Arabian Journal for Science and Engineering最新文献

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.

Automatic inspection of metal surfaces for defects has gained increasing interest in the quality control of industrial products. However, this poses a challenging problem due to the complexity of industrial environments. Traditionally, defect detection relies on image processing or shallow machine learning. Still, these methods are limited to detecting defects only under specific conditions: clear defect outlines, strong contrast, low noise, limited scales, or specific lighting conditions. This work proposes a two-step approach for the automatic detection of metallic defects in real industrial scenarios. The approach focuses on accurately localizing and classifying defects within input images. We employed six convolutional neural networks (CNNs): GoogleNet, Squeezenet, Resnet18, Resnet101, Alexnet, and InceptionV3, to categorize images from the NEU Metal Surface Defects into different varieties of defects: crazing, inclusion, patches, pitted, rolled, and scratches. The approach involves training the CNNs using the Adam optimizer to classify defects. The dataset is preprocessed for color, scaled, and augmented in both phases. The ResNet18 outperformed the other networks, achieving an accuracy (AC%) of 99.77% for (K=10). The proposed approach successfully detected surface flaws in metals under various industrial scenarios. The results are reliable and accurate to detect defects in metal surfaces when compared to existing techniques.

This study investigates the behavior of free vibrations in a variety of porous functionally graded nanobeams composed of ferroelectric barium-titanate (BaTiO₃) and magnetostrictive cobalt-ferrite (CoFe₂O₄). There are four different models of porous nanobeams: the uniform porosity model (UPM), the symmetric porosity model (SPM), the porosity concentrated in the bottom region model (BPM), and the porosity concentrated in the top region model (TPM). The nanobeam constitutive equation calculates strains based on various factors, including classical mechanical stress, thermal expansion, magnetostrictive and electroelastic properties, and nonlocal elasticity. The study investigated the effects of various factors on the free vibration of nanobeams, including thermal stress, thermo-magneto-electroelastic coupling, electric and magnetic field potential, nonlocal features, porosity models, and changes in porosity volume. The temperature-dependent mechanical properties of BaTiO₃ and CoFe₂O₄ have been recently explored in the literature for the first time. The dynamics of nanosensor beams are greatly influenced by temperature-dependent characteristics. As the ratios of CoFe₂O₄ and BaTiO₃ in the nanobeam decrease, the dimensionless frequencies decrease and increase, respectively, based on the material grading index. The dimensionless frequencies were influenced by the nonlocal parameter, external electric potential, and temperature, causing them to rise. On the other hand, the slenderness ratio and external magnetic potential caused the frequencies to drop. The porosity volume ratio has different effects on frequencies depending on the porosity model.

In this work, both experimental and theoretical investigations were carried out on TiO₂ thin film deposited on n-Si by a direct current (DC) magnetron sputtering system. Post-deposition annealing of the film was conducted at 500 °C and 800 °C for 90 min using a high temperature furnace. Experimental results, obtained through x-ray diffraction, showed amorphous nature of the as-deposited TiO₂ film. However, after annealing at 500 °C, a diffraction peak corresponding to anatase TiO₂ appeared. Further increasing the annealing temperature to 800 °C resulted in an improvement in the crystallinity of the film. Surface roughness of the TiO₂ film was investigated using atomic force microscope. The root-mean square value of the surface roughness increased with the rise in annealing temperature. The increase in surface roughness was attributed to increase in the crystallite size of the film. The band gap of the TiO₂ was examined using ultraviolet–visible reflectance spectroscopy analysis. The band gap was decreased with the increase of annealing temperature. The electrical resistivity of the film decreased after the annealing. Theoretical investigations revealed tetragonal structure of TiO₂ and a decrease in its band gap with an increase in the annealing temperature which was associated with the quantum size effect in the material. The static refractive index (n_o) for un-annealed and annealed films (500, 800 °C) were found to be 2.48, 2.69 and 3.03 respectively. Similarly, absorption peaks were also affected by the increase in the annealing temperature. The theoretical investigations validated the experimental results of this work.

In this study, a novel robust design methodology that successfully meets the performance and security criteria for substitution-boxes (s-boxes), critical component in block cipher systems, is proposed. Unlike traditional methods providing low-level randomness, the proposed method utilizes physical true randomness as the entropy source, significantly improving the robustness and effectiveness of the s-box design. Phase noise (jitter) occurring on ring oscillators (ROs) is used for true randomness inputs with high security and unpredictability properties in the proposed method. The success of the proposed method is evaluated by considering key performance metrics of s-boxes such as bijectivity, strict avalanche criterion (SAC), bit independence criterion (BIC), nonlinearity (NL), and differential probability (DP). In the novel method, including the integration of the secure hashing algorithm (SHA)-256 hash function for cryptographic usage adequacy of the noise signal, 106.75 NL, 0.4995 SAC, and 105.7 average BIC-NL values can be obtained for s-boxes without any additional optimization process. Considering the low DP value, the analysis results confirm that the s-boxes produced by the proposed method can provide remarkable resistance against linear and differential cryptanalysis scenarios. Numerical findings also show that the proposed s-boxes are competitive and superior compared to other s-box designs in the literature. In conclusion, we believe that the methodology producing robust and reliable s-box solutions for block cipher systems contains important contributions inspiring future research regarding design principles.

Double-suction centrifugal pumps are ubiquitous in industrial settings and daily life. As energy equipment technology advances, demands for their efficiency and stability continue to rise. This study presents an optimization design approach for such pumps. Employing the Latin cube experimental design method, we optimized five key geometric design parameters of a double-suction centrifugal pump impeller, aiming to maximize efficiency (η). The regression equation yielded predicted impeller efficiency and head of 84.5% and 23.95 m, respectively. Efficiency and head deviations were minimal (0.04% and 2.75%), both within 5%, validating the applicability of the optimization design method combining Latin cube sampling and response surface modeling. The optimized design parameters for the double-suction centrifugal pump are: β_1h = 31.4, β_1s = 15.2, β_2h = 20.2, β_2s = 20.2, φ = 105.1. Numerical simulation results aligned closely with model test data (error < 4%), confirming the accuracy and reliability of the numerical simulation method. The optimized impeller model enhanced pump efficiency by 1.3%, particularly under low flow conditions (improvement > 3%), expanding the pump's efficient operation range. Additionally, the novel Ω (Omega) vortex method effectively captured internal vortex phenomena. Comparative analysis revealed strong static and dynamic interference at the inter-tongue region, dominating pressure pulsation. The optimized model eliminated low-frequency radial force pulsation and reduced force fluctuations under all working conditions. The improved matching between the impeller and chambers led to more uniform and stable flow. This study offers valuable insights for further optimizing double-suction centrifugal pump designs.