Search Results (589)

Cavitation-induced degradation of metallic materials presents a significant challenge for engineers and users of equipment operating with high-velocity fluids. For any metallic material, the mechanical strength and ductility characteristics are controlled by the mobility of dislocations and their interaction with other defects in the crystal lattice (such as dissolved foreign atoms, grain boundaries, phase separation surfaces, etc.). The increase in mechanical properties, and consequently the resistance to cavitation erosion, is possible through the application of heat treatments and cold plastic deformation processes. These factors induce a series of hardening mechanisms that create structural barriers limiting the mobility of dislocations. Cavitation tests involve exposing a specimen to repeated short-duration erosion cycles, followed by mass loss measurements and surface morphology examinations using optical microscopy and scanning electron microscopy (SEM). The results obtained allow for a detailed study of the actual wear processes affecting the tested material and provide a solid foundation for understanding the degradation mechanism. The tested material is the Ni-based alloy INCONEL 625, subjected to stress-relief annealing heat treatment. Experiments were conducted using an ultrasonic vibratory device operating at a frequency of 20 kHz and an amplitude of 50 µm. Microstructural analyses showed that slip bands formed due to shock wave impacts serve as preferential sites for fatigue failure of the material. Material removal occurs along these slip bands, and microjets result in pits with sizes of several micrometers. Full article

Background: Current methods of postural control assessments and interventions to improve postural stability and thereby prevent falls often fail to incorporate the hazardous perturbation situations that frequently accompany falls. Virtual environments can safely incorporate these hazards. The purpose of the study was to identify if virtual slip and trip perturbations can be used as an exposure paradigm in place of real slip and trip perturbations to improve postural control. Methods: Fifteen healthy young adults were included in this study. Two paradigms, real gait exposure (real) and virtual environment gait exposure (virtual), consisting of real and virtual slip and trip trials, were performed by each participant in a counterbalanced order to avoid order effects. At baseline and following real and virtual paradigms, the modified clinical test for sensory integration and balance (mCTSIB), limits of stability (LOS), and single-leg stance (SLS) using BTracks balance plate were administered. Separate one-way (baseline vs. Real vs. Virtual) repeated measures analysis of variance were conducted on response variables. Results: In the posterior left quadrant of the LOS, significant differences were found after the real paradigm compared to baseline (p = 0.04). For the anterior left quadrant and total LOS, significant differences post real paradigm (p = 0.002 and p < 0.001) and virtual paradigm (p = 0.007 and p < 0.001) compared to baseline were observed. For the SLS, the left-leg significant differences were observed post real paradigm (p = 0.019) and virtual paradigm (p = 0.009) compared to BL in path length, while significant main effects were found for mean sway velocity for the left leg only (p = 0.004). For the right leg, significant differences were only observed after the virtual paradigm (p = 0.01) compared to BL. Conclusions: Both virtual and real paradigms were identified to improve postural control. The virtual paradigm led to increased postural control in the right-leg SLS condition, while the real paradigm did not, without any adverse effects. Findings suggest virtual reality perturbation exposure acutely improves postural control ability compared to baseline among healthy young adults. 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

Wind turbine performance in cold regions is affected by icing which can lead to power reduction due to the aerodynamic degradation of the turbine blade. The development of airfoil shapes applied as blade sections contributes to improving the aerodynamic performance under a wide range of weather conditions. The present study considers inverse design coupled with numerical modelling to simulate the effects of varying airfoil thickness and maximum camber. The inverse design process was implemented in MATLAB R2023a, whereas the numerical models were constructed using ANSYS Fluent and FENSAP ICE 2023 R1. The inverse design process applied the modified Garabedian–McFadden (MGM) iterative technique. Shear velocities were calculated from the flow over an airfoil with slip conditions, and then this velocity distribution was modified according to the prevailing icing conditions to obtain the target velocities. A parameter was proposed to consider the airfoil thickness as well when calculating the target velocities. The airfoil generated was then exposed to various atmospheric conditions to check the improvement in the aerodynamic performance. The ice mass and lift-to-drag ratio were determined considering cloud characteristics under varying liquid water content (LWC) from mild to severe (0.1 g/m³ to 1 g/m³), median volume diameter (MVD) of 50 µm, and two ambient temperatures (−4 °C and −20 °C) that characterize freezing drizzle and in-cloud icing conditions. The ice mass on the blade section was not significantly impacted by modifying the shape after applying the process developed (i.e., <5%). However, the lift-to-drag ratio that describes the aerodynamic performance may even be doubled in the icing scenarios considered. Full article

