Abstract

This study investigates the mechanical compression properties of tin-lead and lead-free alloy spherical balls, using more than 500 samples to identify statistical variability in the properties in each alloy. Isothermal aging was done to study and compare the aging effect on the microstructure and properties.

The results showed significant elastic and plastic anisotropy of tin phase in lead-free tin based solder and that was compared with simulation using a Crystal Plasticity Finite Element (CPEF) method that has the anisotropy of Sn installed. The results and experiments were in good agreement, indicating the range of values expected with anisotropic properties.

Keywords<

Pulsed laser deposition (PLD) technique was applied to prepared Chromium oxide (Cr₂O₃) nanostructure doped with Titanium oxide (TiO₂) thin films at different concentration ratios 3,5,7 and 9 wt % of TiO₂. The effect of TiO₂ dopant on the average size of crystallite of the synthesized nanostructures was examined by X-ray diffraction. The morphological properties were discussed using atomic force microscopy(AFM). Observed optical band gap value ranged from 2.68 eV to 2.55 eV by ultraviolet visible(UV-Vis.) absorption spectroscopy with longer wave length shifted  in comparison with that of the bulk Cr₂O₃ ~3eV. This indicated that the synthesized samples a

The increasing population growth resulting in the tremendous increase in consumption of fuels, energy, and petrochemical products and coupled with the depletion in conventional crude oil reserves and production make it imperative for Nigeria to explore her bitumen reserves so as to meet her energy and petrochemicals needs. Samples of Agbabu bitumen were subjected to thermal cracking in a tubular steel reactor operated at 10 bar pressure to investigate the effect of temperature on the cracking reaction. The gas produced was analyzed in a Gas Chromatograph while the liquid products were subjected to Gas Chromatography-Mass Spectrometry (GC-MS) analysis. Heptane was the dominant gas produced in bitumen cracking at all temperatures and the r

Thin films of Nb2O5 have been successfully deposited using the DC reactive magnetron sputtering technique to manufacture NH3 gas sensors. These films have been annealed at a high temperature of 800°C for one hour. The assessment of the Nb2O5 thin films structural, morphological, and electrical characteristics was carried out using several methods such as X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity assessments. The XRD analysis confirms the polycrystalline composition of the Nb2O5 thin films with a hexagonal crystal structure. Furthermore, the sensitivity, response time, and recovery time of the gas sensor were evaluated for the Nb2O5 thin film

A mathematical model constructed to study the combined effects of the concentration and the thermodiffusion on the nanoparticles of a Jeffrey fluid with a magnetic field effect the process of containing waves in a three-dimensional rectangular porous medium canal. Using the HPM to solve the nonlinear and coupled partial differential equations. Numerical results were obtained for temperature distribution, nanoparticles concentration, velocity, pressure rise, pressure gradient, friction force and stream function. Through the graphs, it was found that the velocity of fluid rises with the increase of a mean rate of volume flow and a magnetic parameter, while the velocity goes down with the increasing a Darcy number and lateral walls. Also, t

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The solution gas-oil ratio is an important measurement in reservoir engineering calculations. The correlations are used when experimental PVT data from particular field are missing. Additional advantages of the correlations are saving of cost and time.
This paper proposes a correlation to calculate the solution gas -oil ratio at pressures below bubble point pressure. It was obtained by multiple linear regression analysis of PVT data collected from many Iraqi fields.
In this study, the solution gas-oil ratio was taken as a function of bubble point pressure, stock tank oil gravity, reservoir pressure, reservoir temperature and relative gas density.
The construction of the new correlation is depending on thirty seven PVT reports th

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp