فهرست مطالب

  • Volume:31 Issue: 10, 2018
  • TRANSACTIONS A: BASICS
  • تاریخ انتشار: 1397/07/27
  • تعداد عناوین: 24
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  • A. R. Moghadassi *, E. Bagheripour, F. Parvizian, S. M. Hosseini Pages 1609-1616
    In the current research, ABS-co-PEG nanofiltration membrane was prepared by solution casting technique using N, N dimethyl acetamide as solvent. The effect of PEG concentration as additive in the casting solution on membrane flux, salt rejection, phase inversion time, water content, membrane porosity, membrane tensile strength and fouling was studied. Also the effect of operating conditions such as feed concentration, pressure and temperature on membrane performance were also studied. It was found that increase of PEG content up to 6 %wt in the casting solution initially led to increase in flux and decrease of salt rejection in prepared membranes. The flux was decreased and salt rejection increased by more increase in PEG content from 6 to 10 %wt. In addition, presence of PEG in membrane structure caused to formation of more stable flux during filtration time against fouling. Increase of feed salt concentration caused to flux decreasing. The ABS/PEG membrane showed more stable flux against increase of feed concentration. Moreover, flux was increased by increase of operating pressure and feed temperature. The results also showed a clear trend towards higher values of tensile strength by increase of PEG content ratio.
    Keywords: Nanofiltration, ABS-co-PEG Membrane Fabrication-Characterization, PEG Concentration, Physico-chemical Characterization, Operating Conditions
  • M. S. Lashkenari *, A. KhazaiePoul, S. Ghasemi , M. Ghorbani Pages 1617-1623
    This study investigates the potential of an intelligence model namely, Adaptive Neuro-Fuzzy Inference System (ANFIS) in prediction of the Zn metal ions adsorption in comparision with two well known empirical models included Thomas and Yoon methods. For this purpose, an organic-inorganic core/shell structure, γ-Fe2O3/polyrhodanine nanocomposite with γ-Fe2O3 nanoparticle as core with average diameter of 15 nm and polyrhodanine as shell with thickness of 3 nm, was synthesized via chemical oxidation polymerization. The properties of adsorbent were characterized with transmission electron microscope (TEM) and Fourier transform infrared (FT-IR) spectroscopy. Sixty seven experimental data sets including the treatment time (t), the initial concentration of Zn (Co), column height (h) and flow rate (Q) were used as input data to predict the ratios of effluent-to-influent concentrations of Zn (Ct/C0). The results showed that ANFIS model with the R coefficient of 0.99 can predict Ct/C0 more accurately than empirical models. Also it was found that the result of the Thomas and Yoon methods with R coefficient of 0.828 and 0.829, respectively were so close to each other. Finally, performance of our ANFIS model was compare to Thomas and Yoon methods in two different conditions, i.e. variable initial influent concentration and variable column height. High performance of ANFIS model was proved by the comparitive results.
    Keywords: Adaptive Neuro-fuzzy Inference System, Adsorption, ?-Fe2O3, Polyrhodanine, Fixed Bed Column
  • R. Mortazavi *, S. H. Erfani Pages 1624-1632
    In recent years, privacy concerns about social network graph data publishing has increased due to the widespread use of such data for research purposes. This paper addresses the problem of identity disclosure risk of a node assuming that the adversary identifies one of its immediate neighbors in the published data. The related anonymity level of a graph is formulated and a mathematical model is proposed to solve the problem. The application of the method on a number of synthetic and real-world datasets confirms that the method is general and can be used in different contexts to produce superior results in terms of the utility of the anonymized graph.
