The present investigation deals with experimental study of three-phase direct-contact heat exchanger, for water-Freon R11 system, where water is the continuous phase (liquid) and Freon R11 (liquid-gas) is the dispersed phase. The test section consisted of a cylindrical Perspex column with inner diameter 8cm and 1.2m long, in which, water was to be confined. Liquid Freon R11 drops were injected into the hot water filled column, through a special design of distributors at the bottom of the column. The liquid Freon R11 drops rose on their way up and evaporated into two-phase bubbles at atmospheric pressure. The study was devoted to express the effect of process variables such as c

The ceramic composite with different proportions of clay and silica was prepared with a grain size of 70 μm and the weight percentage was selected for four groups (clayx silica100-x) were x q15, 25, 30 and 50. In this manuscript, for each pressured sample, a sintering procedure was carried out for 3 hours under static air and at various sintering temperatures (1000, 1100, 1200, 1400)°C. After sintering, the density, porosity, water absorption, compression strength and thermal conductivity were measured. The best results were obtained using a mixture of 15% clay and 85% silica which were sintering at 1400°C for three hours under air.

Titanium alloy surface properties have an essential role in the interaction of dental implants with bone, and alteration of the surface of the implant could improve osseointegration. This study was designed to investigate the effect of different heat treatment temperatures on titanium alloy surface properties for dental implants. The effect of different temperatures of heat treatment (750°C, 850°C, 950°C and 1050°C) were investigated on the surface topography, surface chemistry, titanium oxide layer thickness, blood contact angle, & blood drop diameter of titanium alloy. The disks were prepared from titanium alloy (Ti-6Al-4V) and the samples were divided into five groups depending on the different temperatures of heat treatment. The hea

The concept of entransy dissipation was determined for new type of heat exchanger (shell and double concentric tubes heat exchanger). Three parameters, hot oil flow rate, temperature of inlet hot oil and pressure drop of system were investigated with this concept (entransy dissipation). The results showed that the value of entransy dissipation of oil and of system which represents the summation of entransy dissipation of both oil and water increased with increasing the flow rate of hot oil and these values were larger when cold water flow rate was doubled. Also they were increased with increasing the hot oil inlet temperature at a certain flow rate of hot oil. Furthermore, the pressure drops for hot oil in both shell side and inner tubes

In this paper a comparison of the experimental of evacuated tube solar water heater systems with and without mirror flat reflector. The aim of using the reflector to improve thermal efficiency, and the data gathered which are (temperature, solar irradiation and time) for three days were compared. the results from compared data the temperature lower increase in evacuated tube solar water heater system without reflector than the temperature increase in evacuated tube solar water heater system with reflector .The results show (53, 39, 35) % for three days respectively that the evacuated tube solar water heater system with reflector has higher thermal efficiencies than the results (47, 28, 30) % for three days respectively thermal efficiencies

In this paper, The transfer function model in the time series was estimated using different methods, including parametric Represented by the method of the Conditional Likelihood Function, as well as the use of abilities nonparametric are in two methods  local linear regression and cubic smoothing spline method, This research aims to compare those capabilities with the nonlinear transfer function model by using the style of simulation and the study of two models as output variable and one model as input variable in addition t

Abstract: In the current research the absorption and fluorescence spectrum of Coumarin (334) and Rhodamine (590) in ethanol solvent at different concentration (10-3, 10-4, 10-5) M had been studied. The absorption intensity of these dyes increases as the Concentration increase in addition to that the spectrum was shifted towards the longer wavelength (red shift). The energy transfer process has been investigated after achievement this condition. The fluorescence peak intensity of donor molecule was decrease and its bandwidth will increases on the contrary of the acceptor molecule its intensity increase gradually and its bandwidth decreases as the acceptor concentration increase.

In the current research the absorption and fluorescence spectrum
of Coumarin (334) and Rhodamine (590) in ethanol solvent at
different concentration (10-3, 10-4, 10-5) M had been studied. The
absorption intensity of these dyes increases as the Concentration
increase in addition to that the spectrum was shifted towards the
longer wavelength (red shift). The energy transfer process has been
investigated after achievement this condition. The fluorescence peak
intensity of donor molecule was decrease and its bandwidth will
increases on the contrary of the acceptor molecule its intensity
increase gradually and its bandwidth decreases as the acceptor
concentration increase.

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin