International Journal of Engineering
Volume:36 Issue: 2, Feb 2023

This paper mainly deals with the tool wear characteristics of uncoated cemented carbide insert and PVD AlTiN, PVD TiAlN coated carbide inserts during turning of Ti6Al4V-ELI (Extra Low Interstitial). To satisfy the sustainability conditions, the experiments have been conducted under dry and minimum quantity lubrication (MQL) environment. To enhance the effectiveness of MQL, palm oil has been used as the cutting fluid. The same machining parameters are employed for all the cutting tool inserts in dry and MQL environments to understand the machining characteristics better. It was found that cutting speed greatly influences average flank wear. Tool life of PVD TiAlN coated tool is more in both MQL, and dry environments as compared to uncoated cemented carbide insert and PVD AlTiN coated insert. Using palm oil under the MQL environment has produced better results while turning by PVD TiAlN insert. The characteristics like good cooling and lubrication provided significantly less average flank wear during machining of Ti6Al4V-ELI under the MQLenvironment.

Autonomous power generation systems are designed to operate independently from the public power grid. Batteries constitute the important element in stand-alone PV system. They are used to store electricity produced by solar energy at overnight or for emergency use during the non-constant load demand. This paper has three major parts.The first pertains the design of an intelligent method for maximum power point tracking based on fuzzy logic controller to improve the efficiency of a standalone solar energy system. The second part describes the battery state of charge (SOC). The proposed model, which better reflects the real SOC response of the lithium battery, is constructed by using the extended Kalman Filter (EKF) states estimator. This proposed method can be considered as a more accurate and reliable method to estimate the battery state of charge. The third part integrates a management system for the above two renewable energy sources. The performance of the proposed management system by using a fuzzy logic controller based maximum power point tracking FLC-MPPT and the EKF estimator have been simulated in Matlab/Simulink at different solar irradiation and temperature for a given no constant load energy request.

In this article, a fault location technique based on artificial neural networks (ANN) for Terminal-Hybrid LCC-VSC-HVDC has been assessed and scrutinized. As is known, in conventional HVDC systems (LCC-based and VSC-based HVDCs), the same type of filter is used on both sides due to the use of similar converters in both sender and receiver terminals. In this article, it is concluded that due to the use of two different types of converters at the both ends of the utilized Terminal-hybrid LCC-VSC-HVDC system, and the use of different DC filters on both sides, fault location using positive and negative pole currents of the rectifier side has much better results than the rest of input signals. Therefore, it will be finalized that by increasing and designing suitable DC filters on the transmission line of HVDC systems, fault localization matter will be remarkably and surprisingly facilitated. Nowadays, the fault location of HVDC transmission lines with a value of more than 1% is generally discussed in most articles. In this research, the fault location with a value of 0.0045%, i.e., a distance of 22.5 meters from the fault point in the most satisfactory case is obtained, which shows the absolute feasibility of the ANN along with the wavelet transform. To validate the proposed method, a ±100 KV, Terminal-hybrid LCC-VSC-HVDC system is simulated via MATLAB. The outcomes verify that the proposed technique works perfectly under various fault locations, resistances, and fault types.

This paper proposes an approach to improve the system arbitrage and reduce peak load by managing both the generation and load sides simultaneously. The peak load reduction is achieved using a load control program, while the arbitrage is enhanced by minimizing the operating and emission costs. The load management and minimization of operating cost are combined in an optimization approach in a multi-objective framework. The storage battery is utilized to contribute in the shaving of the peak load and reducing the operating and emission cost, where the battery aging is taken into account in the proposed model. The management of load sides is considered as decision variables in the approach. A mixed-integer quadratic program is employed to formulate the optimization approach. The proposed approach is applied to a smart low-voltage distribution grid. The results show that the management of both the demand and generation sides reduces the operating and emission costs and improves the load factor of the system.

