International Journal of Engineering
Volume:29 Issue: 9, Sep 2016

In this study, a novel sodalite nanozeolite was synthesized and characterized by XRF¡ XRD¡ SEM and FTIR analysis. Cu2O nanoparticles (30-60 nm) were coated on a bed of sodalite zeolite. Results of SEM-EDX showed that the amount of copper on the bed of zeolite was 4.5 wt%. modified zeolite by Cu2O nanoparticles was used to sorption of dimethyl phthalate from aqueous solutions in batch process. Results showed that Cu2O nanoparticles have a significant effect on the dimethyl phthalate removal processing from aqueous solution and maximum adsorption rates were 92.98% (with 10, 0.4g, 55min of pH, adsorbent dose and contact time respectively for modified zeolite). The kinetic studies showed that the dimethyl phthalate sorption process was well described by the pseudo second order kinetic model. Also, Langmuir isotherm provided the best fit to the equilibrium data with maximum adsorption capacity of 20.41 mg/g for modified zeolite. Experiments showed increase of temperature has a posetive effect on the dimethyl phthalate sorption process by zeolite. Thermodynamic parameters showed that the sorption of dimethyl phthalate onto zeolite was feasible, spontaneous and endothermic under studied conditions.

This study concerns the performance of degummed cocoons spun by silk worms as a natural ýadsorbent for removal of Methylene Blue (MB) from aqueous solutions. To study the adsorption ýprocess, the effect of various parameters such as contact time, adsorbent dosage, dye initial ýconcentration, and pH of the solution were investigated. According to the experiments, the kinetic ýdata were best described by pseudo second order model and the equilibrium data were properly ýfitted to Langmuir model. The maximum adsorbent capacity at ambient temperature was calculated ýto be 86.2 mg/g. Thermodynamic analysis showed that the process was spontaneous, endothermic ýwith increased randomness at the solid-liquid interface. It was also observed that by manipulating ýthe pH of the solution in acidic range, the adsorbed dye would desorb into the solution suggesting ýthe reusability of the adsorbent. Macroscopic size of the adsorbent offered an additional advantage ýof its ease of separation from the solution.

This research was carried out to assess the dechlorination and decomposition of Polychlorinated biphenyls (PCBs) in the real waste transformer oil using PEG1000/NaOH through a modified household microwave oven. To do so, the influence of polyethylene glycol (PEG) (1.5-7.5 g) and NaOH (0.3-1.5 g) under MW power of 500w on the dechlorination efficiency of PCBs, existed in real waste transformer oil, was investigated. The results show that by increasing the PEG 1000 (1.5- 7.5g) and NaOH (0.3-1.5g) amounts, the dechlorination efficiency of PCBs increased from 35 to 99.99% under microwave power of 500 w at the reaction time of 6 min. The optimum amounts of PEG and NaOH were 5 g and 1 g, respectively. The PCBs dechlorination rate was investigated in the optimum amounts of variables in the various reaction times. The results indicated that the PCBs dechlorination rate was fitted with the one-order kinetic (k = 0.019, R2 = 0.91), and more than 90% of total PCBs were dechlorinated at the first 90 seconds of the reaction time. After 90 seconds, the dechlorination rate decreased. Accordingly, results showed that MW has extraordinary influence on PCBs decomposition from waste transformer oil, and the reaction time decreased more 10 times in comparison to conventional heating.

Development is the fundamental area in enabling India`s economy, urban and provincial structure. Development is a multi-connected structure where all variables are bury connected and multi-centered. All the three limitations time, expense and quality ought to be adjusted in an improved way, so that no segment gets influenced by dismissing those. The goal of the study is to distinguish the administrative variables which will prompt limitations which let-down the development concerning cost, time and quality parts of development from 5 segments which are mind boggling in execution of development venture. A sum of 51 managerial variables is considered from five parts specifically material, labor, equipment, quality control and safety. Information examination is accomplished for 51 calculate at first. Relative significance list is done on these elements and result uncovers that value acceleration of material is 1stmost variable with 0.85 RII esteem, which would be a basic element prompting limitation which may let-down the development. Truancy of work with 0.866 RII esteem as far as time limitation, low material quality observing framework with 0.903 regarding quality requirement and afterward relationship examination is finished with variables harmonizing the three imperatives and result releaved that work efficiency is critical among all components which is associated with 19 different elements above moderate scale,any need and impact on these element will demonstrate sway on different perspectives which may prompt requirement which may let-down the development venture.

One of the most important issues in using computers is data security. In this regard, various techniques of artificial intelligence have already been used for intrusion detection. The main challenge in this area is the running speed of the available implementations. In this research work, we present a hybrid approach which is based on the “linear discernment analysis” and the “extreme learning machine” to build a tool for intrusion detection. In the proposed method, the linear discernment analysis is used to reduce the dimensions of data and the extreme learning machine neural network is used for data classification. This let us to benefit from the advantages of both. We implemented the proposed method on a microcomputer with core i5 1.6 GHz processor by using machine learning toolbox. In order to evaluate the performance of the proposed method, we run it on a comprehensive data set concerning intrusion detection. The data set is called KDD, which is a version of the data set DARPA presented by MIT Lincoln Labs. The experimental results were organized in related tables and charts. Analysis of the results show meaningful improvements in intrusion detection. In general, compared to the existing methods, the proposed approach works faster with higher accuracy.

