Search Results (176)

High-viscosity stratified strata, characterized by complex geotechnical properties such as strong cohesion, low permeability, and pronounced layered structures, exhibit significant lateral friction resistance and high-end resistance during steel sheet pile installation. These factors substantially increase construction difficulty and may even cause structural damage. This study addresses two critical mechanical challenges during vibratory pile driving in Fujian Province’s hydraulic engineering project: prolonged high-frequency driving durations, and severe U-shaped steel sheet pile head damage in high-viscosity stratified soils. Employing the Coupled Eulerian–Lagrangian (CEL) numerical method, a systematic investigation was conducted into the penetration resistance, stress distribution, and damage patterns during vibratory pile driving under varying conditions of cohesive soil layer thickness, predrilled hole spacing, and aperture dimensions. The correlation between pile stress and penetration depth was established, with the influence mechanisms of key factors on driving-induced damage in high-viscosity stratified strata under multi-factor coupling effects elucidated. Finally, the feasibility of predrilling techniques for resistance reduction was explored. This study applies the damage prediction model based on the CEL method to U-shaped sheet piles in high-viscosity stratified formations, solving the problem of mesh distortion in traditional finite element methods. The findings provide scientific guidance for steel sheet pile construction in high-viscosity stratified formations, offering significant implications for enhancing construction efficiency, ensuring operational safety, and reducing costs in such challenging geological conditions. Full article

Compared to spiral bevel gear drives with localized conjugation, line contact spiral bevel gears possess a significantly larger meshing area, theoretically achieving full tooth surface contact and substantially enhancing load capacity. To accurately support the root strength calculation and parameter design of line contact spiral bevel gear drives, this paper presents a theoretical analysis and experimental study of the root bending stress of gear pairs. First, based on the analysis of the meshing characteristics of line contact spiral bevel gear pairs, the load distribution along the contact lines is investigated. Using the slicing method, the load distribution characteristics along the contact line are obtained, and the load sharing among multiple tooth pairs during meshing is further studied. Then, by applying a cantilever beam bending stress model, the root bending stress on such a gear drive is calculated. A root bending moment distribution model is proposed based on the characteristics of the line load distribution previously obtained, from which a formula for calculating root bending stress is derived. Finally, static-condition experiments are conducted to test the root bending stress. The accuracy of the proposed calculation method is verified through experimental testing and finite element analysis. The results of this study provide a foundation for designing lightweight and high-power-density spiral bevel gear drives. Full article

With engineering plastics increasingly replacing traditional materials in various drive and control gear systems across numerous industrial sectors, material selection for any gearwheel critically impacts its mechanical and thermal properties. This paper investigates the engagement of steel and Polyvinylidene Fluoride (PVDF) gear pairs tested under several load conditions to determine polymer gears’ characteristic service life and failure modes. Furthermore, recognizing that the application of polymer gears is limited by insufficient data on their temperature-dependent mechanical properties, this study establishes a correlation between the tribological contact, meshing temperatures, and wear coefficients of PVDF gears. The results demonstrate that the flank surface wear of the PVDF gears is directly proportional to the temperature and load level of the tested gears. Several distinct load-induced failure modes have been detected and categorized into three groups: abrasive wear resulting from the hardness disparity between the engaging surfaces, thermal failure caused by heat accumulation at higher load levels, and tooth fracture occurring due to stiffness changes induced by the compromised tooth cross-section after numerous operating cycles at a specific wear rate. Full article

Cycloidal reducers are widely used in precision drive systems due to their reduced backlash in meshing and compact design. However, their operational durability is limited by surface wear and lubricant degradation under elevated contact loads and boundary lubrication conditions. This study introduces a modified wear prediction model based on four-ball tribological testing, specifically adapted to simulate the complex tribological conditions in cycloidal gear contacts. The model incorporates the total acid number (TAN) and thermal conductivity coefficient of the lubricant as dimensionless factors, enabling a dynamic prediction of wear intensity as the lubrication degrades. This innovation allows an accurate estimation of service life and reliability in high-load, small-contact-area mechanical systems and offers a practical diagnostic tool for the predictive maintenance of gear transmissions. Full article

An excessive temperature rise in vehicle tires during driving can degrade dynamic performance, safety, and fuel efficiency by increasing rolling resistance and softening materials. To mitigate these issues, it is essential to enhance the cooling performance of tires without inducing significant aerodynamic penalties. In this study, we propose the use of sidewall-mounted cooling fins and investigate their aero-thermal effects under both ground-contact and no-ground-contact conditions. Seven fin configurations were tested, with installation angles ranging from −67.5° to 67.5°, with positive angles indicating an orientation opposite to the direction of wheel rotation and negative angles indicating alignment with the direction of rotation. High-fidelity unsteady Reynolds-averaged Navier–Stokes simulations were conducted using the SST k-w turbulence model. The sliding mesh technique was employed to capture the transient flow behavior induced by tire rotation. The results showed that, under no-ground-contact conditions, the 45° configuration achieved a 16.8% increase in convective heat transfer with an increase in drag less than 3%. Under ground-contact conditions, the 22.5° configuration increased heat transfer by over 13% with a minimal aerodynamic penalty (~1.7%). These findings provide valuable guidance for designing passive cooling solutions that improve tire heat dissipation performance without compromising aerodynamic efficiency. Full article

This study proposes the use of Physics-Informed Neural Networks (PINNs) to further advance the curvature interference analysis method. The nonlinear equation system encountered in determining the curvature interference limit line is embedded into the PINN loss function, thereby enabling the solution of high-dimensional, nonlinear equations. Computational results demonstrate that the PINN model achieves a solution accuracy on the order of 10⁻¹³ when solving multidimensional nonlinear systems, which is comparable to the classical Fsolve algorithm. The curvature interference analysis reveals the presence of two curvature interference boundary lines, although they rarely extend to the worm gear tooth surface. A study on the influence of design parameters on the interference boundaries indicates that the axial installation distance has the greatest impact. Inadequate axial spacing causes the interference limit line to shift toward the inner end of the worm gear, significantly increasing the risk of interference in that region. The proposed curvature interference analysis method based on PINNs can be extended to other types of gear drives. It also lays the foundation for future work on establishing both forward and inverse mappings between design parameters and curvature interference using PINNs. Full article

Estuaries are dynamic ecosystems with crucial environmental, economic, and social functions, driving extensive hydro-morphological research supported by numerical modeling. This study systematically reviews estuarine modeling applications over the past 15 years to identify commonly used tools, model configurations, and validation strategies, to examine regional trends in the application, and to explore and discuss the relative emphasis on hydrodynamic, sediment transport, and morphological modeling within the selected studies. Following the PRISMA 2020 methodology, a comprehensive search in Scopus and Web of Science identified 3926 articles, from which 197 met the eligibility criteria. Each study was analyzed to assess modeling software, mesh types, dimensional configurations, and validation parameters. Results indicate that DELFT3D is the most widely used tool, followed by TELEMAC and FVCOM, with a preference for two-dimensional models and structured meshes. Model accuracy, assessed through Skill Scores, confirms their reliability in representing estuarine dynamics. Additionally, findings reveal significant geographical disparities, with China leading research efforts, while Latin America and Africa remain underrepresented. This gap highlights the need to expand modeling efforts in these regions to enhance estuarine management and resilience. Strengthening numerical modeling in diverse contexts will improve the predictive capacity of hydro-morphological processes, supporting sustainable decision-making in estuarine environments. Full article

Structural cracks can critically undermine infrastructure integrity, driving the need for precise, scalable inspection methods beyond conventional visual or 2D image-based approaches. This study presents an automated system integrating photogrammetric 3D reconstruction with deep learning to quantify crack dimensions in a spatial context. Multiple images are processed via Agisoft Metashape to generate high-fidelity 3D meshes. Then, a subset of images are automatically selected based on camera orientation and distance, and a deep learning algorithm is applied to detect cracks in 2D images. The detected crack edges are projected onto a 3D mesh, enabling width measurements grounded in the structure’s true geometry rather than perspective-distorted 2D approximations. This methodology addresses the key limitations of traditional methods (parallax, occlusion, and surface curvature errors) and shows how these limitations can be mitigated by spatially anchoring measurements to the 3D model. Laboratory validation confirms the system’s robustness, with controlled tests highlighting the importance of near-orthogonal camera angles and ground sample distance (GSD) thresholds to ensure crack detectability. By synthesizing photogrammetry and a convolutional neural network (CNN), the framework eliminates subjectivity in inspections, enhances safety by reducing manual intervention, and provides engineers with dimensionally accurate data for maintenance decisions. Full article

To address the issues of severe surrounding-rock failure and ground support component failure in advancing working-face driving roadways (AWFDRs) in ultra-close coal seams, this study used the 5202 air-return roadway in Huaye Coal Mine as a case study and for engineering background. Numerical simulation, theoretical analysis, and industrial application methods were adopted to analyze the laws of the dynamic evolution of vertical stress in such roadways. The mine pressure behaviors of AWFDRs in ultra-close coal seams were also clarified, thereby enabling the proposal of a solution; namely, zoned support technology. The results show that the 5202 air-return roadway, as an AWFDR in an ultra-close coal seam, exhibits five different characteristic behaviors of mine pressure zones during excavation. Zone 1 is influenced by the adjacent working-face mining under goaf; Zone 2 is influenced by the adjacent goaf lateral abutment stress under goaf; Zone 3 is influenced by the stress of the overlying solid coal; Zone 4 is influenced by the adjacent goaf lateral abutment stress under the overlying solid coal; and Zone 5 is influenced by stabilized stress under the overlying solid coal. The mine pressure behaviors of these zones were ranked, from most intense to weakest, as follows: Zone 3 > Zone 1 > Zone 4 > Zone 2 > Zone 5. Based on this, a basic support scheme was proposed, which involves using bolt–mesh–beam supports combined with shed supports under the goaf and bolt–mesh–beam supports combined with roof anchor cables under the overlying solid coal. Additionally, in Zones 1 and 3, roof anchor cables or rib anchor cables were supplemented as reinforcing supports, which were combined with the basic support scheme described above to form a zoned support scheme for the AWFDR. The analysis of mine pressure behavior and implementation of a zoned support scheme for AWFDRs in ultra-close coal seams provides technical and engineering references for roadway supports under similar mining conditions. Full article

This paper presents a vibration analysis method for detecting typical faults in gears of the drive train of a 2 MW wind turbine. The data were collected over a one-year period from an operating wind turbine with a gearbox composed of one planetary stage and two helical gear stages. Failures in two pairs of helical gears were identified: one involving pitting and wear in the gears connecting the intermediate-speed shaft to the low-speed shaft, and another one involving significant material detachment in the gears connecting the intermediate-speed shaft to the high-speed shaft. The continuous evaluation of time signals, frequency spectra, and amplitude modulations allowed the most sensitive sensors and frequencies for predicting surface damage on gear teeth in this type of turbine to be determined. A steady-state frequency analysis was performed, enabling the detection of the aforementioned surface faults. This approach is simpler compared with more complex transient-state techniques. By tracking vibration signals over time, the importance of analyzing gear mesh frequencies and their harmonics was highlighted. Additionally, it was found that the progression of gear damage was dependent on the power output of the wind turbine. As a result, the most appropriate ranges of power were identified, within which the evolution of the vibration measurement was associated with the damage evolution. Since many turbines currently in operation have similar designs and power output levels, the present findings can serve as a guideline for monitoring an extensive number of units. Full article

This paper investigates the special phenomenon that the practical immersed depth of a spiral bevel gear as the driving gear under splash lubrication is significantly less than the static depth. To quantify the practical immersion depth, a computational fluid dynamics (CFD) approach integrated with image processing techniques is utilized to determine the dynamic immersion depth and the associated churning power loss. First, a theoretical method is developed to estimate the churning losses of the bevel gear by replacing the static immersion depth with the practical dynamic immersion depth. Subsequently, the CFD method, which incorporates the overset mesh technique and the volume-of-fluid (VOF) method, is employed to simulate the gear churning phenomenon. Meanwhile, the dynamic immersion depth is determined through image processing techniques that analyze the oil distribution characteristics in the splash-lubricated bevel gear. Finally, experimental results obtained from a dedicated lubrication test rig are favorably compared with the numerical results, confirming that the practical dynamic immersion depth is an accurate and effective parameter for calculating power losses. Full article

Recently, with policies aimed at strengthening domestic manufacturing and technological innovation, the robotics industry has been growing rapidly, and its applications are expanding across various industrial fields. Accordingly, the importance of high-performance speed reducers with flexibility and precision is gradually increasing. The tooth profiles used in conventional harmonic reducers have structural limitations, such as meshing discontinuity, restrictions on the radius of curvature of the tooth base, and distortion of the contact trajectory, especially when the number of teeth is small. These problems limit the design freedom of the reducer and make it difficult to secure contact stability and durability under precision driving conditions. To solve these problems, this paper proposes a new tooth profile design equation, the IH (Involute Harmonic) tooth profiles and the HTPs (Hybrid Tooth Profiles), using the cycloid curve to overcome the structural limitations of the conventional harmonic tooth profile, which is difficult to design under small-tooth-number conditions, and to enable tooth design without restrictions on the number of teeth. HTP tooth profile is a new gear tooth profile design method that utilizes IH tooth profile and cycloid curve to optimize the meshing characteristics of gears. A tooth profile design tool based on the HTP equation was developed using Python 3.13.3. The tool’s effectiveness was validated through simulations assessing tooth meshing and interference. Using the tool, an R21_z3 reducer with a single-stage high reduction ratio was designed to evaluate practical applicability. A prototype was fabricated using 3D printing with PLA material, and experimental testing confirmed the absence of meshing or interference issues, consistent with simulation results. Through this study, we verified the usefulness of the HTP tooth profile design formula and design tool using the IH tooth profile and cycloid curve, and it is expected that the proposed HTP tooth profile can be utilized as a tooth profile applicable to various reducer designs. Full article

In the operation process of modern industrial equipment, as the core transmission component, the operation state of the gearbox directly affects the overall performance and service life of the equipment. However, the current gear operation is still faced with problems such as poor monitoring, a single detection index, and low data utilization, which lead to incomplete evaluation results. In view of these challenges, this paper proposes a shape and property integrated gearbox monitoring system based on digital twin technology and artificial intelligence, which aims to realize real-time fault diagnosis, performance prediction, and the dynamic visualization of gear through virtual real mapping and data interaction, and lays the foundation for the follow-up predictive maintenance application. Taking the QPZZ-ii gearbox test bed as the physical entity, the research establishes a five-layer architecture: functional service layer, software support layer, model integration layer, data-driven layer, and digital twin layer, forming a closed-loop feedback mechanism. In terms of technical implementation, combined with HyperMesh 2023 refinement mesh generation, ABAQUS 2023 simulates the stress distribution of gear under thermal fluid solid coupling conditions, the Gaussian process regression (GPR) stress prediction model, and a fault diagnosis algorithm based on wavelet transform and the depth residual shrinkage network (DRSN), and analyzes the vibration signal and stress distribution of gear under normal, broken tooth, wear and pitting fault types. The experimental verification shows that the fault diagnosis accuracy of the system is more than 99%, the average value of the determination coefficient (R²) of the stress prediction model is 0.9339 (driving wheel) and 0.9497 (driven wheel), and supports the real-time display of three-dimensional cloud images. The advantage of the research lies in the interaction and visualization of fusion of multi-source data, but it is limited to the accuracy of finite element simulation and the difficulty of obtaining actual stress data. This achievement provides a new method for intelligent monitoring of industrial equipment and effectively promotes the application of digital twin technology in the field of predictive maintenance. Full article

A harmonic drive (HD) is a precision reduction device widely utilized in the core joints of high-end equipment such as spacecraft and robots. The design of an excellent tooth profile is the core challenge related to the performance of HD. This investigation aims to propose a design method of a fully conjugated cycloid tooth profile (CTP) for HD. Firstly, the rationality of CTP use for HD is analyzed, and the cycloidal characteristics of the tooth trajectory are studied by use of canonical warping distance. Then, initial CTP equations are constructed, adopting the trajectory mapping results. Presetting the addendum CTP of circular spline, the conjugate CTP of flexspline is then designed using the envelope method. Subsequently, the envelope of the designed flexspline addendum is used to reverse-design the circular spline dedendum. The backlash is calculated to evaluate the CTPs designed with different radial displacement coefficients. Research shows that the tooth trajectory has cycloidal characteristics; therefore, the HDs that use CTP can realize a fully conjugate engagement. Moreover, the variable control parameters enable the proposed CTP expression to have excellent fitting characteristics, resulting in small and uniform mesh backlash distribution. The CTP is expected to become one of the ideal tooth profiles of HD. Full article

The construction industry is a major contributor to global carbon emissions, driving the need for sustainable solutions. Ultra-lightweight structures have emerged as an effective approach to reducing material usage and energy consumption. This study explores the potential of ultra-lightweight architectural systems through a learning-by-doing methodology, integrating innovative composite materials, PolRe, and knitting techniques to enhance tensegrity structures for sustainable, deployable, and efficient structural designs. Combining physical modeling, inspired by Frei Otto and Heinz Isler, with digital simulations using Kangaroo 2 and Python, this research employs form-finding and finite element analysis to validate structural performance. A 1:5 scale prototype was constructed using a manual knitting machine adapted from traditional knitting techniques. The integration of elastic meshes and rigid joints produced modular tensegrity systems that balance tension and compression, creating reversible, deployable, and material-efficient solutions. This study bridges conceptual aesthetics with structural efficiency, providing a template for sustainable, ultra-lightweight, textile-based structures. Full article