With increasing demand for the intensive use of images, especially linked to online applications as well as the massive, continuous revolution of mobile phone technology, the need has emerged for efficient, standard image compression techniques that ensure simplicity and speed. These must be compatible with user needs, but also meet the challenges of improving compression techniques. Polynomial coding is one such techniques still under development, based on a modelling concept of deterministic and probabilistic coding bases. This paper introduces a new mathematical iterative polynomial model to represent both coding bases. The model proposes an efficient hybrid way where coefficients are represented as lossless while residuals are presented as a lossy but with minimum loss, which ensures effective performance in terms of compression ratios and quality. Results show that while the technique has some limitations, the proposed system achieves equivalent compression ratios as the standard JPEG technique, but with superior quality for the same compression ratio.

In this paper, a novel voltage-boosting switched-capacitor multilevel inverter (SCMLI) capable of producing 19 voltage levels using a combination of only 10 switches, 4 diodes, 2 capacitors, and 2 DC sources has been proposed. The main features of the proposed topology are 1) utilization of a very low number of devices, 2) very low Total Standing Voltage (TSV) equal to 6.55 and 3) self-balance property of the capacitors’ voltages. In order to provide the IGBTs of the circuit with the desired switching signals, the Nearest Level Control (NLC) method has been adopted. To clarify the benefits of the designed topology as to the total quantity of switches, DC sources, capacitors as well as the total standing voltage (TSV), and converter boosting, a thorough comparison has been carried out versus the recently published 19-level topologies. Also, for the purpose of performance evaluation and validation, the suggested topology has been tested against various loads through an experimental setup in the laboratory using TMS320F28379D DSP as the processor. The comparative, simulation, and experimental results all imply the superiority of the proposed topology against its predecessor counterparts.

In conventional analyzes of foundations failure, strengh parameters are assumed constant. However, during the failure, soil resistance exhibits maximum and residual amounts, and its strength decreases prematurely by increasing the plastic strain. In addition to change soil strengh parameters in the progressive mechanism, the non-uniform nature of the soil also causes spatial variations of these parameters. Therefore, geotechnical systems should be considered in terms of the uncertainty of soil parameters values, uncertainly using the concepts of statistics and probabilities. The purpose of this study is to investigate foundations in meshless method. In this article, radial point interpolation method (RPIM), a meshless method is proposed for simulation of soil foundation. Difficulties of methods related to mesh are solved by using this method. A code has been developed based on this method and some examples are solved for analyzing the code. In this research, a RPIM in combination with a random field was used to model the spatial variations of soil strengh properties and foundation bearing capacity analysis. For probabilistic analysis, random field is also used to determine the cohesion and the friction angle as well as the dilation angle based on their mean values and standard deviation. In order to investigate the application of the point interpolation method with randomized radial functions, a foundation with definite geometry has been analyzed deterministic and probabilistic and its safety factor has been investigated. Based on the analysis of the progressive failure modeling, it is concluded that the actual failure of the soil and the occurrence of continuous displacements occur simultaneously with the formation of a progressive mechanism of soil failure and the arrival of the slipping path to the ground. In the following, probabilistic distribution functions of the safety factor were determined by probabilistic analysis and the production of random fields, and then the statistical parameters are calculated.

The present study intends the development of an electric parking brake (EPB) for commercial vehicles (CVs). CVs with EPB applications are currently available in an entirely different set of issues than EPB applications on passenger cars, which are presently widely used. Safe parking requires much more focus with an order of magnitude, more thermal capacity, brake mass, and clamp pressures. In the first instance, heat loss from the brake disc was estimated. The investigations also allowed for precise prediction of radiative heat loss by defining surface emissivity. The parameters of air movement, convective heat transfer coefficients, and velocities were investigated, and validation was done with the CFD model. When the temperature dropped to 252 °C, the maximum estimated value of the Nusselt number was 72.25. Nusselt number pattern that looks identical over the arc surface yields 13.38 percent better results. Nu values at maximum temperature were calculated to be 80.5 and 82.6 at 251.8 °C. The “hconv” value was 4.1 percent lower than in the arc region, with the highest value at 400°C being 11.5 W/m2K. The present study adopted unique approach and obtained brake disc temperature and the coefficient of convective heat transfer on disc friction surfaces and hat regions. CFD modeling was done during the cooling phase to evaluate flow patterns and “hconv” fluctuation across the entire disc brake surface area. The mathematical modeling and adopted methodology for computing heat transfer coefficients for different disc regions have helped to better understand of a CV brake disc heat dissipation.

