Search Results (438)

Internal diameter atmospheric plasma spraying (ID-APS) commonly employs an inherently inclined nozzle configuration to overcome geometric interference in confined cylindrical components. This non-orthogonal deposition condition breaks the symmetry of the plasma jet and produces asymmetric thickness distributions, making uniform coating formation difficult to control using conventional models developed for planar or external spraying. In this study, a kinematic-based mathematical model was developed from experimentally measured single-path deposition data obtained under representative internal spraying conditions. A skew-normal formulation was introduced to describe the asymmetric cross-sectional profile, and a superposition framework was established to relate kinematics and geometric constraints to coating quality metrics, including mean thickness, profile uniformity, flatness, and lateral distance. The effects of kinematic parameters and workpiece geometric characteristics were systematically analyzed, and the resulting model was implemented on an internal cylindrical surface to predict spatial thickness evolution. Experimental validation was conducted at both macroscopic and microscopic scales through surface reconstruction and cross-sectional microscopy, confirming that the proposed approach can capture the main features of coating buildup and provide reliable estimates of thickness uniformity. The developed framework offers a practical tool for process design and quality control in ID-APS, reducing dependence on empirical parameter tuning and enabling more consistent thickness control on internal surfaces. Full article

Aero-engine predictive maintenance is challenged by heterogeneous operating conditions, complex degradation patterns, and the need for interpretable maintenance alerts rather than solely numerical life estimates. This study investigates a condition-aware data-driven framework for jet engine health assessment using the NASA C-MAPSS dataset, which contains four benchmark subsets (FD001–FD004) with different operating conditions and fault modes. Instead of formulating the task as conventional remaining useful life regression, this study reformulates degradation assessment as a three-class health state classification problem, including Normal, Warning, and Fault. A unified preprocessing pipeline is developed, incorporating condition-wise normalization, first-order differential feature construction, and per-unit sliding window segmentation to reduce operating-condition bias, capture degradation dynamics, and prevent data leakage. Five representative models are evaluated under the same framework, including XGBoost, LightGBM, Random Forest, a context-aware multi-scale temporal attention convolutional neural network, and a bidirectional long short-term memory network. The results show that the proposed framework achieves consistently high classification accuracy across all four subsets, with the best results of 0.9841 on FD001, 0.9764 on FD002, 0.9891 on FD003, and 0.9832 on FD004. In addition, Bi-LSTM outperforms MSTA-CNN on all subsets, for example improving accuracy from 0.9614 to 0.9747 on FD002 and from 0.9773 to 0.9806 on FD004, which is consistent with the importance of long-term temporal dependency modeling for this task. These findings suggest that the proposed framework provides an effective and maintenance-decision-aligned solution for C-MAPSS-based health monitoring, where the three-class alert output offers clearer operational meaning than a single numerical life estimate. Full article

The ski-jump spillway is an energy-dissipating structure that discharges extra water beyond the dam’s capacity. The scour process occurs below spillways due to the collision of the water jet with high energy. It is critical to acquire information on scour holes to improve the dam’s safety and related components. Machine learning (ML) techniques have successfully demonstrated their effectiveness for modeling scour in hydraulic engineering. The present research considers novel approaches of ML models for estimating the scour hole geometries below ski-jump bucket spillways. This study investigates the capability of two novel feature-engineering approaches, namely Stronger Variable Creator Machine (SVCM) and High Correlated Variables Creator Machine (HCVCM), along with Gene Expression Programming (GEP) and their hybrid forms (SVCM+GEP and HCVCM+GEP), which were employed to predict normalized scour depth, scour length, and scour width below ski-jump spillways. Statistical metrics, graphical analyses, the Rank Mean (RM) method, the cross-validation approach, and $U_{95}$ index were used for the evaluation and reliability assessment of the proposed ML models. The results showed that hybrid ML models consistently outperformed individual algorithms. The results indicated that the SVCM+GEP method with $\mathrm{R}\mathrm{M}=1.83$ and $1.50$ had the highest performance compared to other methods for the prediction of ${\displaystyle \frac{Ds}{Dw}}$ and ${\displaystyle \frac{L_s}{D_w}}$, respectively. In addition, the HCVCM+GEP method with $\mathrm{R}\mathrm{M}=1.33$ was the best model for the prediction of ${\displaystyle \frac{Ws}{Dw}}$. In comparison with the conventional regression-based equations and previously reported ML methods, the proposed hybrid approaches improved the prediction results. In addition, the cross-validation method confirmed the robustness and generalization capability of the suggested hybrid ML models. The superior performance of the hybrid models is attributed to their ability to capture complex nonlinear interactions among hydraulic and geometric variables. The developed SVCM/HCVCM+GEP models provide accurate approaches for predicting scour parameters in hydraulic structures. Full article

BL Lacertae objects (BL Lacs) are active galactic nuclei notable for beamed emission generated in the relativistic jets, forming a small angle with respect to our line-of-sight. The broadband spectra of BL Lacs show a two-component spectral energy distribution (SED). The group of high-energy-peaked BL Lacs (HBLs) exhibit their lower-energy SED peak at the UV to X-ray frequencies. Consequently, these objects are generally bright in the 0.3–10 keV band (compared to other blazar subclasses) and allow us to carry out intense timing/spectral studies on the wide range of timescales (from years down to a few minutes). Although X-ray emission of HBLs is widely accepted to have a synchrotron origin (along with the occasional presence of the inverse-Compton component), many problems associated with the jet particle content, their acceleration up to ultra-relativistic energies and unstable mechanisms responsible for the extreme flux/spectral variability still remain to be solved. This review highlights the basic timing and polarimetric and spectral results obtained in the framework of the numerous studies of HBLs in the 0.3–10 keV band, which was covered by the X-ray instruments operating onboard the different space missions. Moreover, the plausible physical processes responsible for the observed HBL features (relativistic shocks, magnetic reconnection, turbulence etc.) are also addressed. Full article

The use of computational fluid dynamics provides an important tool for the design of supersonic ejectors. Within Reynolds/Favre-averaged simulations, the turbulence model plays an essential role in determining results’ reliability. Existing validation studies show general accuracy problems, whose relevance, partially masked in the double-choked regime, becomes fully evident for the single-choked regime. For this flow regime, errors reported in the literature are strongly erratic, reaching magnitudes higher than 50% in terms of global performance. The absence of clear, unified conclusions by different authors motivates the present work, focused on single-choked ejectors. In the first part, the main ejector flow features are discussed, highlighting the importance of adequately reproducing the turbulence response to different shear intensities. To properly address this point, an original analysis is conducted, exploiting data from previous studies on jets and basic shear flows. The developed analysis explains how the prediction of an ejector jet is influenced by the constitutive relationship of eddy viscosity models and by the modelled balance of the turbulent-dissipation rate. The modelling failures of these two elements are discussed for existing models in common use and addressed through the development of a new Consistent Realizable K − ε model. In Part 2, the analyzed models are used to simulate two test cases, with detailed measurements available. Full article

To meet the requirements for passive heat dissipation and self-cleaning of aluminum alloy enclosures used in 5G base-station active antenna units (AAUs), a scalable surface modification strategy involving sandblasting, NaOH etching, and PFTEOS grafting was developed for 6061 aluminum alloy. Microscale rough structures were first constructed by sandblasting, and hierarchical micro/nano structures composed of microscale pits and nanoscale plate-like/coral-like features were subsequently formed through NaOH etching and boiling-water treatment. Finally, a low-surface-energy PFTEOS layer was grafted onto the structured surface to achieve superhydrophobicity. The effects of sandblasting pressure and etching time on surface morphology, chemical composition, wettability, and infrared emissivity were systematically investigated. The results show that sandblasting enhanced infrared emissivity by increasing surface roughness and promoting optical trapping, while NaOH etching further improved emissivity through the formation of hierarchical micro/nano structures and infrared-active AlOOH/Al₂O₃ phases. After PFTEOS grafting, the surface wettability changed from hydrophilic to superhydrophobic, while the high infrared emissivity was maintained. Compared with the untreated aluminum alloy, the modified surface exhibited a remarkable increase in water contact angle from 80.10° to 153.63° and infrared emissivity from 0.0102 to 0.8951. Moreover, the water contact angle remained above 150° after continuous water-jet impact, indicating good preliminary resistance to hydraulic shear. This work provides a feasible surface-engineering route for integrating high infrared emissivity and self-cleaning capability on aluminum alloy surfaces for outdoor thermal management applications. Full article

We proposed a bilateral parallel offset jet model that enables jet vectoring control without the need for an active high-pressure secondary flow. Flow characteristics, including deflection force, wall pressure distribution, and flow structures, were investigated. The evolutions of key flow structures during jet deflection were investigated, including the passive secondary flow, the shear layer, the boundary layer, and the separation bubble. By analyzing the formation, dissipation, and interactions of the key flow structures, as well as their relationship with pressure characteristics, the mechanism of the jet deflection control was further deduced. The fundamental driving force of the jet deflection stems from the unbalanced pressure difference on either side of the jet, and the valve can control the flow rate of passive secondary flow, thereby altering the near-wall pressure on its side and further generating a pressure that propels the jet to deflect. For walls of different lengths, at a moderate wall length, where L* = 1.5, with the valve controlling the passive secondary flow, a maximum jet vectoring angle of 6.4° can be continuously achieved at a low Reynolds number. Within the range where 20% < δ_v < 100%, the nonlinear error of jet vectoring control is 5.7%. At a short wall length, where L* = 0.5, the driving force generated by the valve to deflect the jet is insufficient, and the maximum vector angle is 0.3°. For longer walls, the impact of the jet against the trailing edge of the wall obstructs jet deflection; therefore, extending the wall is not conducive to jet vectoring control. Featuring a non-expanding wall structure, the bilateral parallel offset jet model provides a new thrust vectoring control scheme characterized by a compact afterbody, no need for a high-pressure secondary air source, and a simple structure. Full article

This study presents a computational investigation of an ingenious Twain co-flow jet (CFJ) airfoil system featuring independently controlled micro-compressors for active flow control. Unlike conventional single-point or synchronously controlled CFJ configurations, the proposed system enables independent tuning of jet momentum coefficients at multiple locations along the airfoil surface. Reynolds-averaged Navier–Stokes (RANS) simulations are employed to analyze the impact of this independent control strategy on boundary layer behavior, lift enhancement, stall delay, and aerodynamic efficiency. The objective of this work is to establish a quantitative relationship between jet momentum distribution and aerodynamic performance, while also evaluating the associated energy consumption characteristics of the system. This technology works incredibly well at low speeds, significantly increasing stall angles and lift coefficients; at higher speeds, it uses less energy and improves the lift-to-drag ratio. Twain configuration offers more accurate control over pressure gradients, enabling adaptive performance during all flight phases. In this work, a Twain-compressor-integrated CFJ system is presented, in which jet momentum coefficients (Cμ = 0.05 and 0.1) are dynamically controlled by two independently controlled micro-compressors across various flight conditions (11.34 m/s, 138 m/s, 208 m/s). By optimizing injection at the leading edge and mid-chord—paired with synchronized suction at strategic withdrawal points—the system achieves precise boundary layer control with near-zero net mass flux. Modulating Cμ improves aerodynamic efficiency while limiting the total propulsion energy expenditure, allowing a smooth transition from high-lift takeoff to low-drag cruise, according to computational fluid dynamics (CFD) analysis. Due to these developments, Twain-compressor CFJ systems are now a scalable option for aircraft that need to be extremely aerodynamically versatile without sacrificing efficiency. Full article

Binder jetting relies on the infiltration of binder droplets into a porous powder bed, where the spatial arrangement of droplets critically influences feature formation and structural integrity. In particular, the role of droplet spacing in regulating infiltration behavior remains insufficiently understood. In this study, droplet infiltration is investigated using a reconstructed three-dimensional powder bed combined with a Volume of Fluid (VOF) model. Both single- and dual-droplet configurations are examined to isolate the effect of droplet spacing on spreading, merging, and capillary-driven penetration. The results show that droplet spacing governs the redistribution of liquid flow between lateral spreading and vertical infiltration. Three distinct regimes are identified as spacing decreases: independent infiltration at large spacing, cooperative merging at intermediate spacing, and over-penetration at small spacing. These regimes reflect a transition from isolated droplet behavior to strongly coupled infiltration within the pore network. An optimal spacing of approximately 150 μm is found to balance spreading and penetration, enabling continuous deposition with controlled infiltration depth. Experimental measurements show good agreement with numerical predictions, with an average deviation of 8.66%. The present study clarifies the mechanism by which droplet spacing controls infiltration behavior and provides practical guidance for parameter selection in binder jetting processes. Full article

In this study, a femtosecond laser beam is delivered to metal wire targets to generate suprathermal electron jets reaching energies of several hundreds of keV. During the process, it is observed that the mirror-imaging distribution of the beam focus with respect to the surface of the target displays highly asymmetric features and different dynamic responses. Especially, the exterior focus exhibits an extraordinary polarity reversal of the macroscopic current, while the interior focus behaves ordinarily. The former is attributed to the strong field at the focal point outside the surface, causing the secondary ionization and driving electrons back to the target, thereby reshaping the distribution of these high-energy hot electrons and the morphology of plasma jets. A numerical model is proposed to simulate the experimental observation and interpret the unexpected phenomenon. Furthermore, the particle-in-cell algorithm is also implemented to verify the results and present more details. This study seeks to emphasize the role of focal position in regulating the photoemission process, which may offer a fresh perspective for research in laser–material interactions and dynamics. Full article

Recently, the coprecession of both the accretion disk and the jet formed following the tidal disruption event associated with the optical transient AT2020afhd, driven by a supermassive black hole of almost ten million solar masses, were independently measured in both the X and radio bands, respectively, showing a periodicity of nearly 20 days over about 300 days. An analytical model of the general relativistic gravitomagnetic Lense-Thirring precession of the effective orbit of a fictitious test particle revolving about a spinning primary can explain the observed precessional features. It yields allowed regions in the system’s parameter space which, as far as the hole’s dimensionless spin parameter is concerned, are essentially in agreement with those obtained in the literature with general relativistic magnetohydrodynamic simulations. The present analytical approach can be extended to include the precession due to the hole’s quadrupole mass moment as well. It breaks the degeneracy in the allowed regions occurring for negative and positive values of the spin parameter when only the Lense-Thirring effect is considered. The best estimate for the hole’s mass yields the range 0.185–0.215 for the dimensionless spin parameter. Using the same strategy with the gravitomagnetic frequency for an extended disk of finite size with a parameterized power-law mass density yields to distinct, generally non-overlapping allowed regions for each value of the power-law index adopted. Some of the assumptions on which this work is based are critically examined. Full article

Laser-induced microjet-assisted ablation is an emerging technology in the field of laser processing. However, the influence of solid boundaries on jet behavior and the associated material removal mechanism remains unclear after observing and analyzing the ablation process. To address this, the present study systematically investigates the effect of the incidence angle on the processing efficiency and material removal mechanism in laser-induced microjet ablation. By controlling the laser power and liquid layer thickness, the dynamic behavior of the microjet, material removal performance, and surface morphology evolution under different inclination angles were explored. Based on video analysis and OpenCV processing, the regulation of jet morphology and impact mode by the incidence angle was revealed. Combined with white light interferometry and ultra-depth-of-field three-dimensional microscopy, the ablation depth and material removal rate were quantitatively characterized. The results showed that under normal incidence, the maximum material removal rate of 0.092 mm³/s was achieved at 9 W, while further increases in power led to a decrease in removal rate due to bubble aggregation. When the sample was tilted to 15°, the material removal rate reached 0.163 mm³/s, representing a 106.30% improvement compared to that at 0°, and the ablation depth also peaked with an average maximum depth of 12.32 ± 0.58 μm and a single-point maximum of 54.36 μm. Furthermore, scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) were employed to elucidate the microstructural features and elemental distribution under different process parameters. Through multi-parameter experiments, this study achieved process parameter optimization and clarified the material removal mechanism influenced by different incidence angles, providing both a process reference and theoretical basis for efficient micro-machining of aerospace materials. Full article

In response to the significant challenges posed by ice accumulation and contamination from various fluids in complex operating conditions for metallic materials, this study utilises picosecond laser precision machining to develop a ‘slippery surface’ featuring a micro-channel network structure. The core innovation of this study lies in the use of laser-machined micrometre-scale array textures to overcome the limitations of traditional isolated pores. These globally interconnected micro-channels serve as highly efficient reservoirs and dynamic transport channels for lubricants, significantly enhancing the interfacial capillary locking force of the lubricant. Experimental results demonstrate that this unique network geometry endows the surface with exceptional fluid replenishment and self-healing properties, enabling it to exhibit outstanding broad-spectrum hydrophobicity towards various fluids—including water, crude oil and ethanol (surface tension range: 17.9–72.0 mN m⁻¹)—with sliding angles consistently below 12°, whilst effectively slowing the dehydration and solidification processes of biological fluids. At a low temperature of −15 °C, the surface achieved an ice formation delay of up to 286 s, with an ice adhesion strength of only 33.9 kPa, ensuring that accumulated ice could be spontaneously detached under minimal external force. Furthermore, the micro-channel network structure serves as a key protective mechanism against mechanical wear, maintaining robust slippery properties even after three hours of high-pressure water jet scouring (Weber number of 300). This reliable interface, achieved through structural management, provides an efficient and scalable platform for addressing the all-weather anti-icing and antifouling requirements of outdoor infrastructure. Full article

Aiming to address the problem of extracting the remote sensing FTIR spectral characteristics of the hot jet of a certain type of aero-engine under different working conditions, this paper proposes a feature construction algorithm for the remote sensing FTIR spectral characteristics of the aero-engine hot jet based on the fusion of the original spectral features and the deep spectral features. The infrared spectrum was collected at a distance of 280 m, covering the spectral range of 2.5–15 μm with a resolution of 1 cm⁻¹. The Neighborhood–Autoencoder Integration Dual-Branch Network (NAIDN) feature construction algorithm is proposed. This algorithm contains a neighborhood integration branch and an autoencoder branch. The neighborhood integration branch converts the radiation intensity values of discrete wavenumber points into local energy aggregation features through a sliding window, accurately extracting the key physical information in the original spectrum. The autoencoder branch uses a three-layer fully connected neural network architecture to mine the deep spectral features of the spectral data. The algorithms of the two branches not only retain the physical interpretability of spectral analysis but also capture the multi-parameter coupling information hidden in the hot jet spectrum through the representation learning ability of the autoencoder, achieving feature fusion across spatial dimensions. Compared with traditional feature construction algorithms, the dual-branch feature construction algorithm proposed in this paper has stronger comprehensive representation capabilities. The content of carbon dioxide (CO₂) and cyanide groups (-C≡N) in the hot jet under different operating conditions varies significantly. In the experiment, an unsupervised clustering algorithm, the Agglomerative Clustering classifier, is selected, and the classification accuracy of the features extracted by the algorithm in this paper reaches 92.97% on this classifier, thereby verifying the effectiveness of the algorithm in this paper. Full article

To clarify the effect of surface characteristics on the interfacial properties of T1100-grade carbon fiber (CF)/bismaleimide (BMI) composites, three CFs (F1, F2, and F3) with different surface treatments and sizing agents were studied. Surface physicochemical properties and sizing–resin reaction behavior were characterized; nano-infrared spectroscopy was innovatively used to quantify interfacial structure. The correlation among surface features, interfacial structure, and mechanical properties was established. All dry-jet wet-spun T1100 CFs show smooth surfaces with similar roughness, and mechanical interlocking contributes little to interfacial adhesion. F3 possesses the highest active carbon, oxygen content, and epoxy value. Its sizing agent exhibits strong reactivity with BMI, forming a ~200 nm thick interface and the highest interfacial shear strength (IFSS) of 95.9 MPa. Constructing a “thick and strong” interface promotes shear failure from brittle to tough, significantly enhancing 90° tensile and interlaminar shear strength (ILSS). This work provides guidance for interface design and engineering applications of T1100/BMI composites in aerospace primary load-bearing structures. Full article