The motion control of a tracked mobile robot remains an important capability for autonomous navigation. Kinematic path-tracking algorithms are commonly used in mobile robotics due to their ease of implementation and real-time computational cost advantage. This paper integrates an extended Kalman filter (EKF) into a common kinematic controller for path-tracking performance improvement. The extended Kalman filter estimates the instantaneous center of rotation (ICR) of tracks using the sensor readings of GPS and IMU. These ICR estimations are then given as input to the motion control algorithm to generate the track velocity demands. The platform to be controlled is a heavyweight off-road tracked vehicle, which necessitates the investigation of slip values. A high-fidelity simulation model, which is verified with field tests, is used as the plant in the path-tracking simulations. The performance of the filter and the algorithm is also demonstrated in field tests on a stabilized road. The field results show that the proposed estimation increases the path-tracking accuracy significantly (about 44%) compared to the classical pure pursuit. Full article

The electroosmotic flow (EOF) of non-Newtonian fluids plays a significant role in microfluidic systems. The EOF of Powell–Eyring fluid within a parallel-plate microchannel, under the influence of both electric field and pressure gradient, is investigated. Navier’s boundary condition is adopted. The velocity distribution’s approximate solution is derived via the homotopy perturbation technique (HPM). Optimized initial guesses enable accurate second-order approximations, dramatically lowering computational complexity. The numerical solution is acquired via the modified spectral local linearization method (SLLM), exhibiting both high accuracy and computational efficiency. Visualizations reveal how the pressure gradient/electric field, the electric double layer (EDL) width, and slip length affect velocity. The ratio of pressure gradient to electric field exhibits a nonlinear modulating effect on the velocity. The EDL is a nanoscale charge layer at solid–liquid interfaces. A thinner EDL thickness diminishes the slip flow phenomenon. The shear-thinning characteristics of the Powell–Eyring fluid are particularly pronounced in the central region under high pressure gradients and in the boundary layer region when wall slip is present. These findings establish a theoretical base for the development of microfluidic devices and the improvement of pharmaceutical carrier strategies. Full article

The 6 February 2023 M_W 7.8 and M_W 7.6 earthquakes in southeastern Türkiye ruptured more than 400 km of the East Anatolian Fault Zone (EAFZ), producing one of the most destructive seismic sequences in recent history. Here, we integrate InSAR data, a new GNSS velocity field, and small-magnitude earthquakes to investigate the coseismic deformation, rupture geometry, and interseismic strain accumulation along the EAFZ. Using elastic dislocation modeling with a variable-strike, multi-segment fault geometry, we constrain the slip distribution of the mainshocks, showing improved fits to the surface displacement compared to the planar fault model. The M_W 7.8 event ruptured a number of fault segments over ~300 km, while the M_W 7.6 event activated a more localized fault system with a peak slip exceeding 15 m. We also model two moderate events (M_W 5.6 in 2020 and M_W 5.3 in 2022) along the southwestern part of the Pütürge segment—an area not ruptured during the 2020 or 2023 sequences. GNSS-derived strain-rate and locking depth estimates reveal strong interseismic coupling and significant strain accumulation in this region, suggesting the potential for a future large earthquake (M_W 6.6–7.1). Similarly, the Hatay region, at the southwestern termination of the 2023 rupture, shows a persistent strain accumulation and complex fault interactions involving the Dead Sea Fault and the Cyprus Arc. Our results demonstrate the importance of combining remote sensing and geodetic data to constrain fault kinematics, evaluate rupture segmentation, and assess the seismic hazard in tectonically active regions. Targeted monitoring at rupture terminations—such as the Pütürge and Hatay sectors—may be crucial for anticipating future large-magnitude earthquakes. Full article

This paper proposes a novel navigation approach for Unmanned Tracked Vehicles (UTVs) using prior-based ensemble deep reinforcement learning, which fuses the policy of the ensemble Deep Reinforcement Learning (DRL) and Dynamic Window Approach (DWA) to enhance both exploration efficiency and deployment safety in unstructured off-road environments. First, by integrating kinematic analysis, we introduce a novel state and an action space that account for rugged terrain features and track–ground interactions. Local elevation information and vehicle pose changes over consecutive time steps are used as inputs to the DRL model, enabling the UTVs to implicitly learn policies for safe navigation in complex terrains while minimizing the impact of slipping disturbances. Then, we introduce an ensemble Soft Actor–Critic (SAC) learning framework, which introduces the DWA as a behavioral prior, referred to as the SAC-based Hybrid Policy (SAC-HP). Ensemble SAC uses multiple policy networks to effectively reduce the variance of DRL outputs. We combine the DRL actions with the DWA method by reconstructing the hybrid Gaussian distribution of both. Experimental results indicate that the proposed SAC-HP converges faster than traditional SAC models, which enables efficient large-scale navigation tasks. Additionally, a penalty term in the reward function about energy optimization is proposed to reduce velocity oscillations, ensuring fast convergence and smooth robot movement. Scenarios with obstacles and rugged terrain have been considered to prove the SAC-HP’s efficiency, robustness, and smoothness when compared with the state of the art. 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

Shallow landslides are one of the main geological hazards that occur during heavy rainfall in Yuexi County every year, posing potential risks to the personal and property safety of local residents. A rainfall-induced shallow landslide named Baishizu No. 15 landslide in Yuexi Country was taken as a case study. Based on the field geological investigation, combined with physical and mechanical experiments in laboratory as well as numerical simulation, the failure mechanism induced by rainfall infiltration was studied, and the movement process after landslide failure was inverted. The results show that the pore-water pressure within 2 m of the landslide body increases significantly and the factory of safety (F_s) has a good corresponding relationship with rainfall, which decreased to 0.978 after the heavy rainstorm on July 5 and July 6 in 2020. The maximum shear strain and displacement are concentrated at the foot and front edge of the landslide, which indicates a “traction type” failure mode of the Baishizu No. 15 landslide. In addition, the maximum displacement during landslide instability is about 0.5 m. The residual strength of soils collected from the soil–rock interface shows significant rate-strengthening, which ensures that the Baishizu No. 15 landslide will not exhibit high-speed and long runout movement. The rate-dependent friction coefficient of sliding surface was considered to simulate the movement process of the Baishizu No. 15 landslide by using PFC^2D. The simulation results show that the movement velocity exhibited obvious oscillatory characteristics. After the movement stopped, the landslide formed a slip cliff at the rear edge and deposited as far as the platform at the front of the slope foot but did not block the road ahead. The final deposition state is basically consistent with the on-site investigation. The research results of this paper can provide valuable references for the disaster prevention, mitigation, and risk assessment of shallow landslides on residual soil slopes in the Dabie mountainous region. Full article

Introduction: Robotic-assisted (RA) spine surgery enhances pedicle screw placement accuracy through real-time navigation and trajectory guidance. However, the absence of traditional direct haptic feedback by freehand instrumentation remains a concern for some, particularly in minimally invasive (MIS) procedures where direct visual confirmation is limited. During RA spine surgery, navigation systems display three-dimensional data, but factors such as registration errors, intraoperative motion, and anatomical variability may compromise accuracy. This technical note describes a visuohaptic intraoperative phenomenon observed during RA spine surgery, its underlying mechanical principles, and its utility. During pedicle screw insertion with a slow-speed automated drill in RA spine procedures, a subtle and rhythmic variation in resistance has been observed both visually on the navigation interface and haptically through the handheld drill. This intraoperative pattern is referred to in this report as a cyclical insertional torque (CIT) pattern and has been noted across multiple cases. The CIT pattern is hypothesized to result from localized stick–slip dynamics, where alternating phases of resistance and release at the bone–screw interface generate periodic torque fluctuations. The pattern is most pronounced at low insertion speeds and diminishes with increasing drill velocity. CIT is a newly described intraoperative observation that may provide visuohaptic feedback during pedicle screw insertion in RA spine surgery. Through slow-speed automated drilling, CIT offers a cue for bone engagement, which could support intraoperative awareness in scenarios where tactile feedback is reduced or visual confirmation is indirect. While CIT may enhance surgeon confidence during screw advancement, its clinical relevance, reproducibility, and impact on placement accuracy have yet to be validated. Full article

