Search Results (1,356)

Generating high-precision normalized digital surface models (nDSMs) from a single remote sensing image remains a challenging and ill-posed problem due to the absence of reliable geometric constraints. In this work, we show that monocular depth provides structurally stable cues of local geometry but lacks the global scale and vertical reference required for absolute height recovery. This intrinsic mismatch limits direct depth-to-height regression, particularly when transferring across heterogeneous terrains, land-cover compositions, and imaging conditions. Building on this idea, we propose the Relative Depth–Absolute Height Prediction Network (RDAH-Net), a framework that exploits relative depth as a geometry-aware prior while learning terrain-dependent height mappings from image appearance to absolute height. As the backbone, we employ a lightweight MobileNetV2 enhanced with a Convolutional Block Attention Module (CBAM), and further incorporate a cross-modal bidirectional attention fusion scheme with positional encoding to achieve a deep and effective fusion of image appearance and depth prior cues. Finally, a PixelShuffle-based upsampling strategy is used to sharpen prediction details and mitigate typical upsampling artifacts. Extensive experiments across diverse regions demonstrate that RDAH-Net achieves robust and generalizable height estimation, providing a practical alternative for large-scale mapping and rapid update scenarios. Full article

We study the predictability and cross-market structural similarity of Brent, WTI, and Dubai crude oil futures by means of a wavelet-based Sharma–Mittal energy entropy measure. The proposed framework combines multiresolution wavelet decomposition with a parametric generalised entropy, allowing the characterisation of informational complexity across scales and entropic parameters. We show that predictability is jointly scale- and parameter-dependent. Despite this dependence, the resulting wavelet entropy surfaces exhibit a high degree of geometric similarity across the three benchmarks. A discrepancy analysis further indicates that cross-market differences are localised in restricted regions of the parameter space, whereas intermediate scales are associated with maximal entropy values. Outside such regions, the entropy surfaces converge. Overall, the results provide evidence of a common multi-scale entropic structure underlying crude oil benchmarks, with regional effects affecting predictability without altering the global structural properties. These findings are consistent with the hypothesis of strong informational integration in global oil markets. Full article

The interaction between circular piers and turbulent open-channel flow generates complex three-dimensional structures, including horseshoe vortices at the pier base and wake vortices downstream. These structures increase vertical velocities, pressure fluctuations, and shear stresses, contributing to erosion and structural instability. Although these phenomena have been widely studied, limited attention has been given to surface geometric modifications as a flow-control strategy. This study employs Large Eddy Simulation (LES) to evaluate the influence of a hexagonal dimple pattern on circular piles in a free-surface channel. The dimples were defined by varying diameter, depth, and spacing to reduce vertical velocity and alter vortex formation. The computational domain represents a 0.40 m wide, 12 m long, and 1.2 m high rectangular channel, with an inlet mass flow of 9.4 kg/s and 0.10 m water depth. Model validation against particle image velocimetry (PIV) data showed 99% correlation, confirming numerical accuracy. Results demonstrate that textured surfaces modify flow dynamics by enhancing kinetic energy dissipation and generating micro-vortices that weaken dominant structures. The optimal configuration (6 mm diameter, 2 mm depth, 1 mm spacing) reduced downward vertical velocity by 42% and wake vortex shedding frequency by 24%, indicating improved hydraulic stability and erosion mitigation potential. Full article

The shift toward lightweight powertrain architectures necessitates a detailed characterization of polymer gears to verify their efficiency and durability. This study investigated the effectiveness of non-contact structured-light 3D scanning for evaluating the surface topography and dimensional tolerance quality of polymer gears produced via distinct manufacturing technologies. A structured-light 3D scanner was used to capture dense point clouds (exceeding 6 million points) of gears produced by three methods: conventional hobbing (POM-C), Material Extrusion (MEX) with carbon fiber reinforcement, and Selective Laser Sintering (SLS). The manufactured parts were compared against the nominal Computer Aided Design (CAD) models to evaluate their geometrical deviations in accordance with DIN 3961 and surface roughness parameters per ISO 25178. The experimental results revealed a consistent ranking of manufacturing quality. The conventionally hobbed POM-C gear exhibited superior precision, achieving DIN quality grades of Q9–Q10 and the smoothest surface finish (S_a = 5.0 µm). Among additive manufacturing techniques, SLS-printed PA 12 showed intermediate quality (Q11, S_a = 12 µm), whereas MEX-printed PPS-CF exhibited significant deviations (exceeding Q12) and the highest surface irregularity (S_a = 25 µm) due to stair-stepping effects. These findings indicate that while additive manufacturing offers geometric flexibility, conventional hobbing retains a decisive advantage in dimensional precision. The optical scanning methodology demonstrated here constitutes an efficient metrological framework for gear quality control, with potential applications extending to the quality assurance of additively manufactured adaptive fixtures and assembly tooling, including automotive assembly operations. Full article

Precise 3D reconstruction of non-cooperative space targets is a prerequisite for active debris removal and on-orbit servicing. However, this task is impeded by severe environmental challenges. Specifically, the limited dynamic range of visible light cameras leads to frequent overexposure or underexposure under extreme space lighting. Compounded by sparse textures and strong specular reflections, these factors significantly constrain reconstruction accuracy. While existing general-purpose feed-forward models such as MapAnything offer efficient inference, their geometric recovery capabilities degrade sharply when facing significant domain shifts. To address these issues, this paper proposes an enhanced 3D reconstruction framework tailored for the space environment named In-Orbit MapAnything. First, to mitigate data scarcity, we construct a high-quality space target dataset incorporating extreme illumination characteristics, which provides comprehensive auxiliary modalities including accurate camera poses and dense point clouds. Second, we propose the SatMap-Adapter module to mitigate feature degradation caused by severe specular reflections. This architecture employs a hierarchical cascade sampling strategy to align multi-level backbone features and utilizes a lightweight adaptive fusion module to dynamically integrate shallow photometric cues, intermediate structural information, and deep semantic features. Finally, we employ a weight-decomposed low-rank adaptation strategy to achieve parameter-efficient fine-tuning while strictly freezing the pre-trained backbone. Experimental results demonstrate that the proposed method decreases the absolute relative error and Chamfer distance by 15.23% and 20.02% respectively compared to the baseline MapAnything model, while maintaining a rapid inference speed. The proposed approach effectively suppresses reconstruction noise on metallic surfaces and recovers fine geometric structures, validating the effectiveness of our feature-enhanced framework in extreme space environments. Full article

In this work, molecular dynamics (MD) simulations are applied to investigate the dependence of the Wenzel–Cassie transition on water droplet size. During the Wenzel–Cassie transition, the critical water droplet and corresponding critical roughness may be expected, which are respectively described as the critical radius (R_Droplet,c) and wetting parameter (W_Roughness,c). From the work, R_Droplet,c may be termed as the smallest droplet size at which the Cassie state is expected for the corresponding W_Roughness,c. In combination with the structural study of water, it is due to the structural competition between interfacial and bulk water. Additionally, R_Droplet,c may be dependent on the W_Roughness,c. It is found that the R_Droplet,c is influenced by the distribution and geometric characteristics of surface roughness. A denser distribution of roughness is expected to result in a lower R_Droplet,c. Consequently, superhydrophobicity may be influenced by the characteristics of surface roughness and the size of the water droplet. The Cassie state is achieved when the wetting parameter of roughness is less than the W_Roughness,c and the water droplet is larger than the R_Droplet,c. Full article