    Keywords: mathematical modeling, graph anonymization, graph modification, social network, privacy, database security
  • P. Karuppanan* , K. Anuradha Pages 1633-1641
    This article proposed a simple self cascode RGC amplifier configuration to increase the gain and bandwidth. The cascode amplifier eliminates the miller capacitance between input and output and facilitates high gain, high input and output impedance with high bandwidth. However, the cascode amplifier requires relatively high supply voltage for proper operation and it decreases the output voltage swing by overdrive voltage. These issues are overcome by self cascode based RGC amplifier; even though it has low bandwidth due to the presence of one of its pole at low frequency. The bandwidth and output impedance of the conventional RGC has increased using a split length compensation technique. To improve the overall performance of the amplifier, introduced a simple self cascode RGC without using additional passive elements. The expression of gain and output impedance for the proposed amplifier is derived using small signal analysis. The calculated value of voltage gain for the projected circuit is 58.37 dB which is more than the self cascode based RGC. The power dissipation of the proposed circuit is 1.07 µWatt and it was compared with CS, cascode, self cascode and SC based cascode, RGC, SC based RGC amplifiers.
    Keywords: Self cascode, Regulated cascode, self cascode based regulated cascode, simple self cascode Regulated Cascode
  • F. Parandeh Motlagh* , A. Khatibi Bardsiri Pages 1642-1650
    The internet and its various services have made users to easily communicate with each other. Internet benefits including online business and e-commerce. E-commerce has boosted online sales and online auction types. Despite their many uses and benefits, the internet and their services have various challenges, such as information theft, which challenges the use of these services. Information theft or phishing attacks are internet attacks that are major approach to success it is social engineering that the phisher has used. In these types of attacks, the attacker deceives the users and steals their valuable information by using a fake website that looks like real websites. The damage caused by fake websites and phishing attacks is so high that researchers are trying to identify these types of websites in different ways. So far, various methods have been developed to identify phishing web sites which most of them based on data- mining and learning machine are trying to identify these malicious websites. Artificial neural network is a data-mining method for identifying phishing websites which is used in most studies; however the error rate of this can be significant in detecting these websites, so learning-based optimization algorithm is used as a Swarm intelligence algorithm to reduce its error. In the proposed method, the error rate of multi-layer artificial neural network in detecting phishing websites is considered as a target function which minimized by using learning-based optimization algorithm. In the proposed method, learning- based optimization algorithm selects weights and bias of multi-layer artificial neural network optimally to minimize the error of clssification as an objective function. The datasets used to evaluate the proposed method are Phishing Websites explaind by others. The results of evaluating phishing attack dataset indicate that the rate of error of fake website detection in the proposed method is constantly reduced by repetition. The results of our assessment also indicate that the average accuracy, sensitivity, specificity, precision of the proposed method are 93.42, 92.27, 93.19 and 92.78%, respectively. The decision tree and regression are more accurate in detecting fake websites than artificial neural network.
    Keywords: Fake Websites, Phishing Attacks, Artificial Neural Network, Swarm Intelligence Algorithm, Learning based Optimization Algorithm
  • S. M. Hosseinirad * Pages 1651-1658
    Wireless sensor network a powerful network contains many wireless sensors with limited power resource, data processing, and transmission abilities. Wireless sensor capabilities including computational capacity, radio power, and memory capabilities are much limited. Moreover, to design a hierarchy topology, in addition to energy optimization, find an optimum clusters number and best location of cluster heads are two important issues. Many routing protocols are introduced to discover the optimal routes in order to remove intermediate nodes to reduce the sensors energy consumption. Therefore, for energy consumption optimization in a network, routing protocols and clustering techniques along with composition and aggregation of data are provided. In this paper, to design a hierarchy topology, a hybrid evolutionary approach, a combination of genetic and imperialist competition algorithms is applied. First, the genetic algorithm is applied to achieve an optimal clusters number where all effective network parameters are taken in into account. Aftermath, the optimal positions of cluster heads inside every cluster are calculated utilizing the imperialist approach. Our results show a significant increment in the network lifetime, lower data-packet lost, higher robust routing compared with standard LEACH and the ICA based LEACH.
    Keywords: Wireless Sensor Networks, LEACH Algorithm, Genetic Algorithm, Imperialist Competitive Algorithm, Network Lifetime
  • M. Ahmadi , S. M. Jameii * Pages 1659-1665
    Recently, underwater Wireless Sensor Networks (UWSNs) attracted the interest of many researchers and the past three decades have held the rapid progress of underwater acoustic communication. One of the major problems in UWSNs is how to transfer data from the mobile node to the base stations and choosing the optimized route for data transmission. Secure routing in UWSNs is necessary for packet delivery. A few researches have been done on secure routing in UWSNs. In this article, a new secure routing algorithm called Secure Routing Algorithm for Underwater (SRAU) sensor networks is proposed to resist against wormhole and sybil attacks. The results indicate acceptable performance in terms of increasing the packet delivery ratio regarding the wormhole and sybil attacks, increasing network lifetime through balancing the network energy consumption, high detection rates against the attacks, and decreasing the end to end delay.
    Keywords: Underwater wireless sensor networks, security, routing, wormhole, sybil attacks
  • M. M. AlyanNezhadi *, H. Hassanpour , F. Zare Pages 1666-1674
    Grid impedance estimation is used in many power system applications such as grid connected renewable energy systems and power quality analysis of smart grids. The grid impedance estimation techniques based on signal injection uses Ohm’s law for the estimation. In these methods, one or several signal(s) is (are) injected to Point of Common Coupling (PCC). Then the current through and voltage of PCC are measured. Finally, the impedance is assumed as ratio of voltage to current signals in frequency domain. In a noisy system, energy of the injected signal must be sufficient for an accurate approximation. However, power quality issues and regulations limit the energy and the voltage levels of the injected signal. There are three main issues in impedance estimation using signal injection: I) Power quality of grid, II) frequency range of estimation, and finally III) accuracy of estimation. In this paper, the stationary wavelet denoising algorithm is employed instead of increasing the energy of injection signal(s). In the paper, a novel method is proposed for impedance estimation based on selecting several appropriate injection signals and denoising the measured signals. The proposed method is able to impedance estimation in a wide frequency range without any effect on power quality. Finally, simulation results have been carried out to validate the proposed method.
    Keywords: Impedance Estimation, Frequency response, Discrete Fourier Transform, Power Quality, smart grids
  • H. S. Kim * Pages 1675-1681
    Thermal imaging technology is used to translate thermal energy or heat into visible light for analyzing the sample images known as a thermogram. It has numerous applications such as for surveillance, medical diagnosis, and other industry which requires a non-contact temperature measurement, etc. The image results of this proposed algorithm show more visible features in terms of the separation between the sampled object and its background. The extraction process used the integrated Otsu method and the high-value thermal algorithm. The color mapping process helps to highlight the necessary characteristics of the sampled thermal images. This work is synthesized using Xilinx Zync 7000 ZED ZC702. The experimental results extracted more significant features and characteristics of the sampled image. In addition, the proposed algorithm shows a faster processing time and minimizes the resource utilization compared with the other methods.
    Keywords: digital images, infrared Thermography, imaging analysis, image segmentation, thermal factors
  • J. Ghasemi *, M. Mehdipoor, J. Rasekhi , K. Gorgani Firouzjah Pages 1682-1688
    Thermistors are very commonly used for narrow temperature-range high-resolution applications, such as in medicine, calorimetry, and near ambient temperature measurements. In particular, Negative Temperature Coefficient (NTC) thermistor is very inexpensive and highly sensitive, whose sensing temperature range and sensitivity are highly limited due to the intrinsic nonlinearity and self-heating properties of NTC thermistor at high operation currents. In this research, a new structure is proposed based on adaptive neuro-fuzzy system for the modeling of sensor nonlinearity. Apart from taking self-heating phenomenon of NTC thermistor sensor, the proposed structure also measures temperature directly, without any linearizing circuitry. Neuro-fuzzy network is trained and tested through data produced in the Laboratory environment. Examination of the proposed method on test data achieved a mean squared error of 0.0195, which is considered as a significant accomplishment.
    Keywords: Temperature, Negative Temperature Coefficient Thermistor, Self-heating, Modeling, Adaptive Neuro-fuzzy Inference System
  • T. Douadi *, Y. Harbouche, R. Abdessemed , I. Bakhti Pages 1689-1697
    This paper deals with the Active and Reactive Power control of double-fed induction generator (DFIG) for variable speed wind turbine. For controlling separately the active and the reactive power generated by a DFIG, field oriented control (FOC) and indirect sliding mode control (ISMC) are presented. These non linear controls are compared on the basis of topology, cost, efficiency. The main contribution of this work based to the short time of response with excellent convergence and high decoupled between active and reactive power in one part and in the second part we define the benefit to use indirect model of DFIG to the conception of indirect sliding mode control by using the relationships between stator powers and rotor currents. The simulation results have shown good performances concerning the tracking of the references both in transient and steady state and prove the effectiveness of sliding mode control to track the given references using PWM inverter.
    Keywords: Doubly Fed Induction Generator, Field Oriented Control, Indirect Sliding Mode, Wind Energy, pulse with modulation PWM
  • B. Sabzalian, V. Abolghasemi * Pages 1698-1707

    Non-negative Matrix Factorization (NMF) is a part-based image representation method. It comes from the intuitive idea that entire face image can be constructed by combining several parts. In this paper, we propose a framework for face recognition by finding localized, part-based representations, denoted “Iterative weighted non-smooth non-negative matrix factorization” (IWNS-NMF). A new cost function is proposed in order to incorporate sparsity which is controlled by a specific parameter and weights of feature coefficients. This method extracts highly localized patterns, which generally improves the capability of face recognition. After extracting patterns by IWNS-NMF, we use principle component analysis to reduce dimension for classification by linear SVM. The Recognition rates on ORL, YALE and JAFFE datasets were 97.5, 93.33 and 87.8%, respectively. Comparisons to the related methods in the literature indicate that the proposed IWNS-NMF method achieves higher face recognition performance than NMF, NS-NMF, Local NMF and SNMF.

    Keywords: Non-negative matrix factorization, face recognition, pattern analysis, features extraction, sparse representation
  • Y. Zhanxin *, Z. Fang, X. Lixiong, L. Hongjun, X. Dapeng, L. Junnan, D. Yu , L. Yalei Pages 1708-1714
    For economic benefit of wind power generation, the equivalent conversion relationships and models between the different “quality” energy are studied deeply in the conversion processes of wind energy. Considering the effect of load demand characteristics and energy supply price on the wind energy utilization mode comprehensively, the multi-objective trans-utilization optimization model of wind energy is established, which the objections are both the maximum wind energy utilization ratio and comprehensive operational benefit of the energy consumption systems. Then, the quantum-behaved particle swarm optimization method is used to solve the model. By contrast to the traditional unitary energy supply mode, the results showed that the proposed models can improve the wind energy comprehensive utilization rate, and increase energy selling benefit of the energy supply system. The rationality and superiority of models are verified, and that provides a new idea for the large-scale develop and utilize wind energy.
    Keywords: Energy Internet, Equivalent Conversion, Energy Selling Benefit, Wind Power Utilization
  • M. Hajiaghaei, Keshteli *, K. S. Abdallah , A. M. Fathollahi, Fard Pages 1715-1722
    Recent papers in the concept of Supply Chain Network Design (SCND) have seen a rapid development in applying the stochastic models to get closer to real-world applications. Regaring the special characteristics of each product, the stracture of SCND varies. In tire industry, the recycling and remanufacturing of scraped tires lead to design a closed-loop supply chain. This paper proposes a two-stage stochastic model for a closed-loop SCND in the application of tire industry. The first stage of model optimizes the expected total cost. Then, financial risk has been considered as the second stage of model to control the uncertainty variables leading to a robust solution. To solve the developed problem, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) have been used. To enhace the efficiency of metaheuristic algorithms, Response Surface Method (RSM) has been applied. Finally, the proposed model is evaluated by different test problem with different complexity and a set of metrics in terms of Pareto optimal solutions.
    Keywords: Stochastic Programming, Closed-loop Supply Chain, Tire Industry, Genetic Algorithm, Particle Swarm Optimization
  • Y. Zare Mehrjerdi *, M. Alipour , A. Mostafaeipour Pages 1723-1733
    In this paper, a mixed-integer linear programming model is proposed to integrate batch picking and distribution scheduling problems in order to optimize them simultaneously in an order picking warehouse. A tow-phase heuristic algorithm is presented to solve it in reasonable time. The first phase uses a genetic algorithm to evaluate and select permutations of the given set of customers. The second phase uses the route first-cluster method to obtain an effective schedule for a given permutation of customers. Computational experiments represent that integrated approach can lead to significant reduction in the makespan. Moreover, Empirical observations on the performance of the heuristic algorithm are reported.
    Keywords: Warehouse, Order Picking System, Order Batching, Picker-to-Part Systems, Distribution Scheduling
  • A. M. Fathollahi, Fard, M. Hajiaghaei, Keshteli *, R. Tavakkoli, Moghaddam Pages 1734-1740
    Nowadays, a rapid growth in the rate of life expectancy can be seen especially in the developed countries. Accordingly, the population of elderlies has been increased. By another point of view, the number of hospitals, retirement homes along with medical staffs has not been grown with a same rate. Hence, Home Health Care (HHC) operations including a set of nurses and patients have been developed recently by both academia and health practitioners to consider elderlies’ preferences willing to receive their cares at their homes instead of hospitals or retirement homes. To alleviate the drawbacks of pervious works and make HHC more practical, this paper introduces not only a new mathematical formulation considering new suppositions in this research area but also a solution approach based on Lagrangian relaxation theory has been employed for the first time. The main strategy of used algorithm aims to fill the gap between the lower bound and upper bound of problem and finds a solution which has both optimality and feasibility properties. By generating a number of numerical examples, results show the performance of the proposed algorithm analyzed by different criteria as well as the efficiency of developed formulation through a set of sensitivity analyses
    Keywords: home health care, vehicle routing problem, Lagrangian relaxation-based algorithm
  • N. Sofyan *, R. A. Nugraha, A. Ridhova, A. H. Yuwono , A. Udhiarto Pages 1741-1748
    One of the possibilities to mass-produce dye-sensitized solar cell (DSSC) device is if it could be embedded to the area atop metal roof. However, the use of metal substrate is constrained by the corrosion caused by the electrolyte solution used in the DSSC device such as iodide/tri-iodide (I-/I3-). In this study, we propose the utilization of polyaniline/reduced graphene oxide (PANi/rGO) nanocomposite as protective coating and at the same time as catalyst for the DSSC counter electrode on AISI 1086 steel substrates. The work was started by synthesizing PANi and rGO and assembling the PANi/rGO nanocomposite in a DSSC device. The characterization was performed using X-ray diffraction (XRD) for crystal structure, infrared (FTIR) for functional groups, scanning electron microscope (SEM) for surface morphology, potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) for corrosion testing, and semiconductor parameter analyzer (SPA) for the DSSC device performance. The result showed that the decrease of corrosion rates in AISI 1086 steel was proportional to the rGO concentrations in PANi/rGO nanocomposites. The lowest corrosion rate was obtained at the highest rGO composition, i.e. PANi/rGO 8 wt% with corrosion rate (CR) of 0.2 mm/year and protection efficiency of 80.3 %. The DSSC performance test revealed that PANi/rGO composite could be used as an alternative catalyst for I-/I3- based redox electrolyte in the DSSC solar cell applications in replacement for platinum. The highest power conversion efficiency of 5.38 % was obtained from PANi/rGO 4 wt%.
    Keywords: AISI 1086 steel, Dye-sensitized Solar Cell counter electrode, Polyaniline, Protective coating, Reduced graphene oxide
  • N. Jahantigh *, A. Shahriari , F. Rakani Pages 1749-1759
    The investigation of the effect of nanoparticles’ mean diameter and temperature of Al2O3–water nanofluid on velocity and energy field using the lattice Boltzmann method is the main objective of this study. The temperature of the vertical walls is considered constant at Tc and Th, respectively, while the up and the down horizontal surfaces are smooth and insulated against heat and mass. The influences of Grashof number (103, 104, 105) Prandtl number (Pr=3.42, 5.83), the various volume fraction of nanoparticles (φ=0, 0.01, 0.03, 0.05) and particle-size (dp= 24, 47, 100 nm) were carried out on heat transfer and flow fields. It was concluded that addition of nanoparticles causes a significantly affect on temperature and flow fields. The decrement of heat transfer is observed with the increment of solid volume fraction, but it increases when Grashof number and nanoparticles’ mean diameter increase. The decrement of nanoparticles’ mean diameter and Prandtl number have the same effect on Nusselt number. In addition, it was resulted that the thermal conductivity model had insignificantly impact on the mean Nusselt number than the dynamic viscosity model.
    Keywords: Nanoparticles Mean Diameter, Natural Convection, Nanofluid, Lattice Boltzmann Model
  • S. S. Patel *, J. M. Prajapati Pages 1760-1766
    Wire electric discharge machine (WEDM) is spark erosion in unconventional machining technique to cut hard and the conductive material with a wire as an electrode. The blanking die material SKD 11 is a high carbon and high chromium tool steel with high hardness and high wearing resistance property. This tool steel has broad application in press tools and dies making industries. In this research study the behavior of six process parameters includes Ton (pulse on time), Toff (pulse off time), IP (peak current), SV (servo voltage), WF (wire feed rate) and WT (wire tension) base on design of experiment method during WEDM of SKD 11 were experimentally studied. The 0.25 mm diameter of the brass wire has used as the electrode to cut the work piece. The surface roughness and kerf width are selected as performance measurement. Response Surface methodology (RSM) is utilized for process optimization as well as for formulating regression model for correlating process parameters with performance measurements.
    Keywords: Wire Electric Discharge Machine, SKD 11, Tool Steel, Response Surface Methodology, Surface Roughness, Kerf Width
  • C. Zhou, L. Zhao *, Y. Yu , X. Li Pages 1767-1772
    To effectively improve the tire grounding behaviors of wheelchair robots, an analytical method is proposed to analyze and optimize the tire grounding safety. Firstly, taking the cushion and tires as the vibration isolation elements with stiffness and damping, the vertical vibration model of the human-wheelchair robot is established. Then, taking the random excitation as the typical input, the formulae of the TDD (tire dynamic deflection) frequency response function H and the RMS (root mean square) response are derived and the response coefficient λ is proposed. Moreover, the influence laws of system parameters on H and λ are revealed. Thirdly, based on λ, the analytical optimization model for the cushion system damping ratio ξ2 is established. Finally, a case study and numerical simulation were carried out. The results show that the relative deviation of the cushion optimal damping is about 0.3%.
    Keywords: wheelchair Robots, Tire , Safety Analysis, Analytical Method, Running Process
  • A. Salarvand, E. Poursaeidi *, A. Azizpour Pages 1773-1781
    In this study, the pitting type of corrosion growth characteristics, fatigue crack initiation and propagation behavior; axial fatigue tests were carried out on precipitation hardened martensitic Custom 450 steel in the air and 3.5wt% NaCl solution. Using the ratio of the depth to the half-width of the pits; (a/c)= 1.5±0.2 the corrosion pit depth growth law was obtained as a function of stress amplitude and elapsed time, t. Fatigue crack growth rates were determined in the near threshold stress intensity factors regime (∆kth). A model was presented for estimation of corrosion fatigue life based on the time to reach critical pit depth (as crack initiation) and crack propagation life. Then. S-N curves were obtained both in air and NaCl solution from axial fatigue testing. Comparison of data from the proposed model and the experimental results (S-N curves) showed good agreement.