Friction Pendulum Bearing (FPB) has emerged as a popular solution for damage protection of bridges under seismic events. The study presents the probabilistic damage analysis for the isolated tub girder continuous bridge under the near and the far fault earthquakes using fragility analysis. The steel tub girder continuous bridge is considered with friction pendulum isolator as the seismic isolation mechanism. In order to represent the hysteretic behavior of friction pendulum isolators, a bilinear force-deformation model was used. Fragility curves are developed for various damage measures namely rotational ductility of pier and girder displacement with the peak ground acceleration (PGA) as an intensity measure (IM). Incremental dynamic analyses (IDA) were performed to develop the fragility curves and probabilistic damage model considering the four threshold damage states. The results suggest that in the case of low PGA level, the near fault earthquake leads to the high probability of exceedance in the case of isolated tub girder bridge. Damage model for piers and girder were developed to correlate component responses levels to overall bridge deterioration states. Finally, recommendations for the bridge developers in the stage of the early bridge seismic isolation design utilizing friction pendulum isolators are discussed.

Cash transfer from the central treasury to the bank branches and automated teller machines (ATMs) all over the city is one of the vital processes in a banking system. There are multiple factors (e.g., location of the treasury, transportation fleet, geographic distribution of the branches and ATMs, the demand for cash, customer satisfaction, and traffic that influence the efficiency of the cash transfer). Moreover, environmental issues, and in particular the issue of greenhouse gas (GHG) emissions are given weight. In this paper, a new mathematical model for a location-routing problem with transport vehicles in the banking system is developed based on urban traffic in such a way that three objectives of decreasing greenhouse emissions, reducing location and routing costs, and increasing customer satisfaction are taken into consideration simultaneously. Furthermore, a new multi-objective genetic algorithm hybridized with a PROMETHEE method, namely the multi-objective genetic-PROMETHEE algorithm (MOGPA), is developed to tackle the proposed model. The efficiency of the proposed algorithm is examined by comparing it with the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective imperialist competitive algorithm (MOICA) for the real-case issue of Saman Bank. Because management assumptions are considered in the preference functions of the proposed algorithm, the results show that the solutions of the proposed algorithm are more efficient and closer to reality.

In this paper, two wideband 10 dB backward directional couplers based on artificial perforated substrates over the frequency range of 25-35 GHz and 32-38 GHz are developed. An analytical method is proposed to design the coupler geometrical parameters. The theoretical modeling is established based on the coupled version of the transmission line (TL) theory using the extended version of the ABCD matrix for four ports microwave network. It is shown that using the proposed method, all required parameters of the directional coupler are determined using the per-unit-length of the applied lines. The geometrical parameters of primary designed couplers are optimized using the particle swarm optimization (PSO) procedure to improve the performance of couplers. The designed couplers are also simulated using High Frequency Structure Simulator (HFSS) software. Moreover, sensitivity analysis is carried out to investigate the effect of fabrication imperfections of the proposed couplers. The obtained results show that the simulated results agree well with the theoretical ones and a low insertion loss (IL) with high return loss is obtained over a wide frequency range bandwidth.

A recommender system is an integral part of any e-commerce site. Shilling attacks are among essential challenges in recommender systems, which use the creation of fake profiles in the system and biased rating of items, causing the accuracy to decrease and the correct performance of the recommender system in providing recommendations to users. The target of attackers is to change the rank of content or items corresponded to their interests. Shilling attacks are a threat to the credibility of recommender systems. Therefore, detecting shilling attacks it necessary to in recommender systems to maintain their fairness and validity. Appropriate algorithms and methods have been so far presented to detect shilling attacks. However, some of these methods either examine the rating matrix from a single point of view or use low-order interactions or high-order interactions. This study aimed to propose a mechanism using users' rating matrix, rating time, and social network analysis output of users' profiles by Gaussian-Rough neural network to simultaneously use low-order and high-order interactions to detect shilling attacks. Finally, several experiments were conducted with three models: mean attack, random attack, and bandwagon attack, and compared with PCA, Semi, BAY, and XGB methods using precision, recall, and F1-Measure. The results indicated that the proposed method is more effective than the comparison methods regarding attack detection and overall detection, which proves the effectiveness of the proposed method.

Gender is an important aspect of a person's identity. In many applications, gender identification is useful for personalizing services and recommendations. On the other hand, many people today spend a lot of time on their mobile phones. Studies have shown that the way users interact with mobile phones is influenced by their gender. But the existing methods for identify the gender of mobile phone users are either not accurate enough or require sensors and specific user activities. In this paper, for the first time, the internet usage patterns are used to identify the gender of mobile phone users. To this end, the interaction data, and specially the internet usage patterns of a random sample of people are automatically recorded by an application installed on their mobile phones. Then, the gender identification is modeled using different machine learning classification methods. The evaluations showed that the internet features play an important role in recognizing the users gender. The linear support vector machine was the superior classifier with the accuracy of 85% and F-measure of 85%.

This study deals with the interaction of dynamic cellular manufacturing (DCM) and hierarchical production planning (HPP) problems with stochastic demands for the first time. Each of these alone does not consider the system factors such as stochastic demands and dynamic cellular formation separately. Accordingly, to fill this gap, this paper presents an integrated optimized model incorporating the most comprehensive design of DCM systems and HPP problems with stochastic demands. This model helps administrators get the optimal size and number of cells to decrease costs. Also, the model applies the principles of HPP to reduce the complexity of the integrated model. Since demands are uncertain, they need to be accurately predicted. Therefore, this study aims to combine the most precise decision variables with the most realistic conditions. A case study from an agriculture mechanization and industrial development company shows that an integrated model can provide managers with a feasible solution to meet demand, reconfigure cells in each period, provide new machinery to increase the required production capacity, and adjust production capacity to help them cope with demand fluctuations. A sensitivity analysis was performed and the results show that increase in forecast error and inter-cell move cost cause less significant changes in total cost but the total cost is sensitive to intra-cell move cost, available time capacities and cell quantity. It is also shown that the total cost was very sensitive to available regular time and available over time and the system should try to increase the time capacity.

A conventional stirrup is widely used in all concrete beams as shear reinforcement to prevent shear failure that happens suddenly and unexpectedly without previous warning. It is a great challenge to figure out another type of stirrup and establish a new formula to calculate the deflection. This article offers an experimental study that predicts a novel formula for calculating deflection in concrete beams reinforced with shear steel plates as a stirrup. The experimental work was established and consists of 16 wide reinforced concrete beams with 216x560x1800 mm dimensions. Instead of the conventional reinforcing stirrups, steel plates with 3.0, 4.0, and 5.0 mm thickness in longitudinal and transverse dimensions and for one-half of the samples, recycled PVC round bubbles were used as the variables explored in this study. In addition, the variables include an examination of the opening form of shear steel plates with varying distances between them. For calculating the deflection of wide beams, a new formula for the effective moment of inertia is proposed, and it yields excellent agreement for several investigations, with a coefficient of variation of 5.48 percent. The formulae for calculating the maximum deflection are established using ACI 318M-14 and EC 2.

The rhizome of ginger (Zingiber officinale Roscoe), usually known as ginger, is one of the most popular species used in food and traditional medicine. Ginger is rich of various hydrophobic and hydrophilic active compounds with diverse properties. Having fresh aroma, pungent taste, and various health benefits, along with being readily available and inexpensive are the advantages of ginger rhizome. In addition to herbal medicine perspective along with utilization as flavoring agent in foods and beverages, ginger rhizome demonstrated potential application in different fields. In this review, the current evidence of main potential applications of ginger, including its usage in preservation of food and food packaging systems, tenderization of meat product, medical properties, acting as an inhibitor of metal corrosion, biodiesel preservation from oxidation, and its role in the synthesis of metal nanoparticles were discussed. Overall, this review provides valuable information about ginger rhizome as a plant-based material, beyond its role in herbal medicine and imparting flavor to our food.