Curved-spoke wheels have been proposed as an effective way to overcome stair-like obstacles with smooth, rotation-only motion. However, when the wheel’s contact point shifts, discontinuous changes in its radius of curvature cause abrupt drops in the robot’s linear speed, often leading to reduced payload stability and slip. As a result, maintaining reliable stair climbing becomes more difficult. At higher speeds, these sudden changes become stronger, further reducing dynamic stability. To address these issues, we propose a passive Compliant Spiral Torsional Suspension (C-STS) attached to the wheel’s drive axis. Through camera-based marker tracking, we analyzed wheel trajectories under various stiffness and speed conditions. In particular, we define the deceleration caused by the velocity drop during contact transitions as our dynamic stability metric and demonstrate that the C-STS significantly reduces this deceleration across low-, medium-, and high-speed climbing, based on comparisons both with and without the suspension. It also raises the average velocity, likely due to a brief release of stored elastic energy, and lowers the net torque requirement. Our findings show that the proposed C-STS greatly improves dynamic stability and suggest its potential for enhancing stair-climbing performance in curved-wheel-based robotic systems. Furthermore, our approach may extend to other reconfigurable wheels facing similar instabilities. 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

In the current paper, an analysis of magnetohydrodynamic Williamson nanofluid boundary layer flow is presented, with multiple slips in a porous medium, using a newly designed human-brain-inspired Ricker wavelet neural network solver. The solver employs a hybrid approach that combines genetic algorithms, serving as a global search method, with sequential quadratic programming, which functions as a local optimization technique. The heat and mass transportation effects are examined through a stretchable surface with radiation, thermal, and velocity slip effects. The primary flow equations, originally expressed as partial differential equations (PDEs), are changed into a dimensionless nonlinear system of ordinary differential equations (ODEs) via similarity transformations. These ODEs are then numerically solved with the proposed computational approach. The current study has significant applications in a variety of practical engineering and industrial scenarios, including thermal energy systems, biomedical cooling devices, and enhanced oil recovery techniques, where the control and optimization of heat and mass transport in complex fluid environments are essential. The numerical outcomes gathered through the designed scheme are compared with reference results acquired through Adam’s numerical method in terms of graphs and tables of absolute errors. The rapid convergence, effectiveness, and stability of the suggested solver are analyzed using various statistical and performance operators. Full article

During the drilling process, stick–slip vibrations are one of the critical causes of bottom-hole assembly (BHA) failure and reduced drilling efficiency. To address this, this study first proposes a drill-string model based on a three-dimensional nonlinear finite beam element, combined with Hamilton’s principle of virtual work, to comprehensively describe the nonlinear behavior of the drill-string system. Next, to improve computational efficiency, the model is reduced using the modal truncation method, which retains the key modes of drill-string vibrations. Based on this, a model predictive control (MPC) method is designed to eliminate stick–slip vibrations. Furthermore, the robustness of the MPC method under parameter uncertainties is also investigated. In particular, the impact of the weight on bit (WOB) on the drill bit’s torsional velocity is further considered, and an MPC angular velocity comprehensive control scheme based on the dynamic WOB (DWOB-MPC) is proposed. This scheme stabilizes the velocity of the drill bit by dynamically adjusting the WOB, thereby eliminating stick–slip vibrations. Simulation results demonstrate that both the proposed MPC and DWOB-MPC methods effectively suppress stick–slip vibrations. Notably, the DWOB-MPC method further reduces the settling time and overshoot, exhibiting superior dynamic performance. Full article