Friction stir welding (FSW) is a key technology for manufacturing T-shaped thin-walled structures and avoiding fusion welding defects. However, the quantitative relationship between its process parameters and the microstructure properties of the joint remains unclear. To address this, this study established regression models via response surface methodology (RSM) relating rotational speed (w), welding speed (v), and plunge depth (h) to the mechanical properties of T-joints. The optimal process parameters (400 rpm, 60 mm/min, 0.21 mm) were determined, under which the ultimate tensile strength (UTS) and weld nugget hardness (WNH) of the joint reached 74.1% (377 MPa) and 94.4% (153 Hv) of the base materials (BM) respectively, with v showing the most significant influence on joint mechanical properties. Microstructural observations revealed that from the BM to the stirring zone (SZ), the grains underwent a continuous evolution from coarsening, partial recrystallization to complete dynamic recrystallization (DRX). In the SZ, due to severe plastic deformation and high heat input, the continuous dynamic recrystallization (CDRX) was the dominant mechanism, and the grain was significantly refined. The heat input in the thermomechanical affected zone (TMAZ) is relatively low, mainly geometric dynamic recrystallization (GDRX). DRX-driven grain refinement was the primary strengthening factor in the joint, with hardness closely related to grain size. However, thermal cycling induced softening in the heat-affected zone (HAZ) and promoted the precipitation of brittle compounds such as Al₃Mg₂ and MgZn₂, which caused crack initiation exhibiting intergranular brittle fracture. Subsequently, under stress drive, it extends to SZ, mainly characterized by ductile fracture. Full article

Laser surface microtexturing has emerged as an effective approach for improving the performance of adhesive joints between dissimilar materials. In this study, the influence of laser-generated micrometric surface features on the mechanical behavior of hybrid adhesive joints was investigated for two material systems: structural steel bonded to polyamide (PA66) and structural steel bonded to technical ceramic (Al₂O₃). Single-lap joints were manufactured using a two-component epoxy adhesive with two nominal bond-line thicknesses (0.1 mm and 1.0 mm). Prior to bonding, selected surfaces were modified by ultrashort-pulse laser microtexturing, producing well-defined circular features with characteristic depths on the order of tens of micrometers. The resulting microstructures were characterized using optical and scanning electron microscopy, and their geometric parameters were quantified through profilometric measurements. Mechanical performance was evaluated under shear and bending loading conditions. The results demonstrate a substantial increase in joint strength for laser-microtextured surfaces compared with non-textured references for both material combinations. The effect of surface microtexturing was more pronounced than the influence of adhesive layer thickness within the investigated range. These findings confirm that laser-induced surface microtexturing is a versatile and application-oriented surface preparation method capable of enhancing the reliability of adhesive bonding in hybrid metal–polymer and metal–ceramic assemblies. Full article

To address the problems of high digging resistance, elevated energy consumption, and severe soil adhesion encountered during mechanized potato harvesting, a bionic potato digging shovel inspired by the corrugated dorsal structure of the white grub was developed. Based on reverse-engineered geometric curves, two longitudinally corrugated shovel models (L-S-1 and L-S-2) were constructed, and a coupled soil–potato–shovel model was established using the Discrete Element Method (DEM) to evaluate soil disturbance characteristics and digging resistance at a forward speed of 0.5 m/s and an entry angle of 35°. The simulation results indicated that the longitudinally corrugated shovel L-S-2 exhibited the best overall performance, reducing digging resistance by 13.87% and increasing the soil fragmentation rate by 20.67% compared with a conventional flat shovel (P-S). Using L-S-2 as the baseline design, additional DEM simulations were conducted at forward speeds ranging from 0.4 to 0.6 m/s to systematically investigate the influence of operating speed on digging performance. To further enhance anti-adhesion performance, a composite bionic shovel (H-L-S-2) was developed by embedding polytetrafluoroethylene (PTFE) hydrophobic material into the surface of L-S-2 and reinforcing the shovel tip using laser cladding. Soil-bin experiments were then performed under controlled conditions with forward speeds of 0.4–0.6 m/s and soil moisture contents of 15–20% at an entry angle of 35°, and the results showed an average resistance reduction rate of 17.46%, with a maximum reduction of 18.02%. Both DEM simulations and soil-bin tests confirmed the effectiveness of the composite bionic shovel in reducing soil adhesion, with the number of adhered soil particles decreasing by 41.2% in simulations and the mass of adhered soil reduced by 37.5% in physical tests. These results demonstrate that coupling a bionic corrugated structure with surface material modification can effectively reduce digging resistance, enhance soil fragmentation, and mitigate soil adhesion, providing a practical approach for optimizing the design of potato digging shovels. Full article

