Search Results (1,245)

Accurately identifying coherent vortex structures (CVSs) in backward-facing step (BFS) flows remains a challenge, particularly in reconciling visual streamlines with mathematical criteria. In this study, high-resolution velocity fields were captured using particle image velocimetry (PIV) in a pressurized BFS setup. Instantaneous streamlines reveal distinct spiral patterns, vortex centers, and saddle points, consistent with physical definitions of vortices and offering intuitive guidance for CVS detection. However, conventional vortex identification methods often fail to reproduce these visual features. To address this, an improved Q-criterion method is proposed, based on the normalization of the velocity gradient tensor. This approach enhances the rotational contribution while suppressing shear effects, leading to improved agreement in vortex position and shape with those observed in streamlines. While the normalization process alters the representation of physical vortex strength, the method bridges qualitative visualization and quantitative analysis. This streamline-consistent identification framework facilitates robust CVS detection in separated flows and supports further investigations in vortex dynamics and turbulence control. Full article

Background: Transcatheter aortic valve implantation (TAVI) has revolutionized the treatment of severe aortic valve stenosis (AS). Balloon post-dilatation (PD) remains an important procedural step to optimize valve function by resolving incomplete valve expansion, which may lead to paravalvular regurgitation and other potentially adverse effects. There are only limited data on the predictors, incidence, and clinical impact of PD during TAVI. Methods: This retrospective, single-center study analyzed 585 patients who underwent TAVI (2016–2022). Pre-procedural evaluations included transthoracic echocardiography and CT angiography to assess key parameters, including the aortic valve calcium score (AVCS); aortic valve calcium density (AVCd); aortic valve maximal systolic transvalvular flow velocity (AV Vmax); and aortic valve mean systolic pressure gradient (AV MPG). We identified imaging predictors of PD and evaluated associated clinical outcomes by analyzing procedural endpoints (according to VARC-3 criteria) and long-term survival. Results: PD was performed on 67 out of 585 patients, with elevated AV Vmax (OR: 1.424, 95% CI: 1.039–1.950; p = 0.028) and AVCd (OR: 1.618, 95% CI: 1.227–2.132; p = 0.001) emerging as a significant independent predictor for PD in TAVI. Kaplan–Meier survival analysis revealed no significant differences in short- and mid-term survival between patients who underwent PD and those who did not. Interestingly, patients requiring PD exhibited a lower incidence of adverse events regarding major vascular complications, permanent pacemaker implantations and stroke. Conclusions: The study highlights AV Vmax and AVCd as key predictors of PD. Importantly, PD was not associated with increased procedural adverse events and did not predict adverse events in this contemporary cohort. Full article

This study explores how different electrode shapes affect plasma flow in a non-transferred plasma torch. Various cathode geometries—including conical, tapered, flat, and cylindrical—were examined alongside stepped anode designs. A 2D axisymmetric computational model was employed to assess the impact of these shapes on plasma behavior. The results reveal that different cathode designs require varying current levels to maintain a consistent power output. This paper presents the changes in electric conductivity and electric potential for different input currents across the arc formation path (from the cathode tip to the anode beginning) and relating to Ohm’s law. Significant variations in plasma jet velocity and temperature were observed, especially near the cathode tip. The study concludes by evaluating thermal efficiency across geometry configurations. Flat cathodes demonstrated the highest efficiency, while the anode shape had minimal impact. Full article

Oyster aquaculture in the U.S. faces severe inefficiencies due to the absence of precise path planning tools, resulting in environmental degradation and resource waste. Current dredging techniques lack trajectory planning, often leading to redundant seabed disturbance and suboptimal shell distribution. Existing vessel models—such as the Nomoto or Dubins models—are not designed to map steering inputs directly to spatial coordinates, presenting a research gap in maneuver planning for underactuated boats. This research fills that gap by introducing a novel hybrid vessel kinetics model that integrates the Nomoto model with Dubins motion primitives. Our approach links steering inputs directly to the vessel motion, enabling Cartesian coordinate path generation without relying on intermediate variables like yaw velocity. Field trials in the Chesapeake Bay demonstrate consistent trajectory following performance across varied path complexities, with average offsets of 0.01 m, 1.35 m, and 0.42 m. This work represents a scalable, efficient step toward real-time, constraint-aware automation in oyster harvesting, with broader implications for sustainable aquaculture operations. Full article

