Arabian Journal for Science and Engineering最新文献

The fluid catalytic cracking (FCC) process continued to be the major source of olefins production with minimum CO₂ emissions and high energy efficiency. It produces approximately 60% of today’s total worldwide olefins demands. This communication presents a comprehensive review on the state-of-art of various approaches to enhance olefin productions from FCC process—meeting the ever-growing demand of olefins. It also emphasizes how the petroleum refineries are shifting their focus from transportation fuels to higher production of light olefins. In this regard, FCC is still the key process technology to produce increased volume of feedstocks toward olefins. Zeolite is the active ingredient of FCC catalysts, which also includes a matrix, binder, and filler to enhance the catalyst's physical strength. Apart from the qualities of the catalyst, the FCC unit's performance is dependent on the operating circumstances, which include the feed composition, temperature, residence duration, hydrocarbon partial pressure, and the catalyst-to-oil ratio (CTO). Therefore, it is very important to balance the catalyst composition and set the operating parameters to maximize the light olefins yields, especially propylene. Thus, the structural makeup of FCC catalysts, which includes zeolite Y and ZSM-5 as well as factors including reactor design, operating conditions, and kinetics modeling of olefin yields are all critically reviewed in this article. In addition, recent modifications in zeolite catalyst and its additives are also discussed in detail.

Circular pipe heat exchangers, widely used in process industries, rely on passive heat transfer augmentation techniques like twisted tape inserts to enhance thermal performance. The challenge lies in identifying the optimal insert design. This study applies hybrid multi-criteria decision-making (MCDM) techniques to address this challenge, aiming to identify the best twisted tape insert configuration for maximizing heat exchanger efficiency. For developing the method, twenty-one passive enhancement techniques have been identified. This study employs a holistic approach, considering eight parameters (surface–volume ratio, Nusselt number, friction factor, thermal performance factor, total investment cost, cost per efficiency and CO₂ emissions) across four criteria (geometric, thermo-hydraulic, economic and environmental criteria) to optimize resource utilization while reducing environmental impact and minimizing costs. The Entropy-CRITIC (Criteria importance through inter-criteria correlation) weighing method (ECWM) was employed to find the weights of all parameters, and ranking of alternatives was done by TOPSIS (Technique of order preference similarity to ideal solution), COPRAS (Complex proportional assessment) and CoCoSo (Combined compromise solution) MCDM methods. These hybrid approaches, combining objective weighting with MCDM ranking, facilitated the identification of ideal twisted tape inserts. To ensure the robustness of the MCDM methods, sensitivity analysis, Spearman rank correlation and rank reversal techniques were employed for validation. COPRAS emerged as the most robust MCDM method, indicating cross-cut twisted tape as the optimal solution for heat transfer augmentation. This research demonstrates the effectiveness of MCDM techniques in selecting optimal sustainable passive inserts for enhancing the thermal performance of circular pipe heat exchangers.

This analysis explores natural leading modes represented by logarithmic functions, achieved by imposing four boundary constraints at the ends of an elastic inhomogeneous beam. The beam possessing constant material inertia, is assumed to be uniformly loaded, and is composed of material with variable stiffness. It is sought analytical expressions for beam deflections in terms of logarithmic functions. Our findings demonstrate that such formulae can be derived for a beam under axially uniform load and with spatially distributed flexural rigidity. Subsequently, the beam shapes and material properties for four specific scenarios are identified: free-free logarithmic beam, cantilevered logarithmic beam, simply-supported logarithmic beam, and simply-supported sliding logarithmic beam. Explicit logarithmic beam responses, governed by a limited number of shape parameters, are illustrated graphically using normalized deflections with respect to the maximum deflection. Highly deflected elastic logarithmic modes emerge as a consequence of high flexural rigidity influenced by the uniformly applied transverse load. These elucidated logarithmic beam modes offer potential practical applications in the structural design of functionally graded materials. They also serve as valuable testing platforms for numerical techniques employed in the analysis of more complex beam problems.

Vitreous materials in the form of both relatively homogeneous glasses and composite glass crystalline materials (GCM) incorporating disperse crystalline phases are currently the most reliable wasteforms effectively used on industrial scale for nuclear waste immobilisation. Glasses are stable solid-state materials with a topologically disordered atomic structure in the form of solid solutions, i.e. solutions frozen via vitrification to a solid state without forming regular crystalline phases. Nuclear waste vitrification is attractive because of technological and compositional flexibility enabling hazardous elements to be safely immobilised and providing a glassy material characterised by high corrosion resistance, mechanical and radiation durability, as well as effectively reducing the volume of the resulting wasteform.

Forward osmosis (FO) is a promising technology that can help to recover freshwater from saline and wastewater streams. However, it faces challenges such as reverse solute flux (RSF). RSF is the movement of salts from the draw solution to the feed solution, which can have several negative impacts on FO performance. This paper focuses into the development of machine learning techniques, including MLR, ANN, and ANFIS, to predict RSF in the FO system. Two commercially available membranes (CTA and TFC) were used to avoid the influence of synthesized membranes. The models were evaluated using experimental data obtained from previous lab-scale experiments. The results showed that the ANFIS and ANN models were both accurate, with R² values of 96% and 97.6%, respectively. The ANFIS model performed slightly better than ANN model, while the MLR model displayed inaccurate predictions, with a lower R² (43.46%) and MSE (2.61 × 10^–2) and higher AARE (2.221). The study also identified the most impactful parameters on RSF, such as the DS type, FS concentration, and FS temperature. The study concludes that machine learning techniques can be successfully applied to model RSF in FO systems with high accuracy and recommends their use in the industry to improve the performance of membrane-based systems.

Target detection from UAV perspective has been a very hot task in recent years. Due to the flying height of the UAV, the detection targets in the photographs are dense and small in scale, resulting in little available information and difficulty in feature extraction. And the prediction bias of small targets can have a large negative impact on the calculation of losses. So for better use of UAV, YOLO-HLFE is designed on the basis of YOLOv7. The coordinate attention mechanism is added to the MP downsampling structure to comprise MPFE downsampling structure, which makes full use of the location information of the target and enhances the feature extraction capability of the network. The complete intersection over union (CIOU) of YOLOv7 is combined with the Normalized Gaussian Wasserstein Distance loss (NWD) to constitute the CIOU-NWD loss to mitigate the prediction bias problem for small targets. In addition, in order to make the anchor point of the model closer to the target scale of the UAV perspective, the clustering method of the model is improved and the anchor point is re-clustered. In experiment using the sliced VisDrone2021-DET dataset and SeaDronesSeeV2 dataset, the mAP50 and mAP of YOLO-HLFE on sliced VisDrone2021-DET dataset reach 52.3% and 30.0%, which are 2.8% and 0.9% higher than the baseline, respectively.

The artificial algae algorithm (AAA) is a recently introduced metaheuristic algorithm inspired by the behavior and characteristics of microalgae. Like other metaheuristic algorithms, AAA faces challenges such as local optima and premature convergence. Various strategies to address these issues and enhance the performance of the algorithm have been proposed in the literature. These include levy flight, local search, variable search, intelligent search, multi-agent systems, and quantum behaviors. This paper introduces chaos theory as a strategy to improve AAA's performance. Chaotic maps are utilized to effectively balance exploration and exploitation, prevent premature convergence, and avoid local minima. Ten popular chaotic maps are employed to enhance AAA's performance, resulting in the chaotic artificial algae algorithm (CAAA). CAAA's performance is evaluated on thirty benchmark test functions, including unimodal, multimodal, and fixed dimension problems. The algorithm is also tested on three classical engineering problems and eight space trajectory design problems at the European Space Agency. A statistical analysis using the Friedman and Wilcoxon tests confirms that CAA demonstrates successful performance in optimization problems.

This study examines the effect of different wall temperatures on the vortex-induced vibration (VIV) of a circular cylinder under thermal buoyancy. It addresses a notable research gap by examining how changes in the Richardson number influence VIV, particularly in the context of two-degrees-of-freedom VIV, and mixed convection heat transfer. Numerical analysis is used, combining Euler’s integration approach with a finite volume solver. Validation against mixed convection heat transfer data is carried out for both stationary and sprung cylinders with one-degree-of-freedom VIV. The findings show that increasing the Richardson number for a heated cylinder slows vortex shedding, leading to the establishment of a stable vortex pair and a decrease in Nusselt number oscillation. Within the lock-in zone (4 ≤ U_r ≤ 7), the heat transfer rate decreases by 12.3% at U_r = 5 as the Richardson number climbs from 0 to 1. Conversely, lowering the Richardson number for a cooled cylinder increases vortex shedding, resulting in increased vibrations and Nusselt number amplitude. Even at U_r = 9, VIV stays in the lock-in area when Ri = − 1.

An investigation of sol–gel synthesized pure and V-doped TiO₂ nanopowder was carried out to explore the modification of the optical properties with doping concentration. The phase presence and crystallite size as estimated by XRD and SEM is found to be changing significantly with doping. Moreover, the optical response captured by UV–Vis absorption, Raman and PL spectra demonstrated a change in band gap with increasing doping. The pure sample shows absorption over the entire measured range with a decrease in band gap as doping increases. The Raman vibration modes corresponding to anatase as well as rutile phases were detected. The PL spectra indicate a decrease in peak intensity with doping and the presence of a blue shift as doping concentration increases. The blue shift in PL for the doped sample may be due to the band tailing effect.

This numerical work is pertinent to exploring the effect of variation in momentum flux ratios, and geometrical parameters on discharge coefficient (Cd) of single and multiple row anti-screech hole arrangements which resembles as that of a conventional afterburner. The three-dimensional fluid flow domains of both single hole and multiple row hole configurations have been modelled in ANSYS ICEM CFD 20.0 tool and discretized with hexahedral elements to capture the velocity boundary layers more accurately. Flow physics between core and bypass flow through the anti-screech holes are obtained by solving the governing equations, namely the continuity, momentum in three directions and energy equations through the CFD code. Turbulence is captured by Reynolds averaged Navier–Stokes (RANS) two equation model, namely shear stress transport (SST) k-ω mode of closure. It is observed that Cd value increases in direct proportion to the diameter of the hole in case of single row hole configuration. An interesting fact of higher Cd values have been observed for trailing holes in case of multiple row hole configuration compared to the initial holes. The contours representing the static pressure and velocity along the midplane of the domains have been presented and analysed for exploring more insight into complex physics. The effect of hole diameter at lower and higher momentum flux values have been explored in this study with respect to the operating density, and it has been reported that Cd values for the initial holes are lesser than trailing holes in case of multiple row configuration.