Arabian Journal for Science and Engineering最新文献

There is a growing trend for groups associated with drug use to exploit social media platforms to propagate content that poses a risk to the population, especially those susceptible to drug use and addiction. Detecting drug-related social media content has become important for governments, technology companies, and those responsible for enforcing laws against proscribed drugs. Their efforts have led to the development of various techniques for identifying and efficiently removing drug-related content, as well as for blocking network access for those who create it. This study introduces a manually annotated Twitter dataset consisting of 112,057 tweets from 2008 to 2022, compiled for use in detecting associations connected with drug use. Working in groups, expert annotators classified tweets as either related or unrelated to drug use. The dataset was subjected to exploratory data analysis to identify its defining features. Several classification algorithms, including support vector machines, XGBoost, random forest, Naive Bayes, LSTM, and BERT, were used in experiments with this dataset. Among the baseline models, BERT with textual features achieved the highest F1-score, at 0.9044. However, this performance was surpassed when the BERT base model and its textual features were concatenated with a deep neural network model, incorporating numerical and categorical features in the ensemble method, achieving an F1-score of 0.9112. The Twitter dataset used in this study was made publicly available to promote further research and enhance the accuracy of the online classification of English-language drug-related content.

Waterflooding is a widely-used secondary oil recovery technique employed in the oil industry. In mature oil fields, waterflooding becomes increasingly essential in order to maximize oil recovery and extend field life, but optimizing its performance remains a complex and challenging task. In recent years, there has been growing interest in developing integrated approaches combining reservoir simulation, well modeling, and data-driven techniques to improve waterflood performance. The Capacitance–Resistance Model (CRM) has been proven to be a fast and effective tool for predicting waterflooding and reservoir characterization. Previous studies have successfully applied CRM to waterflood management to increase oil recovery. This paper develops a novel integrated and iterative workflow for waterflooding optimization in mature fields using the CRM for multilayer reservoirs equipped with Interval Control Valves (ICVs). The proposed approach, which integrates geological and well data with CRM results, was validated using a benchmark field model named the Olympus. This new workflow will help to put connected injection and production wells in different groups to reduce computational costs. In addition, this workflow can be used to determine the optimized number and proper location of the ICVs inside production wells. We determined the workover programs for existing wells, such as installing sensors and ICVs, deepening the wells, or plug-backs. Finally, it can be used for determining optimal water injection rates and well control strategies, such as valve openings in different production layers. As a result, the oil recovery factor increased, and the NPV was maximized, respecting the Olympus field's economic and operational constraints.

It is important to utilize the raw colemanite (RC) mineral, which has abundant reserves in the world, and to reduce its particles to smaller sizes for nanotechnology. However, not only the particle size of the produced colemanite powder but also its other properties need to be elucidated. By using the Taguchi design, the RC mineral was ground in a high-energy ball mill. From signal-to-noise (S/N) ratio, the smallest average particle size was found to be 3.10 µm for the experiment E04/nano-sized amorphous colemanite (NAC) powder. The characteristics of as-received RC mineral and synthesized NAC material were investigated using laser particle size analyzer, optical microscopes, SEM–EDS, XRD, TEM, HRTEM, and TGA–DTA devices. It was found that the NAC powder was not homogeneous, a small peak within the 300–20 nm range appeared, and d₉₀, d₅₀, d₁₀, and d_min values were, respectively, 14.6 µm, 3.08 µm, 232 nm, and 26 nm. In the XRD analysis, the pure colemanite, calcite, and silica minerals were determined. The crystal structure of the NAC powder almost turned amorphous, and the crystallite size of (031) peak was reduced to 7.3 nm. It was deduced that the average particle size was 8.29 nm (R² = 0.86), and the d-spacing value was 0.307 nm. This significant finding was attributed to the mobility of balls and moreover it was interpreted with an equation. An unknown transition in TGA–DTA was referred to the calcite mineral. Finally, it is believed that the synthesized NAC material will be beneficial to engineering studies as a natural/mineral additive.

Methylammonium iodide (MAI) and methylammonium bromide (MABr) reactants were synthesized in powder form. Tin-based perovskites (MASnI_xBr_3−x (x = 3, 2, 1, 0)) were deposited as a thin film on glass substrates using the ultrasonic spray pyrolysis (USP) method. X-ray diffraction (XRD) was used to examine the crystallographic characteristics of the synthesized MAI/MABr powders and perovskite thin films. A shift occurred in the XRD peaks by changing the I/Br ratios. Morphological analysis of the MAI and MABr were carried out by scanning electron microscopy (SEM). While the average particle size was calculated a ~ 94 μm for MAI, it was obtained as ~ 188 μm for MABr. The Fourier transform infrared (FTIR) spectroscopy peaks observed for synthesized MAI and MABr were found to be compatible with commercial MAI and MABr FTIR peaks. Elemental analysis of MASnI_xBr_3−x (x = 3, 2, 1, 0) perovskite thin films was performed energy dispersive spectroscopy (EDS). Forbidden band gap (E_g) values of perovskite thin films were obtained from Tauc curves. The E_g value increased with an increasing I/Br ratio. The deposition of highly stoichiometric MASnI_xBr_3–x perovskites thin films was achieved by the USP method. This method has many parameters need to be optimized. This study gives optimum parameters that are difficult to determine.

Carbon dioxide (CO₂) flooding is a widely adopted enhanced oil recovery (EOR) technique known for its ability to displace crude oil effectively by altering its properties. However, in high-temperature Malaysian reservoirs, achieving the minimum miscibility pressure (MMP) for successful miscible flooding can be challenging. This study investigates the potential of using fatty acid methyl esters (FAMEs) derived from biomass sources to lower the MMP in CO₂-crude oil systems, thereby enhancing CO₂-EOR performance. FAME, renewable and sustainable, presents an innovative alternative to conventional petroleum-based chemicals in EOR. The study involved two types of biomass-derived FAME, sourced from Rubber Seed Oil and Palm Kernel Oil, and two types of crude oil, Tapis and Dulang, tested using the slim tube method at 90 °C and pressures up to 4500 psi. Our findings indicate the presence of Methyl Oleate in Rubber Seed Oil and Methyl Laurate in Palm Kernel Oil, both likely derivatives formed during biodiesel production through transesterification. The MMP for Tapis crude oil was 3620 psi, and for Dulang crude oil, it was 3860 psi, exceeding both the reservoir and fracture pressures of the formation. This can lead to inefficient CO₂ injection, reservoir fracturing, and increased costs. However, the addition of 5% vol. FAME to Tapis crude oil demonstrated promise, with Methyl Laurate reducing the MMP by 17.12% and Methyl Oleate by 3.34%. Increasing the concentration of Methyl Laurate to 10% vol. resulted in a substantial 21% MMP reduction. Notably, the presence of waxes and asphaltenes further lowered the MMP compared to pure Tapis crude oil, with Methyl Laurate achieving a 6.42% reduction compared to 17% for Methyl Oleate. In conclusion, this study explores the use of biomass-derived FAME to improve CO₂ flooding performance by lowering MMP. The findings suggest that FAME, particularly Methyl Laurate, offers a sustainable solution to address MMP challenges in CO₂-based EOR operations, contributing to the advancement of the oil industry in the region.

In order to harness the abundant solar energy in the desert environment, more and more large-scale photovoltaic systems have been installed in deserts terrains. However, the typical sandstorms and accumulation of dust on the solar panels are the challenges to reckon with in order to effectively harvest the high intensity solar radiation. The conventional dust mitigation techniques demand large instrumentation, electric power, and huge quantity of water, enormous manpower and logistics at the remote and hostile locations. A very low power consuming instant dust repelling system, based on electrostatic and electro-dynamic forces has been developed and tested for its dust mitigating performance. The design of the system is basically fabricating an interdigitated electrode on the surface of the solar panel, energized by the low power, low frequency single-phased alternating voltage source. The standing electric wave established in between the electrode levitates the dust particles and is simultaneously repelled by electrostatic forces. The system design was electrically and geometrically optimized and tested in the lab and also in real-life condition, and the efficiency of dust removal as high as 90 ± 1 ℅ was achieved, and this dust elimination helped to restore the initial open circuit voltage and the short current of the tested solar cells. The attractive features of the developed electro-dynamic dust repelling system are that it is automatic, unmanned, low cost, low power, and quite efficient.

Using high-order shear and normal deformation theory (HSNDT), this study analyzes the dynamic response and time history of the impact force of the sandwich plate with the auxetic core under low-velocity impact. The impact was modeled using a two-degree-of-freedom mass and spring model, and the Hertz linearized model was utilized to derive the contact force's time history. The rectangular sandwich panel has simple supported boundary conditions and consists of three layers: two aluminum top face sheets and one auxetic core layer with a negative Poisson's ratio. Using the energy technique, the system's governing equations are derived. The equilibrium equations were solved by the analytic approach of the Navier method in the space domain and the numerical method of Newmark in the time domain. The use of HSNDT distinguishes this article from others on similar topics, and the flexibility of the thick core in the thickness direction is considered. The Effects of different geometric and material properties have been investigated, and the results have been compared with those of other similar papers and studies for validation. The data indicate that the greater the degree of inclination of the cell, the longer the impact period and the lower the peak impact force. Moreover, the larger angle of the auxetic cell reduces the deflection at the impact site. In terms of minimizing deflection, the auxetic honeycomb sandwich panel is 25% superior to the non-auxetic honeycomb panel.

In this article, the physical properties of Ge-based lead-free halide double perovskite compounds X₂GeSnCl₆ (X = Na, K) are studied in the framework of density functional theory by using the Wien2k code. Compounds show stability with negative values of ground state energy and formation energy. The band structure in electronic properties exhibits the semiconducting nature with 2.24 eV and 2.21 eV direct band gaps by using a modified Becke Johnson approximation which gives clear results of the band gap. On the other hand, electronic charge density exhibits the covalent band of Cl with Ge and Sn while the ionic bond between Cl and (Na, K). Optical conductivity is high and maximum output in the visible region of the solar energy spectrum along with maximum absorbance for both compounds while reflectivity is lower in the visible region which makes the compounds suitable for solar cell and opto-electronic applications. Using BoltzTraP classical theory in the thermoelectric property valuable results are observed with higher ZT values of K₂GeSnCl₆ with 0.99 which makes it a good candidate for thermoelectric applications. Both compounds are mechanically and dynamically stable with brittle nature; also covalent bonding nature is confirmed by Cauchy pressure with negative values.

This study aims to conduct resource assessments at five offshore locations (L1–L5) in the Gulf of South Suez for possible development of wind farms. For this purpose, the hourly mean wind speed and direction data at 100 m above mean sea level (AMSL) and other meteorological data at near water surface from ERA5 (fifth-generation reanalysis for the global climate weather) is used. Statistical analyses, wind power, energy estimation, plant capacity factor, etc., have been performed using Windographer software. The cost of energy and greenhouse gas emissions are conducted based on international installation cost per kW and emissions factor per kWh from the literature. The data covers 43 years, between 1979 and 2021. The results show that at L1 to L5 locations, the long-term mean wind speed (WS) and wind power density (WPD) values are 8.678 m/s and 533 W/m², 4.371 m/s and 78 W/m², 8.917 m/s and 587 W/m², 7.856 m/s and 406 W/m², 8.072 m/s and 453 W/m², and 7.876 m/s and 406 W/m² at 100 m ASL, respectively. Based on the site-specific parameters (WS, WPD, WPC, MWVI, MWSI, AWVI, AWSI, minimum zero power, maximum rated power, PCF, COE, and maximum wind duration), values of 8.917 m/s, 587 W/m², 1.125, 34.92, 0.358, 101.9, 6.26%, 5.76%, 54.04%, 0.007 USD/kWh, and 91%; L2 are identified as the most relevant area for wind farm development among the studied locations. At L2 site, the wind turbine WT2 can deliver annually 21.266 GWh of energy at respective plant capacity factors of 48.55%.

This study focuses on the optimization of ventilation hole design in steel wheels used for heavy commercial vehicles. The primary objective is to reduce the weight of the wheel while ensuring compliance with radial fatigue and cornering fatigue test requirements. Four distinct ventilation types were parametrized using ANSYS Mechanical, with the von Mises stress on the disk, number of ventilations, and wheel weight serving as design parameters. Stress analysis and weight comparisons were performed between wheels featuring different ventilation types and an ellipse ventilation wheel. Incorporating the design of experiment (DoE) and response surface optimization (RSO) module in ANSYS Workbench 2022 R1 was employed to compare and evaluate the obtained values. Subsequently, the multi-objective genetic algorithm (MOGA-II) method was employed for optimization, aiming to identify the optimal design. The optimization process, utilizing a maximum of 20 iterations, a convergence stability percentage of 2%, and a maximum allowable Pareto percentage of 70%, yielded 1, 3, 3, and 3 candidate design points for round, slot, trapezoid, and halfmoon-type ventilation holes, respectively. Among the various ventilation types considered, the halfmoon-type ventilation hole exhibited the most promising results. Compared to the current design, the optimized wheel achieved a weight reduction of 0.9 kg (2.05%). This outcome demonstrates the effectiveness of the proposed methodology. Although lighter designs were not attainable while maintaining the same stress values for the other three ventilation types, the halfmoon-type ventilation hole was ultimately selected as the preferred design.