Search Results (21,184)

Flow-field parameters of bow shocks in high-altitude rarefied flow are fundamental for seeker radiation noise evaluation and thermal-protection design. The conventional direct simulation Monte Carlo (DSMC) method is computationally expensive, making it difficult to achieve real-time prediction and massive sample generation of flow-field parameters. This paper presented a surrogate model adopting a convolutional neural network (CNN) to rapidly predict bow-shock reactive flow-field parameters. A blunt body with a nose radius of 0.1–1.0 m was investigated. The Latin hypercube sampling methodwas used to construct a sample space spanning altitudes of 80–150 km and Mach numbers of 15–35. DSMC-calculated data was segmented into training and test sets at a ratio of 4:1 and verified by the bow-shock ultraviolet experiments. An encoder–decoder CNN with a parallel decoder strategy was established to develop a bow-shock reactive flow surrogate model (CNN-BS) and conduct error evaluation. The results show that the mean absolute percentage errors for temperature, velocity, pressure, and nitric oxide number density are below 8%, with coefficients of determination close to 1. The average prediction time is 0.5 s, enabling online data generation. The CNN-BS model provides efficient support for radiation-noise evaluation and thermal-protection design of hypersonic blunt bodies. Full article

Infra-hepatic inferior vena cava (IVC) balloon occlusion is an effective strategy for reducing intraoperative bleeding during precision liver surgery, yet rapid balloon inflation can produce abrupt transient deviations in downstream venous pressure that are not yet quantitatively characterized. Current practice relies on operator experience, with no quantitative framework to balance occlusion efficacy against downstream pressure safety. A computational fluid dynamics (CFD) model of the balloon-occluded IVC was developed in ANSYS 2025 R2 with two-way fluid–structure interaction (FSI), Carreau–Yasuda blood rheology, and a balloon described by an Ogden hyperelastic model; the flow regime was laminar (Re ≈ 254). Reduced-order ARX models of four input–output subsystems were identified from CFD-generated data, and a model predictive control (MPC) strategy was formulated to penalize downstream pressure overshoot through a weighted cost function. The identified models achieved training normalized root-mean-square errors of 0.0363 to 0.1164 and out-of-sample validation errors of 0.1224 to 0.2381. Conventional sigmoid inflation induced a 45.82% overshoot in downstream pressure (P_aft); the optimal input signal (q = [⁰,¹,⁰,⁰], λ = 0.1) reduced this to 6.05%, a reduction of 39.77 percentage points, while preserving >90% flow occlusion at U_F = 3 × 10⁴ Pa. The proposed framework offers a quantitative basis for balloon-occlusion device design that limits downstream pressure overshoot, motivating subsequent benchtop, ex vivo, and in vivo validation. Full article

The vibration characteristics of clamped–clamped Alumina–Steel axially functionally graded (AFG) fluid-conveying Timoshenko pipes are investigated using a physics-based generalized integral transform technique (GITT) benchmark and a multi-layer perceptron (MLP) surrogate trained on GITT data. Parametric GITT sweeps over the power-law gradation index k, dimensionless flow velocity u, and aspect ratio $L/D$ quantify how axial material gradation controls the first two natural frequencies (${\omega }_1$, ${\omega }_2$) and the maximum vibration deflection ($y_M$): increasing k reduces ${\omega }_1$ and ${\omega }_2$; on u-sweeps at $L/D=50$, larger k also increases $y_M$ and lowers the critical flow velocity, whereas on $L/D$-sweeps at $u=3.0$, $y_M$ decreases with k. A feedforward MLP surrogate fitted to $N_{\mathrm{s}}=336$ GITT samples via an interior block-wise train–test split and three independent networks with output-specific preprocessing achieves $R^2>0.99$ on held-out data, with maximum relative errors below 9%, and reproduces representative GITT parametric curves in overlay validation. After one-time offline training, MLP inference is orders of magnitude faster than online GITT runs, enabling large-scale global sensitivity analysis based on Sobol indices, SHAP values, and partial dependence plots; these identify u as the dominant influence on the modal responses, while SHAP ranks k first for ${\omega }_2$. The physics-based GITT and MLP surrogate workflow combines high-fidelity material–structure benchmarking with efficient metamodeling for design optimization, reliability assessment, and sensitivity-driven screening of Alumina–Steel AFG fluid-conveying pipes. Full article

