Journal of Brilliant Engineering (BEN)

Mohammad Hossein Chamani

Face recognition is used as one of the most successful biometric methods due to the availability of advanced resources such as faster processors and higher memory and providing intelligent methods based on the power of these resources. Nevertheless, there are still many challenges in this area. The face plays an important role in the transmission of emotions and carries the characteristics hidden in it, the identity of individuals. Face recognition has been added to some control devices, security, welfare, criminal identification, and many other areas, which is the main motivation for research in this field. In this paper, the DCSFR method is presented to pay attention to the main features of the face such as eyes, lips, mouth, and nose, which is the main novelty of this work, to get higher accuracy or speed than the previously existing methods. In this approach, instead of using general information in face recognition, facial components such as eyes, nose, mouth are separated into another image, and face classification operations (deep learning by convolution neural network) are performed on separated components. The results show that the computational cost with the proposed method is reduced by about 70%. Also, it can be achieved that CNN does not perform as well as the complete picture of the disassembled components.

https://doi.org/10.36937/ben.2022.4563

Nwzad abdulla

The behavior of slender columns under axial load is more critical than short columns due to the elastic instability. In the structural design of composite members, determining the column capacity under axial load is essential when considering the length effect. Composite members like concrete-filled uPVC tubes (uPVCC) capture attention when ductility is the primary objective due to its significant elongation at failure 42% compared to less than three percent for super-advanced materials such as fiber-reinforced polymers (FRP). In the present study, Six short and slender concrete-filled uPVC specimens (uPVCC) were tested under axial compression load. For comparison purpose, a similar number of specimens were tested without the plastic tube. Test results show that the plastic tube offers considerable confinement to the concrete and enhances the deformation capacity of the composite member by changing the failure mode from brittle to ductile. The columns without the plastic tube were more influenced by the slenderness ratio, undergoing 43-46% reduction in strength compared with 17-21% for the uPVCC. In order to evaluate the strength of the specimens a database of 128 data, short and slender plain and uPVCC specimens, was assembled and combined with present twelve test results were employed to develop simple equations for predicting the capacity of plain and uPVCC columns. Another thirty-two test data from published literature were used to check the validity of the strength equations. Based on statistical indexes, the derived equations showed good performance with acceptable accuracy in predicting the strength of slender columns with and without the uPVC tube.

https://doi.org/10.36937/ben.2022.4593

VAHID JAFARPOUR Maryam Abasi

One of the most advanced methods of metal shaping techniques is hydroforming, which uses fluid at extreme pressure to deform metal sheets that cannot be fabricated by conventional approaches. This method is perfect for the production of lightweight, seamless, continuous, mesh-shaped, high-quality, and important high-strength automotive and aircraft components. When it comes to pipe hydroforming, the ductility of the metal pipe has a direct impact on the forming load route. (Internal deformation pressure and axial feeding). This research focuses on the impact of operational circumstances. (i.e., the impact of ultimate longitudinal feeding and forming pressure) on the whole procedure and keeps the other factors fixed. The control algorithms were designed to control longitudinal feeding and pressure over the shaping process modeling. Most of the pipe hydroforming paths are created during the multi-stage procedure for loading. Hence the deformation limit strains obtained in the middle of the deformation procedure depend on the route. The present work optimizes the loading path angles in the pipe deformation procedure using an intelligent algorithm for fuzzy logic control. This prevents the tube from breaking or rupturing during the forming process due to high strains. The mentioned control algorithm and fuzzy adaptive neural system (ANSYS) were used to simulate the hydroforming procedure.

https://doi.org/10.36937/ben.2022.4683

Yıldırım ÖZÜPAK

Direct Current (DC) motors are widely used in industrial applications. The limited use of brushed models in some areas has brought Brushless Direct Current Motors (BLDC) to the fore. The constant need for maintenance of brushed type motors creates a disadvantage in variable conditions and in areas that are used continuously. For this reason, brushless DC motors have a wide range of uses. Brushless DC motors stand out with their high-performance values. Brushless DC motors with outer rotor type are used in applications that require high torque and inertia. The fact that electrical machines have moving parts and the computational complexity created by these parts have led electrical machine designers to alternative ways such as software and simulation programs where the results can be predicted. In this paper, a Brusgless Permanent Magnet Direct Current motor (BLPMDC) was designed and analyzed. The obtained speed, efficiency, torque, and air gap flux distributions were examined and the results were compared with literature for the motor type. In this study, applications were made to examine the effects of design parameters such as rotor structure, rotor position, magnet arrangement and materials used in the structures on the efficiency and output power of the motor. Efficiency-speed and power-speed values were obtained for different structures and features of the engine. The results obtained are compared with each other and presented in the article in the form of graphs and tables.

https://doi.org/10.36937/ben.2022.4658

Blessing Olamide Taiwo

Blasting operation involves the use of a specific explosive quantity, detonated to fragment insitu and oversize rock block for particle reduction. Rock fragmentation size distribution has a direct influence on the proposed costs of mining one ton of the ore and the cost of run-off-mine processing. The focus of this study is on investigating the effect of charge load ratio and blast design parameters such as stiffness ratio, maximum instantaneous charge, and specific charge on rock fragmentation particle size distribution in dolomite quarry located at Akoko Edo state, South-west Nigeria. The 50% passing sizes (X50, m), 80% passing size (X80, m), and characteristic size (Xc, m) of blast results were determined using Wipware software. It was observed that the optimum mean size (X50, m), 80% passing fragment size (X80, m), and characteristic size (Xc, m) of rock depends strongly on the explosive bottom and column loading ratio, stiffness ratio, and specific charge. The regression analysis result reveals that the explosive specific charge and stiffness ratio influence the fragment size distribution with a negative correlation relationship, and the explosive bottom and column loading ratio has a positive correlation relationship with the blast fragmentation. Multivariate Regression (MVR) models were developed for the prediction of blast fragmentation sizes (X80, X50, and Xc) with R2 values of 0.76, 0.52, and 0.63 respectively. Based on the low correlation value obtained from the developed models, the proposed multivariate Regression (MVR) models are less suitable for the prediction of blast fragmentation particle size distribution.

https://doi.org/10.36937/ben.2022.4660