International Journal of Engineering
Volume:32 Issue: 7, Jul 2019

Industrial process control system due to integration of equipment, existing material and energy recycle streams and their effects are extraordinary importance. The process in terms of safety, product quality and control stability have a challenge when there was defects in a process control system. The isomerization process is gaining importance in the presence of refining context due to upgrading the octane number of light naphtha fractions and also simultaneously reduces aromatic compounds especially benzene content. In this study, the isomerization unit control system of Imam Khomeini Oil Refinery Company (IKORC, shazand, Iran), by defined four controllers include: the temperature controller on pre-heater exchanger, the concentration controller on depentanizer, deisopentanizer and deisohexanizer towers. This work is based on the nine principles of the plant-wide process control, was investigated. It should be noted that currently lack these four controllers in isomerization unit, confront this unit to challenge in dealing with sudden disturbances. The results show that obtained data from dynamic simulation by Aspen Hysys v7.3 had an acceptable compliance with the principles of plant-wide process control theory.

Punching shear capacity is a key factor for governing the collapsed form of slabs. This fragile failure that occurs at the slab-column connection is called punching shear failure and has been of concern for the engineers. The most common practice in evaluating the punching strength of the concrete slabs is to use the empirical expressions available in different building design codes. The estimation of punching loads involves experimental setup which is time-consuming, uneconomical and also, more manpower and materials are required. The present study demonstrates the use of data mining techniques as a substitute of former to predict the punching loads on the variation of various parameters. In this study, various type of data mining techniques including Adaptive Neuro-fuzzy Inference System (ANFIS), Artificial Neural Network (ANN) and Generalized Neural Network (GRNN) were applied to model and estimate the punching load of reinforced concrete slab–column connections. For the study, a data set consisting of 89 observations from available literature was analysed and randomly selected 62 observations were used for model development whereas the rest 27 were used to test the developed models. While the outcomes of ANN and GRNN model provides suitable estimation performance, the Gaussian membership based ANFIS model performed best in the determination of coefficient of correlation (Cc). Sensitivity study indicates that the parameter effective depth of slab (d) is the most influencing one for the estimation of punching load of reinforced concrete slab–column connections for this data set.

In this paper, we propose an efficient hybrid Particle Filter (PF) algorithm for video tracking by employing a genetic algorithm to solve the sample impoverishment problem. In the presented method, the object to be tracked is selected by a rectangular window inside which a few numbers of particles are scattered. The particles’ weights are calculated based on the similarity between feature vectors of the scattered particles and that of the central particle. Before the resampling stage of PF algorithm, particles with the highest weights are evolved using a genetic algorithm. The evolved particles’ coordinates are transferred to the next frame by a random walk model, and the rectangle involving new particles is specified. Moreover, we utilize the idea of partitioning (selecting parts of target in the first frame with a distinct color/texture) and reducing image size to decrease the number of particles. The partitioning idea also helps our method in resolving the occlusion problem. Simulation results demonstrate the outperformance of the suggested approach comparing with other methods in terms of precision and tracking time when it encounters with the challenges such as full and partial occlusions, illumination and scale variations, fast motions, and color similarity between the object and background.

Nowadays, with huge progress in digital imaging, new image processing methods are needed to manage digital images stored on disks. Image retrieval has been one of the most challengeable fields in digital image processing which means searching in a big database in order to represent similar images to the query image. Although many efficient researches have been performed for this topic so far, there is a semantic gap between human concept and features extracted from the images and it has become an important problem which decreases retrieval precision. In this paper, a convolutional neural network (CNN) is used to extract deep and high-level features from the images. Next, an optimization problem is defined in order to model the retrieval system. Heuristic algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO) have shown an effective role in solving the complex problems. A recent introduced heuristic algorithm is Grasshopper Optimization Algorithm (GOA) which has been proved to be able to solve difficult optimization problems. So, a new search method, modified grasshopper optimization algorithm (MGOA) is proposed to solve modeled problem and to retrieve similar images efficiently, despite of total search in database. Experimental results showed that the proposed system named CNN-MGOA achieves superior accuracy compared to traditional methods.

Object tracking through multiple cameras is a popular research topic in security and surveillance systems especially when human objects are the target. However, occlusion is one of the challenging problems for the tracking process. This paper proposes a multiple-camera-based cooperative tracking method to overcome the occlusion problem.  The paper presents a new model for combining convolutional neural networks (CNNs), which allows the proposed method to learn the features with high discriminative power and geometrical independence. In the training phase, the CNNs are first pre-trained in each of the camera views, and a convolutional gating network (CGN) is simultaneously pre-trained to produce a weight for each CNN output. The CNNs are then transferred to the tracking task where the pre-trained parameters of the CNNs are re-trained by using the data from the tracking phase. The weights obtained from the CGN are used in order to fuse the features learnt by the CNNs and the resulting weighted combination of the features is employed to represent the objects. Finally, the particle filter is used in order to track objects. The experimental results showed the efficiency of the proposed method in this paper.

Cogging torque reduction of axial flux permanent magnet brushless dc (PMBLDC) motor is an important issue which demands attention of machine designers during design process. This paper presents magnet notching technique to reduce cogging torque of axial flux PMBLDC motor designed for electric vehicle application. Reference axial flux PMBLDC motor of 250 W, 150 rpm is designed with 48 stator slots and 16 rotor poles of NdFeb type permanent magnet without notching. Three dimensional finite element modeling and analysis is performed to obtain cogging torque profile of initially designed reference machine. Notches are created on permanent magnets and its influence on cogging torque is analyzed with 3-D finite element modeling and analysis. It is analyzed that magnet notching is an effective technique to reduce cogging torque of axial flux PMBLDC motor.

In this paper, the design and the results of a microwave radiation system for agriculture applications is discussed. The system is fabricated and successfully tested on weed seeds. The device, which uses a commercial 1 kW magentron, proved to be effective for preventing the germination control of popular weeds of Iran. Seven weed species were tested separately by using this system and then the irradiated soil was cultivated in a greenhouse. The results show that by increasing soil temperature up to 70 oC, the germination rate of weed seeds is less than 20 percent (in some cases zero percent). It should be mentioned that the safety of the system is also studied according to ICNIRP standard.

Nowadays, nurses scheduling is one of the most important challenges with which health care centers are encountered. The significance of nurses’ work quality has led researchers to be concerned about scheduling problems, which have an impact on nurses’ performance. Observing the interests of hospital and patients, providing their satisfaction, and meeting their needs are among the main objectives of scheduling, which are focused on in this research. For this end, goal programming is used for modeling and problem solving of the nurses scheduling process. Hence, a developed comprehensive model with 7 goals related to management aspects and nurses’ interests have been designed considering emergency department characteristics of a large hospital in Tehran as a case study. Finally, the model was solved via GAMS software. The model resulted in an optimal pattern for nurses scheduling in a 28-days horizon. According to the definition presented in the modeling process, 3 goals associated with proportion, sequence, and isolation of working days were fulfilled. However, 4 goals of nurses’ interests, number of working days, and isolate off days have illustrated a few deviations due to resource limitation. In addition, a comparison between the results and the current scheduling indicated a higher efficiency of optimal scheduling. Sensitivity analysis of the nurses scheduling also revealed that with an increase in the number of nurses, the goals would improve significantly. Implementation of this scheduling not only improves work justice and performance of the nurses but also increases their satisfaction from the scheduling process.

The problem of maximal hub covering as a challenging problem in operation research. Transportation programming seeks to find an optimal location of a set of hubs to reach maximum flow in a network. Since the main structure's parameters of the problem such as origin-destination flows, costs and travel time, change periodically in the real world applications, new issues arise in handling it. In this paper, to deal with the periodic variations of parameters, a bi-objective mathematical model is proposed for the single allocation multi-period maximal hub covering problem. The ε-constraint approach has been applied to achieve non-dominated solutions. Given that the single-objective problem found in the ε-constraint method is computationally intractable. Benders decomposition algorithm by adding valid inequalities is developed to accelerate the solution process. Finally, the proposed method is carried out by CAB data set, and the results confirm the efficiency of it regarding optimality and running time.

Regarding the development of distribution systems in the recent decades, fuel consumption of trucks has increased noticeably, which has a huge impact on greenhouse gas emissions. For this reason, the reduction of fuel consumption has been one of the most important research areas in the last decades. The aim of this paper is to propose a robust mathematical model for a variant of a vehicle routing problem (VRP) to optimize sales of distributers, in which the time of distributor service to customers is uncertain. To solve the model precisely, the improved differential evolution (IDE) algorithm is used and obtained results were compared with the result of a particle swarm optimization (PSO) algorithm. The results indicate that the IDE algorithm is able to obtain better solutions in solving large-sized problems; however, the computational time is worse than PSO.

The composites combining aluminum and silica nanoparticles with the addition of tetramethylammonium hydroxide (Al-SiO2(T)) and butanol (Al-SiO2(B)) as mixing media have been successfully fabricated. Corrosion behavior of Al-SiO2 composites before and after exposure in 1M NaCl solution was examined using potentiodynamic polarization (Tafel curve analysis). The study was also equipped with scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and X-ray diffraction (XRD) investigations. Before exposure, Al-SiO2(T) exhibited the best corrosion resistance. Performance improvement was indicated by Al-SiO2(B) up to 10 times better than Al-SiO2(T) after exposure. The increased SiO2 content did not significantly enhance the corrosion resistance of the composites. The Al-SiO2 composites with 5% SiO2 content showed very high corrosion resistance (as the optimum composition). Furthermore, pitting corrosion was observed in the Al-SiO2 composites, indicated by the formation of corrosion products at grain boundaries. The product was affected by the presence of SiO2 in the Al matrix and the NaCl environment at 90°C (approach to synthetic geothermal media: Na+, Cl, H+, OH-). Our study revealed the presence of g-Al2O3, g-Al(OH)3, and Al(OH)2Cl as the dominant corrosion products.

This article reports the active control of base flows using the experimental procedure. Active control of base pressure helps in reducing the base drag in aerodynamic devices having suddenly expanded flows. Active control in the form of microjets having 0.5 mm radius placed at forty-five degrees apart is employed to control the base pressure. The Mach numbers of the present analysis are 1.7, 2.3, and 2.7. The length to diameter (L/D) ratio is varied from 10 to 1 and the nozzle pressure ratio (NPR) being changed from 1 to 10 in steps of 1 for base pressure measurements. The area ratio for the entire analysis is fixed at 2.56. Wall pressure distribution along the enlarged duct is also recorded. No change in base pressure increase/decrease is thoroughly analysed as well. From the experimental investigation, it is found that control plays an important in modifying the base pressure without disturbing the wall pressure distribution. The base pressure variation is entirely different at L/D = 1 compared to a higher L/D ratio due to change in reattachment length and the requirement of the duct length at higher inertia levels. The quality of the flow in the duct in the presence and absence of control remained the same.

In this experiment effect of two full and half width sinusoidal inner tubes in triplex-tube heat exchanger with phase change material (PCM) was investigated. Length and diameter of the tubes have been chosen such that the area of each tube to be the same. Charging and discharging processes were carried out by inner tube, outer tube and both. Results indicated, PCM melting and solidification time for the full width sinusoidal inner tube, in the processes of charging and discharging from the inner tube, outer tube and two sides were shorter than the half width sinusoidal inner tube. Comparing the charging and discharging processes of these tubes with a straight inner tube indicated significant improvement in the amount and reduction in time of PCM melting. The melting mode in the straight tube process was incomplete after about 32.5 hours, however in the case of full and half width sinusoidal inner tube, the melting times were 8 and 10 hours, respectively. Moreover, it was an improvement of 54% in melting time from the outer tube in the full width sinusoidal tube and 35.8% in the half width sinusoidal tube.

In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method in the signal separation, using the morphological difference of the components in the automatic vibration signal, different sparse dictionaries were constructed to separate the components, eliminates the noise components and extracted the effective fault characteristic component, the extracted impact components are decomposed by EEMD and the energy feature of each IMF component is calculated as the fault features, then put the fault features into SVM (Support Vector Machine) and identify the faults. Through the construction simulation example and the typical fault simulation test of automatic machine, it showed that the morphological component analysis method had better noise reduction and signal separation effect. Compared with the traditional EEMD method, the feature extraction method based on the MCA-EEMD can distinguish automaton fault types more effectively.

Al7075 alloy reinforced with h-Boron Nitrate (BN) composites were processed by stir casting technique. The produced composite was subjected to microstructural studies using OLYMPUS -BX51M, tensile, hardness, density and wear tests. Tensile strength and hardness were found to increase by 12.8% and 20% respectively due to increased dislocation density with the addition of reinforcement. Microstructure showed grain refinement with reinforcement addition and reinforcement acts as nucleating sites with an approximately uniform distribution of reinforcements. Wear test was conducted with different loads 10, 20 and 30N for a sliding distance of 1500 m. Wear mass loss of composites showed improved wear resistance with variation in reinforcements. Worn surfaces were examined using SEM, which showed the presence of delamination, plough and debris on the surface. Due to the addition of low-density h-BN, the density of composites decreases with increase in reinforcement content.

