Search Results (723)

Since direct laser surface texturing of polymers is an emerging area, considerable attention is given to this technique with the aim of forming a basis for follow-up research that could open the way for potential technological ideas and optimization in novel applications. Laser pre-processing of ballistic textiles can raise surface roughness of smooth para-aramid fibres and as a result can improve the adhesion of functional coatings applied in following processing steps, thus opening new possibilities for material performance improvement. The impact resistance of ballistic fabric depends on the ability of its yarns in contact with the projectile absorb energy locally and disperse it to adjacent yarns without undergoing severe damage or failure. In addition to the yarn deformation and fracture, yarn resistance to pull-out contributes to the dissipation of impact energy significantly. The objective of this study is to optimize Kevlar^® KM2+ fabric surface topographies by adjusting the continuous wave (CW) CO₂ laser parameters in such a way that it increases the surface roughness and resistance to the yarn pull-out from the fabric without destroying the unique structure of the of Kevlar^® KM2+ fibres. Experimental research measured data show increase in surface roughness by 50–53% and set of laser parameter variants have been obtained that allow for an increase in KM2+ 440D woven fabric yarns pull out force from fabric in the range from 50% up to 99% compared to the untreated one. Full article

The ODYSEA (Ocean DYnamics and Surface Exchange with the Atmosphere) mission will provide simultaneous two-dimensional measurements of currents and winds for the first time. According to the ODYSEA radar concept, with a high incidence angle, current noise is primarily driven by backscattered power, which is triggered by wind speed. Therefore, random noise will affect the quality of observations. In low wind conditions, the absence of surface roughness increases the noise level considerably, to the point where the measurement becomes unusable, as the error can exceed 3 m/s at 5 km posting compared to mean current amplitudes of tens of cm/s. Winds higher than 7.5 m/s enable current measurements at 5 km posting with an RMS accuracy below 50 cm/s, but derivatives of currents will amplify noise, hampering the understanding of ocean dynamics and the interaction between the ocean and the atmosphere. In this context, this study shows the advantages and limitations of using noise-reduction algorithms. A convolutional neural network, a UNet inspired by the work of the SWOT (Surface Water and Ocean Topography) mission, is trained and tested on simulated radial velocities that are representative of the global ocean. The results are compared with those of classical smoothing: an Adaptive Gaussian Smoother whose filtering transfer function is optimized based on local wind speed (e.g., more smoothing in regions of low wind). The UNet outperforms the kernel smoother everywhere with our simulated dataset, especially in low wind conditions (SNR << 1) where the smoother essentially removes all velocities whereas the UNet mitigates random noise while preserving most of the signal of interest. Error is reduced by a factor of 30 and structures down to 30 km are reconstructed accurately. The UNet also enables the reconstruction of the main eddies and fronts in the relative vorticity field. It shows good robustness and stability in new scenarios. Full article

This review surveys theoretical frameworks developed to describe rubber contact and friction on rough surfaces, with a particular focus on tire–road interaction. It begins with classical continuum approaches, which provide valuable foundations but show limitations when applied to viscoelastic materials and multiscale roughness. More recent formulations are then examined, including the Klüppel–Heinrich model, which couples fractal surface descriptions with viscoelastic dissipation, and Persson’s theory, which applies a statistical mechanics perspective and later integrates flash temperature effects. Grosch’s pioneering experimental work is also revisited as a key empirical reference linking friction, velocity, and temperature. A comparative discussion highlights the ability of these models to capture scale-dependent contact and energy dissipation while also noting practical challenges such as calibration requirements, parameter sensitivity, and computational costs. Persistent issues include the definition of cutoff criteria for roughness spectra, the treatment of adhesion under realistic operating conditions, and the translation of detailed power spectral density (PSD) data into usable inputs for predictive models. The review emphasizes progress in connecting material rheology, surface characterization, and operating conditions but also underscores the gap between theoretical predictions and real tire–road performance. Bridging this gap will require hybrid approaches that combine physics-based and data-driven methods, supported by advances in surface metrology, in situ friction measurements, and machine learning. Overall, the paper provides a critical synthesis of current models and outlines future directions toward more predictive and application-oriented tire–road friction modeling. Full article

During the actual service process, water-lubricated bearings on ships are often in complex operating environments such as low speed, heavy load and salt-sand water areas. To meet the requirements of high load-bearing capacity, long service life and the ability to discharge sand and dissipate heat during the service of bearings, research has been conducted on water-lubricated bearings made of polyetheretherketone (PEEK) with a semi-groove structure. Mathematical and physical models based on the averaged Reynolds equation have been established. By adopting the method of multi-physics field coupling, the lubrication characteristics of the bearings under the coupling influence of multiple factors in the salt-sand water environment (lubrication interface (the surface roughness of the bearing bush), different working conditions (water supply pressure, rotational speed, eccentricity)) are analyzed. Finally, a water-lubricated bearing test bench is set up to conduct bearing lubrication performance tests under multiple factors. The research shows that compared with liquid water, the salt-sand water environment exhibits better lubrication characteristics. The maximum water film pressure, the deformation amount of the bearing bush and the bearing capacity of the bearings increase with the increase of the rotational speed, water supply pressure and eccentricity, while the friction coefficient decreases. With the increase of the roughness of the bearing bush, these parameters decrease slightly and the friction coefficient increases. The presence of salt-sand particles can weaken the influence of roughness on the lubrication characteristics of the bearings. After considering the thermal effect, the mechanical load and thermal load act on the surface of the bearing bush together, resulting in an increase in the deformation amount of the bearing bush, a 0.11% drop in the water film pressure, and the highest temperature of the water film being concentrated at the outlet of the groove. The local semi-groove structure of PEEK can make the friction coefficient as low as 0.019. The comparison errors between the simulation and the experiment are within 10% (for water film pressure) and 2.6% (for friction coefficient), which verifies the reliability of the model. Full article

The unique hollowed-out catamaran hulls and complex environmental conditions in lake areas hinder traditional ranging algorithms (combining target detection and stereo matching) from accurately obtaining depth information near the center of ships. This not only impairs the navigation of electric tourist boats but also leads to high computing resource consumption. To address this issue, this study proposes a ranging method integrating improved ORB (Oriented FAST and Rotated BRIEF) with stereo vision technology. Combined with traditional optimization techniques, the proposed method calculates target distance and angle based on the triangulation principle, providing a rough alternative solution for the “gap period” of stereo matching-based ranging. The method proceeds as follows: first, it acquires ORB feature points with relatively uniform global distribution from preprocessed binocular images via a local feature weighting approach; second, it further refines feature points within the ROI (Region of Interest) using a quadtree structure; third, it enhances matching accuracy by integrating the FLANN (Fast Library for Approximate Nearest Neighbors) and PROSAC (Progressive Sample Consensus) algorithms; finally, it applies the screened matching point pairs to the triangulation method to obtain the position and distance of the target ship. Experimental results show that the proposed algorithm improves processing speed by 6.5% compared with the ORB-PROSAC algorithm. Under ideal conditions, the ranging errors at 10m and 20m are 2.25% and 5.56%, respectively. This method can partially compensate for the shortcomings of stereo matching in ranging under the specified lake area scenario. Full article

Additive manufacturing (AM) enables the fabrication of complex components with high geometric freedom, but it can introduce near-surface flaws due to rapid solidification, resulting in porosity and lack of fusion. In addition, localized melting and steep thermal gradients favor the formation of micro-cracks. Conventional ultrasonic techniques have shortcomings in detecting such flaws because of front-wall interference, further affected by surface roughness and anisotropy. This study evaluates the effectiveness of the Total Focusing Method (TFM), an advanced ultrasonic imaging technique implemented in Full Matrix Capture (FMC), for near-surface flaw detection in Laser Powder Bed Fusion (LPBF) AM components. To assess TFM performance, subsurface side-drilled holes (SDHs) in AM Ti-5Al-5V-5Mo-3Cr (Ti-5553) material were used as the reference reflectors and compared with Phased Array Ultrasonic Testing (PAUT) under identical conditions. Results showed that TFM achieved higher spatial resolution and more reliable detection of shallow flaws, successfully detecting features as shallow as 0.40 ± 0.05 mm below the surface, whereas PAUT was limited to greater depths. These findings demonstrate TFM as a reliable non-destructive evaluation method for shallow flaws in AM parts, while contributing one of the first systematic comparative datasets of PAUT and TFM for shallow SDHs in LPBF titanium alloys. Full article

Floods are among the most frequent and destructive natural hazards worldwide, with increasingly severe socioeconomic consequences due to rapid urbanization, land use changes, and climate variability. While the combination of Geographic Information Systems (GIS) with models such as HEC-RAS has been extensively explored for flood risk management, many existing studies remain limited to one-dimensional (1D) models or use coarse-resolution terrain data, often underestimating flood risk and failing to produce critical multivariate flood characteristics in densely built urban areas. This study applies a two-dimensional (2D) hydraulic modeling framework in HEC-RAS combined with GIS-based spatial analysis, using a high-resolution (1 × 1 m) LiDAR-derived Digital Terrain Model (DTM) and a hybrid mesh refined between 2 × 2 m and 8 × 8 m, with the main contributions represented by the specific application context and methodological choices. A key methodological aspect is the direct integration of synthetic hydrographs with defined exceedance probabilities (10%, 1%, and 0.1%) into the 2D model, thereby reducing the need for extensive hydrological simulations and defining a data-driven approach for resource-constrained environments. The primary novelty is the application of this high-resolution urban modeling framework to a Romanian urban–peri-urban setting, where detailed hydrological observations are scarce. Unlike previous studies in Romania, this approach applies detailed channel and floodplain discretization at high spatial resolution, explicitly incorporating anthropogenic features like buildings and detailed land use roughness for the accurate representation of local hydraulic dynamics. The resulting outputs (inundation extents, depths, and velocities) support risk assessment and spatial planning in the Ungheni locality (Iași County, Romania), providing a practical, transferable workflow adapted to data-scarce regions. Scenario results quantify vulnerability: for the 0.1% exceedance probability scenario (with a calibration accuracy of ±15–30 min deviation for peak flow timing), the flood risk may affect 882 buildings, 42 land parcels, and 13.5 km of infrastructure. This framework contributes to evidence-based decision-making for climate adaptation and disaster risk reduction strategies, improving urban resilience. Full article

This study describes the approach to develop hybrid nanostructures made of four varieties of ceramic nanotubes and three types of conductive polymers embedded with gold nanoparticles through a novel technique, which can exhibit distinct sensory properties not documented in the existing literature. Atomic force microscopy (AFM) analysis highlighted the characteristics of their surface roughness, identifying which could be the best choice for electrochemical electrodes depending on their surface structure. The incorporation of gold nanoparticles modifies the surface structure and forces the original grains to create voids that allow the gold particles to penetrate deeper and gather in small clusters, which in turn leads to a minor increase in grain size and localized sharpening of the peaks. The analysis mainly identified the peaks that were higher in relation to the valleys to identify a Gaussian distribution. It turned out that the configuration of ZnO nanotubes in the composites leads to the highest Ra values, with Al₂O₃ nanotubes coming in second place. Regarding the contribution of conducting polymers, PANI:EB presented the highest importance for all composites, while P3HT was relevant in several other cases. The evaluation of the electrode roughness, as described in this paper, is essential for the evaluation of its potential electrochemical activity and acts as a reliable measure that goes beyond the role of the evaluation of the active surface area (EASA). In our opinion, the evaluation of the EASA by traditional approaches described in the literature is not relevant for sensor applications, since the evaluation of the electrode surface structure must be performed before electrochemical tests, because the general electrochemical tests designed for sensor applications do not evaluate the EASA. Consequently, a thorough assessment of the electrode surface structure is advised, choosing the optimal electrodes according to this design, and additional data obtained from cyclic voltammetry will finally ascertain the true EASA and the actual performance of the respective electrode for identifying the target molecules. Full article

The seepage characteristics and heat transfer efficiency in rough fractures are indispensable for assessing the lifetime and production performance of geothermal reservoirs. In this study, a two-dimensional rough rock fracture model with different secondary roughness is developed using the wavelet analysis method to simulate the coupled flow and heat transfer process under multiscale roughness based on two theories: local thermal equilibrium (LTE) and local thermal nonequilibrium (LTNE). The simulation results show that the primary roughness controls the flow behavior in the main flow zone in the fracture, which determines the overall temperature distribution and large-scale heat transfer trend. Meanwhile, the nonlinear flow behaviors induced by the secondary roughness significantly influence heat transfer performance: the secondary roughness usually leads to the formation of more small-scale eddies near the fracture walls, increasing flow instability, and these changes profoundly affect the local water temperature distribution and heat transfer coefficient in the fracture–matrix system. The eddy aperture and eddy area fraction are proposed for analyzing the effect of nonlinear flow behavior on heat transfer. The eddy area fraction significantly and positively correlates with the overall heat transfer coefficient. Meanwhile, the overall heat transfer coefficient increases by about 3% to 10% for eddy area fractions of 0.3% to 3%. As the eddy aperture increases, fluid mixing is enhanced, leading to a rise in the magnitude of the local heat transfer coefficient. Finally, the roughness characterization was decomposed into primary roughness root mean square and secondary roughness standard deviation, and for the first time, an empirical correlation was established between multiscale roughness, flow velocity, and the overall heat transfer coefficient. Full article

The aim of the study is to investigate the influence of the physicochemical characteristics of the molecular and supramolecular structure of polymers on electroadhesive interactions and their change under the action of a constant electric field. Currently, this effect is modeled in electroadhesion studies, but the range of variable parameters is limited and includes permittivity, moisture content, and surface roughness. It is important to consider other physicochemical parameters, such as material crystallinity and surface characteristics, changes in which can affect the magnitude of electroadhesive forces. In this study, the electric field strength was varied by altering the constant voltage in the range of 3–8 kV. Polyethylene, ethylene-vinyl acetate copolymers, and polyvinyl acetate were used as substrates for adhesive systems. The influence of the concentration of vinyl acetate groups, which determine the energy characteristics of the surface, and the degree of crystallinity on electroadhesive interactions under conditions of an external constant electric field and without it was traced. The degree of crystallinity was varied both by the cooling rate and the orientation during drawing. It was shown that by changing the polar component of the surface energy and the proportion of the crystalline phase in the substrate, electroadhesive interactions can be increased by 4 times to 120 Pa compared to polyethylene. The obtained laws are explained by the local dipoles induced by polar functional groups, which enhance the polymer’s surface interactions with other materials and external fields. At the same time, the fixation of macromolecules in crystalline regions complicates polarization under the influence of an electric field. Full article

Nano- and micro-indentation have become essential tools for quantifying the micromechanical behavior of rocks beyond traditional macroscopic tests. This review summarizes the historical evolution, experimental methodologies, and interpretation models (e.g., Oliver–Pharr, Doerner–Nix, energy-based methods, Hertz/ECM/Lawn), with a particular focus on rock-specific challenges such as heterogeneity, anisotropy, and surface roughness. A structured literature survey (1980–August 2025) covers representative studies on shale, limestone, marble, sandstone, claystone, and granite. The transition from classical hardness measurements to advanced instrumented indentation has enabled more reliable determination of localized properties, including hardness, elastic modulus, fracture toughness, and creep. Special attention is given to the applicability and limitations of different interpretation models when applied to heterogeneous and anisotropic rocks. Current challenges include high sensitivity to surface conditions and difficulties in capturing the full complexity of natural rock behavior. Looking forward, promising directions involve intelligent systems that integrate AI-driven data analytics, robotic automation, and multiscale modeling (from molecular dynamics to continuum FEM) to enable predictive material design. This review aims to provide geoscientists and engineers with a comprehensive foundation for the effective application and further development of indentation-based testing in rock mechanics and geotechnical engineering. Full article

In this study, the modeling of rough surfaces by eddy-viscosity-based roughness models is investigated, specifically focusing on surfaces representative of deterioration in aero-engines. In order to test these models, experimental measurements from a rough T106C blade section at a Reynolds number of 400 K are adopted. The modeling framework is based on the k-ω-SST with Dassler’s roughness transition model. The roughness model is recalibrated for the k-ω-SST model. As a complement to the available experimental data, a high-fidelity test rig designed for scale-resolving simulations is built. This allows us to examine the local flow phenomenon in detail, enabling the identification and rectification of shortcomings in the current RANS models. The scale-resolving simulations feature a high-order flux-reconstruction scheme, which enables the use of curved element faces to match the roughness geometry. The wake-loss predictions, as well as blade pressure profiles, show good agreement, especially between LES and the model-based RANS. The slight deviation from the experimental measurements can be attributed to the inherent uncertainties in the experiment, such as the end-wall effects. The outcomes of this study lend credibility to the roughness models proposed. In fact, these models have the potential to quantify the influence of roughness on the aerodynamics and the aero-acoustics of aero-engines, an area that remains an open question in the maintenance, repair, and overhaul (MRO) of aero-engines. Full article

Against the backdrop of climate change and the accelerated process of urbanization, the risks of extreme weather and natural disasters that cities are facing are increasing day by day. Based on the framework of the local climate zone (LCZ), this paper studies the spatio-temporal evolution of the urban surface morphology and the heat island effect of Tongren City. Using the comprehensive mapping technology of remote sensing and GIS, combined with the inversion of surface temperature, the distribution of LCZs and the changes in heat island intensity were analyzed. The results show that: (1) The net increase in forest coverage area leads to a decrease in shrub and grassland area, resulting in an ecological deficit. (2) The built-up area expands along transportation routes, and industrial areas encroach upon natural space. (3) The urban heat island pattern has evolved from a single core to multiple cores and eventually becomes fragmented. (4) Among the seasonal dominant driving factors of urban heat islands, the impervious water surface is in summer, the terrain roughness and building height are in winter, and the building density is in spring and autumn. These findings provide feasible insights into mitigating the heat island effect through climate-sensitive urban planning. Full article

This study explores the formulation of chitosan microparticles through ionic gelation and presents detailed physicochemical characterization, release studies, and the utility and potential uses for drug delivery. Three formulations were prepared under rate-controlled conditions (stirring at 800 rpm and pH maintained at 4.6) with and without stabilizers to examine the effects of formulation parameters on particle morphology and structural stability. To determine different structural and chemical characteristics, Attenuated Total Reflectance Fourier-Transform Infrared spectroscopy (ATR–FTIR), Scanning Electron Microscopy (SEM), and dynamic light scattering (DLS) were utilized, which confirmed that the particles formed and assessed size distribution and structural integrity. Atomic force microscopy (AFM) was used to quantify surface roughness and potential nanomechanical differences that may derive from the use of different modifiers. Coformulation of bovine serum albumin (BSA) permitted assessment of encapsulation efficiency and drug release capacity. Based on in vitro release evidence, the protein released at a different rate, and the dispersion of formulations under physiological conditions (PBS, pH 7.4, 37 °C) confirmed the differences in stability between formulations. The tunable physical characteristics, mild fabrication conditions, and controlled drug release demonstrated that the chitosan particles could have useful relevance as a substrate for localized drug delivery and as a bioactive scaffold for tissue regenerative purposes. Full article

Many agencies use pavement condition assessments such as the Pavement Surface Evaluation and Rating (PASER) and Pavement Condition Index (PCI) to develop localized pavement management programs. However, both techniques involve some subjectivity and inconsistent measurement practices, making it difficult to scale uniformly across all 86 thousand miles of local agency roadway in Indiana’s 92 counties. International Roughness Index (IRI) data is one emerging data source that could address this need. This paper evaluates the feasibility of using Connected Vehicle-estimated IRI (IRI_CVe) data for long-term statewide pavement monitoring on local roads. The analysis is based on approximately 4.1 billion daily IRI_CVe records collected over a multi-year study period from connected vehicles operating throughout the state. A modular data processing workflow was developed to clean and process these records and is presented in detail in the paper. The study includes network-level condition comparisons, insights on spatiotemporal trends, and localized segment-level condition monitoring. In 2024, approximately 53% of paved local roads in Indiana had at least one IRI_CVe observation per year. Coverage varied widely by county: for example, 79% of roads in urban Hamilton County had coverage, but only 14% had coverage in rural Martin County. The findings in this study demonstrate the potential of IRI_CVe to support local agency pavement asset management by providing cost-effective data-driven insights in near real-time. Full article