In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

The extraction of iron from aqueous chloride media in presence of aluminum was studied at different kinds of extractants(cyclohexanone, tributyl phosphate, diethyl ketone), different values of normality (pH of the feed solution), agitation time, agitation speed, operating temperature, phase ratio (O/A), iron concentration in the feed, and extractant concentration]. The stripping of iron from organic solutions was also studied at different values of normality (pH of the strip solution) and phase ratio (A/O). Atomic absorption spectrophotometer was used to measure the concentration of iron and aluminum in the aqueous phase throughout the experiments.The best values of extraction coefficient and stripping coefficient are obtained under the

Diverting river flow during construction of a main dam involves the construction of cofferdams, and tunnels, channels or other temporary passages. Diversion channels are commonly used in wide valleys where the high flow makes tunnels or culverts uneconomic. The diversion works must form part of the overall project design since it will have a major impact on its cost, as well as on the design, construction program and overall cost of the permanent works. Construction costs contain of excavation, lining of the channel, and construction of upstream and downstream cofferdams. The optimization model was applied to obtain optimalchannel cross section, height of upstream cofferdam, and height of downstream cofferdamwith minimum construction cost

This work concerned on nanocrystalline NiAl2O4 and ZnAl2O4 having spinel structure prepared by Sol–gel technique. The structural and characterization properties for the obtained samples were examined using different measurements such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), finally, Field emission scanning electron microscope (FESEM).The Spinel-type for two prepared compound (NiAl2O4) and (ZnAl2O4) at different calcination temperature examined by XRD. Williamson-Hall Methods used to estimate crystallite size, Average distribution crystallite size of two compound were, 34.2 nm for NiAl2O4 and32.6 for ZnAl2O4, the increase in crystallite size affecting by increasing in calcination temperature for both comp

In this study, aluminum nanoparticles (Al NPs) were prepared using explosive strips method in double-distilled deionized water (DDDW), where the effect of five different currents (25, 50, 75, 100 and 125 A) on particle size and distribution was studied. Also, the explosive strips method was used to decorate zinc oxide particles with Al particles, where Al particles were prepared in suspended from zinc oxide with DDDW. Transmission electron microscopy (TEM), UV-visible absorption spectroscopy, and x-ray diffraction are used to characterize the nanoparticles. XRD pattern were examined for three samples of aluminum particles and DDDW prepared with three current values (25, 75 and 125 A) and three samples prepared with the same currents for zin

        In this study, Zinc oxide nanostructures were synthesized via a hydrothermal method by using zinc nitrate hexahydrate and sodium hydroxide as a precursor. Three different annealing temperatures were used to study their effect on ZnO NSs properties. The synthesized nanostructure was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Atomic force microscope (AFM), and Fourier Transform Infrared Spectroscopy (FTIR). Their optical properties were studied by using UV -visible spectroscopy. The XRD analysis confirms that all ZnO nanostructures have the hexagonal wurtzite structure with average crystallite size within the range of (30.59 - 34