International Journal of Engineering
Volume:28 Issue: 1, Jan 2015

Waste ground tires were treated by two strains of Thiobacillus ferrooxidans (PTCC 1646 and DSMZ 583) and by a consortium obtained from a hot water spring with high sulfur content (S Sarein) in order to devulcanize the ground tire. The processes were made in 3 l flasks at 30 °C for the pure cultures and 50 °C for S-Sarein for 20 days. The increase of sulfate in the media and decrease of sulfur in all ground tire samples indicated the desulfurization process. The samples were then blended with other tire ingredients in order to investigate their physical and thermo-mechanical properties. The results showed that most properties of the samples were enhanced compared to the blanks. The tensile strength, modulus, tear resistance and the rheological behavior were improved in the compound containing waste tire treated by PTCC 1646. Whereas, the elongation at break was best improved in the compound sample containing waste tire devulcanized by DSMZ 583.

The aim of this research was to remove COD and color from a hazardous municipal landfill leachate using electro-Fenton process. The effects of four important parameters including H2O /Fe2+ molar ratio, current density, pH and reaction time on the process were carefully considered. The response surface methodology (RSM) was applied to minimize the number of runs and investigate the optimum operating conditions. Thirty runs were carried out and the optimum conditions for COD and color removal were statistically obtained as 95.80 and 96.36% at H2O2/Fe2+ molar ratio 0.23, current density 79.20 mA, pH 4.61 and reaction time 14.72 min.

In recent years, identification of proton exchange membrane fuel cell (PEMFC) parameters has drawn attention of many researchers. Polarization curve has a key role in proton exchange membrane fuel cell. However, the main problem associated with accurate modeling is lack of information on precise parameters of the model. In this regard, the most common method for actual parametric identification of PEMFC is use of optimization techniques. In this paper, we have employed a Tribe-PSO algorithm, multi-layered and multi-phased hybrid particle swarm optimization model to identify parameters of PEMFC model. In addition, the results of Tribe-PSO are compared to Particle Swarm Optimization (PSO) algorithm, Genetic Algorithm, and Artificial Immune System (AIS). The results of computer simulations show that the Tribe-PSO algorithm has an appropriate convergence feature and acceptable computation capability, and it is an efficient method in deriving parameters of the PEMFC stack model.

One of the most suitable biometric methods for identifying individuals is finger veins. In this paper we have proposed a new algorithm for finger vein recognition with a high accuracy level. First we extracted veins from finger vein images using entropy based thresholding. The method extracted veins well, but the images were very noisy. It means that the extracted veins may appeare as broken lines. So we applied Radon transformation to segmented images. The Radon transform is not sensitive to noise due to its integral nature. So in comparison with other methods, it is more resistant to noise. This transformation does not require the extraction of vein lines accurately. Also with using this method, the recognition accuracy and speed increased. For extracting dominant features from finger vein images, the common spatial pattern (CSP) algorithm was applied to the blocks of Radon transformation. To improve the classification accuracy, redundant features were eliminated using genetic algorithm. Finally we used 1-NN classifier to identify people using their finger veins. The study was performed on the Peking University finger vein data set. Experimental results showed that the proposed method had good performance in recognizing individuals and obtained the recognition rate of 100%.

The k-means algorithm is known to have a quadratic time complexity in terms of n, the input data size. This quadratic complexity debars the algorithm from being effectively used in large applications. In this article, an attempt is made to develop a faster version (in terms of both number of iterations and execution time) of the classical k-means algorithm which requires comparatively lesser number of iterations. The underlying modification includes a gradual directional movement of intermediate clusters and thereby improving compactness and separability properties of cluster structures simultaneously. This process also results in an improved visualization of clustered data. Experimental results using various types of data sets prove our claim. Comparison of results obtained with the classical k-means and the present algorithm indicates usefulness of the new approach.

Voice over Internet Protocol (VoIP) is an emerging trend of applications on the Internet today. As with any recent technology, VoIP also introduces both fortuity and problems. Existing VoIP honeypot experimental set ups based on SIP (Session Initiation Protocol) deals with the basic attacks like DoS (Denial of Service), enumeration detection, signature collection and SPIT (Spam over Internet Telephony). We propose a method using honeypot where Naive Bayes’ classifier is used to categorize attack packets into VoIP MAC spoofing, SIP port scanning and VoIP service abuse attack, which are not concentrated much in the extant prevention methods. VoIP honeypot results are treated more valuable than the existing Intrusion Detection System (IDS) as the datasets used in IDS are predefined and can identify only the existing pattern of attacks. But honeypot can identify attacks which originate from new patterns than the existing IDS. For result analysis, we propose a test-bed using Zoiper (SIP clients), Asterisk server, Artemisa honeypot and Wireshark as network packet analyzer. The test-bed demonstrates how honeypot identifies and prevents unsolicited users, thus improving the robustness of the VoIP system in terms of security.

This paper presents a hybrid approach involving Continuous Action Reinforcement Learning Automata (CARLA) and particle swarm optimization (PSO) to design a optimal and intelligent proportionalintegral- derivative (PID) controller of an automatic voltage regulator (AVR) system. The proposed method is CARLA which is able to explore and learn to improve control performance without the knowledge of the analytical system model. The role of an AVR is to hold the terminal voltage magnitude of a synchronous generator at a specified level. Hence, the stability of the AVR system would seriously affect the security of the power system. CARLA-PSO is a method that combines the features of PSO and CARLA in order to improve the optimize operation. The proposed method was indeed more efficient and robust in improving the step response of an AVR system. Numerical simulations are also provided to verify the effectiveness and feasibility of PID controller of AVR based on CARLA-PSO algorithm.

In this paper, an innovative analytical approach to find oscillation frequency in inverter based ring oscillators has been proposed. It is shown that the input and output voltages of each stage fall on an elliptical state path. In each part of the path, the transistors operation region of the stage is determined and the stage equation is written. The time of each working region is calculated using parametrical waveforms for the input and output voltages. It is concluded that the oscillation period is the sum of all those time intervals.

In this paper, a low voltage ultra wide band (UWB) low noise amplifier (LNA) is designed in a standard 0.18μm CMOS technology. In order to possibly minimize the amount of supply voltage, the forward body bias technique is combined with the folded cascode structure and for extending and flatting the band width, the feedback topology is used. With an optimized configuration combining advantages of feedback topology and forward body bias, folded cascode topology, the adjustable wide input matching is got and noise figure (NF) is controlled to a relevant low status. This novel structure achieves peak gain of 12dB and noise figure varying from 4.6-2dB within the band of 3-15GHz. The LNA uses supply of 0.8V while consuming only 12.5mW of dc power. To the best of our knowledge, this structure for low voltage UWB LNA has not been reported previously.

Automatic License Plate Recognition, ALPR, is an important part of today’s traffic monitoring and toll-gate systems. It usually consists of two major parts: plate localization and character recognition. In this paper, we propose a real-time algorithm for detection and recognition of Persian license plates in four styles. To be real time, we employ simple and effective techniques and implement our algorithm in pure C++. Unlike conventional methods for finding the location of the plate based on structural features, we use a sliding and classifying approach combined with some statistical information. In recognition phase, two fast and accurate features are trained by a neural network. The proposed system is evaluated on 100 images of Iranian vehicles, taken from different highway/toll-gate cameras. In localization phase, system detects 100% of the plates properly and in recognition phase, 97.8% of characters are correctly recognized. The overall processing time for single plate is 0.06 s at resolution of 407x309 and 0.24 s at resolution of 1150×650. These specifications made our algorithm industryready and currently. It is used by several corporations working on parking management and law enforcement systems.

This experimental study focoused on the analysis and optimization of some effective surface parameter like reflectance, series resistance, fill factor and surface recombination velocity to enhance the performance of Si solar cell. Near sub wave length structure is introduced to overcome the contact problem of nano texturization where reflection loss is less than micro texturization. Screen printing technique is the low cost industrial established process but it also raises some unwanted problem which reduces the fill factor. Light Induced Plating (LIP) of c-Si solar cell is a critical process generally leading to increase in fill factor and efficiency associated with marginal reduction in short circuit current (Jsc). In this paper, the increase in Jsc is reported at the LIP treated solar cell due to unintentional deposition of silver nanoparticle on the surface of solar cell. The array of silver nanoparticle on the Si surface results into plasmonic effect as evidence by the reduction of reflectance and increase in external quantum efficiency without depositing added nano particles. Also, new type of texturization, contact optimization and better LIP treatment are reported.

