International Journal of Engineering
Volume:31 Issue: 6, Jun 2018

In this paper, a genetic algorithm (GA) has been used to predict the vapor pressure of pure organic compounds based on Riedel equation. Initially, the coefficients of Riedel equation were optimized. Then, a new term was added to the original Riedel equation to reduce error of the model in prediction of vapor pressures of pure materials. 110 components at two different pressures (10 and 100 kPa) were chosen to investigate the capability of mentioned models. Absolute average relative deviation percent (AARD %) was reported for 40 components as testing materials to compare the calculated results of two models with experimental data. Results showed that the exerted modification on Riedel equation decreases the errors in prediction of vapor pressures of chemical components.

Uncontrolled intersections are the intersections where there are no external signs or signals to control the movement of vehicles. In mixed traffic conditions priority rules are often violated by the road users. In All-way-stop-controlled intersections (AWSC), the vehicle should stop themselves before they enter the intersection and should check whether any vehicles are present in the other approaches of the intersection. If no vehicle is present, then they can cross the intersection. For this study, data were collected from two uncontrolled three-legged intersections located at various parts of India and critical gap required for each vehicle combination to cross the intersection are extracted. Gap Acceptance method is used for mixed traffic condition because it is based on the critical gap and follow-up time, which in turn depends on the type of vehicles and traffic conditions. This study tries to analyze the effect of vehicle type on gap acceptance behaviour at uncontrolled three-legged intersection. From this study, it is observed that size of the vehicles and traffic volumes has an influence on the critical gap. Depending on the major road vehicle type combinations, the critical gap for each right turning subject vehicle varied from minimum of 1.4 s to a maximum of 8.7s.

Recently, steel structures have been accounted for a large percentage of the buildings due to their advantages such as higher execution speed and easier construction. In steel structures, welded joints are commonly used and their quality plays a key role in stability of buildings under applied loads. Hence, to increase resiliency of welded steel structures against natural hazards, welded joints quality should be improved. In this article, a statistical study was done on welding defects of different connections in 50 welded steel buildings that were being constructed in district 12 (Mashhad, Iran). The reasons for selecting this district were high rates of construction and high potential of hazards. Actually, initial information about joints importance and weld defects were collected by distributed questionnaires among building designer engineers and weld inspectors. In this paper, we used the Expert Choice software that works according to Analytic Hierarchy Process (AHP) to prioritize weld defects in different connections of the buildings and define management solutions to improve them. The priority results revealed that in the non-rigid connections crater, slag inclusion and spatter are more critical whereas in the rigid connections Lack of Penetration (LoP) and Lack of Fusion (LoF) are more critical than the other welding defects in steel building structures.

Though it is vital to estimate infiltration as one of the key factors in effective management of water resources, only few studies have been carried out either to determine the infiltration or to compare the performance of infiltration models for coarse textured soils. Thus, the present study was conducted to accomplish two objectives. First to estimate the Horton’s infiltration model parameters for coarse textured soils (particle size distribution greater than 0.075 mm, according to the Unified Soil Classification System) and to compare the infiltration capacities estimated by the model with those measured in the field. Second to measure the infiltration in the coarse textured soil using both single and double ring infiltrometers and to compare them. Study location was Hapugala area in Galle District, Sri Lanka. In this study, the least squares fitting technique was employed to estimate the Horton’s model parameters from the field measured data. A good agreement was found between the model estimated infiltration values and those measured at field. Horton’s infiltration model estimations fitted very well with much coarse textured soil. The highest difference between the single and double ring infiltrometer measurements were also observed for the much coarse textured soil. Overall, the infiltration measurements by the double ring infiltrometer were 20-35% lower, on average, than that of the single ring infiltration measurements suggesting considerably high infiltration along the lateral direction in the single ring compared to the double ring infiltrometer.

The analysis of pavements and their ingredients has always been important due to a good understanding of their behavior under different conditions; that leads to more accurate relations. Due to the extent of asphalt mixture application in the world, the assessment of different behaviors of this mix is very important from various aspects of performance and safety. Given that the asphalt mixtures are inherently very sensitive to temperature changes due to bitumen content, identification and analysis of the viscoelastic and visco-elasto-plastic behavior of the mixture is of particular importance. The scope of present research is to provide new model of viscoelastic behavior of asphalt concrete pavements with a combined effect of stress and temperature using genetic programming techniques. For this purpose, a number of dynamic creep tests under various temperatures and different stress levels were done. Beside, in this study a comparison is made between the generalized model and proposed model in estimating the visco elastic response of asphalt samples. Performance of the genetic programming model is quite satisfactory. The new proposed model will also help further researchers willing to perform similar studies, without carrying out destructive tests.

Acrylic polymer that is highly stable against chemicals and is a good choice when concrete is subject to chemical attack. In this study, self-compacting concrete (SCC) made using acrylic polymer, nanosilica and microsilica has been investigated. The results of experimental testing showed that the addition of microsilica and acrylic polymer decreased the tensile, compressive and bending strength of the concrete. The addition of nanosilica and an increase in polymer content increased the bending strength of concrete and decreased the tensile and compressive strengths. Because, in the laboratory, the number of samples were limited and the amount of variation was small, comprehensive results cannot be achieved. With the help of neural networks, estimating any amount within the range of the input data is possible. In this paper, in addition to the experimental results, a backpropagation neural network (BNN) was used to simulate the testing on the strength of self-compacting polymeric concrete. The results showed that the use of the normalized mean squared error, resilient backpropagation training, tangent-sigmoid and log sigmoid transfer functions and five neurons in each hidden layers in a two-layer BNN produced good results with a regression value of 0.95 and error of 0.17.

Image classification and retrieval systems have gained more attention because of easier access to high-tech medical imaging. However, the lack of availability of large-scaled balanced labelled data in medicine is still a challenge. Simplicity, practicality, efficiency, and effectiveness are the main targets in medical domain. To achieve these goals, Radon transformation, which is a well-known technology in medical field, is utilized along with a deep network to propose a retrieval system for a highly imbalanced medical benchmark. The main contribution of this study is to propose a deep model which is trained on the Radon-based transformed input data. The experimental results show that applying this transformation as input to feed into a convolutional neural network, significantly increases the performance, compared with other retrieval systems. The proposed scheme clearly increases the retrieval performance, compared with almost all models which use Radon transformation to retrieve medical images.

In this paper a novel method for detecting targets in inactive radars is presented. In this method, the time history of cellsof the ambiguity function is used for detection. For this purpose, the cell history is considered as a random field. Then, using adaptive filter, the string time of the desired target are separated from the string time of noise and clusters in the environment. In order to evaluate the performance of the proposed method for an environment including three targets with simulated different distances and speeds, the results were compared with the other two methods at the same conditions. Based on the results obtained, this method has the ability to detect targets for SCNRs of up to -10 dB for all three values of the probability of false alarms. The obtained results also showed the superiority of the proposed method compared to other alternatives in such manner. Accordingly, the probability of detection for the proposed method at least 12.5 percent better than ACM and 8 percent better than NNTD. It also shows that for SCNRs larger than zero dB, this method has a 100% detection capability.

One of the key challenges of employing photovoltaic systems is to extract maximum power of the panels. This problem is known as maximum power point tracking (MPPT) technique. The MPPT stands for establishing situation in which output power of the panels reaches its maximum allowable power. In this context, this paper is to assess the technical requirements to achieve maximum output power of a number of photovoltaic (PV) panels in Z-source inverters. For the sake of simplicity and without loss of generality, a generic 7-level Z-source multi-level inverter to use with the PV panels is considered for our purpose. The conducted assessment is performed in terms of the analysis of the input resistance of the connected inverter. The simulation results showed that achieving the maximum power point (MPP) depends on the various governing factors including components of the inverter (i.e. load, frequency switching, and electric elements value), irradiance level, ambient temperature, and partial shading effect. Also, as the results demonstrate, in a number of combinations of the conditions there is not an optimum situation in terms of achieving MPPT. In addition, major parts of the findings are implemented on a practical system.

Disasters inevitably trigger far-reaching consequences affecting all living things and the environment. Therefore, top managers and decision-makers in disaster management seek comprehensive approaches to evaluate facilities and network preparedness in dealing with the response phase of predicted disaster scenarios in terms of number of casualties, costs, and unmet demands. In this regard, previous studies on the preparedness phase have often been limited to the location of eligible facilities without considering other important factors such as current assets, entities and configuration. Thus, the present study proposes a reconfiguring and repositioning model in order to simultaneously assess whether existing support bases should remain, be consolidated or phased out as well as whether new support base facilities should be established and subsequently supply and demand requirements considered. In the proposed model, in addition to considering a scenario tree for destruction and demands, network links affected by the intensity of disaster events are also evaluated. Furthermore, in order to increase reliability, the destruction of network links takes into account that link failures give rise to vulnerability in related links. In the proposed model, multi-stage stochastic programming has been implemented on various real destruction and demand scenarios. The results indicate definite advantages in the re-positioning or reconfiguring model compared with current configurations. Moreover, the superior capability of the applied solving approach versus one of the traditional approaches is also appraised.

Despite the fact that Titanium material has been considered as difficult to cut material, its usage has been increasing day by day in all engineering sectors; wherever criticality is encountered. Many studies are going on in view of increasing tool life at high cutting speed to improve productivity. In this study, attempt has been made to see the effect of iron as a partial substitution along with cobalt binder in cutting tool material for turning of titanium alloy. The iron-rich binder carbide tool samples were produced through powder metallurgy route using a powders with mean particle size of less than 0.5µm. Turning experiments were conducted at different speeds to evaluate the effects of iron-rich binder on tool flank wear. Results of turning experiments clearly showed that iron-rich binder tend to increase tool life in comparison to conventional WC-Co composite cutting tools.

One of the most important points in a supply chain is customer-driven modeling, which reduces the bullwhip effect in the supply chain, as well as the costs of investment on the inventory and efficient transshipment of the products. Their homogeneity is reflected in the Inventory Routing Problem, which is a combination of distribution and inventory management. This paper expands the classical Inventory Routing Problem based on the Multiple Delivery Strategy along with one of the functionalities of routing problem, namely, "backhauls", with a priority consideration for linehaul customers. Then it has been modeled in the form of a problem with Multi-period, multi-product, and multi- vehicle planning horizons in which stock out is not allowed. Moreover, for an optimal use of the vehicle capacity to serve the linehaul and backhaul customers, this study adopted a “split service” problem to the model, which also increases the complexity of the problem. First, considering the above-mentioned assumptions, a new mathematical model is proposed in the form of mixed integer programming for the problem defined in this paper. Then, since the stated problem can be considered among the non-deterministic polynomial-time hard, an efficient meta-heuristic genetic algorithm is provided for solving it. At the end, the numerical results obtained by this algorithm are analyzed using the randomized test problems. The result shows that by adopting a split service approach, 70% of the test problems will demonstrate cost reduction.

This paper presents a three-level supply chain model which includes single supplier, several distribution centers and sets of retailers. For this purpose, by adopting the queuing approach, a mixed nonlinear integer programming model is formulated. The proposed model follows minimizing the total cost of the system by determining: 1) the number and location of distribution centers between candidated ones; 2) the possibility of allocating each of the retailers to the distribution centers; 3) the amount of retailers demand; and 4) the policy of distribution centers. In the proposed model, the cost of waiting in queue is also considered. In order to make the problem more realistic, we consider uncertain demand and lead-time, which follow Poisson and Exponential distributions, respectively. Hence, we apply continuous-time Markov process approach to obtain the amount of annual ordering, purchase and inventory. Then, the results are used to formulate the location-inventory problem. Finally, the proposed model is solved using GAMS software version 24.1.3.

In this paper, the stability analysis and control design of heterogeneous traffic flow is considered. It is assumed that the traffic flow consists of infinite number of cooperative non-identical vehicular platoons. Two different networks are investigated in stability analysis of heterogeneous traffic flow: 1) inter-platoon network which deals with the communication topology of lead vehicles and 2) intra-platoon network which deals with communication topology of individual platoons. The unidirectional communication topology is employed to describe the inter-platoon and intra-platoon networks topologies. By introducing a new decoupling approach, the 3N-order closed-loop dynamics of both networks is transformed to N third-order dynamical equations. Both inter-platoon and intra-platoon string stability are performed by presenting new approaches. Several simulation results are provided to show the effectiveness of the proposed approaches.

