Abdolsamad Zarringhalam Moghaddam

In this study, TiO₂ nanoparticles immobilized on sackcloth fibre were used for the photodegradation of acid dye, and the efficiency of heterogeneous photocatalysts was predicted using the support vector machines model and artificial neural network model. Acid Red 73 was applied as a model compound. The experimental results were determined as the function of key factors such as initial H₂O₂ concentration, dye concentration, dissolved anions, pH, and time. The obtained results were used for training the models. To find the most suitable and reliable network, different algorithms and transfer functions were tested. The trial and error method was used to find the optimum number of neurons and layers. The root mean squared of error (RMSE), the sum of square error (SSE), and R² for the models were calculated. Results show that support vector machines and neural network models can effectively learn and model the aforementioned process and predict the efficiency of photodegradation of coloured wastewater.

This study aims to propose the importance of employing statistical analysis and modeling for investigation on the design and optimization of CMS membranes for gas separation. The factorial methodology is used to optimize permeability and selectivity through implementing the general factorial design considering the three main parameters such as choice of precursor materials, blend composition and the final pyrolysis temperature. Findings by statistical analysis showed that the linear and quadric terms of these three variables had significant effects. The optimal conditions are the Matrimid, blend composition 70%, and pyrolysis temperature at 800°C. Under these conditions, the model estimated a CO₂/CH₄, H₂/CO₂, and O₂/N₂ selectivity of 120.2, 8.39, and 8.06, respectively. Employed statistical technique and developed models can be used as a useful tool for design and optimization of appropriate gas separation membranes with effective performance for various industrial applications. POLYM. ENG. SCI., 54:147–157, 2014. © 2013 Society of Plastics Engineers

The current paper reviews the effects of the oxygenated and nitrogenated additives to see the results of the physicochemical efficiency and performance through engine tests work by gas oil mixtures. The oxygenated compounds used in the formulations compose of 2-methoxy ethyl ether (MXEE), nitromethane, and nitroethane. The presence of ethanol and MXEE significantly alter the characteristics of flash point and distillation curve behaviors and marking up the cetane number, improving the fuel's performance in engine tests. The fuel formulations comprising 2–5% v/v additives, 5–10% v/v ethanol, and diesel 90–95% v/v were produced. The soot formation can be reduced by more than 50%, 30%, and 27% by application of the diesel formulations; E-NE5–10, E-NM5–10, and E-MX5–10, respectively.

Formation of a gas hydrate with two different gas compositions (natural gas and a mixture of methane‐ethane‐propane) was investigated using a special method of producing the hydrate from ice. Gas uptake, splitting the fraction of each component between the gas phase and hydrate phase, and purification of methane were studied in the presence of silica‐based porous media. Addition of a small amount of colloidal silica media increased considerably the gas storage capacity of the hydrate phase. In the presence of silica‐based porous media, the purification factor of CH₄ became significantly higher. The results can provide the basis for the storage of natural gas in hydrate form and application of the hydrate‐based gas separation technology to achieve methane with high purity from natural gas.

In this article, experimental measurements of flame temperature profile on a cylindrical tube circumference engulfed in a small‐scale pool fire were carried out. Three models were presented for flame temperature distribution with analytical and numerical based methods. The first model that is based on correlation showed the best agreements with experimental data, and other two models had almost acceptable predictions. The results revealed that the analytical and mathematical based model is more general than correlation methods and may be used to predict flame temperature and have wider‐range application usage. Copyright © 2011 John Wiley & Sons, Ltd.