International Journal of Engineering
Volume:30 Issue: 12, Dec 2017

Travels within the city are done in different ways, by vehicle or on foot. Thus, inevitably, a part of the travel is always done on foot. Since intersections as traffic nodes are determinant factor in transportation network capacity, any disruption in them leads to severe reduction in network capacity. Unfortunately, pedestrian behavior has received little attention in Iran. While this is a very important and effective part of traffic engineering. In some cases, pedestrians are the main cause of increasing road users’ delay, therefore, the most important action before anything, is identifying the characteristics of pedestrians. Identifying issues such as speed, volume and density of pedestrians are necessary to control the traffic flow and delay, and can lead to better design of facilities associated with pedestrians. Cases that are studied in this study are: the relationship between speed, density and pedestrians’ flow rate while crossing the street. In this study, the data was collected by filming four intersections in Rasht Metropolis for 15 hours, and the number of pedestrians crossing that were studied was 8489. Two intersections had traffic lights and the other ones had no traffic lights. Then, the relationship between speed, density and volume of pedestrians were obtained by determining the variables of speed, density and volume of pedestrians and using linear and nonlinear regression method and finding the correlation coefficient between the variables. The results showed that for pedestrians, there is a relationship between the flow rate and density with a high correlation coefficient in crossing through crosswalk (R2=0.99) and outside the crosswalk (R2=0.99). But the relationship between speed and flow rate was not significant (crossing through crosswalk, R2=0.29 and outside the crosswalk, R2=0.24); furthermore, speed and density had no significant relationship (crossing through crosswalk, R2=0.36 and outside the crosswalk, R2=0.28).

The occurrences of accidents on the railways are inevitable in today’s world and the factors which may cause it, except the atmospheric and accidental ones, are identified and preventable as well. Therefore, these factors can be investigated and useful actions can be performed in order to reduce these accidents. The main impetus of the present research is the statistical analysis of the causes of railway accidents in Iran. Our achievement illustrates that except the train collision accidents with vehicles, all the accidents vary upon a sixth order curve which means the instability and unpredictability of the railway accidents during the last years. According to the performed studies, it is clarified that the railway accidents during the 10 years from 2000 to 2010 have not had a stable flow and have been under fluctuations and each of the kinds and causes of the accidents has its own contribution to the occurrence of these railway related happenings. Based on the analyses, derailment is the major factor of the various railway accidents and it includes about 55% of these accidents. Damage to people and collisions with non-rail vehicles are placed in the second category. Hereupon, efforts must be made by providing the necessary equipment for the simple access of the people beyond the lines such as pedestrian bridges in order to reduce the railway accidents.

Business Process Management Systems (BPMS) is a complex information system that provides designing, administrating, and improving the business processes. Task allocation to human resources is one of the most important issues which should be managed more efficiently in BPMS. Task allocation algorithms are defined in order to meet the various policies of organizations. The most important of these policies could be reducing the average cycle time, balancing the resource workload, increasing the product quality and minimizing the production costs. Therefore, choosing an appropriate resource in task allocation algorithms could influence on overall policy of the organization. In heavy load conditions or when the number of human resources is limited, workload balancing can increase the stability of the system. In this paper, a task allocation algorithm is proposed to rebalance the resource workload in runtime while minimizing cycle time by offering dependent pair tasks to resources for concurrent processing. The experimental results show that the combination of previous algorithms with the proposed algorithms would have 4.42% reduction in cycle time in contrast to most efficient state-of-the-art algorithms.

In In this paper, two low profile, single fed cavity backed slot antennas providing a circularly polarized (CP) wave are introduced. One of the antennas presents a right-handed CP (RHCP) wave, while the other one offers a left handed CP (LHCP) wave. The proposed antennas consist of a square shaped Substrtae Integrated Waveguide (SIW) cavity incorporatng two couples of radiating slots to radiate two field components with 90° phase difference far from the antennas. A single layer of printed circuit board (PCB) process is employed for both antennas to provide low cost, light weight and also to be compatible with planar circuits. An inset feed line is used to excite two orthogonal modes including TE120 and TE210 with suitable phase difference for generating CP wave. Antenna structures is numerically evaluated using High Frquency Structure Simulator (HFSS) and a prototype of RHCP antenna is fabricated and its radiation charateristics including reflection coefficient, gain, Axial Ratio (AR) and radiation patterns are reported.

In this paper, we present mathematical analyses to consider the effect of material properties on the sensitivity of the Microelectromechanical systems (MEMS) piezoelectric hydrophone and improve the sensitivity by choosing the proper material. The selected structure in the present paper is a piezoelectric hydrophone able to work at low frequencies. The piezoelectric hydrophones are widely used in sonar structure. Sonar systems are used in marine vessels and transportation, military submarines, battleships, etc. Piezoelectric hydrophones work by converting the received sound pressure to electrical signals. This conversion of sonar energy to electrical energy is performed by the piezoelectric material in the structure of the hydrophone. Thus, the applied piezoelectric material has significant effect on sensitivity and performance of the sensor. In this paper, the sensitivity of the sensor has been improved from -201.3 dB to -192.6 dB by choosing the proper material with higher piezoelectric coefficients (PZT-2 instead of PZT-5A).

This paper proposes a switching adaptive control for trajectory tracking of unmanned aircraft systems. The switching adaptive control method is designed to overcome the wind disturbance and achieve a proper tracking performance for control systems. In the suggested system, the wind disturbance is regarded as a finite set of uncertainties; a controller is designed for each uncertainty, and a performance signal is obtained for switching between controllers through a set of visualizers. Each sub-system is robustly stable and the hysteresis logic-based switching is used to obtain the stabilization of a general system. The new system indicates more appropriate results for overcoming the air disturbance compared with the back-stepping adaptive controllers. Finally, the modeling results for the performance of the designed controller are presented.

This paper addresses an unrelated multi-machine scheduling problem with sequence-dependent setup time, release date and processing set restriction to minimize the sum of weighted earliness/tardiness penalties and the sum of completion times, which is known to be NP-hard. A Mixed Integer Programming (MIP) model is proposed to formulate the considered multi-criteria problem. Also, to solve the model for real-sized applications, a Pareto-based algorithm, namely controlled elitism non-dominated sorting genetic algorithm (CENSGA), is proposed. To validate its performance, the algorithm is examined under six performance metric measures, and compared with a Pareto-based algorithm, namely NSGA-II. The results are statistically evaluated by the Mann–Whitney test and t-test methods. From the obtained results based on the t-test, the proposed CENSGA significantly outperforms the NSGA-II in four out of six terms. Additionally, the statistical results from Mann–Whitney test show that the performance of the proposed CENSGA is better than the NSGA- II in two out of six terms. Finally, the experimental results indicate the effectiveness of the proposed algorithm for different problems.

In the oil supply chain, the refined petroleum products are transported by various transportation modes, such as rail, road, vessel and pipeline. The latter provides one of the safest and cheapest ways to connect production areas to local markets. This paper addresses the operational scheduling of a multi-product tree-like pipeline connecting several refineries to multiple distribution centers under demand uncertainty. A new deterministic mixed-integer linear programming (MILP) model is first presented, and then a two-stage stochastic model is proposed. The aim of this model is to meet depot requirements at the minimum total cost including pumping and stoppages costs. The efficiency and utility of the proposed model is shown by two numerical examples, which one of them uses the industrial and real data.

Nowadays, prediction of corporate bankruptcy is one of the most important issues which have received great attentions among academia and practitioners. Although several studies have been accomplished in the field of bankruptcy prediction, less attention has been devoted for proposing a systematic approach based on fuzzy neural networks. The present study proposes fuzzy neural networks to predict bankruptcy of the listed companies in the Tehran stock exchange. Four input variables including growth, profitability, productivity and asset quality were used for prediction purpose. Moreover, the Altman's Zscore is used as the output variable. The results reveal that the proposed fuzzy neural network model has a high performance for the bankruptcy prediction of the companies.

