Arabian Journal for Science and Engineering最新文献

To achieve a green recycled concrete with excellent mechanical properties and workability, this paper utilized recycled concrete powder, fly ash and granulated ground blast furnace slag as primary materials. Recycled concrete aggregates served as coarse aggregates in the formulation of a recycled concrete powder-based geopolymer recycled concrete (RCPGRC). The study investigated the impact of additional water consumption (AWC), recycled fine aggregate content (RFAC) and the mass ratio of solid powder to aggregate (P/A) on both the mechanical property and workability of RCPGRC. Employing variance and range analysis, the research comprehensively assessed the contributing factors to the concrete's performance and identified the optimum mixture ratio. Characterization of the phase composition and micromorphology were characterized through X-ray diffraction and scanning electron microscopy. The results show that: (1) The AWC had the greatest influence on the unconfined compressive strength (UCS), slump, and setting times, while RFAC and P/A were smaller. AWC of 3%, RFAC of 10%, and P/A of 26% were the inflection points of the UCS, slump, and setting times with AWC, RFAC, and P/A, respectively. (2) The production rate and quantity of geopolymer gels production, as well as the cracks and voids, were affected when the mixture ratios deviated from these optimal inflection points. (3) These inflection points can be utilized as the indexes for rapid judge the optimum mixture ratio of RCPGRC.

Electrocatalytic water splitting has been considered as one of the most significant and sustainable approaches for hydrogen production. To make the process more efficient and affordable, there is a need to develop robust, cheap, highly active and stable electrocatalysts. Herein, facile synthesis of copper phosphide nanoparticles (Cu₃P NPs) with size ranging from 30 to 80 nm was carried out by using solvothermal process. Variety of characterization techniques like FTIR, XRD, Raman spectroscopy, dynamic light scattering and SEM–EDX, verified the successful synthesis of Cu₃P NPs with spherical morphology. Three-electrode system containing glassy carbon, platinum mesh and Hg/HgO as working, counter and reference electrode, respectively, was used for the electrochemical characterization. Electrochemical studies, i.e., CV, LSV and chronoamperometric analysis, revealed efficiency and stability of electrocatalyst for electrolysis of water including hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Briefly, the Cu₃P NPs exhibited an excellent OER activity, achieving the current density of 10 mA cm⁻² with an overpotential of 450 mV. Tafel slope value 63 mV dec⁻¹ suggested fast OER reaction kinetics. The Cu₃P catalyst also exhibited significant HER activity, approaching a current density of 10 mA cm⁻² with an overpotential of 447 mV. Fast HER reaction kinetics was observed with a Tafel slope value of 132 mV dec⁻¹. Moreover, the chronoamperometric studies revealed the stability of electrocatalyst providing favorable conditions for sustainable, long-term oxygen and hydrogen production.

High-power nonlinear load characteristics are one of the typical characteristics of multi-electric aircraft power systems. The study provides an improved CNN-LSTM stability analysis method for solving the stability problem of the aircraft power system caused by high-power nonlinear load switching. To address the issue of sample imbalance, this approach creatively incorporates the cost factor into the CNN loss function. In order to handle the issue of computational complexity, the projection layer is added to the LSTM, and a methodology known as CNN-LSTMP is proposed. This algorithm solves the problems of low computational efficiency and huge computational volume. The time series data utilized by the experiment are created by simulating the transient switching process. The data are then labeled, normalized, and model training is carried out. A deep learning algorithm that satisfies the prediction requirements can be created by applying this method to the established simulation model of a multi-electric aircraft power system for stability analysis. According to the results of the experiments, this method’s transient stability analysis accuracy is 93.32%, which has a positive impact on transient analysis and may satisfy application requirements.