Flooding in the Kathmandu Valley has intensified in recent years due to rapid urbanization, unregulated land-use change, and insufficient drainage infrastructure. Existing flood hazard assessments are often based on low-resolution datasets and lack proper field validation. This study presents an integrated flood modeling framework that combines Unmanned Aerial Vehicle (UAV)-derived Digital Elevation Models (DEMs), field-based flood measurements, and hydrological simulations to assess urban flood hazards in the Bagmati-Nakkhu confluence, Nepal. High-resolution UAV-derived DEM and field survey data, including flood marks and high-water levels, were used as the foundation for the analysis. Hydrological modeling was conducted using the Hydrologic Engineering Center—Hydrologic Modeling System (HEC-HMS) to estimate the peak discharges of the Nakkhu River (2000–2024), which were then used to derive design flows for return periods of 5 to 150 years using the Gumbel distribution. These flows were used as boundary condition inputs for the Hydrologic Engineering Center—River Analysis System (HEC-RAS) to simulate flood depth and inundation extent under different scenarios. Flood extents for the 27 September 2024 event were derived from Sentinel-2 imagery and validated against surveyed flood marks. Additionally, land use/land cover (LULC) mapping based on UAV data was used to support flood impact analysis. The results show that flood depths ranged from approximately 0.5 m to 2.8 m, with inundation areas increasing by 35–50% under extreme rainfall. Model validation demonstrated strong agreement with simulated results, with deviations generally within ±0.3–0.5 m. Scenario analysis further indicates that urban expansion significantly increases runoff and flood extent, particularly in low-lying areas near the river confluence. Socio-economic exposure analysis for the 27 September 2024 event indicates that approximately 2569 residents (56.4% of the study zone population) and 4.011 km (77.42%) of the local road network were exposed to inundation. Overall, the results demonstrate that integrating high-resolution UAV data, field observations, and hydrological modeling greatly improves the accuracy and reliability of flood hazard assessments in data-scarce urban environments. Full article

Objective: This study aims to explore the differences in chemical composition among Tibetan medicinal Rhododendron species and their potential correlation with anti-complement activity, with the goal of identifying promising medicinal resources. In Tibetan medicinal practice, the two groups of large-leaved Rhododendron (Tibetan: Dama) and small-leaved Rhododendron (Tibetan: Tali) are often used interchangeably despite unclear chemical and taxonomic bases. By comparing chemical profiles and evaluating anti-complement effects, this investigation seeks to provide preliminary scientific evidence for clarifying medicinal origins and facilitating the targeted development of high-quality resources. Methods: Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) was employed to analyze seven Rhododendron samples. Separation was achieved on a Waters CORTECS UPLC C18 column (2.1 × 100 mm, 1.6 μm) using a gradient mobile phase system consisting of acetonitrile and 0.1% formic acid in water, at a flow rate of 0.3 mL/min and a column temperature of 30 °C. Data were acquired in both positive and negative electrospray ionization (ESI) modes. Compound identification was performed using Peakview 1.2 software by comparison with databases and literature. Grey relational analysis and partial least squares (PLS) regression, combined with 5000 bootstrap resampling iterations, were applied to establish spectrum–effect relationships and to screen for characteristic peaks potentially associated with anti-complement activity. Results: A total of 52 compounds were tentatively identified, including flavonoids (e.g., hyperin, isoquercitrin, taxifolin-3-O-arabinoside), terpenoids (e.g., grayanotoxin I/III), and chromanes (e.g., anthopogochromane series). The CH₅₀ values of the ethanol extracts ranged from 179.29 to 579.47 μg/mL, with Rhododendron principis showing the strongest activity (179.29 ± 11.86 μg/mL), followed by Rhododendron vellereum (198.61 ± 7.93 μg/mL). Spectrum–effect analysis revealed that four unidentified peaks (F5315, F5822, F5368, F5991) exhibited negative regression coefficients and VIP means close to or above 0.8, suggesting a possible positive correlation with anti-complement activity. Among these, F5315 (VIP = 0.909), F5822 (VIP = 0.877), and F5368 (VIP = 0.834) showed relatively higher values and were considered preliminary candidate peaks warranting further investigation. Conclusions: This study tentatively identifies 52 compounds from the ethanol extracts of seven Tibetan medicinal Rhododendron species and reports their anti-complement activities. The findings reveal chemical distinctions between the large-leaved (Dama) and small-leaved (Tali) groups, offering a potential chemical basis for species differentiation and quality evaluation. Furthermore, four unknown peaks were preliminarily screened through spectrum–effect analysis as potential anti-complement candidates, which may serve as a foundation for future activity-guided isolation and quality marker studies. Full article

To mitigate the negative impacts of traditional rigid revetments on river ecosystems, this study focuses on perforated plate grid revetments, aiming to reveal the hydrodynamic mechanisms and parameter collaborative optimization pathways that simultaneously achieve anti-scour stability and ecological water exchange. A series of flume scour tests were conducted, combined with high-resolution large eddy simulation (LES) validated by experimental data, to systematically analyze the regulatory effects of key design parameters—such as opening ratio and longitudinal offset angle—on near-bottom flow velocity attenuation, vortex structures, and water exchange efficiency. The results indicate that a prototype parameter combination of 0.25 m grid height and 0.50 m plate grid spacing can reduce local scour depth by about 30% and enhance vertical exchange through the synergy of jetting from the openings and internal vortices. The longitudinal offset of adjacent holes may enhance the transverse water exchange but may also significantly reduce the longitudinal exchange intensity; hence, further research is needed. A hole-to-baffle height ratio greater than 0.40 is identified as a critical threshold for improving exchange efficiency. This study proposes a collaborative design framework in which grid spacing controls scour safety and aperture parameters regulate exchange functions, providing an experimental basis for the precise design and performance enhancement of ecological revetments. Full article

A robust evaluation of predictive uncertainty is essential for deploying machine learning models in high-risk sectors. While various techniques such as Gaussian Processes and Bayesian Neural Networks have been considered to address model uncertainty, the measurement uncertainty associated with input data, particularly regarding heteroscedasticity and autocorrelation, is often overlooked. This work introduces the Generalized Least Squares Support Vector Machine (GLS-SVM), a kernel-based regression model designed to integrate the full variance–covariance matrix of the response variable into the training process. A GUM-consistent methodology was developed for evaluating prediction uncertainty, including a correction for model bias. The model’s performance was validated against standard Least Squares Support Vector Machines (LS-SVMs) and Gaussian Processes (GPs) through two case studies: a simulated regression problem with correlated data and the calibration of a mass flow controller. Performance was quantified using a comparability index ($C_{\mathrm{index}}$), defined as the absolute error of the prediction weighted by its expanded uncertainty. Results demonstrated that, in the simulated case study, the GLS-SVM achieved a $C_{\mathrm{index}}$ consistently below 0.65, indicating that its predictions are statistically consistent with the ground truth. In contrast, competing models significantly exceeded unity, with peak values near 8, indicating a failure to provide physically consistent estimations. For the calibration of the mass flow controller, the GP models produced uncertainties one to three orders of magnitude smaller than the measurement uncertainties, whereas GLS-SVM yielded uncertainties that were more physically consistent with the underlying measurement process. Eventually, the proposed approach offers a versatile, metrologically informed framework for data-driven regression tasks where measurement covariance information is available and rigorous uncertainty quantification is required. Full article

In mountainous river basins, groundwater systems are sustained by complex recharge processes and geological heterogeneity, making groundwater flow simulation challenging in data-scarce regions where hydrological inputs are often assumed to be spatially uniform. This study developed a heterogeneous geological model of the Kofu Basin, Japan, using multiple boreholes and simulated the groundwater flow by integrating MODFLOW with climate-driven recharge outputs from SWAT+. Simulated groundwater flow was evaluated against findings from previous stable isotope studies to assess the plausibility of the simulated recharge system. After calibration, the model performance improved substantially: RMSE decreased by 91.28%, MAE decreased by 84.38%, and NSE increased from 0.9530 to 0.9996. Independent validation showed good regional agreement between observed and simulated groundwater heads (R² = 0.9307; NSE = 0.9254), although RMSE and MAE remained relatively high at 32.70 m and 19.76 m, respectively, suggesting remaining uncertainty in local-scale groundwater head simulation. Simulated velocity vectors indicated localized shallow flow and more coherent regional basinward flow in the deeper aquifer. This pattern is consistent with the interpretation that mountain-derived recharge contributes to the deeper regional groundwater system. The results highlight the value of combining hydrogeological models and geochemical evidence to support recharge-process interpretation in complex mountainous basins. Full article

The glymphatic system has been proposed as a brain-wide pathway that promotes the exchange between cerebrospinal and interstitial fluids and facilitates the clearance of metabolic waste products, including amyloid-β and tau proteins. Diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) has emerged as a non-invasive magnetic resonance imaging technique proposed to indirectly assess glymphatic-related fluid dynamics. This systematic review evaluated the methodological consistency and clinical applicability of the ALPS index in neurodegenerative diseases. A structured search of PubMed (MEDLINE) and Web of Science identified human studies published up to January 2026 investigating DTI-ALPS in neurodegenerative conditions. Data regarding study populations, MRI acquisition parameters, image-processing methods, statistical approaches, and clinical associations were extracted and synthesized. Ten studies met the inclusion criteria. Across studies, lower ALPS index values were generally associated with cognitive impairment, amyloid burden, and disease severity, particularly in Alzheimer’s disease. Several studies incorporated multimodal biomarkers, including amyloid positron emission tomography and cerebrospinal fluid markers, thereby improving the biological interpretation of DTI-ALPS findings. However, substantial methodological heterogeneity was identified across studies, including variability in region-of-interest placement, diffusion acquisition protocols, and image-processing pipelines. Furthermore, the interpretation of diffusivity metrics as direct measures of glymphatic flow remains controversial. Current evidence suggests that DTI-ALPS may represent a promising non-invasive imaging marker of glymphatic-related alterations; however, its biological specificity and clinical applicability remain insufficiently established. Standardized acquisition protocols, harmonized analytical pipelines, and longitudinal multicenter studies are required to clarify its role in neurodegenerative disease research. Full article

To study the soil moisture dynamics and rainfall infiltration characteristics of karst sloping farmland and their driving factors, an abandoned farmland was selected for this study, and five monitoring points (from the foot, S1, of the slope to the top, S5) were set along the terrain gradient. The volumetric water content data of the 0–40 cm soil layer was obtained through in situ monitoring for one year. The infiltration characteristics were quantified in combination with a staining tracer test, and the soil properties were determined. The results showed that the soil moisture content increased with the deepening of the soil layer, and there was significant slope differentiation. The moisture content in the downhill slopes (S1, S2) was significantly higher than that in the uphill slopes (S4, S5), and the annual average value of S5 was 27.4% lower than that of S1. The moisture difference (Δθ, the difference in moisture content between hillslope and flatland) changed from positive to negative from the foot of the slope to the top, indicating that moisture was transported downward along the slope surface. A dye tracer showed that from S1 to S5, the water transport pathway gradually shifted from exhibiting deeper vertical penetration and narrower lateral spread to showing shallower vertical penetration and wider lateral spread. The preferential flow index decreased from 46.6 ± 2.3% to 34.7 ± 2.1%, indicating a progressive reduction in rapid vertical channeling, while the lateral flow index reached its peak (21.4 ± 2.7%) in the middle of the slope (S3), suggesting enhanced horizontal water redistribution at this position. Correlation analysis indicated that soil bulk density was extremely significantly negatively associated with infiltration capacity, while capillary porosity, non-capillary porosity, total porosity, organic matter, and high aggregate content were extremely significantly positively associated with infiltration capacity. These results revealed that the topographic gradient affected soil moisture and water infiltration paths by regulating soil physical properties in this karst forest ecosystem. It should be noted that the research results are only applicable to one slope and should not be directly extended to all karst slope agricultural landscapes. Full article

In this study, double-pass hot compression tests were conducted to systematically investigate the effects of hot deformation parameters on the static recrystallization (SRX) behavior of SA-508M Gr.3 steel used for nuclear reactor pressure vessels. The deformation temperatures were set to 950, 1050, and 1150 °C, with strain rates of 0.01, 0.1, and 1 s⁻¹. The first-pass strains were 0.05, 0.10, and 0.15; the inter-pass time was fixed at 60 s; and the second-pass strain was maintained at 0.05. Based on the experimental data, a kinetic model describing SRX softening behavior was established. The activation energy for SRX was determined to be 81.45 kJ·mol⁻¹, and the Avrami exponent was 0.5742. The characteristic time for 50% recrystallization (t_0.5) was quantified under different deformation conditions. In addition, the microstructural evolution of SRX after double-pass hot compression was characterized using electron backscatter diffraction (EBSD). The results show that increasing the deformation temperature and strain rate leads to opposite trends in the flow stress during double-pass deformation, with the flow stress decreasing with temperature and increasing with strain rate. Meanwhile, inter-pass static softening is enhanced, resulting in a pronounced stress drop during the second pass. An increase in the first-pass strain further intensifies the stress drop and enhances the extent of SRX. EBSD analysis reveals consistent microstructural evolution: with increasing deformation temperature, strain rate, and the first-pass strain, the misorientation distribution shifts from low-angle grain boundaries (LAGBs) to high-angle grain boundaries (HAGBs), indicating an increased degree of SRX. These findings provide a theoretical basis and experimental support for process parameter optimization and engineering applications of SA-508M Gr.3 steel. Full article

Precast multi-girder bridges are widely utilized in highway infrastructure but are susceptible to transverse connection deterioration, which can lead to single-girder load-bearing failures. Existing structural health monitoring methods based on the correlation of total dynamic strain responses often fail to identify early-stage damage due to the static masking effect, where dominant, in-phase quasi-static components overshadow subtle, damage-sensitive dynamic features. To overcome this limitation, this paper proposes a novel condition indicator based on the correlation of high-frequency dynamic strain increments. An online streaming processing pipeline is developed, incorporating automated single-vehicle crossing event extraction, frequency-targeted signal decoupling, and indicator smoothing. Theoretical derivations on a dual-beam model demonstrate that the proposed indicator is a structural-intrinsic metric, exhibiting high sensitivity to joint stiffness while remaining robust against variations in vehicle weight and speed. Numerical simulations on an 8-slab finite element bridge model under stochastic traffic flow further verify the effectiveness of the framework. Results indicate that the proposed indicator can localize both progressive degradation and sudden brittle failures. Additionally, the method maintains reliability down to a signal-to-noise ratio of 30dB and robustness to hyper-parameter selection. While the current framework is established based purely on numerical validation and has not yet been tested using real bridge strain data, it shows numerical feasibility and provides a solid theoretical and algorithmic foundation for the automated condition evaluation of precast multi-girder bridges, supporting future field validation for both long-term maintenance and emergency response. Full article

Growing interest in transporting hydrogen via natural gas pipelines highlights the need to understand flame characteristics during accidental leakage. However, limited literature is available on addressing the flame horizontal projection length of hydrogen-blended natural gas jet fires under inclined conditions. Therefore, a series of experiments was conducted to investigate inclined H₂/CH₄ jet fires, with methane used as a surrogate for natural gas. Experiments with hydrogen content ranging from 0% to 20% were performed to examine the effects of inclination angle (0°, 30°, 45°, 60°, and 90°), nozzle diameter (2, 3, and 4 mm), and gas flow rate (4–25 L/min) on the flame morphological characteristics. It was found that the flame color evolves from a transparent blue base to a yellow luminous tip with increasing hydrogen content or fuel exit velocity, accompanied by soot enrichment in the luminous region. The flame horizontal projection length was quantified under different conditions. Results show it is only slightly affected when the hydrogen content is below 20%, whereas it increases with fuel exit velocity and nozzle diameter, and decreases with inclination angle. An explicit model was proposed by introducing the dimensionless heat release rate (${\dot{Q}}^{*}$), which predicts the flame horizontal projection length with good agreement with experimental data. The findings provide a basis for the safety design and risk assessment of hydrogen-blended natural gas pipelines. Full article

Evaluating grouting effectiveness in deep shafts remains difficult because water-control performance is jointly governed by hydraulic response, seepage-path sealing, grout-body quality, and surrounding rock stability under complex hydrogeological conditions. In this study, an integrated evaluation and seepage analysis framework was developed for the Lianhuashan Phosphate Mine shaft project in Zhongxiang City, Hubei Province, China. Multi-source engineering data from hydrogeological observations, geophysical detection, construction records, and laboratory tests were used to evaluate six representative working faces, and a two-dimensional Darcy flow model was established to interpret the seepage-control mechanism. The evaluation results show differences among the treated sections: the auxiliary shaft at the −29.8 m outlet achieved the highest comprehensive score of 74.79, whereas the main shaft at +13 m showed the weakest performance, with a score of 50.16. Overall, three sections were rated as good, two as moderate, and one as poor. The dominant controls on grouting effectiveness are total shaft inflow, surrounding rock integrity/stability, seepage point number, and sealing-related indices. Numerical simulations further show that grouting reduced total shaft inflow from 6.6080 to 2.0198 m³/h, corresponding to a reduction of 69.43%, and shifted the main hydraulic-gradient concentration from the shaft wall to the outer boundary of the grouted ring. Reducing grouting ring permeability from 5.10 × 10⁻¹³ to 1.00 × 10⁻¹⁴ m² further lowered shaft inflow to 0.2929 m³/h and increased water-control efficiency to 95.57%, whereas increasing ring thickness from 8 to 16 m reduced shaft inflow from 2.7063 to 1.7260 m³/h. In addition, moving the water-rich zone away from the shaft reduced total inflow from 2.5503 m³/h at X_f = 10 m to 2.0079 m³/h at X_f = 26 m. These results indicate that effective shaft grouting depends on the coordinated control of inflow suppression, conductive-path sealing, and structural stabilization. The proposed framework provides a practical basis for grouting evaluation and water hazard control in deep shafts under complex hydrogeological conditions. Full article

River morphological changes significantly influence water purification functions; however, systematic research on the evolution of natural river morphology and its underlying mechanisms remains insufficient. This study investigates the Shiwuli River, a typical tributary of Chaohu Lake, by quantitatively analyzing its morphological evolution characteristics based on high-resolution satellite imagery from 2014 to 2024. Combined with field monitoring data from all four seasons of 2024, the study explores the influence mechanisms of river sinuosity, cascade flow, and wetlands on water purification. The results indicate significant morphological changes in the Shiwuli River: the total length decreased by 3.95 km, sinuosity decreased by 0.22, and the average width increased by 27.85 m. The comprehensive attenuation coefficient of pollutants in the monitored sections was consistently greater than zero, demonstrating the self-purification capacity of the natural meandering river, with the highest purification capacity observed in summer and the weakest in winter. Dissolved oxygen (DO) content was generally higher in concave banks than in convex banks, and the rate of increase in DO per unit length rose with increasing sinuosity. The cascade flow formed by rolling dams significantly enhanced DO concentration (by 19.23–26.25%), with average pollutant reduction rates ranging from 12.64% to 33.76%. The wetland sections exhibited average reduction rates of 79.07% for total phosphorus (TP), 39.33% for total nitrogen (TN), 47.43% for ammonia nitrogen (NH₃-N), and 45.67% for chemical oxygen demand (COD), demonstrating significantly better purification effects compared to the main river channel. This study reveals that the synergistic interaction among river sinuosity, cascade flow, and wetland systems enhances the water body’s self-purification capacity, providing a scientific basis for river ecological restoration and sustainable utilization of water resources. Full article