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The possibility of predicting the mass transfer controlled CaCO₃ scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO₃ scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

One of the most important problems in the oil production process and when its continuous flow, is emulsified oil (w/o emulsion), which in turn causes many problems, from the production line to the extended pipelines that are then transported to the oil refining process. It was observed that the nanomaterial (SiO₂) supported the separation process by adding it to the emulsion sample and showed a high separation rate with the demulsifiers (RB6000) and (sebamax) where the percentage of separation was greater than (90 and 80 )%  respectively, and less than that when dealing with (Sodium dodecyl sulfate and Diethylene glycol), the percentage of separation was (60% and 50%) respectively.

   The high proportion

Background: In dentistry, dentist takes the advantages of soft lining materials due to the viscoelastic properties. The major problem is the adhesion of the soft liner with the denture base material. Materials and Methods: Heat cured of high impact acrylic resin specimens prepared with dimensions 75x13x13mm for shear bond strength test, soft lining material (Refit and Mollosil) with a 3-mm thickness and used to join each two acrylic blocks. Also four specimens with the same previous dimensions utilized for chemical and physical surface analysis. The specimens grouped as control (without plasma) and experiment (with oxygen plasma) treated high impact acrylic specimens. Results: Plasma treatment increased the shear bond strength for both Refi

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

This paper presents a research for magnetohydrodynamic (MHD) flow of an incompressible generalized Burgers’ fluid including by an accelerating plate and flowing under the action of pressure gradient. Where the no – slip assumption between the wall and the fluid is no longer valid. The fractional calculus approach is introduced to establish the constitutive relationship of the generalized Burgers’ fluid. By using the discrete Laplace transform of the sequential fractional derivatives, a closed form solutions for the velocity and shear stress are obtained in terms of Fox H- function for the following two problems: (i) flow due to a constant pressure gradient, and (ii) flow due to due to a sinusoidal pressure gradient. The solutions for

Titanium oxide nanoparticles-modified smectite (SMC-nTiO2) as a low-cost adsorbent was investigated for the removal of Rhodamine B (RhB) from aqueous solutions. The adsorbents (SMC and SMC-nTiO2) were characterized by scanning electron microscopy, Fourier transforms infrared spectroscopy, and energy-dispersive X-ray spectroscopy. The effects of various parameters like contact time, adsorbent weight, pH, and temperatures were examined. Three kinetic equations (pseudo-first-order (PFO), pseudo-second-order (PSO), and intra-particle diffusion) were used to evaluate the experimental kinetic of the data and the results showed that the adsorption process is in line with the PSO kinetic model. Adsorption equilibrium isotherms were modeled using La

The approach of green synthesis of bio-sorbent has become simple alternatives to chemical synths as they use for example plant extracts, plus green synthesis outperforms chemical methods because it is environmentally friendly besides has wide applications in environmental remediation. This paper investigates the removal of ciprofloxacin (CIP) using green tea nano zero-valent iron (GT-NZVI) in an aqueous solution. The synthesized GT-NZVI was categorized using SEM, AFM, BET, FTIR, and Zeta potentials techniques. The spherical nanoparticles were found to be nano zero-valent, with an average size of 85 nm and a surface area of 2.19m2/g. The results showed that the removal efficiency of ciprofloxacin depends on the initial pH (2.5-10),