The integration of hydrogen into natural gas infrastructure presents a viable strategy for mitigating greenhouse gas emissions and advancing toward carbon neutrality. This study investigates the combustion characteristics and emissions profiles of hydrogen-enriched natural gas mixtures, specifically focusing on the composition of Russian pipeline natural gas. A comprehensive mathematical model was developed to predict emission concentrations and simulate fuel mixture combustion using MATLAB Simulink software. This versatile model facilitates further analysis within the MATLAB ecosystem. The simulation results demonstrate a significant correlation between the hydrogen content in the natural gas mixture and the resulting heat power output. With a constant fuel consumption rate, a notable decrease in heat power was observed as the hydrogen concentration increased, reaching a maximum reduction of 44.9% at a 45% hydrogen content. These findings underscore the feasibility of partially substituting natural gas with hydrogen, while also highlighting the necessity for increased fuel flow rates to maintain equivalent power output levels. This poses additional challenges for natural gas grid operators, necessitating infrastructure adaptations to accommodate higher fuel demands. The insights gained from this research contribute to the growing body of knowledge surrounding hydrogen integration in the energy sector, offering valuable implications for decarbonization strategies and the optimization of natural gas infrastructure.

This article discusses the vibration, bending, and buckling analysis of a seven-layer sandwich beam with a balsa wood core reinforced with carbon nanotubes (CNT), shape memory alloy (SMA) nanoparticles, and piezoelectromagnetic layers. The governing equations of motion are obtained using the Hamiltonian principle. To measure the validity of this research, the obtained results are compared with the other results, and the results are in agreement with each other. The primary goal is to enhance the sandwich structure’s strength and rigidity by using CNTs reinforcement and SMA nanoparticles, with the piezoelectromagnetic layers functioning as sensors to improve the overall mechanical performance of the beam The use of CNTs can have a favorable effect on the stiffness of the beam and strength-to-weight ratio and also, the effect of the thickness ratio of core on deflection, critical buckling load, and vibration frequency is significant, so that with a decrease of 11.1% in the thickness ratio, the deflection decreases by about 50.2%, the critical buckling load increases by about 101%, and the vibration frequency increases by about 40.7%. Also, with an increase of 0.5 and 3.5 percent of CNT, the deflection of a sandwich beam reduces by 20 and 50 percent, respectively.

This study employs a multi-criteria decision-making (MCDM) technique to identify the optimal parameters for the electrical discharge turning (EDT) process used to machine cylindrical EN24 steel alloy. EDT, a significant configuration of EDM, offers a valuable approach for machining cylindrical workpieces. A face-centred central composite design (FCCCD) is employed to establish the experimental design. The CRITIC–TOPSIS method is subsequently implemented to optimize the input parameters: gap current (Ig), pulse on time (Ton), rotational speed (N), and magnetic field assistance (B). Each parameter is investigated at three distinct levels. The study focuses on four response variables: material removal rate (MRR), tool wear rate (TWR), overcut (OC), and surface roughness (R_a). Analysis of variance (ANOVA) is conducted to assess the influence of each input parameter on the observed responses. Criteria importance through inter-criteria correlation (CRITIC) is employed to assign weights to each response, followed by applying the technique for order of preference by similarity to ideal solution (TOPSIS) to identify the ideal machining parameters. The results indicate that run number 16 (Ig: 16A, Ton: 60 µs, N: 1400 RPM, and B: 0.30 T) represents the optimal configuration. Scanning electron microscopy (SEM) analysis further corroborates this finding, confirming superior surface quality compared to other experimental runs.

ZnO-based nanocomposites have attracted a great attention for energy storage systems and detection of volatile organic compounds. In this study, pure and Ce-doped MnO₂–ZnO composites were fabricated through a co-precipitation method. The results of X-ray diffraction verified the formation of tetragonal MnO₂ and hexagonal ZnO phases. Scanning electron microscope images of pure and Ce-doped MnO₂–ZnO composites displayed the formation of rods and semi-spherical particles. The pure and Ce-doped MnO₂–ZnO composites exhibited semi-stable colossal dielectric constant values of 2.12 × 10⁵ and 1.36 × 10⁵, respectively, at a frequency of 45 Hz, which are proper for capacitive energy storage applications. Gas sensing measurements demonstrated that Ce-doped MnO₂–ZnO composite has a high sensitivity toward 100 ppm acetone gas at operating temperature of 240 °C, while for 100 ppm ethanol this sensor has a high sensitivity at 180 °C. As a result, through adjusting the operating temperature, the selectivity of Ce-doped MnO₂–ZnO sensor can be controlled for acetone and ethanol gases. Furthermore, this sensor possesses good selectivity and stability as well as proper linear relations between the sensitivity and concentrations of acetone and ethanol gases.

This study advocates for the use of recycled materials, which are more environmentally sustainable as they decrease natural resource consumption. In this research, a mortar anode composed of recycled fine aggregate (RFA) from laboratory concrete blocks, carbon fiber (CF) waste from industrial processes, and graphite powder (GP) was developed, resulting in a conductive recycled mortar (CRM). The manufacturing process utilized Portland composite cement, RFA with a sand/cement ratio of 1.00, a water/cement ratio of 0.6, a GP/cement ratio of 0.50, CF comprising 0.5%, and carboxymethyl cellulose (CMC) comprising 0.4% by weight of cement. Chloride profiles indicated that the specimens with the CRM anode were effective, as the chlorides migrated into the mortar. For M0.5CF (2.81%) and M0.5CF0.5GP (3.72%) of free chlorides, the Ti–RuO₂ mesh did not expel the chlorides but rather accumulated them at 1 cm from the surface, resulting in a negative efficiency (− 20.02%). However, at 1 cm from the cathode, the efficiency levels were comparable across the anodes: Ti–RuO₂ mesh (84.54%), M0.5CF (84.76%), and M0.5CF0.5GP (81.11%), underscoring the potential of using a CRM anode for electrochemical chloride removal.

Corrosion is one of the most significant challenges for oil pipelines. It can occur due to various factors such as moisture, oxygen, and contaminants in the oil. Corrosion weakens the pipeline material, leading to leaks, ruptures, and structural failure. To enhance the ability to decrease the corrosion problems of oil pipelines, an efficient Back Propagation Neural Network is developed to predict the corrosion rate and analyse the importance of the features that affect the corrosion. This method is based on the database generated by coupling an analytical corrosion rate model and Monte Carlo simulation by using Spearman’s (SP) correlation coefficient to generate the relevance between each feature, negating the feature variables with a strong correlation and then combining with a Genetic Algorithm (GA) and a Back Propagation (BP) Neural Network to build a regression prediction model. The proposed approach has been termed SP-GA-BP. The results showed that the proposed method can predict well with R² = 0.99519 MAE = 0.18926 MSE = 0.0072213 RMSE = 0.084978, thereby indicating that the Temperature, CO₂ Pressure, and Corrosion Inhibitor efficiency can affect the corrosion rate efficaciously. Furthermore, with the introduction of external interference, the results exhibited a high level of precision. The proposed method and the obtained results may provide a good reference value for oil pipeline maintenance.

The impacts of incorporating silane-functionalized halloysite nanoclay (SNC) in sodium polyacrylamide (PA) superabsorbent polymer (SAP) and its reinforcement potential in cementitious materials are carefully investigated. Unlike previous studies, this work uniquely explored the dual functionality of SNC to enhance both the water absorption capacity and mechanical strength of SAPs and, subsequently, its reinforcing effects on cementitious materials. This study comprehensively examines the mechanical and durability characteristics of cement mortar and concrete when a small percentage of SNC/SAP composite is added at 0.2, 0.4, 0.6, and 0.8%. The optimum concentration of SNC/SAP composite in the cement mix was found to significantly improve the hydration of cement, thereby enhancing its mechanical properties and strength by filling the micropores. X-ray diffraction (XRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), and scanning electron microscopy (SEM) analyses were carried out to characterize the surface morphology and its influence on cementitious materials. The results indicate that the SNC/SAP cementitious nanocomposite enhances the compressive, flexural, and tensile strengths by up to 54%, 63%, and 67%, respectively, compared to those of conventional mortar specimens at 56 days. Furthermore, shrinkage tests revealed the excellent water-holding capacity of the composite hydrogel, which promoted internal curing and reduced microcrack formation. The findings demonstrate that SNC not only improves the properties of SAP hydrogels but also significantly enhances the mechanical properties and durability of cementitious materials, making it a promising additive for protective cementitious coatings in buildings. This study addresses the critical need for durable, crack-resistant concrete, providing a novel approach to enhancing the longevity and performance of cementitious materials.