Search Results (744)

Flooding and overtopping are major concerns in coastal areas due to their potential to cause severe damage to infrastructure, economic activities, and human lives. Traditional methods for predicting these phenomena include numerical and physical models, as well as empirical formulations. However, these methods have limitations, such as the high computational costs, reliance on extensive field data, and reduced accuracy under complex conditions. Recent advances in machine learning (ML) offer new opportunities to improve predictive capabilities in coastal engineering. This paper reviews ML applications for coastal flooding and overtopping prediction, analyzing commonly used models, data sources, and preprocessing techniques. Several studies report that ML models can match or exceed the performance of traditional approaches, such as empirical EurOtop formulas or high-fidelity numerical models, particularly in controlled laboratory datasets where numerical models are computationally intensive and empirical methods show larger estimation errors. However, their advantages remain task- and data-dependent, and their generalization and interpretability may lag behind physics-based methods. This review also examines recent developments, such as hybrid approaches, real-time monitoring, and explainable artificial intelligence, which show promise in addressing these limitations and advancing the operational use of ML in coastal flooding and overtopping prediction. Full article

In ultrafast science, the strong-field approximation (SFA) provides a powerful framework to describe high-order harmonic generation (HHG) and related phenomena. Meanwhile, within the current ab initio theoretical framework, the use of nonlocal potentials in calculating multi-electron molecular wave functions is almost unavoidable. We find that when such wave functions are directly applied to compute transition dipole moments for correcting SFA, it introduces a fundamental gauge transformation problem. Specifically, the nonlocal potential contributes an additional gauge-dependent phase function to the dipole operator, which directly modifies the phase of the transition dipole. As a consequence, the saddle-point equations acquire an entirely different structure compared to the standard SFA, leading to a splitting of the conventional short and long classical trajectories in HHG into multiple distinct quantum trajectories. Here, ‘‘complex molecules’’ refers to multi-center molecular systems whose nonlocal electronic structure leads to gauge-dependent strong-field responses. Our analysis highlights that the validity of gauge in-variation cannot be assumed universally in SFA framework. Our approach combines the molecular strong-field approximation with gauge transformation analysis, incorporating nonlocal pseudopotentials, saddle-point equations, and multi-center recombination effects. Full article

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental condition characterized by persistent social communication difficulties, restricted interests, repetitive behaviors, and frequent medical comorbidities. Although early brain development in ASD has been extensively investigated, its biological progression across adulthood and aging remains largely unexplored. Growing evidence suggests that perivascular space (PVS) abnormalities may indicate impaired neurovascular integrity and reduced glymphatic clearance in ASD. Enlarged perivascular spaces (ePVS) in children commonly present alongside increased extra-axial CSF accumulation and more severe clinical manifestations, consistent with early alterations in CSF homeostasis and neuroimmune signaling. However, whether these abnormalities persist or evolve with aging remains unknown. Given that glymphatic and vascular integrity decline with age, and adults with ASD show elevated rates of sleep, metabolic, and cardiovascular disorders, PVS alterations may represent a unifying mechanism linking early neurodevelopmental divergence with later neurovascular vulnerability and cognitive aging. Advances in ultra-high-field MRI and automated segmentation now enable precise in vivo quantification of PVS burden, offering new opportunities for lifespan studies. By combining structural and functional methodologies, researchers may determine whether PVS constitute enduring traits, dynamic indicators of disease, or actionable therapeutic targets. Understanding their trajectories could provide critical insights into the continuum between neurodevelopmental and neurodegenerative phenomena in autism. Full article

The Finite Element Method is an indispensable tool for analyzing the transient thermal phenomena in welding processes. This study aims to simulate the temperature field during Gas Metal Arc Welding of an AISI 304L V-groove butt joint, employing a volumetric heat source model. The numerical simulations were conducted using ABAQUS SIMULIA^® (version 6.11-3) on a plate measuring 200 mm × 50 mm × 9.5 mm. For validation, the numerical results were compared against experimental data obtained at the Welding Engineering Research Laboratory of Federal University of Rio Grande. A parametric study was performed by varying the geometric parameter b (controlling the volumetric heat distribution depth) to enhance the model’s accuracy and achieve the closest approximation to experimental observations. The calibrated volumetric source demonstrated high accuracy, yielding low percentage differences between predicted and experimental peak temperatures: 1.02%, 2.50%, and 4.44% at the 4 mm, 8 mm, and 12 mm thermocouple positions, respectively. Full article

Flexible grid regulation necessitates Francis turbines to operate at heads of 120–180 m (compared to the rated head of 154.6 m), breaking the designed rotational symmetry and inducing hydraulic instabilities that threaten structural integrity and operational reliability. This study presents extensive field measurements of pressure pulsations in a 600 MW prototype Francis turbine operating at heads of 120–180 m and loads of 20–600 MW across 77 operating conditions (7 head levels × 11 load points). We strategically positioned high-precision piezoelectric pressure sensors at three critical locations—volute inlet, vaneless space, and draft tube cone—to capture the amplitude and frequency characteristics of symmetry-breaking phenomena. Advanced signal processing revealed three distinct mechanisms with characteristic pressure pulsation signatures: (1) Draft tube rotating vortex rope (RVR) represents spontaneous breaking of axial symmetry, exhibiting helical precession at 0.38 Hz (approximately 0.18 f_n, where f_n = 2.08 Hz) with maximum peak-to-peak amplitudes of 108 kPa (87% of the rated pressure p_rated = 124 kPa) at H = 180 m and P = 300 MW, demonstrating approximately 70% amplitude reduction potential through load-based operational strategies. (2) Vaneless space rotor-stator interaction (RSI) reflects periodic disruption of the combined C₂₄ × C₁₃ symmetry at the blade-passing frequency of 27.1 Hz (N_r × f_n = 13 × 2.08 Hz), reaching peak amplitudes of 164 kPa (132% p_rated) at H = 180 m and P = 150 MW, representing the most severe symmetry-breaking phenomenon. (3) Volute multi-point excitation exhibits broadband spectral characteristics (4–10 Hz) with peak amplitudes of 146 kPa (118% p_rated) under small guide vane openings. The spatial amplitude hierarchy—vaneless space (164 kPa) > volute (146 kPa) > draft tube (108 kPa)—directly correlates with the local symmetry-breaking intensity, providing quantitative evidence for the relationship between geometric symmetry disruption and hydraulic excitation magnitude. Systematic head-dependent amplitude increases of 22–43% across all monitoring locations are attributed to effects related to Euler head scaling and Reynolds number variation, with the vaneless space demonstrating the highest sensitivity (0.83 kPa/m, equivalent to 0.67% p_rated/m). The study establishes data-driven operational guidelines identifying forbidden operating regions (H = 160–180 m, P = 20–150 MW for vaneless space; H = 160–180 m, P = 250–350 MW for draft tube) and critical monitoring frequencies (0.38 Hz for RVR, 27.1 Hz for RSI), providing essential reference data for condition monitoring systems and operational optimization of large Francis turbines functioning as flexible grid-regulating units in renewable energy integration scenarios. Full article

This paper presents a comparative analysis of the influence of Fused Deposition Modeling (FDM) parameters—specifically material type, infill geometry, and density—on the vibro-acoustic characteristics of loudspeaker enclosures. The enclosures were designed as exponential horns to intensify resonance phenomena for precise evaluation. Twelve unique configurations were fabricated using three materials with distinct damping properties (PLA, ABS, wood-composite) and three internal geometries (linear, honeycomb, Gyroid). Key vibro-acoustic properties were assessed via digital signal processing of recorded audio signals, including relative frequency response and time-frequency (spectrogram) analysis, and correlated with a predictive Finite Element Analysis (FEA) model of mechanical vibrations. The study unequivocally demonstrates that a material with a high internal damping coefficient is a critical factor. The wood-composite enabled a reduction in the main resonance amplitude by approximately 4 dB compared to PLA with the same geometry, corresponding to a predicted 86% reduction in mechanical vibration. Furthermore, the results show that a synergy between a high-damping material and an advanced, energy-dissipating infill (Gyroid) is crucial for achieving high acoustic fidelity. The wood-composite with 10% Gyroid infill was identified as the optimal design, offering the most effective resonance damping and the most neutral tonal characteristic. This work provides a valuable contribution to the field by establishing a clear link between FDM parameters and acoustic outcomes, delivering practical guidelines for performance optimization in personalized audio systems. Full article