Since the electric motor of pure electric vehicle replaced the engine, the "masking effect" disappears, and the problem of vibration and noise of the transmission becomes prominent. This is generated during the gear meshing and is transmitted to the housing through the shaft and bearing. Thereby, radiation noise of the housing are generated. The prediction and analysis of the vibration and noise problems of transmission can be avoided during the design process, which will shorten the development cycle and reduce the development costs. In this paper, the finite element model and boundary element model of the three-axis four-speed automated mechanical transmission (AMT) for pure electric bus were established by Finite Element Method (FEM) and Boundary Element Method (BEM) for modal and acoustic analysis. The excitation of the gear system is used as the input, and the direct boundary element method is used to predict the noise of the AMT. The correctness of the simulation method is verified by the comparing simulation with bench test results.

In this work both experimental and numerical analysis are carried out to investigate the effect of solar radiation on the cabin air temperature of Maruti Suzuki Celerio car parked for 90 min under solar load condition. The experimental and numerical analysis encompasses on temperature increment of air at various locations inside the vehicle cabin. The effect of 90 min exposure to the environment is simulated with the help of Discrete Ordinance (DO) and Surface to Surface (S2S) radiation models using ANSYS FLUENT 18.2. Moreover, the impacts of using different turbulence model on the accuracy of the simulation results and the comparison between steady state and transient state simulation results have also been studied. The results of the simulation are compared with the experimental data to contrast the model. The absolute average deviation in temperature predicted by DO and S2S model from the experimental data are 10.07 and 10.01%, respectively. In this work both experimental and numerical analysis are carried out to investigate the effect of solar radiation on the cabin air temperature of Maruti Suzuki Celerio car parked for 90 min under solar load condition. The experimental and numerical analysis encompasses on temperature increment of air at various locations inside the vehicle cabin. The effect of 90 min exposure to the environment is simulated with the help of Discrete Ordinance (DO) and Surface to Surface (S2S) radiation models using ANSYS FLUENT 18.2. Moreover, the impacts of using different turbulence model on the accuracy of the simulation results and the comparison between steady state and transient state simulation results have also been studied. The results of the simulation are compared with the experimental data to contrast the model. The absolute average deviation in temperature predicted by DO and S2S model from the experimental data are 10.07 and 10.01%, respectively.

Fuel cells directly convert chemical energy into electrical power using electrochemical reactions. Solid oxide fuel cell (SOFC) is one of the high-temperature fuel cells that propose a promising future from the standpoint of power generation. In this study, optimization of an SOFC system is performed using Taguchi approach after verification of the model in compare with experimental results. Current density, inlet temperature of SOFC, and utilization factor are considered as input parameters and the electrical power is selected as the output response. The analysis of variance (ANOVA) results indicate that the current density is the most effective parameter on electrical power which has 52% of contribution followed by inlet temperature of SOFC and utilization factor by 25 and 20% of contributions, respectively. The electrical power enhances by increasing current density and inlet temperature of SOFC and reducing utilization factor. Signal to noise ratio (S/N) analysis elucidate that the current density of 9500 A/m2, the inlet temperature of SOFC of 850 °C, and the utilization factor of 75% is the optimum condition in order to achieve the highest electrical power. The results show that the electrical power is 644.3 kW at the optimum condition.

An experimental investigation is conducted to calculate the shock standoff (SSO) distance in front of an acute-angled wedge. For this experimentation, simple water flows channel analysis is carried out. The flow velocity is varied from 13.2 cm/s to 25.5 cm/s increasing in steps of 1 cm/s. A velocity of 13.2 cm/s corresponds to Froude number 1.13 and velocity of 25.5 cm/s to Froude number 1.41. The Froude number ranged from 1.13 to 1.41 in steps of 0.04. The study is conducted on 5 mm thick acrylic sheets and of wedge angles 50°, 60°, and 75° to obtain a relation for calculating the SSO distance concerning the Froude number. It is found that the pressure uphill strongly depends upon the Fr and wedge angle. The SSO distance determined experimentally and using the proposed correlation are found to be in good agreement.