Search Results (199)

The paper presents an experimentally validated regression model for dry clutch friction lining wear, accounting for the influence of clutch temperature, initial slip speed, torque, and closing time. The experimental data have been collected by using a custom-designed disk-on-disk computer-controlled tribometer and conducting repetitive real operation-like clutch closing cycles for different levels of the above operating parameters. The model is designed to be cycle-wise, predicting cumulative worn volume expectation and standard deviation after each closing cycle. It is organized around three distinctive submodels, which provide predictions of: (i) wear rate expectation, (ii) wear rate variance, and (iii) elevated wear rate during run-in operation. Finally, the wear rate expectation and variance submodels and the overall, cumulative worn volume model are validated on independent experimental datasets. The main novelty of the presented research lies in the development of stochastic multi-input cycle-wise dry cutch wear model for clutch design and monitoring applications. Full article

Driven by stringent emission regulations, advanced combustion modes utilizing turbulent jet ignition technology are pivotal for enhancing the performance of marine low-speed natural gas dual-fuel engines. This review focuses on three novel combustion modes, yielding key conclusions: (1) Compared to the conventional DJCDC mode, the TJCDC mode exhibits a significantly higher swirl ratio and turbulence kinetic energy in the main chamber during initial combustion. This promotes natural gas jet development and combustion acceleration, leading to shorter ignition delay, reduced combustion duration, and a combustion center (CA50) positioned closer to the Top Dead Center (TDC), alongside higher peak cylinder pressure and a faster early heat release rate. Energetically, while TJCDC incurs higher heat transfer losses, it benefits from lower exhaust energy and irreversible exergy loss, indicating greater potential for useful work extraction, albeit with slightly higher indicated specific NOx emissions. (2) In the high-compression ratio TJCPC mode, the Liquid Pressurized Natural Gas (LPNG) injection parameters critically impact performance. Delaying the start of injection (SOI) or extending the injection duration degrades premixing uniformity and increases unburned methane (CH₄) slip, with the duration effects showing a load dependency. Optimizing both the injection timing and duration is, therefore, essential for emission control. (3) Increasing the excess air ratio delays the combustion phasing in TJCPC (longer ignition delay, extended combustion duration, and retarded CA50). However, this shift positions the heat release more optimally relative to the TDC, resulting in significantly improved indicated thermal efficiency. This work provides a theoretical foundation for optimizing high-efficiency, low-emission combustion strategies in marine dual-fuel engines. Full article

This paper presents a comprehensive study of torsional stick–slip vibrations in rotary drilling systems through a comparison between two lumped parameter models with differing complexity: a simple two-degree-of-freedom (2-DOF) model and a complex high-degree-of-freedom (high-DOF) model. The two models are developed under identical boundary conditions and consider an identical nonlinear friction torque dynamic involving the Stribeck effect and dry friction phenomena. The high-DOF model is calculated with the Finite Element Method (FEM) to enable accurate simulation of the dynamic behavior of the drill string and accurate representation of wave propagation, energy build-up, and torque response. Field data obtained from an Algerian oil well with Measurement While Drilling (MWD) equipment are used to guide modeling and determine simulations. According to the findings, the FEM-based high-DOF model demonstrates better performance in simulating basic stick–slip dynamics, such as drill bit velocity oscillation, nonlinear friction torque formation, and transient bit-to-surface contacts. On the other hand, the 2-DOF model is not able to represent these effects accurately and can lead to inappropriate control actions and mitigation of vibration severity. This study highlights the importance of robust model fidelity in building reliable real-time rotary drilling control systems. From the performance difference measurement between low-resolution and high-resolution models, the findings offer valuable insights to optimize drilling efficiency further, minimize non-productive time (NPT), and improve the rate of penetration (ROP). This contribution points to the need for using high-fidelity models, such as FEM-based models, in facilitating smart and adaptive well control strategies in modern petroleum drilling engineering. Full article

The scenario adaptability of agricultural machinery chassis in hilly and mountainous regions has become a key area of innovation in modern agricultural equipment development in China. Due to the fragmented nature of farmland, steep terrain (often exceeding 15°), complex topography, and limited suitability for mechanization, traditional agricultural machinery experiences significantly reduced operational efficiency—typically by 30% to 50%—along with poor mobility. These limitations impose serious constraints on grain yield stability and the advancement of agricultural modernization. Therefore, enhancing the scenario-adaptive performance of chassis systems (e.g., slope adaptability ≥ 25°, lateral tilt stability > 30°) is a major research priority for China’s agricultural equipment industry. This paper presents a systematic review of the global development status of agricultural machinery chassis tailored for hilly and mountainous environments. It focuses on three core subsystems—power systems, traveling systems, and leveling systems—and analyzes their technical characteristics, working principles, and scenario-specific adaptability. In alignment with China’s “Dual Carbon” strategy and the unique operational requirements of hilly–mountainous areas (such as high gradients, uneven terrain, and small field sizes), this study proposes three key technological directions for the development of intelligent agricultural machinery chassis: (1) Multi-mode traveling mechanism design: Aimed at improving terrain traversability (ground clearance ≥400 mm, obstacle-crossing height ≥ 250 mm) and traction stability (slip ratio < 15%) across diverse landscapes. (2) Coordinated control algorithm optimization: Designed to ensure stable torque output (fluctuation rate < ±10%) and maintain gradient operation efficiency (e.g., less than 15% efficiency loss on 25° slopes) through power–drive synergy while also optimizing energy management strategies. (3) Intelligent perception system integration: Facilitating high-precision adaptive leveling (accuracy ± 0.5°, response time < 3 s) and enabling terrain-adaptive mechanism optimization to enhance platform stability and operational safety. By establishing these performance benchmarks and focusing on critical technical priorities—including terrain-adaptive mechanism upgrades, energy-drive coordination, and precision leveling—this study provides a clear roadmap for the development of modular and intelligent chassis systems specifically designed for China’s hilly and mountainous regions, thereby addressing current bottlenecks in agricultural mechanization. Full article

This study investigates the operational performance of fruit-picking robots under varying terrain slopes and soil moisture conditions, with a focus on comparing wheeled and tracked locomotion systems. A modular robot platform was designed and tested in both controlled environments and actual mountainous orchards in Shandong, China. The experiments assessed key performance metrics—average speed, slip rate, and path deviation—under combinations of four slope levels (0°, 8°, 18°, 28°) and three soil moisture levels (dry 10%, moderate 20%, wet 35%). Results reveal that wheeled robots perform optimally on dry and flat terrain but experience significant slippage and path deviation under steep and wet conditions. In contrast, tracked robots maintain better stability and terrain adaptability, demonstrating lower slip rates and more consistent trajectories across a wide range of conditions. A synergistic deterioration effect was observed when high slope and high soil moisture co-occur, significantly degrading the performance of wheeled systems, while tracked systems mitigated these effects. Complementary semi-structured interviews with 20 orchard stakeholders—including farmers, growers, and hired pickers—highlighted key user expectations: robust traction, terrain adaptability, reduced physical labor, and operational safety. The findings suggest that future agricultural robots should adopt adaptive hybrid mobility systems and integrate environmental perception capabilities to enhance performance in complex agricultural scenarios. These insights contribute practical and theoretical guidance for the design and deployment of intelligent fruit-picking robots in diverse field environments. Full article

