This paper studies the influence of temperature on the corrosion rate of coated AA6111 aluminum alloy used in vehicle bodies under static and vibration states. The vibration test system was collected laboratory and used for testing of five different types of paints (EASI, Numix, Lesonal, DENSO and Polaron paints) in the 5 % NaCl solution using immersion test method. Lesonal paint provided the best corrosion protection, while DENSO paints show large values of corrosion rate, other coatings exhibit moderate values. Model of paints corrosion was developed to characterize the corrosion processes occur at the surfaces. It is found that corrosion rate obtained at vibration cases is larger than static cases and vibration effect

Photonic Crystal Fiber Fabry–Perot Interferometers (FPI) based on Surface Plasmon Resonance (SPR) was investigated in this paper in order to detect changes in photonic crystal fiber sensitivity with increasing temperature. FPI is composed of a PCF (ESM-12) solid core spliced with a single-mode fiber (SMF) on one side and a 40nm thick gold Nano film on the other. In order to obtain the SPR curve, the end of PCF can be spliced with the side of SMF before covering the gold film on the PCF. SPR results are included in the suggested sensor, based on the conclusions of the investigations. Resolution (R) is 0.0871, Signal-to-Noise Ratio (SNR) is 0.1867, a figure of merit (FOM) is 0.0069, and sensitivity (S) is 1.1481 . This sensor proposed is s

This work aimed to use effective, low-cost, available, and natural adsorbents like eggshells for removal of  hazardous organic dye result from widely number of  industries and study the influence of different eggshell particle size (75, 150) Mm.  The adsorbent was characterized by SEM, EDX, BET and FTIR . The initial pH of dye solutions  varying from 4 to 10 , the initial concentrations of methyl violet (MV) 2B range (20-80) mg/L, dosage range (0.5-10) g, contact time (30-180) min, and particles size of the adsorbent (75, 150) Mm were selected to be studied. Two adsorption isotherms models have been used to fit the experimental data. Langmuir and Freunlich models were found to more represent the experiments with high

Improving the permanent deformation resistance of asphalt pavements is a vital challenge. Nanomaterials have emerged as promising additives due to their ability to enhance the binder stiffness and elasticity. This study evaluated the influence of five nanomaterials, namely Nano-Silica (NS), Nano-Alumina (NA), Nano-Zinc (NZ), Nano-Titanium (NT), and Carbon Nanotubes (CNTs) incorporated into a base asphalt binder at varying dosages, with up to 10% for NS, NA, and NT, and up to 5% for NZ and CNT. Fifteen modified binders were assessed using the Multiple Stress Creep Recovery (MSCR) test to obtain non-recoverable creep compliance (Jnr), while the corresponding hot mix asphalt samples underwent repeated load testing and rut depth predict

Hypoxic training, which in turn is one of the methods adopted in sports training methods, especially in activities that depend on the aerobic system in its performance, which includes training with a lack of oxygen by reducing its molecular pressure, since this method targets functional organs and works temporary responses during training and permanent responses After training as an adaptation to these devices as a result of training in this way, the study aimed to identify the effect of hypoxic exercises using the training mask and the extent of the change in some biochemical indicators, in addition to that to identify the effect of these exercises on the indicator of energy expenditure and )VMA) and the achievement of the effectiveness of

Abstract

Much attention has been paid for the use of robot arm in various applications. Therefore, the optimal path finding has a significant role to upgrade and guide the arm movement. The essential function of path planning is to create a path that satisfies the aims of motion including, averting obstacles collision, reducing time interval, decreasing the path traveling cost and satisfying the kinematics constraints. In this paper, the free Cartesian space map of 2-DOF arm is constructed to attain the joints variable at each point without collision. The D*algorithm and Euclidean distance are applied to obtain the exact and estimated distances to the goal respectively. The modified Particle Swarm Optimization al

The current study aims at using non-hatchable artemia eggs of local origin and making use of these eggs by decapsulating and presenting them as food for the larvae of the Cyprinus carpio as a source of animal protein with high nutritional value instead of throwing them away. The results showed that the second parameter (A2) was highly significant at the level (P≤0.05) in the growth rates of the larvae that were fed on decapsulated artemia eggs alone, and it was better than the two control parameters (A1), in which the larvae were fed with feed designated for Cyprinus carpio fish. It also outperformed the third parameter (A3), in which the feed was mixed with artemia eggs with 50% decapsulation, which also outperformed the control paramete

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye