Search Results (920)

The evaporation dynamics of droplets on smooth and inclined micro-pillar surfaces were experimentally investigated. The surface temperature was increased from 50 °C to 120 °C, with the inclination angles being 0°, 30°, 45°, and 60° respectively. The dynamic parameters, including contact area, nucleation density, bubble stable diameter, and droplet asymmetry, were recorded using two high-speed video cameras, and the corresponding evaporation performance was analyzed. Experimental results showed that the inclination angle had a significant influence on the evaporation of micro-pillar surfaces than smooth surfaces as well as a positive correlation between the enhancement performance of the micro-pillars and increasing inclination angles. This angular dependence arises from surface inclination-induced tail elongation and the corresponding asymmetry of droplets. With definition of the one-dimensional asymmetry factor (ε) and volume asymmetry factor (γ), it was proven that although the asymmetric thickness of the droplets reduces the nucleation density and bubble stable diameter, the droplet asymmetry significantly increased the heat exchange area, resulting in a 37% improvement in the evaporation rate of micro-pillar surfaces and about a 15% increase in its enhancement performance to smooth surfaces when the inclination angle increased from 0°to 60°. These results indicate that asymmetry causes changes in heat transfer conditions, specifically, a significant increase in the wetted area and deformation of the liquid film, which are the direct enhancement mechanisms of inclined micro-pillar surfaces. Full article

Bioinspired soft adhesive systems capable of stable and intelligent object manipulation are critical for next-generation robotics. In this study, a soft gripper combining an octopus-inspired suction mechanism with a frog-inspired hexagonal friction pattern was developed to enhance adhesion performance under diverse surface conditions and orientations. The hexagonal pattern, inspired by frog toe pads, contributed to improved stability against tilting and shear forces. The integrated strain gauge enabled real-time monitoring of gripping states and facilitated the detection of contact location and changes in load distribution during manipulation. The system demonstrated robust adhesion under both dry and wet conditions, with adaptability to various object geometries and inclinations. These results suggest broad potential for bioinspired gripping platforms in fields such as collaborative robotics, medical tools, and underwater systems. Full article

This paper focuses on the sealing failure problem of double-lip seal rings for high-speed ball bearings used in unmanned aerial vehicles. By using ANSYS 2023R1 software, a thermal–stress–wear coupled finite element model was established. Taking the contact pressure and volume loss due to wear as indicators to evaluate sealing performance, this study analyzed the influence of lip seal structural parameters on sealing performance, performed response surface optimization of the seal structure parameters and conducted a comparative test on lip seals before and after optimization. The research results show that the contact pressure at the main lip of the lip seal was the greatest, which was 0.79 MPa, and the volume loss due to wear lip seal was 7.94 × 10⁻⁷ mm³. Optimal sealing performance is achieved when the seal lip inclination angle is 41.68°, the middle width of the lip seal is 0.153 mm, the main lip height is 0.179 mm, the spring center distance is 0.37 mm and the radial interference is 0.0034 mm. After optimization, the grease leakage rate of the sealing ring decreased by 48% compared to before optimization. Full article

In response to the need for separation and utilization of residual film mixtures after transformation of protaetia brevitarsis larvae, a pneumatic drum-sieve-type separator for transforming mixtures of protaetia brevitarsis larvae was designed. First, the suspension velocity of each component was determined by the suspension speed test. Secondly, the separation process of residual film, larvae, and insect sand was formulated on the basis of biological activities, shape differences, and aerodynamic response characteristics. Eventually, the main structural parameters and working parameters of the machine were determined. In order to optimize the separation effect, a single-factor experiment and a quadratic regression response surface experiment containing three factors and three levels were carried out, and the corresponding regression model was established. The experimental results showed that the effects of the air speed at the inlet, inclination angle of the sieve cylinder, and rotational speed of the sieve cylinder on the impurity rate of the residual film decreased in that order, and that the effects of the rotational speed of the sieve cylinder, inclination angle of the sieve cylinder, and air speed at the inlet on the inactivation rate of the larvae decreased in that order. Through parameter optimization, a better combination of working parameters was obtained: the rotational speed of the sieve cylinder was 24 r/min, the inclination angle of the sieve cylinder was −0.43°, and the air speed at the inlet was 5.32 m/s. The average values of residual film impurity rate and larval inactivation rate obtained from the material sieving test under these parameters were 8.74% and 3.18%, with the relative errors of the theoretically optimized values being less than 5%. The results of the study can provide a reference for the resource utilization of residual film and impurity mixtures and the development of equipment for the living body separation of protaetia brevitarsis. Full article

Water systems are highly vulnerable to biofilm formation, which can compromise water quality, operational efficiency, and public health. Factors such as surface material properties and gravitational orientation of the surface play critical roles in the early stages of microbial attachment and biofilm development. This study examines the impact of gravity and surface composition on the initial adhesion of Pseudomonas fluorescens AR11—a model organism for biofilm research. Focusing on stainless steel (SS) and polycarbonate (PC), two materials commonly used in water and wastewater infrastructure, bacterial adhesion was evaluated at surface inclinations of 0°, 45°, 90°, and 180° to assess gravitational impact. After three hours of contact, fluorescence microscopy and image analysis were used to quantify surface coverage and cluster size distribution. The results showed that both material type and orientation significantly affected early biofilm formation. PC surfaces consistently exhibited higher bacterial adhesion at all angles, with modest variations, suggesting that material properties are a dominant factor in initial colonization. In contrast, SS showed angle-dependent variation, indicating a combined effect of gravitational convection and surface characteristics. These insights contribute to a deeper understanding of biofilm dynamics under realistic environmental conditions, including those encountered in space systems, and support the development of targeted strategies for biofilm control in water systems and spaceflight-related infrastructure. Full article

In this study, the tool axis inclination angle with respect to the surface normal is used to compare the wear of spherical and toroidal milling cutters. Five different surface types were machined in this investigation using three toroidal and three spherical milling cutters at inclination angles of 15°, 35°, and 55°. Each cutter processed 45 surfaces, nine of each type. The MM1-200 microscope was used to monitor tool wear under a microscope after the surfaces had been machined. A comparison diagram and microscopic pictures of tool wear in relation to the wear surface are presented in the paper. Additionally, it contrasts the tool edge’s state at the conclusion of machining with its state following five years of storage, during which time the tool was subjected to environmental influences. Full article

This study investigates the influence of inclination on a submerged plate (SP) device acting as both a breakwater (BW) and a wave energy converter (WEC) subjected to representative regular and realistic irregular waves of a sea state across 11 inclination angles. Numerical simulations were conducted using ANSYS Fluent. Regular waves were generated by Stokes’s second-order theory, while the WaveMIMO technique was employed to generate irregular waves. Using the volume of fluid (VOF) method to model the water–air interaction, both approaches generate waves by imposing their vertical and horizontal velocity components at the inlet of the wave flume. The SP’s performance as a BW was analyzed based on the upstream and downstream free surface elevations of the device; in turn, its performance as a WEC was determined through its axial velocity beneath the plate. The results indicate that performance varies between regular and irregular wave conditions, underscoring the importance of accurately characterizing the sea state at the intended installation site. These findings demonstrate that the inclination of the SP plays a critical role in balancing its dual functionality, with certain configurations enhancing WEC efficiency by over 50% while still offering relevant BW performance, even under realistic irregular sea conditions. Full article

Falls are a major safety concern in physically demanding occupations such as roofing, where workers operate on inclined surfaces under unstable postures. While inertial measurement units (IMUs) are widely used in wearable fall detection systems, they often fail to capture early indicators of instability related to foot–ground interactions. This study evaluates the effectiveness of plantar pressure sensors, alone and combined with IMUs, for fall detection on sloped surfaces. We collected data in a controlled laboratory environment using a custom-built roof mockup with incline angles of 0°, 15°, and 30°. Participants performed roofing-relevant activities, including standing, walking, stooping, kneeling, and simulated fall events. Statistical features were extracted from synchronized IMU and plantar pressure data, and multiple machine learning models were trained and evaluated, including traditional classifiers and deep learning architectures, such as MLP and CNN. Our results show that integrating plantar pressure sensors significantly improves fall detection. A CNN using just three IMUs and two plantar pressure sensors achieved the highest F1 score of 0.88, outperforming the full 17-sensor IMU setup. These findings support the use of multimodal sensor fusion for developing efficient and accurate wearable systems for fall detection and physical health monitoring. Full article

In wind-assisted orchard spraying operations, the dynamic response of leaves—manifested through changes in their posture—critically influences droplet deposition on both sides of the leaf surface and the penetration depth into the canopy. These factors are pivotal in determining spray coverage and the spatial distribution of pesticide efficacy. However, current research lacks comprehensive quantification and correlation analysis of the temporal response characteristics of leaves under wind disturbances. To address this gap, a systematic analytical framework was proposed, integrating real-time leaf segmentation and tracking, geometric feature quantification, and statistical correlation modeling. High-frame-rate videos of fluttering leaves were acquired under controlled wind conditions, and background segmentation was performed using principal component analysis (PCA) followed by clustering in the reduced feature space. A fine-tuned Segment Anything Model 2 (SAM2-FT) was employed to extract dynamic leaf masks and enable frame-by-frame tracking. Based on the extracted masks, time series of leaf area and inclination angle were constructed. Subsequently, regression analysis, cross-correlation functions, and Granger causality tests were applied to investigate cooperative responses and potential driving relationships among leaves. Results showed that the SAM2-FT model significantly outperformed the YOLO series in segmentation accuracy, achieving a precision of 98.7% and recall of 97.48%. Leaf area exhibited strong linear coupling and directional causality, while angular responses showed weaker correlations but demonstrated localized synchronization. This study offers a methodological foundation for quantifying temporal dynamics in wind–leaf systems and provides theoretical insights for the adaptive control and optimization of intelligent spraying strategies. Full article

This study presents the design and development of a structurally optimized mobile robotic system with a machine learning-based energy-efficient path planning framework. Topology optimization (TO) and finite element analysis (FEA) were applied to reduce structural weight while maintaining mechanical integrity. The optimized components were manufactured using Fused Deposition Modeling (FDM) with ABS (Acrylonitrile Butadiene Styrene) material. A custom power analysis tool was developed to compare energy consumption between the optimized and initial designs. Real-world current consumption data were collected under various terrain conditions, including inclined surfaces, vibration-inducing obstacles, gravel, and direction-altering barriers. Based on this dataset, a path planning model was developed using machine learning algorithms, capable of simultaneously optimizing both energy efficiency and path length to reach a predefined target. Unlike prior works that focus separately on structural optimization or learning-based navigation, this study integrates both domains within a single real-world robotic platform. Performance evaluations demonstrated superior results compared to traditional planning methods, which typically optimize distance or energy independently and lack real-time consumption feedback. The proposed framework reduces total energy consumption by 5.8%, cuts prototyping time by 56%, and extends mission duration by ~20%, highlighting the benefits of jointly applying TO and ML for sustainable and energy-aware robotic design. This integrated approach addresses a critical gap in the literature by demonstrating that mechanical light-weighting and intelligent path planning can be co-optimized in a deployable robotic system using empirical energy data. Full article

This research investigates enhancing the performance of an Archimedes screw-type hydrokinetic turbine (ASHT). A 3D transient computational model employing the six degrees of freedom (6-DOF) methodology within the ANSYS Fluent software 2022 R1, was selected for this purpose. A central composite design (CCD) methodology was applied within the response surface methodology (RSM) to enhance the turbine’s power coefficient ($C_p$). Key independent factors, including blade length (L), blade inclination angle ($\gamma$), and external diameter ($D_e$), were systematically varied to determine their optimal values. The optimization process yielded a maximum $C_p$ of 0.337 for L, $\gamma$, and $D_e$ values of 168.921 mm, 51.341°, and 245.645 mm, respectively. Experimental validation was conducted in a hydraulic channel, yielding results that demonstrated a strong correlation with the numerical predictions. This research underscores the importance of geometric design optimization in improving the energy capture efficiency of the ASHT, contributing to its potential viability as a competitive renewable energy solution in the pre-commercial phase of development. Full article

This paper explores the complex dynamics of mixed convective flow in a Casson fluid saturated in a non-Darcy porous medium, focusing on the influence of gyrotactic microorganisms, internal heat generation, and multiple convective mechanisms. Casson fluids, known for their non-Newtonian behavior, are relevant in various industrial and biological contexts where traditional fluid models are insufficient. This study addresses the limitations of the standard Darcy’s law by examining non-Darcy flow, which accounts for nonlinear inertial effects in porous media. The governing equations, derived from conservation laws, are transformed into a system of no linear ordinary differential equations (ODEs) using similarity transformations. These ODEs are solved numerically using a finite differencing method that incorporates central differencing, tridiagonal matrix manipulation, and iterative procedures to ensure accuracy across various convective regimes. The reliability of this method is confirmed through validation with the MATLAB (R2024b) bvp4c scheme. The investigation analyzes the impact of key parameters (such as the Casson fluid parameter, Darcy number, Biot numbers, and heat generation) on velocity, temperature, and microorganism concentration profiles. This study reveals that the Casson fluid parameter significantly improves the velocity, concentration, and motile microorganism profiles while decreasing the temperature profile. Additionally, the Biot number is shown to considerably increase the concentration and dispersion of motile microorganisms, as well as the heat transfer rate. The findings provide valuable insights into non-Newtonian fluid behavior in porous environments, with applications in bioengineering, environmental remediation, and energy systems, such as bioreactor design and geothermal energy extraction. Full article

Ball-end milling cutters are normally used for complex surface machining. During the milling process, the tool posture and cutting parameters of the ball-end milling cutters have a significant impact on chip formations and morphological changes. Based on the Cutter Workpiece Engagement (CWE) model, this study establishes a chip flow model for ball-end milling cutters with consideration of the tool posture variation. The machining experiments of Ti-6Al-4V with a 15° inclined plane and different feed directions were carried out. The influence mechanism of time-varying tool posture on chip formation was systematically investigated. The results reveal an interaction between the chip flow direction and the cutting velocity direction. The included angle between the chip flow directions at the maximum and minimum contact points in the CWE area affects the degree of chip curling, with a smaller angle leading to weaker curling. This research provides a theoretical foundation for the optimization of posture parameters of ball-end milling cutters and expounds on the influence of the chip flow angle on chip deformation. Full article

In high-elevation mining areas, the roadbeds of certain surface ore haul roads are predominantly composed of sandstone. These sandstones are exposed to cold climatic conditions for long periods and are highly susceptible to erosion by the effects of freeze–thaw, which can degrade their support properties. This paper investigates the mechanism of strength deterioration of sandstone containing prefabricated cracks under cyclic loading and unloading after experiencing freeze–thaw. Sandstone specimens containing prefabricated cracks were prepared and subjected to 0, 20, 40, 60, and 80 freeze–thaw cycle tests. The strength changes were tested, and the crack extension process was analyzed using numerical simulation techniques. The study results show the following: 1. The wave propagation speed within the sandstone is more sensitive to changes in the number of freeze–thaw cycles. In contrast, mass damage shows significant changes only when more freeze–thaw cycles are experienced. 2. As the number of freeze–thaw cycles increases, the frequency of energy release from the numerical model accelerates. 3. The trend of the Cumulative Strain Difference (${\epsilon }_c$) reflects that the plastic strain difference between numerical simulation and actual measurement gradually decreases with increasing stress cycle level. 4. With the increase in freeze–thaw cycles, the damage morphology of the specimen undergoes a noticeable change, which is gradually transformed from monoclinic shear damage to X-shaped conjugate surface shear damage. 5. The number of tensile cracks dominated throughout the cyclic loading and unloading process, but with the increase in freeze–thaw cycles, the percentage of shear cracks increased. As the freeze–thaw cycles increase, sandstones are more inclined to undergo shear damage. These findings are important guidelines for road design and maintenance in alpine mining areas. Full article

Numerous dark linear recurrent features called Recurring Slope Lineae (RSL) are observed on Martian surfaces, hypothesized as footprints of high-salinity liquid flow. This paper experimentally examined this “wet hypothesis” by analyzing the aspect ratios (length/width) of the flow traces on the granular material column to investigate how they vary with the granular material column, liquid and its flow rate, and inclination. While pure water produced low aspect ratios (<1.0) on the Martian regolith simulant column, high-salinity fluid (CaCl₂(aq)) traces exhibited significantly higher aspect ratios (>4.0), suggesting that pure water alone is insufficient to explain RSL formulation. Furthermore, the aspect ratios of high-salinity fluid traces on Martian regolith simulants were among the highest observed across all studied granular materials with similar particle sizes, aligning closely with actual RSL observed on Martian slopes. The results further suggest that variable ARs of actual RSL at the given slope can partly be explained by variable flow rates of high-salinity flow as well as salinity (i.e., viscosity) of flow. The results can be attributed to the unique granular properties of Martian regolith, characterized by the lowest permeability and Beavers–Joseph slip coefficient among the studied granular materials. This distinctive microstructure surface promotes surface flow over Darcy flow within the regolith column, leading to a narrow and long-distance feature with high aspect ratios observed in Martian RSL. Thus, our findings support that high-salinity flows are the primary driver behind RSL formation on Mars. Our study suggests the presence of salts on the Martian surface and paves the way for further investigation into RSL formulation processes. Full article