    Keywords: Corrosion Fatigue, Corrosion Pit, Crack Propagation, High Cycle Fatigue, Custom 450 Steel
  • A. Arefin , R. Islam * Pages 1782-1788
    Nowadays the demand for reducing pollutant emissions and fuel consumption have paved the way of developing more fuel-efficient power generation system for transportation sector. Micro gas turbine (MGT) system can be an alternative to internal combustion reciprocating engine due to its light-weight and less fuel consumption. In this paper, some major running and operating characteristics of MGT are evaluated for the validation of the system for range extender electric truck. First noise characteristic of the system are investigated, then performance at high ambient temperature and variation of electrical output with and without the use of air filtration are investigated. The noise characteristics of MGT are different from diesel engine. At lower rpm and lower operating temperature, the electrical output of the system increases rapidly. All the found results are either compared with other systems or validated by comparing with the data provided by the manufacturer where necessary. The emission characteristics of MGT are different from other reciprocating engines. With the increase of power output the emissions of MGT reduces significantly. Finally, some noise reduction methods are recommended.
    Keywords: Micro Gas Turbine, Range Extender Electric Vehicle, Truck, Noise Characteristics, Air Filtration
  • G. Khankari *, S. Karmakar Pages 1789-1795
    This paper proposes an approach for improving the plant efficiency by reducing the heat rejection temperature of power cycle using Kalina Cycle System 11 (KCS11) which is integrated at the steam condenser of a 500 MWe SubC (subcritical) coal-fired power plant. It is modelled by using power plant simulation software ‘Cycle Tempo’ at different plant operating conditions. Results show that the additional net electric power of 5.14 MWe from KCS11 improves the net energy and exergy efficiencies of the power plant by about 0.302 % point and 0.27 % point, respectively at full load over the stand-alone coal-fired steam power plant. Thereby, the carbon dioxide (CO2) emission is reduced by about 2.02 t/h at full load. Combined plant efficiencies decrease with decrease in evaporator outlet temperature due to decrease in vapour quality of binary mixture at turbine inlet and higher steam turbine back pressure. Levelized Cost of Electricity (LCoE) generation and payback period of the combined cycle power plant are about Rs 1.734 and 4.237 years, respectively and the cost of fuel saving is about Rs 0.685 per kg of coal which is lower than the fuel cost.
    Keywords: Condenser waste heat, Energy, Exergy, Environment, Kalina Cycle
  • A. Khormali *, A. R. Sharifov , D. I. Torba Pages 1796-1802
    In this work, scaling tendency and amount of precipitation of barium sulfate (BaSO4) were determined; the process is depending on temperature, pressure and mixing ratio of injection and formation of waters. Results showed that BaSO4 precipitation is largely dependent on mixing ratio. Temperature and pressure had no influence on BaSO4 precipitation. Different scale inhibitors, including a new inhibitor package, were used for preventing BaSO4 precipitation. The new scale inhibitor consists of three different acids such as phosphonate acid, hydrochloric acid solution, isopropyl alcohol, ammonium chloride and water. In addition, the lowest interfacial tensionon the boundary of oil and new inhibitor occurred at 10% of hydrochloric acid. Furthermore, effect of temperature, mixing ratio of waters and barium concentration on the inhibition efficiency of BaSO4 formation was studied. Results showed that the new inhibitor has the highest efficiency for preventing BaSO4 precipitation at any temperature, mixing ratio and barium concentration. Moreover, formation damage due to BaSO4 formation with and without scale inhibitors was determined by core flood tests. In the presence of new inhibitor, the damaged rock permeability ratio was improved from 0.59 to 0.924.
    Keywords: Barium Sulfate, Formation Damage, Scale Inhibition, Scale Prediction