This paper deals with modeling and optimization of the roll-bonding process of Ti/Cu/Ti composite for determination of the best roll-bonding parameters leading to the maximum Ti/Cu bond strength by combination of neural network and genetic algorithm. An artificial neural network (ANN) program has been proposed to determine the effect of practical parameters, i.e., rolling temperature, reduction in thickness, post-annealing time, post-annealing temperature and rolling speed on the bond strength of Ti/Cu composite. The most suitable model with correlation coefficient (R2) of 0.98 and mean absolute error (MAPE) 3.5 was determined using genetic algorithm (GA) and the optimum practice condition are proposed. Moreover, the sensitivity analysis results showed the post-annealing temperature with the negative effects is the most influential parameter on the strength of bonding.

Due to significant environmental advantages, biocomposites have recently received increasing attention. In the present research, strength of hat-shaped coir fiber biocomposites tubes reinforced with nano powder was evaluated experimentally under 3-point bending tests. The tubes were manufactured using hand lay-up technique and based on Taguchi design of experiment. The effects of different parameters including fiber loading, type of nano powder and its weight percentage and also weight percentage of NaOH in alkali treatment were analyzed. Optimization was also performed using Taguchi L8 orthogonal array. Moreover, analysis of variance (ANOVA) was conducted to determine the significance of the parameters. In this study, finite element model was also created in ABAQUS software to compare with the results obtained from the experiments to achieve validated finite element model. There was a good agreement between the results from experiments and those obtained in numerical simulations.

In this paper, numerical simulation for a two-dimensional viscous and incompressible flow past the elliptical airfoil is presented by Random Vortex Blob (RVB). RVB is a numerical technique to solve the incompressible, two-dimensional and unsteady Navier-Stocks equations by converting them to rotational non-primitive formulations. In this method, the velocity vector at a certain point can be calculated without considering any grid around it, so the RVB method can be treated as a meshless method. Accordingly, the turbulent flow past a cylinder as well as an elliptical airfoil is investigated. In both cases, the obtained mean time velocities are compared with available numerical and experimental results where an acceptable agreement is observed. Having known the velocity field, by employing momentum balance, the drag and lift coefficients caused by flow past the elliptical airfoil with different diameter ratios and Re=105 are calculated and compared with experimental data where a good consistency is achieved.

This paper investigates the parametric excitation of a micro-pipe conveying fluid suspended between two symmetric electrodes. Electrostatically actuated micro-pipes may become unstable when the exciting voltage is greater than the pull-in value. It is demonstrated that the parametric excitation of a micro-pipe by periodic (ac) voltages may have a stabilizing effect and permit an increase of the steady (dc) component of the actuation voltage beyond the pull-in value. Mathieu type equation of the system is obtained by applying Taylor series expansion and Galerkin method to the nonlinear partial differential equation of motion. Floquet theory is used to extract the transition curves and stability margins in physical parameters space (Vdc-Vac). In addition, the stability margins are plotted in flow velocity and excitation amplitude space (u-Vac space). The results depict that the micro-pipe remains stable even if the flow velocity is more than the critical value for a certain dc voltage. For instance, in absence of the (ac) component, it is shown that pull-in voltages associated to critical velocities 3 and 6 are 14.06 and 5.4 volt, respectively. However, transition curves show that superimposing an (ac) component with forcing frequency Ω=10 increases the pull-in voltage beyond these values. Furthermore, for the present pull-in voltages the critical velocities 3 and 6 could be increases with imposing some (ac) component. These results are discussed in detail in simulation results section where the transion curves are ploted quantitatively.

The influence of temperature, mean nanoparticle size and the nanoparticle concentration on the dynamic viscosities of nanofluids are investigated in an analytical method followed by introduction of modified equations for calculating the nanofluids’ viscosities. A new correlation is developed for effective viscosity based on the previous model where the Brownian movement of the nanoparticles is considered as the key mechanism. In previous studies, the proposed models were not appropriate for nanoparticles larger than 36 nm. They were also focused on low concentrations of nanoparticles up to 5%. The possibility of homogeneous dispersion of the nanoparticles and the Stokes law are observed here. This new model is explained in terms of temperature, mean nanoparticle diameter, nanoparticle volume concentration and both the nanoparticle and base fluid thermophysical characteristics for the effective viscosity of nanofluids. A combined correction factor is introduced to take into account the simplification for a free stream boundary condition outside the boundary layer. A good agreement is observed between the effective viscosity obtained in this new model and those of recorded experiments conducted for different nanofluids. The results show that the present model is valid for large volume concentration (0%