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

This paper introduces a robust neural adaptive MIMO control strategy to improve the stability and adaptability of bipedal locomotion amid uncertainties and external disturbances. The control combines nonlinear dynamic inversion, finite-time convergence, and radial basis function (RBF) neural networks for fast, accurate trajectory tracking. The main novelty of the presented control strategy lies in unifying instantaneous feedback, real-time learning, and dynamic adaptation within a multivariable feedback framework, delivering superior robustness, precision, and real-time performance under extreme conditions. The control scheme is implemented on a 5-DOF underactuated $\mathrm{R}\mathrm{A}\mathrm{B}\mathrm{B}\mathrm{I}\mathrm{T}$ robot using a $\mathrm{d}\mathrm{S}\mathrm{P}\mathrm{A}\mathrm{C}\mathrm{E}\mathrm{D}\mathrm{S}1103$ platform with a sampling rate of $∆t=1.5 \mathrm{m}\mathrm{s} (667 \mathrm{H}\mathrm{z})$. The experimental results show excellent performance with the following: The robot achieved stable cyclic gaits while keeping the tracking error within $e=\pm 0.04 \mathrm{r}\mathrm{a}\mathrm{d}$ under nominal conditions. Under severe uncertainties of trunk mass variations ${∆m}_{\mathrm{t}\mathrm{r}\mathrm{u}\mathrm{n}\mathrm{k}}=+100\%$, limb inertia changes ${∆I}_{\mathrm{l}\mathrm{i}\mathrm{m}\mathrm{b}}=\pm 30\%$, and actuator torque saturation at $\tau =\pm 150 \mathrm{N}\mathrm{m}$, the robot maintains stable limit cycles with smooth control. The performance of the proposed controller is compared with classical nonlinear decoupling, non-adaptive finite-time, neural-fuzzy learning, and deep learning controls. The results demonstrate that the proposed method outperforms the four benchmark strategies, achieving the lowest errors and fastest convergence with the following: $\mathrm{I}\mathrm{A}\mathrm{E}=1.36$, $\mathrm{I}\mathrm{T}\mathrm{A}\mathrm{E}=2.43$, $\mathrm{I}\mathrm{S}\mathrm{E}=0.68$, $t_{ss}=1.24 \mathrm{s}$, and $M_p=2.21\%$. These results demonstrate evidence of high stability, rapid convergence, and robustness to disturbances and foot-slip. Full article

With the further implementation and development of the Western Development Strategy, studying the mechanical behavior and deformation characteristics of deep-buried tunnels in layered hard rock under high ground stress conditions holds considerable engineering significance. To study the mechanical properties and long-term deformation and failure characteristics of different bedding stratified rocks, this research employed an MTS815 electro-hydraulic servo rock testing system and a French TOP rheometer. Triaxial compression tests, rheological property tests, and long-term cyclic and unloading tests were conducted on shale samples under varying confining pressures and bedding angles. The results indicate that (1) under triaxial compression, shale demonstrates pronounced anisotropic behavior. When the confining pressure is constant, the peak strength of the rock sample exhibits a “U”-shaped variation with the bedding angle (its minimum value at 60°). For a fixed bedding angle, the peak strength of the rock sample progressively increases as the confining pressure rises. (2) The mode of shale failure varies with the angle: at 0°, shale exhibits conjugate shear failure; at 30°, shear slip failure along the bedding is controlled by the bedding weak plane; at 60° and 90°, failure occurs through the bedding. (3) During the creep process of layered shale, brittle failure characteristics are evident, with microcracks within the sample gradually failing at stress concentration points. The decelerated and stable creep stages are prominent; while the accelerated creep stage is less noticeable, the creep rate increases with increasing stress level. (4) Under low confining pressure, the peak strength during cyclic loading and unloading creep processes is lower than that of conventional triaxial tests when the bedding plane dip angles are 0° and 30°, which is the opposite at 60° and 90°. (5) In the cyclic loading and unloading process, Poisson’s ratio gradually increases, whereas the elastic modulus, shear modulus, and bulk modulus gradually decrease. Full article

Aiming at the problems of energy utilization efficiency and braking stability in electric vehicles, a high-efficiency and energy-saving control strategy that takes both driving and braking into account is proposed with the distributed hub motor-driven vehicle as the research object. Under regular driving and braking conditions, the front and rear axle torque distribution coefficients are optimized by an adaptive particle swarm algorithm based on simulated annealing and a multi-objective co-optimization strategy based on variable weight coefficients, respectively. During emergency braking, the anti-lock braking strategy (ABS) based on sliding mode control realizes the independent distribution of torque among four wheels. The joint simulation verification based on MATLAB R2023a/Simulink-Carsim 2020.0 shows that under World Light Vehicle Test Cycle (WLTC) conditions, the optimization strategy reduces the driving energy consumption by 3.20% and 2.00%, respectively, compared with the average allocation and the traditional strategy. The braking recovery energy increases by 4.07% compared with the fixed proportion allocation, improving the energy utilization rate of the entire vehicle. The wheel slip rate can be quickly stabilized near the optimal value during emergency braking under different adhesion coefficients, which ensures the braking stability of the vehicle. The effectiveness of the strategy is verified. Full article

Rotary drilling systems with PDC bits, commonly used for drilling deep wells in the production and exploration of oil and natural gas, frequently encounter severe vibrations. These vibrations can cause significant damage to the drilling system, particularly its downhole components, leading to drilling performance inefficiencies, notably reducing the rate of penetration and incurring high costs. This paper presents a parametric study on a proposed new axial semi-active tool designed to mitigate these unwanted vibrations. The tool, an axial absorber with tunable stiffness and damping coefficients over a wide range, composed of a hybrid magnetorheological elastomer-fluid (MRE-F), is installed above the PDC bit. In this study, the lumped parameter model considering axial and torsional vibrations is followed to assess the effectiveness of including the proposed absorber in the drill-string system’s behavior and to estimate the optimal coefficient values for achieving high-efficiency drilling. The drilling system response shown in this study indicates that, with optimal axial absorber coefficient values, the bit dynamically stabilizes, and unwanted vibrations are minimized, effectively eliminating the occurrence of bit-bounce and stick–slip, even when operating at critical frequencies. The proposed semi-active control tool has been proven to significantly reduce maintenance time, reduce the costs associated with severe vibrations, extend the lifespan of bottom-hole assembly components, and achieve smoother drilling with a simple addition to the drilling system. Full article

The rapid expansion of land reclamation necessitates a fundamental understanding of the strain rate effects on structured clays. While the rate effect has been widely studied in various soils, the interplay between bond structure and strain rate sensitivity remains unclear. This study investigates these mechanisms using artificially cemented kaolin (ACK) with controlled curing periods (2 and 30 days) to simulate naturally bonded clays. A series of undrained triaxial tests was conducted under low (100 kPa) and high (600 kPa) confining stresses, employing constant strain rates (0.01–5%/h) pre-peak and stepwise rate changes post-peak. The results reveal that the strain rate effects are governed by the bond structure maturity and drainage mechanisms. For the 30-day curing ACK, the pre-peak strength under low confining stress shows minimal rate sensitivity due to the rigid bond, while high confining stress induces a “negative” rate effect attributed to localised drainage along shear planes. The post-peak behaviour consistently exhibits a positive isotach-type rate effect (+3%/log-cycle) driven by viscous sliding. In contrast, the 2-day curing ACK displays negative rate effects pre-peak influenced by ongoing curing and post-peak strength reductions (−8%/log-cycle) linked to stick-slip dynamics. These findings establish a framework for predicting rate-dependent behaviour in structured clays, offering insights into land reclamation and subsequent construction work. Full article

To address the limitations of low modeling accuracy in physics-based methods—which often lead to poor vehicle-tracking performance and high energy consumption—this paper proposes an intelligent vehicle modeling and trajectory tracking control method based on a dilated convolutional neural network (DCNN). First, an effective dataset was constructed by incorporating historical state information, such as longitudinal tire forces and vehicle speed, to accurately capture vehicle dynamic characteristics and reflect energy variations during motion. Next, a dilated convolutional vehicle system model (DCVSM) was designed by combining vehicle dynamics with data-driven modeling techniques. This model was then integrated into a model predictive control (MPC) framework. By solving a nonlinear optimization problem, a dilated convolutional model predictive controller (DCMPC) was developed to enhance tracking accuracy and reduce energy consumption. Finally, a co-simulation environment based on CarSim and Simulink was used to evaluate the proposed method. Comparative analyses with a traditional MPC and a neural network-based MPC (NNMPC) demonstrated that the DCMPC consistently exhibited superior trajectory tracking performance under various test scenarios. Furthermore, by computing the tire-slip energy loss rate, the proposed method was shown to offer significant advantages in improving energy efficiency. Full article

To address the performance degradation in model predictive control (MPC) under vehicle state uncertainties caused by external disturbances (e.g., crosswinds and tire cornering stiffness variations) and rigid constraint conflicts, we propose a robust MPC framework with adaptive weight adjustment and dynamic constraint relaxation. Traditional MPC methods often suffer from infeasibility or deteriorated tracking accuracies when handling model mismatches and disturbances. To overcome these limitations, three key innovations are introduced: a three-degree-of-freedom vehicle dynamic model integrated with recursive least squares-based online estimation of tire slip stiffness for real-time lateral force compensation; an adaptive weight adjustment mechanism that dynamically balances control energy consumption and tracking accuracy by tuning cost function weights based on real-time state errors; and a dynamic constraint relaxation strategy using slack variables with variable penalty terms to resolve infeasibility while suppressing excessive constraint violations. The proposed method is validated via ROS (noetic)–MATLAB2023 co-simulations under crosswind disturbances (0–3 m/s) and varying road conditions. The results show that the improved algorithm achieves a 13% faster response time (5.2 s vs. 6 s control cycles), a 15% higher minimum speed during cornering (2.98 m/s vs. 2.51 m/s), a 32% narrower lateral velocity fluctuation range ([−0.11, 0.22] m/s vs. [−0.19, 0.22] m/s), and reduced yaw rate oscillations ([−1.8, 2.8] rad/s vs. [−2.8, 2.5] rad/s) compared with a traditional fixed-weight MPC algorithm. These improvements lead to significant enhancements in trajectory tracking accuracy, dynamic response, and disturbance rejection, ensuring both safety and efficiency in autonomous vehicle control under complex uncertainties. The framework provides a practical solution for real-time applications in intelligent transportation systems. Full article

Increasing developments in the offshore energy sector have led to demand for robotics use in inspection, maintenance, and repair maintenance tasks, particularly for the service life extension of structures. These robots experience slippage due to varying surface conditions caused by environmental factors and marine growth, leading to inconsistent traction forces and potential mission failures in single-drive systems. This paper explores control strategies and mechanical configurations both in simulation and on the physical industrial robot to mitigate slippage in offshore robotic operations, improving reliability and reducing costs. This study examines mechanical and control modifications such as multi-wheel drive (MWD), PID velocity control, and a feedback-linearized slip control system with an individual wheel disturbance observer to detect surface variations. The results indicate that a 3 WD setup with slip control handles the widest range of conditions but suffers from high control effort due to chattering effects. The simulations show potential for slip control; practically, challenges arise from low sampling rates compared to traction changes. In real-world conditions, a PID-controlled MWD system, combined with increased normal force, achieves better traction and stability. The findings highlight the need for further investigation into the mechanical design and sensor feedback, with the refinement of slip control strategies and observer design for the offshore environment. Full article

Casing deformation (CD) is generally believed to be caused by the slip of fractures in the strata and its shear effects on horizontal wells. However, the casing deformation mode based on this theory cannot fully match the measurement data, and the differential deformation characteristics and the mechanism behind this phenomenon are not completely clear. To elucidate the mechanisms of CD and enhance prevention and control measures, the CD modes in Shunan Block were identified and deformation mechanisms of these modes were comprehensively investigated. Our research shows the following: (1) Under the mechanism of penetrating fracture shear deformation, CD exhibit obvious shear deformation, and the natural fractures near the intersection point with the wellbore are prone to form a higher risk of deformation. (2) Natural fractures with tips approaching the wellbore experience intense stress concentration (1.6 times higher than shear stress) during activation, resulting in compression and asymmetrical CD. (3) The shear deformation induced by penetrating fractures is 15.52 mm, while the fracture tip-induced compression deformation demonstrates a substantially greater magnitude at 44.17 mm. This compressive deformation exceeds the shear deformation by a factor of approximately 2.85. (4) The stress concentration at the fracture tip is highly sensitive to the injection rate. Hence, adherence to the “avoiding stress concentration” principle is crucial in hydraulic fracturing operations. The conclusion indicates that in addition to penetrating fracture shear deformation, fracture tip compression deformation is another significant mechanism that causes CD. This research finding can offer theoretical guidance for developing effective measures to prevent and control CD in the exploitation of deep shale gas. Full article