In this paper, a method of low power analog testing is proposed. In spite of having Oscillation Based Built in Self-Test methodology (OBST), a look up TABLE based (LUT) low power testing approach has been proposed to find out the faulty circuit and also to sort out the particular fault location in the circuit. In this paper an Operational Amplifier, which is the basic building block in the analog circuit, is designed and is taken for testing purpose. Fault coverage is identified after fault modeling, fault injection and fault simulation. More than 93% fault coverage is achieved and there is a scope of increasing more fault coverage. Since analog testing prefaces the challenge of power dissipation during testing, some power minimization techniques like sleepy stack method, current correlation method have adhered during the testing process. Test power reduction up to 84 % is achieved in this work

Linear Low Density Polyethylene-Natural Rubber (LLDPE-NR) composite in the ratio of 70:20 were made with different loading of nanosilica and micro-scale Palm Oil Fuel Ash (POFA). Linear Low Density Polyethylene grafted with maleic anhydride (LLDPE-g-MAH) of 10wt% was added as compatibiliser. The composites were produced by using two-roll mill machine. The tensile properties of the composites were determined by carrying out tensile test. From the test, it was found that the tensile strength of LLDPE-NR decreased with increasing of weight percentages of POFA in the composition. Tensile strength of LLDPE-NR increased with increasing weight percentages of nanosilica in the composition. The water absorption test was done on all samples, and it was found that water absorption of LLDPE-NR nanocomposites decreased with increasing nanosilica content. However, water absorption of LLDPE-NR microcomposites increased with increasing POFA content.

This paper designs a reliability distribution network with limited capacity under partial and complete facility disruptions. To increase the reliability of the distribution network, a new mixed integer linear programing model is developed by considering multiple mitigation strategies including diversification, fortification, and transshipment. The distribution network constitutes of reliable distribution centers which are more expensive, always available and not affect by disruption, and unreliable distribution centers which might be fortified at any level of reliability. Several numerical examples with sensitivity analyses are conducted to illustrate the usefulness of the proposed model. Results demonstrate that the transshipment strategy is more effective than the other mitigation strategies on distribution network reliability and cost.

Industries are one of the main sources of pollution in the world. Besides, the levels of energy resources consumption including water, electricity and fossil fuel are very different among industries. On the other hand, Iranian government pays a large amount of energy subsidy to manufacturing units. Because of it, the government wants to know which of manufacturing industries are efficient, produce less environmental pollutions, and must be supported. Besides, manufacturing industries are classified into various groups. In this paper, the conventional data envelopment analysis (DEA) model has been extended to multi-group state for evaluating manufacturing systems. The main feature of the proposed model is that it takes into consideration inputs/outputs prices (cost/revenue). In other words, we propose a linear multi-group cost/revenue efficiency model. The data on 59 Iranian manufacturing industries grouped under 23 classes to demonstrate the model. The inputs are energy resources such as the amount of fossil fuel, water and electricity consumption as well as a non-energy resource such as the number of employees. The results show that the efficiency scores and energy consumption performance are greatly changed when each industry is evaluated in its own group.

This paper describes the innovative offshore point-absorber wave energy converter (WEC), IRWEC1, under development by the Hydrodynamics, Acoustics and Marine propulsion Group at Babol Noshirvani University of Technology. Totally enclosed in an outer shell, with no external moving parts, IRWEC1 is completely sealed which make it a robust and trustable system. Important motion for this WEC is the pitch motion, so, a pendulum is designed for transferring this motion to the PTO; in this paper, the WEC is evaluated for a wide range of waves in the wave tank. The wave characteristics are presented by which the system had appropriate pitch motion and acceptable extracted electrical energy.

Landing impact and runway unevenness have proximate consequence on performance of landing gear system and conduce to discomfort of passengers and reduction of the pilot’s capability to control aircraft. Finally, vibrations caused by them result in structure fatigue. Fuzzy logic controller is used frequently in different applications because of simplicity in design and implementation. In the present paper, this control approach is performed by minimum error criteria procedure and bees algorithm as the optimization technique for the model of semi-active suspension system that chooses damping performance of shock absorber at touchdown to be the purpose of control on landing gear and its efficiency is evaluated with the competence of passive control. Results of numerical simulation by matlab/simulink software indicate that the force induced to body and the vertical vibration of fuselage have significant improvement about 60% and 50% averagely for fuzzy intelligent method optimized by bees algorithm compared to passive performance which lead to increase in quality of landing, easiness of passengers and structure’s fatigue life in various operation conditions.

Many researchers have developed algorithms to predict welding parameters. Variety of welding types is very much because the confine mixture of pressure and temperature could be selected. This paper introduces a response surface methodology (RSM) for optimization and prediction the influence of Ar and CO2 gases and electrical current on tensile strength of St52’s gas metal arc weld (GMAW) line. After doing experiments the optimum levels of input variables for achieving high tensile strength and contribution of parameters have been obtained by RSM and analysis of variance (ANOVA); respectively. In this study the maximum error is 0.44%. Thus it can be concluded that, the RSM is one of the best methods and can be used to predict the output parameters and save the time and cost of additional experiments.

With the increase of the people who have problems with his walking, a new type of gait rehabilitation training robot has been put forward and designed. In order to meet the requirements of the gait rehabilitation training, the whole mechanical structure and control system have been designed, and the model machine for gait rehabilitation training robot has been made.Using the human gait analysis system of the INSENCO, a large number of experiments on human bodies have carried out, and human gait parameters have been measured and recorded. As was shown in the experiments, the robot designed has achieved the goal of free movement and weight-reducing, and the weight-reducing device is flexible in height and pull, which accomplished the aim of rehabilitation training.