Cold plasma is a relatively low temperature gas, so this feature enables us to use cold plasma to treat thermally sensitive materials including polymers and biologic tissues. In this research, the non-thermal plasma system is designed with diameter (3 mm, 10 mm) Argon at atmospheric pressure as well as to be suitable for use in medical and biotechnological applications.
The thermal description of this system was studied and we observed the effect of the diameter of the plasma needle on the plasma, when the plasma needle slot is increased the plasma temperature decrease, as well as the effect of the voltages applied to the temperature of the plasma, where the temperature increasing with increasing the applied voltage . Results showed t

This study aimed to investigate the influence of longitudinal steel embedded tubes located at the center of the column cross-section on the behavior of reinforced concrete (RC) columns. The experimental program consisted of 8 testing pin-ended square sectional columns of 150×150 mm, having a total height of 1400 mm, subjected to eccentric load. The considered variables were the steel square tube sizes of 25, 51 and 68 mm side dimensions and the load eccentricity (50 and 150) mm. RC columns were concealed steel tubes with hollow ratios of 3%, 12% and 20% depending on tube sizes used. The experimental results indicated an improvement in the overall behavior of eccentric columns when steel embedded tubes are used. The maximum gain in

In this work, the behavior of reinforced concrete columns under biaxial bending is studied. This work aims at studying the strengthening of columns by using carbon fiber reinforced polymer (CFRP). The experimental work includes investigation of eight reinforced concrete columns (150*150*500mm) tested under several load conditions. Variables considered in the test program include; effect of eccentricity and effect of longitudinal reinforcement (Ø12mm or Ø6mm). Test results are discussed based on load – lateral deflection behavior, load –longitudinal deflection behavior, ultimate load and failure modes. The CFRP reinforcement permits
a complete change in the failure mode of the columns .The effect of longitudinal reinforcement in

The response of floating stone columns of different lengths to diameter ratio (L/D = 0, 2, 4, 6, 8, and 10) ratios exposed to earthquake excitations is well modeled in this paper. Such stone column behavior is essential in the case of lateral displacement under an earthquake through the soft clay soil. ABAQUS software was used to simulate the behavior of stone columns in soft clayey soil using an axisymmetric finite element model. The behavior of stone column material has been modeled with a Drucker-Prager model. The soft soil material was modeled by the Mohr-Coulomb failure criterion assuming an elastic-perfectly plastic behavior. The floating stone columns were subjected to the El Centro earthquake, which had a magnitude of 7.1 an

This paper studies the behavior of axially loaded RC columns which are confined with carbon fiber reinforced polymers’ sheet (CFRP) and steel jackets (SJ). The study is based on twelve axially loaded RC columns tested up to failure. It is divided into three schemes based on its strengthening type; each scheme has four columns. The main parameters in this study were the compressive strength of the concrete and steel reinforcement ratio. Furthermore, the results of the experimental test showed a substantial enhancement in the column's load-carrying capacity. When compared to the original columns, the CFRP sheet had a significant effect on improving the ductility of the column by increasing the axial deformation by about 59.2 to 95.7

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi