortadella-type sausages during refrigerated storage

BACKGROUND: The effectiveness of chitosan films containing Zataria multiflora Boiss essential oil (ZEO) (5 and 10 g kg^?1) and grape seed extract (GSE) (10 g kg^?1) on lipid oxidation and microbial (lactic acid bacteria, aerobic mesophiles and inoculated Listeria monocytogenes) characteristics of mortadella sausage at 4 °C for 21 days was evaluated. The release of total phenolics (TPs) into sausage was also assessed. RESULTS: All films exhibited antibacterial activity against L. monocytogenes on agar culture media. Chitosan films containing ZEO were the most effective on the growth of bacteria. The growth of L. monocytogenes was significantly inhibited by ZEO‐GSE containing films especially during storage of the sausages for 6 days. Aerobic mesophiles and lactic acid bacteria were the most sensitive and resistant groups to films by 0.1–1.1 and 0.1–0.7 log cycles reduction, respectively. Sausages wrapped by 10 g kg^?1 GSE + 10 g kg^?1 ZEO films had the lowest degrees of lipid oxidation, which was 23% lower than the control. The TPs of ZEO films decreased to zero after 6 days, whereas TPs of GSE films followed a slight decrease during the storage. CONCLUSION: Antimicrobial/antioxidant chitosan film could be developed by incorporating GSE and ZEO for extending the shelf life of mortadella sausage. Copyright © 2011 Society of Chemical Industry     

Extraction of ferulic acid from sugar beet pulp by alkaline hydrolysis and organic solvent methods

Extraction of ferulic acid from sugar beet pulp was carried out using three extraction solvents, sodium hydroxide (0.5, 1, 2 M), methanol and their mixture (alkaline methanolic solvent). The Ferulic acid extracted by each solvent was identified and quantified by HPLC method and the effects of solvent type, concentration and reaction time on ferulic acid solubilisation were assessed. There were differences in the contents of products extracted in the experiment conditions. The minimum amount of ferulic acid was obtained from methanolic extract while the highest concentrations (957.4 mg/L ferulic acid) were obtained employing the highest NaOH concentration (2 M), and reaction time (12 h), so phenolic compounds are better released with alkaline hydrolysis than in methanol conditions. Finally a simple procedure for the purification of ferulic acid from the alkaline extracts is presented and evaluated by FT-IR spectrum.     

Genetic-based minimum classification error mapping for accurate identifying Peer-to-Peer applications in the internet traffic

In this paper, we propose a hybrid approach using genetic algorithm and neural networks to classify Peer-to-Peer (P2P) traffic in IP networks. We first compute the minimum classification error (MCE) matrix using genetic algorithm. The MCE matrix is then used during the pre-processing step to map the original dataset into a new space. The mapped data set is then fed to three different classifiers: distance-based, K-Nearest Neighbors, and neural networks classifiers. We measure three different indexes, namely mutual information, Dunn, and SD to evaluate the extent of separation of the data points before and after mapping is performed. The experimental results demonstrate that with the proposed mapping scheme we achieve, on average, 8% higher accuracy in classification of the P2P traffic compare to the previous solutions. Moreover, the genetic-based MCE matrix increases the classification accuracy more than what the basic MCE does.     

Adaptive enhancement and binarization techniques for degraded plate images

Multimedia Tools and Applications - Vehicle License Plate Recognition (VLPR) is one of the most important aspects of applying computer techniques in Intelligent Transport Systems (ITS). They face...     

Multi expression programming: a new approach to formulation of soil classification

This paper presents an alternative approach to formulation of soil classification by means of a promising variant of genetic programming (GP), namely multi expression programming (MEP). Properties of soil, namely plastic limit, liquid limit, color of soil, percentages of gravel, sand, and fine-grained particles are used as input variables to predict the classification of soils. The models are developed using a reliable database obtained from the previously published literature. The results demonstrate that the MEP-based formulas are able to predict the target values to high degree of accuracy. The MEP-based formulation results are found to be more accurate compared with numerical and analytical results obtained by other researchers.     

Multi agent architecture for dynamic incremental process planning in the flexible manufacturing system

Due to rapid changes of markets and pressures of competitions, industries are adopting their production ways to support diversity of customer’s needs and increase of new product developments. This paper deals with development of an agent-based architecture of dynamic systems for process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A previously proposed negotiation protocol is customized and improved to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks and the suitable process plans are searched and generated to cope with both the dynamic status and disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans.