This paper has investigated experimentally the dynamic buckling behavior of AISI 303 stainless steel Aluminized and as received long columns. These columns, hot-dip aluminized and as received, are tested under dynamic buckling, 22 specimens, without aluminizing (type 1), and 50 specimens, with hot-dip aluminizing at different aluminizing conditions of dipping temperature and dipping time (type 2), are tested under dynamic compression loading and under dynamic combined loading (compression and bending) by using a rotating buckling test machine. The experimental results are compared with Perry Robertson interaction formula that used for long columns. Greenhill formula is used to get a mathematical model that descripts the buckling behavior

In the present work experiments were conducted to study  the effect of solid loading (1,5 and 9 vol.%) on the enhancement of carbon dioxide absorption in bubble column at various volumetric gas flow rate (0.75, 1 and 1.5 m³/h) and absorbent concentration (caustic soda)( 0.1,0.5 and 1 M  ). Activated carbon and alumina oxide (Al₂O₃) are used as solid particles. The Danckwerts method was used to calculate interfacial area and individual mass transfer coefficients during absorption of carbon dioxide in a bubble column. The results show that the absorption rate was increased with increasing volumetric gas flow rate, caustic soda concentration and solid loading. Mass transfer coefficient and interfac

Self is the main factor of personality and the acceptance of others where each of them are connecting and plays an important role in emotional maturation. The researches affirmed that the leading behavior depending on good human relations between the employers and the employees will enhance their goals and the goals of the institution at the same time . This study aims to measure the emotional maturation among the leactures of the university according to sex variable and identify the correlation between emotional maturation and the level of leading behavior among the lecturers of the university. The sample consists of two samples where the lst is to build the measwe consisting of (200)males and famales lecturers and the 2nd which is the

Fe2O3/ MgO composites with various ratios (90/10,80/20,70/30,60/40 and 50/50 %wt.) were synthesized. Their structure was determined using the X-ray diffractometer. The observed X-Ray patterns showed that the prepared composites were polycrystalline with rhombohedral Hematite (α-Fe2O3) whereas the preferred planes for crystal growth are (104) and (110).The dielectric properties of the Fe2O3/ MgO, with various ratios, were studied as function of frequency over the range (50Hz – 1MHz). The conductivity as function to frequency σa.c(ω) obey the power law relation σa.c(ω) =Aωs where the factor s was found to be in the range 0.329-0.491. The dielectric constant is increasing; but not in a regular way, with the increasing MgO content. The

Many problems were encountered during the drilling operations in Zubair oilfield. Stuckpipe, wellbore instability, breakouts and washouts, which increased the critical limits problems, were observed in many wells in this field, therefore an extra non-productive time added to the total drilling time, which will lead to an extra cost spent. A 1D Mechanical Earth Model (1D MEM) was built to suggest many solutions to such types of problems. An overpressured zone is noticed and an alternative mud weigh window is predicted depending on the results of the 1D MEM. Results of this study are diagnosed and wellbore instability problems are predicted in an efficient way using the 1D MEM. Suitable alternative solutions are presented

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The nonlinear refractive (NLR) index and third order susceptibility (X3) of carbon quantum dots (CQDs) have been studied using two laser wavelengths (473 and 532 nm). The z-scan technique was used to examine the nonlinearity. Results showed that all concentrations have negative NLR indices in the order of 10−10 cm2/W at two laser wavelengths. Moreover, the nonlinearity of CQDs was improved by increasing the concentration of CQDs. The highest value of third order susceptibility was found to be 3.32*10−8 (esu) for CQDs with a concentration of 70 mA at 473 nm wavelength.