One of the main controlling parameters in diesel engine combustion is the fuel – air mixing process that has direct effects on engine performance and pollutant emissions, reviewing over previous literature showed that split injection strategies could satisfy this purpose very well. For the first time and in this paper, pilot and double injection strategies were combined and formed new triple injection strategy that has not been considered by any other researchers. In this study after achieving successful validation between modeling and experimental results for both single and double injection strategies, optimization of triple injection strategy was conducted, in which first pulse of double injection strategy divided in to two pulses, then amount of injected fuel in each pulse kept constant and different delay times between first and second pulse of injections were investigated. For better understanding the processes the injections were done inside the engine, diagrams of heat release rate, in cylinder temperature, in cylinder pressure, NOx and soot emissions were presented. Results showed that decreasing the delay time between second and third pulse of injections could decrease the ratio of premixed combustion of third pulse and in optimum cases, reduction in both NOx and soot emissions could be achieved in comparition with single and double injection strategies, without any significant effects on engine performance. Furthermore, triple injection strategy with second pulse of injection that started at 4 crank angle before top dead center was selected to be the optimum case in reduction of both emissions.

The enhancement of operating life cycle of electronic devices necessitates the development of efficient cooling techniques. Therefore, in the present work the effects of employment of Phase Change Material, in the adiabatic section of heat pipe for electronic cooling applications were experimentally and numerically investigated. Tricosane (100 ml) is chosen as PCM in this study, where Al2O3 nanoparticles were dispersed in PCM by an ultrasound mechanism with volume fractions of 0.5, 1 and 2%. Transient thermal behavior of the evaporator, energy storage materials and condenser were studied during the charging process with heating powers of 13, 18 and 23W. The performance of system with Tricosane and nanoparticles improved for 1% concentration and reduced for 2% concentration; which concludes for the optimized doping of nanoparticles. In addition, CFD simulation of heat pipe is carried out for the above mentioned opertating conditions. The experimental and simulation results were compared at various operating conditions to establish correlation between them. The numerical results observed to match closely with experimental results. Finally, the thermal performance of heat pipe-PCM module is predicted through CFD simulation for the filling volumes of 115 cc and 130 cc at 13 W, 18 W and 23 W.

The purpose of this research is to study the mechanical behavior of a micropump with clamped circular diaphragm which is the main component of drug delivery systems. In this paper, the non-linear governing equations of the circular microplate using Kirchhoff thin plate theory was been extracted based on the modified couple stress (MCST) and classical (CT) theories. Then, the non-linear equation of static deflection is solved using Step-by-Step Linearization Method (SSLM) in order to escape the nonlinearity of the differential equation and Galerkin-based reduced-order model is applied to investigate the dynamic motion of the microplate. Afterwards, static and dynamic stabilities of the micropump have been studied based on both MCST and CT, then compared. Also, volumetric flow rate of the micropump was been delved based on both theories and in entire research, presence of the length scale parameter in modified couple stress theory brings this opportunity to study the size effect on the mechanical behavior of the micropump.

Electrical discharge machining has the capability of machining complicated shapes in electrically conductive materials independent of hardness of the work materials. This present article details the development of multiple regression models for envisaging the material removal rate and roughness of machined surface in electrical discharge machining of Hastelloy C276. The experimental runs are devised as per Taguchi’s principles and empirical relations are established using multiple regression analysis. Taguchi’s methodology can be applied as a single aspects optimization technique for attaining the best set of possible process parameter for material removal rate and roughness of the machined surface. A statistical tool called analysis of variance is employed for determining the significance of input process variables that influences the desired performance measures such as material removal rate and roughness of the electrically machined surface. The developed multiple regression models are flexible, competent and precise in prediction of desired performance measures. The developed regression models were validated and the predicted results from the evolved regression models are closer with the experimental outcomes.