The integration of electrically conductive functionalities into polymer components via additive manufacturing has gained increasing relevance across fields such as sensing, energy storage, and structural electronics. Achieving reliable performance in such applications requires a deeper understanding of how processing conditions affect the internal structure of conductive thermoplastic composites—particularly the orientation and distribution of anisotropic fillers. This study analyzes a PLA-based composite containing carbon nanotubes, carbon black, and graphite flakes to evaluate the influence of extrusion temperature on electrical resistivity and micromechanical properties. To complement scanning electron microscopy, a novel micromechanical mapping approach based on nanoindentation was applied, enabling spatially resolved analysis of local stiffness and hardness. Results show that increasing extrusion temperature improves filler dispersion and alignment, enhancing conductivity and mechanical homogeneity—up to a threshold of 210 °C. Even small temperature changes significantly affect particle orientation and distribution. Unlike global resistivity measurements, the combined use of nanoindentation and microscopic imaging reveals location-specific structural phenomena and filler behavior within the matrix. This newly established method provides high-resolution insight into internal composite architecture and offers a robust foundation for optimizing process-structure-property relationships in conductive polymer systems. Full article

The development of minimally invasive diagnostic devices in the biomedical field has grown significantly, especially those that take advantage of photoacoustic phenomena. Photoacoustic imaging is an imaging technique that exploits the photoacoustic effect, relying on the conversion of absorbed light into ultrasound waves. Thanks to lab-on-fiber technology, optical fiber can be functionalized to generate and receive a photoacoustic signal. Weak acoustic signals often limit this process, as conversion efficiency can be influenced by factors such as tissue heterogeneity, light scattering, and the attenuation of the acoustic waves within tissues. Consequently, there is significant interest in the development of highly sensitive systems with broad bandwidths. While the literature has largely focused on standard devices utilizing the interferometric effect in homogeneous slabs, this study explores the potential of multilayer structures that leverage Bragg reflection to be realized on the fiber tip. We numerically investigated both periodic and aperiodic designs of polymeric multilayer structures to further enhance the optical performance of opto-acoustic sensors. We demonstrate an enhancement in sensitivity of up to about three orders of magnitude without compromising bandwidth. This work highlights the advantages of multilayer sensor designs in improving sensitivity and performance for high-frequency opto-acoustic sensing. Full article

Electromagnetic wave propagation in complex environments demands accurate yet efficient modeling techniques. This study introduces a physics-informed neural network (PINN) framework for two-dimensional transient electromagnetic analysis, where Helmholtz equations are directly incorporated into the loss function. The model learns spatiotemporal field evolution without relying on spatial discretization or labeled data. Various excitation and material conditions are examined, including single and dual Gaussian sources in both free space and inhomogeneous regions with dielectric and conducting inclusions. Through this formulation, the network captures key wave phenomena such as propagation, reflection, and scattering with high precision. Validations against finite-difference time-domain (FDTD) simulations confirm strong agreement in both temporal and spatial field distributions. The results demonstrate that the proposed PINN provides an effective, mesh-free alternative for modeling electromagnetic wave dynamics, offering scalability for complex and data-sparse scenarios. Full article

This article presents a comprehensive overview of the current and emerging roles of cryogenics and superconductivity in medical diagnostics, imaging, and therapy. Beginning with the historical foundations of both fields and their technological maturation, this review emphasizes how cryogenic engineering and superconducting materials have become indispensable to modern medical systems. Cryogenic technologies are highlighted in applications such as cryosurgery, cryotherapy, cryostimulation, and cryopreservation, all of which rely on controlled exposure to extremely low temperatures for therapeutic or biological preservation purposes. This article outlines the operating principles of cryomedical devices, the refrigerants and cooling methods used, and the technological barriers. This paper reviews the latest applications of superconductivity phenomena in medicine and identifies those that could be used in the future. These include cryogenic therapy, radiotherapy (cyclotrons, particle accelerators, synchrotron radiation generation, isotope production, and proton and ion beam delivery), magnetic resonance imaging (MRI), nuclear magnetic resonance spectroscopy (NMR), positron emission tomography (PET), and ultra-sensitive magnetic signal transducers based on SQUIDs for detecting ultra-low bio-signals emitted by human body organs. CT, MRI/NMR, and PET features are compared using the operation principle, specific applications, safety, contraindications for patients, examination time, and additional valued peculiarities. This article outlines the prospects for the development of superconducting and cryogenic materials and technologies in medical applications. Advances in diagnostic imaging are reviewed, with particular attention on the progression from conventional MRI scanners to ultra-high-field (UHF) systems exceeding 7–10.5 T, culminating in the 11.7 T Iseult whole-body MRI magnet. Another important application area described in this article includes biofunctionalized magnetic nanoparticles and superconducting quantum interference devices (SQUIDs), which enable the ultrasensitive detection of biomagnetic fields and targeted cancer diagnostics. Finally, this article identifies future directions of development in superconducting and cryogenic technologies for medicine. Full article

This study investigates the impact of high-resolution Sea Surface Temperature (SST) boundary conditions on atmospheric simulations over the southwestern Atlantic Ocean (12–27° S, 32–48° W). Numerical experiments were conducted using the WRF model with two distinct SST configurations: standard resolution GFS SST data (0.5°) and high-resolution RTG-SST-HR satellite-derived data (0.083°). Simulations covered contrasting seasonal periods (January and July 2016) to capture varying upwelling intensities and atmospheric circulation patterns. Model performance was evaluated against observational data from the Brazilian National Buoy Program (PNBOIA) using statistical metrics including RMSE and Pearson correlation coefficients for wind components. The high-resolution SST experiment demonstrated significant improvements in wind field representation, with RMSE reductions of up to 0.5 m/s for zonal wind components and correlation improvements of approximately 0.1 across multiple validation sites. Most notably, the enhanced SST resolution enabled better representation of mesoscale atmospheric systems, including improved organization and intensification of cyclonic systems in areas near the cyclogenesis regions. The RTG-SST data captured sharp thermal gradients and coastal upwelling signatures that were spatially smoothed in the GFS fields, leading to more realistic surface heat flux patterns and atmospheric boundary layer dynamics. These improvements were particularly pronounced during summer months when thermal gradients were strongest, highlighting the critical importance of accurate SST representation for capturing high-intensity atmospheric phenomena in regions of strong air-sea interaction. Full article

This work investigates the influence of ground effect on the performance of a UAV propeller through a combined experimental, analytical, and numerical approach. A dedicated test bench was designed and constructed to enable controlled measurements of thrust and power under static conditions. During experimental campaigns, it was observed that the measured thrust significantly exceeded theoretical free-air predictions, suggesting the presence of a ground-like amplification effect. To quantify and validate this phenomenon, complementary methods were employed: blade element momentum-based analytical modeling corrected for ground proximity and high-fidelity CFD simulations performed using ANSYS CFX. Three configurations were analyzed numerically—an isolated propeller, a propeller with a motor, and a propeller–motor–mounting plate configuration—highlighting the progressive impact of structural elements on the flow field. The results showed close agreement between corrected analytical predictions, CFD solutions, and experimental data, with deviations below 8%. The presence of the mounting plate induced pressure redistribution and jet reflection, analogous to the helicopter ground effect, leading to thrust amplification of up to 30% relative to free-air conditions. This study confirms the critical role of the experimental setup and mounting configuration in propeller characterization and establishes a validated methodology for capturing ground effect phenomena relevant to UAV propulsion systems. Full article

Under the DC field, live contamination is more likely to deposit on the surface of insulators due to the action of the external electric field. The deposition of dirt on the surface of Ultra High Voltage (UHV) insulators can lead to the occurrence of flashover phenomena, causing significant economic losses. Due to the particularity of UHV insulators, many traditional surface anti-pollution technologies designed for normal voltage insulators are not applicable to them. In order to prevent the harm of contamination accumulation affecting the safe operation of transmission lines, in this study, tetragonal BaTiO₃ was mixed into room-temperature vulcanized silicone rubber for the first time to prepare a composite coating with piezoelectric properties. This coating can use the piezoelectric effect to remove the contamination adhering to the surface of UHV insulators under a DC field. In this study, the piezoelectric properties of the prepared tetragonal BaTiO₃ were verified through material characterization. The results show that the introduction of piezoelectric fillers can significantly accelerate the dissipation of charges on the insulator surface under slight disturbances, which helps to reduce the accumulation of charged pollutants on the insulator surface. The anti-pollution performance under electric field conditions was verified through a simulation experimental device. Finally, through experiments in a real converter station environment, the anti-pollution effect of the insulator under actual working conditions was verified. Full article

Direct Numerical Simulations (DNS) are widely employed to simulate thermo-fluid dynamics in packed bed reactors, offering high-fidelity insights into complex flow and heat transfer phenomena. However, recent studies have revealed notable differences in isothermal turbulent flow results across different DNS frameworks, leaving open the question of how conjugate heat transfer is affected. This study presents a comparison between DNS based on a finite volume method (FVM) and a lattice Boltzmann method (LBM) for predicting turbulent heat transfer in a low porosity face-centered cubic (FCC) packed unit. First, the methods are compared with respect to the required resolution and computational cost. Subsequently, global parameters for drag, heat transfer, and spatial as well as temporal variances are evaluated. The flow topology is further analyzed by examining the mean and fluctuating components of hydrodynamic and thermal fields. While good agreement between the methods is shown regarding time-averaged velocity and temperature profiles, more pronounced differences are observed when comparing the respective temporal variances between the two methods. Additionally, the FVM, which relies on a surface-fitted mesh, requires more degrees of freedom to obtain a grid-converged solution but delivers results of higher certainty than the LBM. These findings highlight important methodological considerations when selecting DNS approaches for resolving turbulent heat transfer in complex porous geometries. Full article

Identifying the causes and mechanisms of heat hazards in mining operations is essential for effective heat hazard prevention and control. In recent years, hydrothermal phenomena have frequently occurred in the eastern part of the Chenghe Mining Area, located in the central Weibei Coalfield. However, research on the geothermal fluid migration patterns and heat generation mechanisms in this region remains limited. This study comprehensively explores the geothermal field characteristics in the area, based on well temperature logging data, rock thermal conductivity, temperature control models, temperature curve analysis, and numerical simulations. It reveals the key controlling factors and mechanisms behind the formation of geothermal anomalies in the region. The results show that the overall geothermal heat flow trend in the area is characterized by low heat in the northwest and high heat in the southeast. The formation of geothermal anomalies is primarily influenced by water-conducting faults and coal seams. Based on this, the temperature control models are classified into two types: the fault + deep circulating thermal water uplift model and the coal seam heat-resistant-folded temperature control model. Heat transfer occurs through groundwater convection along the F1 fault and its secondary faults, which transport heat. The heat generation mechanism in the study area involves the heating of groundwater during deep circulation, followed by the upward migration of the heated water along the F1 fault, which adds an additional heat source to the surrounding rock of the fault, creating localized thermal anomalies. The findings of this study provide direct guidance for safe production in the Chenghe Mining Area and offer a universal theoretical framework for understanding the causes of heat hazards in mining areas with strong tectonic activity in northwestern China. Full article