The main objective of this study is to experimentally investigate the effect of the CMC polymeric drag reducer on the pressure drop occurred along the annulus of the wellbore in drilling operation and investigate the optimum polymer concentration that give the minimum pressure drop. A flow loop was designed for this purpose consist from 14 m long with transparent test section and differential pressure transmitter that allows to sense and measure the pressure losses along the test section. The results from the experimental work show that increasing in polymer concentration help to reduce the pressure drop in annulus and the optimum polymer concentration with the maximum drag reducing is 0.8 kg/m³. Also increasing in flow rate a

Experimental investigations had been done in this study to demonstrate the effect of natural particles used as a reinforcement material to unsaturated polyester resin. The tensile test and water absorption were investigated according to (ASTM D638) and (ASTM D570), respectively. The influence of sunflower husk and pomegranate husk particles, used as a reinforcement material, on the tensile strength, Young's modulus and water absorption with different weight fraction (3%, 7% and 10%) and particle grain size (50µm, 100 µm and 150 µm), has been investigated. The water absorption of polymer composites was studied by measuring the specimen weight before and after immersion in water for one hundred days. In the experiments of tensile test,

   The ZnTe alloy was prepared as  deposited thin films on the glass substrates at a thickness of 400±20 nm using vacuum evaporation technique at pressure (1 × 10^-5) mbar and room temperature. Then the thin films under vacuum (2 × 10^-3 mbar) were annealing at (RT,100 and 300) °C for one hour. The structural properties were studied by using X-ray diffraction and AFM, the results show that the thin films had approached the single crystalline in the direction (111) as preferred orientation of the structure zinc-blende for cubic type, with small peaks of tellurium (Te) element for all prepared thin films. The calculated crystallite size (C_s) decreased with the increase in the anne

In this paper, silicon carbonitried thin films were prepared by the method of photolysis of the silane (SiH4) and ethylene (C2H4) gases, with and without ammonia gas (NH3), which is represented by the ratio between the (PNH3) and (PSiH4 + PC2H4 + PNH3), (which assign by the letter X), X has the values (0, 0.13, 0.33). This method carried out by using TEA-CO2 laser, on glass substrate at (375 oC), deposition rate (0.416-0.833) nm/pulse thin film thickness of (500-1000) nm. The optical properties of the films were studied by using Absorbance and Transmittance spectrums in wavelength range of (400-1100) nm, the results showed that the electronic transitions is indirect and the energy gap for the SiCN films increase with increasing of nitrog

This research studies the development and synthesis of blended nanocomposites filled with Titanium dioxide (TiO2). Blended nanocomposites based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The optimum quantity from nano partical of titanium dioxide was selected and different weight proportions 1%, 3%, 5%, and 7% ratios of new epoxy are blended with UPR resin. The dielectric breakdown strength and thermal conductivity properties of the blended nanocomposites were compared with those of the basis material (UPR and 3% TiO2).The results show good compatibility epoxy resins with the UPR resin on blending, dielectric breakdown strength values  are higher while thermal conductivity values of

This research studies the development and synthesis of blended nanocomposites filled with Titanium dioxide (TiO2). Blended nanocomposites based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The optimum quantity from nano partical of titanium dioxide was selected and different weight proportions 1%, 3%, 5%, and 7% ratios of new epoxy are blended with UPR resin. The dielectric breakdown strength and thermal conductivity properties of the blended nanocomposites were compared with those of the basis material (UPR and 3% TiO2).The results show good compatibility epoxy resins with the UPR resin on blending, dielectric breakdown strength values  are higher while thermal conductivity values of

Conducting polyaniline / ZnO nano composites are synthesized
using a simplified cheap method with one step in –situ chemical
polymerization, and AC conductivity (σac) of the prepared samples is
studied in the range of frequency from 50 Hz to 15MHz.). The
presence of polarons in the conjugated polymer chain are responsible
for the ac conductivity is reliance on the frequency in these
composites. The effect of increasing the ZnO nano particle
concentration irradiation and gamma radiation on the electric
conductivity was analyzed. The result showed that the
nanocomposite prepared has the highest conductivity, from pure
polyaniline and the exponential factor S was found increasing with
ZnO content it was 0

Computer models are used in the study of electrocardiography to provide insight into physiological phenomena that are difficult to measure in the lab or in a clinical environment.

The electrocardiogram is an important tool for the clinician in that it changes characteristically in a number of pathological conditions. Many illnesses can be detected by this measurement. By simulating the electrical activity of the heart one obtains a quantitative relationship between the electrocardiogram and different anomalies.

Because of the inhomogeneous fibrous structure of the heart and the irregular geometries of the body, finite element method is used for studying the electrical properties of the heart.

This work describes t

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com