INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN)
Year:2008 | Volume:19 | Issue:7|Papers Count:13

Heat exchangers are one of the most common process equipments in the process industry with much more significance nowadays due to the importance of energy saving and optimization. The shell and tube type accounts for the majority of the exchangers in use. Changes in processing conditions necessitate prediction of new situations that may arise which is only possible through reliable modeling and simulation procedures. In the present work two separate models (a plug flow model and a cross flow model) were developed. Pressure drop and flow analysis calculations were carried out using Willis and Johnson method for the shell side while tube side process drop was evaluated using the Bell method. Based on these calculation methods a combined model with different combination from the two base models was developed to provide a more real prediction. The simulation results were checked against experimentation taken place at Delaware University and about±10% error was recorded.

Inhibiting of gel forming, under certain pH and temperature conditions, is one of the most effective ways in leaching process of siliceous zinc concentrates. In order to provide the crucial conditions for extracting zinc from siliceous zinc concentrates, the variables, e.g. temperature, pH, time duration, rotation speed of mixer and the remaining time which are known to affect the leaching process efficiency have been optimized. Experimental results indicate that the decreasing pH to close one, keeping solution temperature near boiling-point, mixing speed close to 200 rpm and the time duration of each period to be 180 minutes, optimizes the efficiency. Furthermore, to inhibit gel forming and super saturation which decreases efficiency, extraction time should be decreased. Due to gradual pH increase in the second stage of the experiments, impurities will not be dissolved and hence their omission will be more effective.

This research aims at study of the effect of sulfide on operation of one of the aerobic biological treatment processes, activated sludge. For this purpose, two pilot plant units were designed and constructed. One of these units was run for wastewater sulfide contaminant (sample), and the other one was run for wastewater without sulfide contaminant (Reference). First of all, in a quantities study, sample system was run with different influent sulfide concentrations, and compared with reference system. Then, concentration of influent sulfide was increased gradually until the inhibitory effect of sulfide on treatment process appeared. Finally, the concentration at which sulfide was inhibitory and resulted in process malfunction was determined. Also, the reference system was run with different influent COD and detention times. At the end, the behavior of pilot plants of the reference system and the sample system, were simulated with Contois model, and the microbial growth kinetic coefficient, and inhibiting coefficient of sulfide were defined.

Biodesulfurization of oil component is an important biological Attraction of the oil industry. Researches and studies in this area are going on to reach to the industrial scale. On this way, there are so many problems which can be solved by proper research. In current article, the aim is creating desirable technical knowledge for a special bacteria immobilization our studies around this subject proved that this method is very useful. Immobilization process has been performed successfully and the desirable support (calcium alginate) was selected. As the second step the concentration of calcium chloride and Naalginate was optimized (0.05 mol for the first and 700 mlg for the second) optimization steps was complete through the factorial method. In the last step through the same methods we could prove that our immobilized bacteria is renewable and can be recovered for using in another desulfurization experiment.

In the 1970s, regulations in some countries forced users of heavy residue to limit pollutant emissions at industrial sites, also forced producers to upgrade their heavy products for export and domestic use. For this reason Iran as a producer, exporter and consumer has to develop new upgrading processes. The most common processes for upgrading heavy oil are catalytic processes, but existence of heavy metals, asphaltenes, sulfur and nitrogen compounds in heavy oil poses several serious problems in the process. Hence at first, the unwanted materials must be lowered to the acceptable limit in the feed .Of all the techniques conceived and tested to separate asphaltenes from oily feed, only one has been developed industrially, deasphalting by light solvents. In this study, deasphalting of vacuum bottom of Tehran and Arak refineries were evaluated using light alkane solvents such as n-pentane, n-heptane and L.S.R.G. (Light Straight Run Gasoline) and compared with propane deasphalting units in refineries. Results show that pentane and heptane are good solvents for asphaltene separation as well as nickel, vanadium, sulfur and nitrogen compounds but more efficient compared to propane. Finaly, according to the qualitative and quantitative specification of produced DAOs using pentane, heptane and L.S.R.G. it was shown that liquid solvents are suitable feed for catalytic units (e.g. FCC) after unifining process.

By anodizing of titanium and then electroplating of Platinum on surface anodized titanium, electrodes with high effective surface catalytic were made. Consideration of surface morphology using scanning electron microscope (SEM) shows that, with anodizing, micro porous layer on titanium surface was prepared. The electro catalytic behavior of this type of electrodes in the isopropanol electro oxidation and in the chlorine evolution reaction was studied. Comparison of electro catalytic activity of this type of electrodes with platinum electrodes shows that, these electrodes have more than electro catalytic activity of platinum electrodes. Thereby we can use of this type of electrodes in chloro-alkaline industry as a suitable anodes.

In present study a mathematical model is developed in order to examine the effects of heat and mass transfer on removal efficiency of particulate matters in Venturi type scrubbers. The governing equations including the particulate concentration, gas temperature, droplets temperature, droplets diameter, and droplets velocity equations are obtained by using the conservation laws and solved numerically. To validate the mathematical model, necessary data was measured and collected in a commercial cement plant that uses this type of scrubbers for controlling of air pollution. A good agreement between plant data and the model predictions is noticed in general, and results obtained from the model reveal that the existing of temperature difference between gas and liquid droplets decreases the overall removal efficiency of particulate matters. This is due to very rapid reduction of relative velocity between droplets and gas, resulted from heat and mass transfer between them especially in throat section of Venturi. The effects of variation of various operating parameters on extent of reduction in removal efficiency were examined by using the model. This study confirms that in most industrial applications of Venturi scrubbers it is necessary to use a direct or an indirect cooling tower for decreasing of gas temperature before entering the Venturi.

In this paper, the performance of a two-phase closed thermo-siphon (heat pipe) with water as the working fluid for thermal control of a batch reactor was studied. In the simulation performed, the influence of some parameters such as: filling ratio of 30%-80% and input heat power between 200- 1200 watt and heating time on the uniformity of the temperature distribution in the reactor were studied. The important observations of this research project were the consistency of the temperature inside the reactor and also finding the optimal filling ratio of the heat pipe as well. The results of this simulation are applicable in design and control of reactor temperature and also optimization of the heat pipe.

Discovery of hidden and valuable knowledge from large data warehouses is an important research area and has attracted the attention of many researchers in recent years. Most of Association Rule Mining (ARM) algorithms start by searching for frequent itemsets by scanning the whole database repeatedly and enumerating the occurrences of each candidate itemset. In data mining problems, the size of data is often too large to fit in main memory. However, in some cases such as records of sales of a large supermarket, the probability of a particular item to be present in a transaction is often very low. This is due to the fact that a large number of items are usually available for purchase and also the fact that a small set of items is purchased by a customer in a shopping. In this paper, we make use of these facts to propose an efficient method for mining frequent itemsets. In our approach, the database is scanned just once, and data is encoded into a compressed form and held in a proper data structure in main memory. In each iteration, the time required to measure the frequency of itemsets, is reduced further (i.e., enumerating n-dimensional candidate itemsets is much faster than (n-1)- dimensional itemsets). We evaluate the efficiency of our technique using both synthetic and real-life datasets and compare it with other ARM methods proposed in past research.

This paper presents a model for ranking efficient units by a new approach. In the proposed method, the idea of excluding the unit being scored from the production possibility set is changed to the idea of weakening the unit being scored. We propose a model for ranking efficient DMUs that is more efficient and less problematic than the models based on excluding the under evaluation unit.

In Shamir threshold scheme one that is called dealer, chooses the key and then shares some partial information about it, called among the participants, secretly. In this paper, we use some numerical methods with piecewise constant basis functions in Shamir threshold scheme. We first introduce operational matrix of this functions and then show how dealer multiplies this matrix by vector of shares to obtain a new vector and distributes it.

In stochastic volatility models, European option prices are solutions to parabolic differential equations. In this paper we propose a finite difference scheme for solving these equations numerically. We prove the stability and convergence of this method in norm infinity. Then we use the ADL method to separate the operators, this allows us to apply Thomas algorithm to solve the corresponding linear systems in each step.