Piles transfer structural loads to the hard layers of the soil or rock; thus, any damage to the pile foundations could have irreparable consequences. A surface blast can create a ground shock that transmits the blast energy along the surface and at depths. Explosion research necessitates technical design to mitigate the adverse effects on nearby structures and facilities. The blast impact range and the safe distance at which the pile will avoid structural damage are two critical parameters for the design of a pile under blast loading. Therefore, this study used the coupled Eulerian-Lagrangian method to determine the blast impact range and safe distance for reinforced concrete piles (RC piles) subjected to blast loading. The results for clayey and sandy soils revealed that an increase in the explosive depth had no significant effect on the safe distance, despite a decrease in the compressive and tensile damage to the pile. Increasing the mass and depth of the blast decreased the ultimate compressive bearing capacity of the pile and increased the blast impact range. Sandy soil performed better than clayey soil against blast loading. The findings of this study can be applied to various projects, including critical structures near gas transmission lines or vulnerable to terrorist attacks.

Image restoration is the operation of obtaining a high-quality image from a corrupt/noisy image and is widely used in many applications such as Magnetic Resonance Imaging (MRI) and fingerprint identification. This paper proposes an image restoration model based on projection onto convex sets (POCS) and particle swarm optimization (PSO). For this task, a number of convex sets are used as constraints and images are projected to these sets iteratively to reach restored image. Since relaxation parameter in POCS has a significant effect on restoration results, PSO is developed to find the best value for this parameter to be used in restoration process. The proposed scheme for image restoration is evaluated on three popular images with 4 configurations of noise, compared with 5 competitive restoration models. Results demonstrate that the proposed method outperforms other models in 32 out of 48 cases in images with different noise configurations with respect to relative error, ISNR, MAE and MSE measures.

The separation of carbon dioxide is essential for the environment. Using membranes to separate this gas is economical, but the weakness in permeability and mechanical strength has prevented their commercialization. Robeson proved that permeability and selectivity have the opposite relationship and provided an upper limit for pairs of gases. Worth to be mentioned that any membrane placed above this limit could be commercialized. Scientists proposed mixed matrix membranes to overcome this problem. These membranes contain two phases, polymer, and inorganic. This research focuused on membrane technology and aimed to prepare a membrane that has a good performance for CO2 separation and at the same time its cost is economical, so by adding a reasonable price zeolite available in the market named 4A to the Pebax1657 polymer and changing the operating conditions of the process, permeability and Selectivity was measured. Pebax polymer and 4A zeolite were selected as respectively the polymer and mineral phases for membrane fabrication. The fabricated membranes were evaluated by XRD, FT-IR, FE-SEM, BET, EDAX, TGA/DSC, and mechanical strength tests. Finally, the selectivity of CO2 compared to N2, O2, and CH4 improved by 53, 67, and 75%, respectively, and obtained a good position on the Robeson diagram.

Discussion of distribution and distribution network design and planning, including location, pricing, optimal selection of distribution channels, as well as marketing decisions, is of great importance in the supply chain. Due to the changes and uncertainty of market demand, the design and planning of the distribution network and static sale have encountered many problems in practice. This article presents a nonlinear mathematical programming model for locating, inventory control, and marketing of manufactured products for a multi-activity organization that includes manufacturing, distribution, retail, and wholesale units. The model includes the localization of distribution centers and the corresponding inventory management, taking into account marketing-related parameters such as multi-channel pricing. A centralized decision support is developed to select the appropriate sales channel, to determine the quantity of products sold in each channel and the discounts granted for each specific channel using real data. In this model, the goal is to maximize profit while increasing customer value by considering competitors' price and choosing the best channel to deliver the product to the customer. Finally, for a small problem instance, the proposed model was solved using the GAMS 28.2.0 x64 optimization software package. Validation study and sensitivity analysis are performed to imply the effectiveness of the formulated mathematical model.