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

As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

The main objective of this research is to find the coefficient of permeability (k) of the soil and especially clayey soil by finding the degree of consolidation (rate of consolidation). New modify procedure is proposed by using the odometer (consolidation) device. The ordinary conventional permeability test usually takes a long time by preparing and by testing and this could cause some problems especially if there is a need to do a large number of this test and there were a limited number of technicians and/or apparatus. From this point of view the importance of this research is clear, since the modified procedure will require a time of 25 minute only. Derivation made to produce an equation which could be used to fined the permeabi

This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

New thermally stable aromatic poly(amide-imide)s ( PAI1- PAI4 ) were synthesized from direct polycondensation reaction of Terephthalic acid and Phthalic acid with two new different diamine monomers derivatives of 1,2,4,5-tetracarboxilic benzene dianhydride as a second diacides in a medium consisting of triphenyl phosphite (TPP) in N-methyl-2pyrrolidone (NMP) / pyridine solution containing dissolved calcium chloride CaCl2. The polymerization reaction produced a series of novel poly(amide-imide) in high yield. The new monomers were characterized by FTIR, 1H-NMR spectroscopy. The resulting polymers were typically characterized by means of FT-IR, 1H-NMR spectroscopy, and solubility tests. Thermal properties of the poly(amide-imide)s were als

New complexes of Cu (ll), Ni (ll), Co (ll), and Zn (ll) wi th 2-amino-5-p-Fiouro Phenyl 1, 3, 4-Thiadiazole have been synthesized. The products were isolated, studied and characterized by physical measurements, ie,(Ff-IR), UV-Vis and the melting points were determined. The new Schiff base (L) has been used to prepare some complexes. The prepared complexes were identified and their structural geometry were suggested

The introduction of concrete damage plasticity material models has significantly improved the accuracy with which the concrete structural elements can be predicted in terms of their structural response. Research into this method's accuracy in analyzing complex concrete forms has been limited. A damage model combined with a plasticity model, based on continuum damage mechanics, is recommended for effectively predicting and simulating concrete behaviour. The damage parameters, such as compressive and tensile damages, can be defined to simulate concrete behavior in a damaged-plasticity model accurately. This research aims to propose an analytical model for assessing concrete compressive damage based on stiffness deterioration. The prop

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

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