The corrosion behavior of Titanium in a simulated saliva solution was improved by Nanotubular Oxide via electrochemical anodizing treatment using three electrodes cell potentiostat at 37°C. The anodization treatment was achieved in a non-aqueous electrolyte with the following composition: 200mL ethylene glycol containing 0.6g NH4F and 10 ml of deionized water and using different applied directed voltage at 10°C and constant time of anodizing (15 min.). The anodized titanium layer was examined using SEM, and AFM technique. The results showed that increasing applied voltage resulted in formation titanium oxide nanotubes with higher corrosion resistance (more positive value of the corrosion potential). The results revealed that good adhered well-ordered vertically aligned titania nanotubes with inner tube diameter of 82nm an mean length of 3microns could be obtained at 30VDC. Low corrosion current density (579 nA.cm-2) and corrosion potential equal to (-209 mV) were observed for untreated titanium metal while a dramatic fall down of the corrosion current was observed for nanotubes TiO2 (76 nA.cm-2) and more positive value of corrosion potential (-138 mV) was observed revealing good corrosion resistance of the improved titanium in saliva solutions.
Predicting the rate of penetration (ROP) is a significant factor in drilling optimization and minimizing expensive drilling costs. However, due to the geological uncertainty and many uncontrolled operational parameters influencing the ROP, its prediction is still a complex problem for the oil and gas industries. In the present study, a reliable computational approach for the prediction of ROP is proposed. First, fscaret package in a R environment was implemented to find out the importance and ranking of the inputs’ parameters. According to the feature ranking process, out of the 25 variables studied, 19 variables had the highest impact on ROP based on their ranges within this dataset. Second, a new model that is able to predict the ROP using real field data, which is based on artificial neural networks (ANNs), was developed. In order to gain a deeper understanding of the relationships between input parameters and ROP, this model was used to check the effect of the weight on bit (WOB), rotation per minute (rpm), and flow rate (FR). Finally, the simulation results of three deviated wells showed an acceptable representation of the physical process, with reasonable predicted ROP values. The main contribution of this research as compared to previous studies is that it investigates the influence of well trajectory (azimuth and inclination) and mechanical earth modeling parameters on the ROP for high-angled wells. The major advantage of the present study is optimizing the drilling parameters, predicting the proper penetration rate, estimating the drilling time of the deviated wells, and eventually reducing the drilling cost for future wells.
Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability. In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation pore pressure, and in-situ stresses of the studied area were included as inputs. The second step was by optimizing the process using a genetic algorithm (GA), as a class of optimizing methods for complex functions, to obtain the maximum ROP along with the related wellbore trajectory (AZI and INC). Finally, the suggested azimuth (AZI) and inclination (INC) are premeditated by considering the results of wellbore stability analysis using wireline logging measurements, core and drilling data from the offset wells. The results showed that the optimized wellbore trajectory based on wellbore stability analysis was compatible with the results of the genetic algorithm (GA) that used to reach higher ROP. The recommended orientation that leads to maximum ROP and maintains the stability of drilling deviated wells (i.e., inclination ranged between 40°—50°) is parallel to (140°—150°) direction. The present study emphasizes that the proposed methodology can be applied as a cost-effective tool to optimize the wellbore trajectory and to calculate approximately the drilling time for future highly deviated wells.
Activated carbon is a porous material that has a great character to be used for drug delivery system as carrier.It is agreed that drug carriers maintain the concentration of drugs within the required range for a long period of time and undetermined toxicity resulting from the use of overdoses , the ability to direct the drug to the affected area, immunity, biophysics, and drug efficacy. activated carbon was used in two different particle sizes (0.6µm size with surface area 544.4704 m2/g and 11.042 nm size with surface area 985.6013m2/g ) and Naproxen was used as a drug model. In this research study the effect of the number of parameters, including particle size, weight of drug to carrier weight ratio, on drug loading and temperature, time ,PH solution on mass transfer coefficient in unloading drug. the result of experiments was find that maximum loading efficiency obtain when the particle size of activated carbon was in Nano. size and the ratio of weight drug to AC weight was 1.5. The unloading process was studied by studying the mass transfer coefficient and knowing the effect of the variables on its value ,these variables are time and temperature in addition to the PH value of the solution. The highest value of the mass transfer coefficient was obtained at the beginning of the unloading time ,at temperature 37 co and at solution in PH 6.5 .
In this work, an absorption technology was used actually to investigation the mass transfer coefficient of carbon dioxide from a gaseous mixture (air, carbon dioxide) in blended solution Monoethanolamine (MEA) and Diethanolamine (DEA) in a bubble column reactor (BCR) . The bubble column reactor(BCR) was made of Plexiglas with 1.5 m high and 0.1 m inside diameter. The overall mass transfer coefficient ( was evaluated at different operating conditions , gas flow rate, air Flow rate ,liquid flow rate .Where the gas flow rates were 10, 15 and 20 L /min , air flow rate 100,150 and 200 L/h ,and liquid flow rate 5 ,10,15 L /min . This experiment by using continuous process with helping centrifugal pump . High-performance gas chromatographic (GC) was performed to evaluate loading during absorption experiment . The experimental results have shown that the loading in range of 0.581-1.367 (mol /mole amine),and the maximum value of overall mass transfer coefficient ( KG) was 0.04 S-1 .
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