Ethanol upgrading via catalytic C–C coupling, commonly known as the Guerbet reaction, offers a sustainable route to produce 1-butanol, a high-performance biofuel. To address gaps in the mechanistic understanding of the catalytic reaction, we investigated the process involving a fixed-bed reactor, operated at 275–325 °C, 21 bar, and weight hourly space velocities of 0.25–2.5 g_EtOH/(g_cat·h), using helium as a carrier gas, with a 5:1 He/EtOH molar ratio. The catalyst was a MgO–Al₂O₃ mixed oxide (Mg/Al = 2:1), derived from a hydrotalcite precursor. A detailed kinetic model was developed, encompassing 15 species and 27 reversible steps (10 sorption and 17 reaction steps), within a 1+1D sorption–reaction–transport framework. Four C₄-forming pathways were included: aldol condensation to form crotonaldehyde, semi-direct coupling to form butyraldehyde and crotyl alcohol, and direct coupling to form 1-butanol. To avoid overfitting, Arrhenius parameters were grouped by reaction type, resulting in sixty rate parameters and one active site-specific density parameter. The optimized model achieved high accuracy, with an average prediction error of 1.44 times the experimental standard deviation. The mechanistic analysis revealed aldol condensation as the dominant pathway below 335 °C, with semi-direct coupling to crotyl alcohol prevailing above 340 °C. The resulting model provides a robust framework for understanding and predicting complex reaction networks in ethanol upgrading systems. Full article

Superhydrophobic coatings possess distinct wettability characteristics and hold significant potential in metal corrosion protection and underwater drag reduction. However, their practical application is often hindered by poor durability arising from the fragility of their micro/nanostructured surface roughness. In this study, a durable superhydrophobic coating featuring a hierarchical, hydrangea-like micro/nanostructure was successfully fabricated on an aluminum alloy substrate via a simple one-step cold-spraying technique. The coating consisted of hydrangea-shaped SiO₂ nanoparticles modified with 1H,1H,2H,2H-perfluorodecyltrimethoxysilane (PFDT) to produce multiscale roughness, while epoxy resin (EP) served as the binding matrix to enhance mechanical integrity. The hydrangea-like SiO₂ nanostructures were characterized by solid cores and wrinkled, petal-like outgrowths. This unique morphology not only increased the surface roughness but also provided more active sites for air entrapment, thereby enhancing the coating’s overall performance. The h-SiO₂@PFDT-EP composite coating exhibited excellent superhydrophobicity, with a WCA of 170.1° ± 0.8° and a SA of 2.7° ± 0.5°. Durability was evaluated through sandpaper abrasion, tape peeling, acid and alkali immersion, artificial weathering, and salt spray tests. The results demonstrated that the coating retained stable superhydrophobic performance under various environmental stresses. Compared with bare 6061 aluminum and EP coatings, its corrosion current density was reduced by four and three orders of magnitude, respectively. Furthermore, the coating achieved a maximum drag-reduction rate of 31.01% within a velocity range of 1.31–7.86 m/s. The coating also displayed excellent self-cleaning properties. Owing to its outstanding durability, corrosion resistance, and drag-reducing capability, this one-step fabricated superhydrophobic coating showed great promise for applications in marine engineering and defense. Full article

This study investigates the dynamic behavior of an articulated boom offshore crane under various load application laws. The following steps were taken to perform numerical simulations using the finite-element method (FEM): Definition of the model’s geometry, materials, and boundary conditions. The modal analyses reveal significant resonance frequencies in the direction of load application (payload). The crane’s displacement, velocity, and acceleration responses are closely related to load application laws, specifically the time required to reach the structure’s full payload (epsilon). It is highly correlated with the dynamic factor (maximum acceleration multiplied by payload), which has a wide range of effects on the structure, including the effects of overstress, overturning, buckling, and so on. The main findings reveal a very strong exponential correlation, allowing the dynamic effect to be estimated as a function of epsilon time. This is a useful tool for increasing the safety and reliability of offshore lifting operations. Full article

Grouting, as a widely applicable and versatile foundation treatment technology, plays a crucial role in addressing seepage control problems in cover layers due to its flexibility and convenience. The effectiveness of grouting largely depends on slurry diffusion; however, due to the opaque nature of geotechnical media, the diffusion mechanism of slurry in the cover layers remains insufficiently understood. To investigate this, a visual grouting model device was designed and fabricated, and grouting tests were conducted using transparent soil materials to simulate the cover layers. The slurry diffusion patterns and the velocity field within the transparent soil were analyzed. The results show that, based on refractive-index matching, fused quartz sand of specific gradation and white mineral oil were selected as simulation materials for the cover layers. A stable slurry suitable for transparent grouting was also chosen to satisfy visualization requirements. The transparent soil grouting model, integrated with a Digital Image Correlation (DIC) monitoring system, has the advantages of demonstrating simple operation, real-time monitoring, and high precision. These tests verify the feasibility of visualizing slurry diffusion in cover layers. Furthermore, step-pressure grouting tests preliminarily reveal the dynamic mechanism of slurry diffusion. The results suggest that, in the cover layer, the cover layer in this grouting test is mainly splitting grouting, accompanied by compaction grouting. These methods offer new insights and methods for model testing of cover layer grouting mechanisms. Full article

Monitoring the structural health of bridges in road infrastructure is crucial for ensuring public safety and efficient maintenance. This paper presents a multi-level semi-automatic methodology for bridge monitoring, using Multi-Temporal Differential SAR Interferometry (MT-DInSAR) data. The proposed approach requires a dataset of satellite-derived MT-DInSAR measurements for the Area of Interest. The methodology involves creating a georeferenced database of bridges which allows the filtering of measurement points (generally named Persistent Scatterers—PSs) using spatial queries. Since existing datasets often provide only point geometries for bridge locations, additional data sources such as OpenStreetMaps-derived repositories have been utilized to obtain linear representations of bridges. These linear features are segmented into 20 m sections, which are then converted into polygonal geometries by applying a uniform buffer. Spatial joining between the bridge polygons and PS datasets allows the extraction of key statistics, such as mean displacement velocity, PS density and coherence levels. Based on predefined velocity thresholds, warning flags are triggered, indicating the need for further in-depth analysis. Finally, an upscaling step is performed to provide a practical tool for infrastructure managers, visually categorizing bridges based on the presence of flagged pixels. The proposed approach facilitates large-scale bridge monitoring, supporting the early detection of potential structural issues. Full article

Seismic data processing is essential in hydrocarbon exploration, with normal moveout (NMO) correction being a pivotal step in enhancing seismic signal quality. However, conventional NMO correction often suffers from the stretch effect, which distorts seismic reflections and degrades data quality, especially in long-offset data. This study addresses the issue by analyzing synthetic models and proposing a nonhyperbolic stretch-free NMO correction technique. The proposed method significantly improves seismic data quality by preserving up to 90% of the original amplitude, maintaining frequency content stability at 30 Hz, and achieving a high reduction of stretch-related distortions. Compared to conventional NMO, our technique results in clearer seismic gathers, enhanced temporal resolution, and more accurate velocity models. These improvements have substantial implications for high-resolution subsurface imaging and precise reservoir characterization.This work offers a robust and computationally efficient solution to a longstanding limitation in seismic processing, advancing the reliability of exploration in geologically complex environments. Full article

An engineered molecular motor composed of an ATP-dependent kinesin-1 monomer and an ATP-independent diffusing microtubule-associated protein is proposed, and its dynamics are studied theoretically. It is shown that the engineered motor can move directionally on microtubules towards the plus end, bearing great potential for applications in therapeutics or nanorobotics. The engineered motor can have an unloaded velocity similar to the wild-type kinesin-1 dimer, can take a mechanical (either forward or backward) step by hydrolyzing an ATP molecule under any load, and can generate the maximum force that is about half of that generated by the wild-type kinesin-1 dimer. Full article

In this article, we present the extended simple equations method (SEsM) for finding exact solutions to systems of fractional nonlinear partial differential equations (FNPDEs). The expansions made to the original SEsM algorithm are implemented in several directions: (1) In constructing analytical solutions: exact solutions to FNPDE systems are presented by simple or complex composite functions, including combinations of solutions to two or more different simple equations with distinct independent variables (corresponding to different wave velocities); (2) in selecting appropriate fractional derivatives and appropriate wave transformations: the choice of the type of fractional derivatives for each system of FNPDEs depends on the physical nature of the modeled real process. Based on this choice, the range of applicable wave transformations that are used to reduce FNPDEs to nonlinear ODEs has been expanded. It includes not only various forms of fractional traveling wave transformations but also standard traveling wave transformations. Based on these methodological enhancements, a generalized SEsM algorithm has been developed to derive exact solutions of systems of FNPDEs. This algorithm provides multiple options at each step, enabling the user to select the most appropriate variant depending on the expected wave dynamics in the modeled physical context. Two specific variants of the generalized SEsM algorithm have been applied to obtain exact solutions to two time-fractional shallow-water-like systems. For generating these exact solutions, it is assumed that each system variable in the studied models exhibits multi-wave behavior, which is expressed as a superposition of two waves propagating at different velocities. As a result, numerous novel multi-wave solutions are derived, involving combinations of hyperbolic-like, elliptic-like, and trigonometric-like functions. The obtained analytical solutions can provide valuable qualitative insights into complex wave dynamics in generalized spatio-temporal dynamical systems, with relevance to areas such as ocean current modeling, multiphase fluid dynamics and geophysical fluid modeling. Full article

This study investigates three-dimensional two-phase flows in complex geometries found in industrial process equipment design using finite-element numerical simulations. The governing equations are formulated in three-dimensional Cartesian coordinates and solved on unstructured meshes employing the Taylor–Hood “Mini” element, selected for its numerical stability and convergence properties. The convective term in the momentum equation is discretized using a first-order semi-Lagrangian scheme. The two fluid phases are separated by an interface mesh composed of triangular surface elements, which is independent of the primary volumetric fluid mesh. Surface tension effects are incorporated as a source term using the continuum surface force (CSF) model, with the curvature computed via the Laplace–Beltrami operator. At each time step, the positions of the interface mesh nodes are updated according to the local fluid velocity field. The results show that the methodology is stable and can be used to accurately model two-phase flows in complex geometries found in several engineering solutions. Full article

This paper proposes a novel navigation approach for Unmanned Tracked Vehicles (UTVs) using prior-based ensemble deep reinforcement learning, which fuses the policy of the ensemble Deep Reinforcement Learning (DRL) and Dynamic Window Approach (DWA) to enhance both exploration efficiency and deployment safety in unstructured off-road environments. First, by integrating kinematic analysis, we introduce a novel state and an action space that account for rugged terrain features and track–ground interactions. Local elevation information and vehicle pose changes over consecutive time steps are used as inputs to the DRL model, enabling the UTVs to implicitly learn policies for safe navigation in complex terrains while minimizing the impact of slipping disturbances. Then, we introduce an ensemble Soft Actor–Critic (SAC) learning framework, which introduces the DWA as a behavioral prior, referred to as the SAC-based Hybrid Policy (SAC-HP). Ensemble SAC uses multiple policy networks to effectively reduce the variance of DRL outputs. We combine the DRL actions with the DWA method by reconstructing the hybrid Gaussian distribution of both. Experimental results indicate that the proposed SAC-HP converges faster than traditional SAC models, which enables efficient large-scale navigation tasks. Additionally, a penalty term in the reward function about energy optimization is proposed to reduce velocity oscillations, ensuring fast convergence and smooth robot movement. Scenarios with obstacles and rugged terrain have been considered to prove the SAC-HP’s efficiency, robustness, and smoothness when compared with the state of the art. Full article

Granitic faults within the crystalline upper-to-middle continental crust play a critical role in accommodating tectonic deformation and controlling earthquake nucleation. To better understand their frictional behavior, we review experimental studies conducted under both dry and hydrothermal conditions using velocity-stepping (VS), constant-velocity (CV), and slide-hold-slide (SHS) tests. These approaches allow the quantification of frictional strength, velocity dependence, and healing behavior across a range of conditions. Our synthesis highlights that the friction coefficient of granite gouges decreases with increasing temperature and pore fluid pressure, decreasing slip velocity, and increasing slip displacement. The velocity-weakening regime shifts to higher temperatures with increasing slip velocity or decreasing pore fluid pressure. Temperature, normal stress, pore fluid pressure, and slip velocity interact to modulate frictional stability. In particular, microstructural observations reveal that grain size reduction, pressure solution creep, and fluid-assisted chemical processes are key mechanisms governing transitions between velocity-weakening and velocity-strengthening regimes. These insights support the growing application of microphysical-based models, which integrate micromechanical processes and offer improved extrapolation from the laboratory to natural fault systems compared to classical rate-and-state friction laws. The collective evidence underscores the importance of considering fault rheology in a temperature- and fluid-sensitive context, with implications for interpreting seismic cycle behavior in continental regions. Full article