Thin-walled laminated cooling plates integrate internal channels and pin-fin cores, producing reduced and spatially non-uniform stiffness that changes welding restraint and distortion. This study investigates stiffness-controlled plastic-strain evolution in laser butt welding of GH3230 laminated plates, with geometrically identical solid plates as reference. A coupled heat-transfer and thermo-mechanical finite element model was developed in MSC Marc using a composite Gaussian surface–volumetric moving heat source and temperature-dependent properties. The thermal solution was validated against near-weld thermal cycles and fusion geometry; mechanical predictions were evaluated by CMM distortion and residual-stress measurements. Both structures show comparable residual-stress magnitudes and spatial trends, indicating that residual stress is governed mainly by the local weld thermal gradient. In contrast, the laminated plate exhibits larger angular/bending distortion. Simulations show that, although the plastic-strain pattern is similar, the laminated plate develops higher peak plastic strain confined to a narrower band near the weld, with the transverse plastic strain dominating. Plastic strain–temperature paths reveal continued transverse plastic-strain accumulation during cooling with limited recovery, consistent with restraint redistribution induced by stiffness non-uniformity. An equivalent restraint–stiffness spring model explains this “narrower-but-stronger” plastic zone and links stiffness to yielding and residual plastic-strain magnitude, supporting distortion prediction and stiffness-informed control of welded laminated cooling plates. Full article

This study investigates the early-age bond behavior between steel reinforcement and lightweight alkali-activated concrete (LWA-AAC) using pull-out tests and modeling. Deformed and plain steel bars with different diameters were embedded in two LWA-AAC matrices to examine the effects of curing age, matrix strength, confinement, and bar surface geometry. The bond of plain bars is governed primarily by adhesion and friction and shows weak dependence on matrix strength or confinement. In contrast, the bond strength of deformed bars increases with curing age and matrix strength, while reduced confinement promotes a transition from ductile pull-out to brittle splitting failure. This confinement-sensitive transition highlights the dominant role of matrix tensile capacity in controlling bond stability in LWA-AAC. Compared with lightweight ordinary Portland cement (OPC) concrete, LWA-AAC exhibits more brittle bond behavior, characterized by smaller peak slip, steeper post-peak softening, and lower residual bond stress. Existing OPC-based bond models show limited applicability to LWA-AAC due to differences in failure mechanisms and confinement sensitivity. New empirical models incorporating matrix tensile strength and geometric confinement are proposed to predict bond parameters and bond–slip responses, providing a mechanism-informed basis for the design of reinforced LWA-AAC structures. Full article

This study presents a multidisciplinary investigation of the archeological site of Iuvanum (Abruzzo, central Italy), integrating geophysics, geomatics, architectural analysis and archeology with the purpose of exploring the relationship between surface remains and buried structures of archeological value. This research focuses on the area covering part of the forum and part of the basilica, where ground-penetrating radar (GPR) surveys were conducted to detect subsurface anomalies potentially associated with unexcavated architectural features. GPR line scans were acquired under complex topographic conditions, processed, and assembled into a three-dimensional representation, from which volumes of interest (VOIs) were extracted. These geophysical results were integrated into a comprehensive three-dimensional framework together with high-resolution UAV photogrammetry, digital elevation models, orthophotos and a virtual architectural model (VAM) of the site. The integrated visualization environment greatly facilitates the recognition of spatial relations between the detected anomalies and the hypothesized architectural elements. The observed GPR anomalies confirmed wall remains that were initially speculated or located along their geometrical continuation. Pavement levels, as well as some structures asymmetrical with respect to the purely geometric reconstruction, were also identified. This study demonstrates how integrating GPR with geomatic and archeological approaches improves the reliability and interpretative depth of non-invasive archeological prospecting. The proposed workflow provides a reproducible methodological framework propedeutical to excavation planning and suitable for the integration of information from multi-data sensors. Full article

Surface texture plays a key role in pavement safety and performance, yet its degradation is influenced by multiple interacting factors that vary across road networks. This study developed statistical models to characterize and predict surface texture evolution on Portuguese highways using linear mixed-effects modeling. Texture measurements collected on 7204 pavement sections, each 100 m in length, over three monitoring cycles were analyzed alongside traffic, climatic, pavement structural, geometric, and spatial variables. The hierarchical structure of the data, with repeated measurements nested within pavement sections, was explicitly accounted for via random intercepts and random slopes. At the same time, temporal correlation was modeled via an autoregressive error structure. Two model specifications were evaluated: a model including only traffic and climatic variables and an extended model incorporating pavement and geometric characteristics. Results indicate that texture evolution is statistically associated with cumulative traffic loading, temperature-related indicators, precipitation, surface course type, lane position, vertical alignment, and altitude. The extended model showed a significantly better fit and superior predictive performance, as confirmed by information criteria and cross-validation metrics. The findings highlight the importance of accounting for section-level heterogeneity and roadway characteristics when modeling texture degradation. The proposed modeling framework provides a statistically scalable and robust tool for texture prediction, accounting for regional-specificities and long-term pavement management decisions. Full article

In engineering practice, additively manufactured (AM) metal and metal alloy structural components, which often contain geometric discontinuities to fulfil functional requirements, are subjected to cyclic service loads. Among the possible loading configurations, far-field Mode I loading is frequently considered as a nominal reference condition. Within this context, a methodology for the fatigue assessment of notched AM Scalmalloy components subjected to Mode I far-field loading is proposed, combining the Strain Energy Density (SED) approach with a multiaxial critical plane-based fatigue criterion. The fatigue assessment is carried out at a verification point whose position is defined as a function of the characteristic length of the SED control volume for Mode I loading, determined through two alternative procedures, and of the surface roughness of the component. The proposed methodology is validated against experimental fatigue data available in the literature for AM Scalmalloy specimens featuring a circumferential semi-circular notch and subjected to Mode I far-field cyclic loading, which induces a locally multiaxial stress state at the notch root, given that the formulation does not rely on material-specific assumptions and could in principle be extended to other notched AM metal and metal alloy components. Full article

Offshore wind energy is an attractive renewable energy source due to its advantages. However, the chaotic marine environment makes the analysis of offshore wind energy extremely difficult. Furthermore, studying the behavior of wind turbines under rare and hazardous natural events such as rogue waves is crucial for the safety and operation of wind turbines and the platforms mounted on them. Therefore, this study numerically investigates the aerodynamic, hydrodynamic, and structural properties of the National Renewable Energy Laboratory (NREL) 5 MW wind turbines under the effect of the Draupner wave, the first marine rogue wave ever recorded. To this end, the geometric and structural information of the NREL 5 MW wind turbines mounted on monopile and jacket platforms is explained. The characteristics of the Draupner wave and the variations in its wave height time series are investigated. The recorded wave height time series values are imported into the QBlade program, and the dynamics of NREL 5MW monopile and jacket wind turbines are simulated. Based on the simulation data, the aerodynamic, hydrodynamic, and structural properties of these structures are examined and analyzed. The results demonstrate that Draupner waves have a significant effect on the aerodynamic, hydrodynamic, and structural parameters of the wind turbines. These parameters are observed to reach their highest values, particularly between the 250th and 280th seconds, when the Draupner wave height reaches its peak. Our findings indicate that the jacket structure experienced higher total forces due to its larger wetted surface area and geometric complexity, while the monopile foundation showed higher inertial loading in the X-direction because of its larger added mass. Additionally, we observed that total aerodynamic power generation is significantly affected by the passage of the Draupner rogue wave. We discuss our findings and their limitations. This numerical study is intended to be a milestone for researchers working on the structural health of offshore wind turbines and platforms under the effect of rogue waves. Full article