Quality of products has been one of the most important issues for manufacturers in the recent decades. One of the challenging issues is evaluating capability of the process using process capability indices. On the other hand, usually the missing data is available in many manufacturing industries. So far, the performance of estimation methods of missing data on process capability indices has not been evaluated. Hence, we analyze the performance of a process capability index when we deal with the missing data. For this purpose, we consider a multivariate process capability index and evaluate four methods including Mean Substitution, EM algorithm, Regression Imputation and Stochastic Regression Imputation to estimate missing data. In the analysis, factors including percent of missing data (k), sample size (m), correlation coefficients (r) and the estimation methods of missing data are investigated. We evaluate the main and interaction effects of the factors on response variable which is defined as difference between the estimated index and the computed index with full data by using General Linear Model in ANOVA table. The results of this research show that the Stochastic Regression Imputation has the best performance among the estimation methods and the percent of missing data (k) has the highest effect on response variable. Also, we conclude that the sample size has the lowest effect on response variable among the mentioned factors.

Considering to the reliability in modeling of facility location problems is one of the most effective ways to hedge against failures of system from time to time. In reality, the combined facility location network design problem with respect to the reliability of system has several applications in industries and services such as locating health care service centers, locating gas compressor stations, and designing water tubing networks. In this paper, a mixed integer non-linear programming formulation is developed to model the combined facility location network design problem with unreliable facilities. The new mathematical formulation considers different costs including facility location, link construction/improvement, and transportation costs. It particularly takes the maximum allowable failure cost of the system into account. Then, the proposed model is linearized by suitable techniques and solved to efficiently obtain the solutions. Besides, a practical case study is presented in detail to illustrate the application of the proposed mathematical model. Finally, a sensitivity analysis is done to provide an insight into the behavior of the proposed model in response to changes of key parameters of the problem. The results demonstrate the capability of the model.

The devolatilization of a non-coking coal and the reduction of iron oxide fines by volatile matter (VM) were studied non-isothermally using thermogravimetery (TG) in argon atmosphere. The devolatilization of the coal showed five different regions in terms of the rate of devolatilization. The maximum rate of devolatilization and the maximum weight loss occur between 640oC and 725oC furnace temperature. The effect of the heating rate and the coal particle size on devolatilization were studied. Increasing the heating rate and the particle size resulted in lower devolatilization. Nonisothermally reduction of iron oxide by VM in a multi-layered array was investigated. A reduction degree of 40 percent was reached while heating the pack from room temperature to 95 oC.Three distinct regions of reduction were observed for reduction of Fe2O3. The XRD patterns confirmed the stepwise reduction of iron oxide.

Pure copper materials are not used as journal bearing material due to their low mechanical and hardness properties. With technological improvements, self-lubricated sintered bearings and plastic materials are used where continuous lubricating is impossible. Cu– composites were prepared by powder metallurgy method from copper, tin and solid lubricant (MoS2) powders in the range of 0–7 wt% of MoS2. The wear tests with an experimental plan of six loads (5-30 N) and five sliding speeds (0.5-2.5 m/s) were conducted on Pin-On-Disc machine to record a loss in mass due to wear for a six total sliding distance of 500 to 3000m. It was confirmed that with increasing concentration of MoS2, the coefficient of friction of composites decreases.

During the last two decades, inertance tube pulse tube cryocoolers (ITPTC) applications in astronautics instruments gained momentum due to their high reliability. Moreover, significant efforts were made in order to improve ITPTCs operation. Investigations showed that most losses occur in the regenerator part. Due to complexity of physics of these losses, effects of the regenerator efficiency on the cryocooler performance were investigated in this work. Tocalculate heat transfer between solid matrix and acting fluid in the regenerator, Dual Energy Equation (DEE) model was used. Calculation of entropy flow inside the regenerator showed that almost 85% of the energy losses are due to viscous and inertial losses besides most of the energy losses occuring in its hot end. Therefore, in order to optimize the system, multi-mesh regenerator was studied. Results showed that under fixed CHX wall temperature of 150 (K), COP of the PTC with optimum multi-mesh regenerator is 1.07 times higher than the value of uniform mesh regenerator ITPTC. A precise agreement was observed between simulation results and available experimental data published in the literature.

In this paper, performance and emissions of a four-stroke SI engine operating on ethanol gasoline blends of E0, E5 and E10 in a rational range of exhaust gas recirculation (EGR) with the aid of a 3D CFD code has been studied. CFD codes do not share high expenses and operational difficulties of experimental studies, but they do present acceptable results. The results of simulation were compared with the experimental data. There is a good agreement betweethe results. In this study, a novel method for decreasing the engine emissions has been investigated for the fuels under study. Calculations were carried out for EGR ratios between 0 and 20%. The results revealed that using ethanol gasoline blended fuels marginally increases the power output of the engine. The concentration of CO and HC emissions were measured and found to decrease when ethanol blends were introduced. This was due to the high oxygen percentage in ethanol. In contrast, the concentration of CO2 and NOx was found to increase when ethanol is introduced. Increasing EGR level while proved to have a significant decreasing effect on engine power, but also hada slight emission reducing effect on almost all of the CO and HC levels up to 10% of EGR and a notable plummet in NOx emission levels.

Nonlinear free and forced vibration of a transversely isotropic rectangular magneto-electro elastic thin plate with simply supported boundary conditions is studied based on the thin plate theory along with the von Karman’s nonlinear strains. The partial differential equation of motion is transformed to an ordinary differential equation using Galerkin method. A perturbation method is used to solve the equation analytically and a closed-form solution is obtained for the frequency response and nonlinear frequency of the magneto-electro-elastic plate. The results are compared with the available results. Numerical examples are carried out to show the effects of several parameters on the nonlinear behavior of these plates.

With ever increasing importance of distributed generation, especially microturbines, it is absolutely vital to carry out feasibility study and research on manufacturing such systems in Islamic Republic of Iran to shed light on manufacturing capabilities, limitations and constraints. The design process of a semi-industrial prototype microturbine was conducted by Niroo Research Institute (N.R.I.). The design process and the results have been presented in several papers. Having completed the initial evaluation, the research team was able to determine and prepare production processes and workshop plans. With the technical cooperation of the companies specialized in different areas of manufacturing, the main components of the prototype were manufactured. Investment casting and CNC machining are among the most important processes involved in the manufacturing of the prototype microturbine. In this paper, we present manufacturing method of the main components and identify current and potential manufacturing capabilities in the country along with the existing limitations and constraints.

Nowadays, electrical discharge machining (EDM) has become one of the most extensively used nontraditional material removal processes. Its unique feature of using thermal energy to machine hard tomachine electrically conductive materials is its distinctive advantage in the manufacturing of moulds, dies and aerospace components. However, EDM is a costly process and hence proper selection of its process parameters is essential to reduce production cost and improve product quality. In this study the effect of input EDM process parameters on AISI2312 hot worked steel, widely used in mold manufacturing, is modeled and optimized. The proposed approach is based on statistical analysis on the experimental data. The input parameters are peak current (I), pulse on time (Ton), pulse off time (Toff), duty factor (η) and voltage (V). Material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR) are the most important performance characteristics of the EDM process. The experimental data are gathered using Taguchi L36 design matrix. Taguchi robust design technique was applied to obtain the signal to noise ratio (S/N ratio) for the quality characteristics being investigated. In order to establish the relations between the input and the output parameters, various regression functions have been fitted on the evaluated S/Ns data based on output characteristics. The significance of the process parameters on the quality characteristics of the EDM process was also evaluated quantitatively using the analysis of variance (ANOVA) method. Then, statistical analyses and validation experiments have been carried out to select the best and most fitted models. In the last section of this research, simulated annealing (SA) algorithm has been employed for optimization of the performance characteristics. Using the proposed optimization procedure, proper levels of input parameters for any desirable group of process outputs can be identified. A set of verification tests is also performed to verify the accuracy of optimization procedure in determining the optimal levels of machining parameters. The results indicate that the proposed modeling technique and simulated annealing algorithm are quite efficient in modeling and optimization of EDM process parameters.