Search Results (2,465)

To address the challenges of strong electromechanical coupling, nonlinear friction, and poor disturbance rejection in semi-direct-drive scraper conveyor systems under complex coal mining conditions, this paper aims to propose a high-performance drive control strategy that balances dynamic response speed with steady-state operational smoothness. First, an integrated electromechanical coupling dynamic model incorporating Permanent Magnet Synchronous Motor (PMSM) vector control and the time-varying meshing stiffness of a two-stage planetary gear train is established. Subsequently, a Sliding Mode Control (SMC) strategy optimized with a saturation boundary layer is designed and compared with traditional Proportional-Integral (PI) control under multiple operating conditions. Time-frequency domain analysis indicates that SMC significantly enhances the dynamic stiffness of the drive system. Under sudden load change conditions, the speed recovery time is shortened by approximately 76%, and the steady-state error is reduced by 37% compared to PI control. Microscopic characteristic evaluation based on FFT and Total Variation (TV) metrics reveals that SMC achieves active disturbance rejection through spectral broadening of the electromagnetic torque. Crucially, the steady-state cumulative control effort of SMC is equivalent to that of PI, implying no additional mechanical stress burden, while the equivalent dynamic transmission force fluctuation in the mechanical chain is reduced by about 3%. The study confirms that the proposed strategy successfully achieves a synergistic optimization of “macroscopic rapid response” and “microscopic smooth operation,” providing a theoretical basis for the high-precision control of heavy-duty underground transmission equipment. Full article

Accurate braking-distance prediction for heavy-duty multi-axle trucks remains challenging due to the large gross vehicle weight, tandem-axle interactions, and strong transient load transfer during emergency braking. Recent studies on tire–road friction estimation, commercial-vehicle braking control (EBS/AEBS), and weigh-in-motion (WIM) sensing have highlighted that unmeasured vertical-load dynamics and time-varying friction are key sources of prediction uncertainty. To address these limitations, this study proposes an integrated sensing–simulation–AI framework that combines real-time axle-load estimation, full-scale robotic braking tests, fused road-friction sensing, and physics-consistent machine-learning modeling. A micro-electro-mechanical systems (MEMS)-based load-angle sensor was installed on the leaf-spring panel linking tandem axles, enabling the continuous estimation of dynamic vertical loads via a polynomial calibration model. Full-scale on-road braking tests were conducted at 40–60 km/h under systematically varied payloads (0–15.5 t) using an actuator-based braking robot to eliminate driver variability. A forward-looking optical friction module was synchronized with dynamic axle-load estimates and deceleration signals, and additional scenarios generated in a commercial ASM environment expanded the operational domain across a broader range of friction, grade, and loading conditions. A gradient-boosting regression model trained on the hybrid dataset reproduced measured stopping distances with a mean absolute error (MAE) of 1.58 m and a mean absolute percentage error (MAPE) of 2.46%, with most predictions falling within ±5 m across all test conditions. The results indicate that incorporating real-time dynamic axle-load sensing together with fused friction estimation improves braking-distance prediction compared with static-load assumptions and purely kinematic formulations. The proposed load-aware framework provides a scalable basis for advanced driver-assistance functions, autonomous emergency braking for heavy trucks, and infrastructure-integrated freight safety management. All full-scale braking tests were carried out at approximately 60% of the nominal service-brake pressure, representing non-panic but moderately severe braking conditions, and the proposed model is designed to accurately predict the resulting stopping distance under this prescribed braking regime rather than to minimize the absolute stopping distance itself. Full article

This article examines how everyday architecture can advance spatial justice in post-active conflict cities through ethnographic and participatory design. Drawing on a decade of work by the StreetSpace studio in Belfast (2015–2025), the paper explores how architecture students and community participants co-design spatial strategies that enhance mixed-use mid-density living, inclusive mobility, and street-level accessibility. In a context where car dominance, segregation, and privatisation of public space continue to fragment urban life, the everyday street becomes a testbed for envisioning an equitable and community-centred city. The studio’s methodology is grounded in ethnographic engagement, informed by an embedded anthropologist, and includes stakeholder mapping, walking workshops, and collaborative drawing. These practices reveal lived experiences and shape community-driven briefs for housing, schools, public spaces, and multifunctional infrastructure. Anchored in spatial justice discourse and feminist theory (Jane Jacobs, David Harvey, Roberto Rocco, Phil Hubbard, Leslie Kern, and Caroline Criado Perez), the work positions the everyday as a site of architectural agency and proposes a contemporary vernacular that is socially embedded and climate-resilient. This work unfolds through complex and often contested processes that require sustained, iterative engagement with people and places. Meaningful collaboration is neither linear nor inherently caring; it frequently involves conflict, disagreement, and competing priorities that must be navigated over time. Through long-term relationships with government departments, local authorities, and NGOs, StreetSpace demonstrates how architectural pedagogy can nonetheless contribute to policy formation and more inclusive urban redevelopment by engaging in compromise, critical negotiation, and moments of care alongside friction and resistance. Through a series of collaborations and public events the project has contributed to the transformation of Botanic Avenue, informed studies of the East Belfast Greenways through contributions to Groundswell and participated in embedded public processes in collaboration with PPR, culminating in an exhibition at the MAC in Belfast in 2025. Full article

To enhance the assessment accuracy of tunnel face instability risks of active collapse during shield tunneling, this study establishes a novel unified analytical framework that couples the effects of unsaturated transient seepage induced by excavation drainage with soil stratification and heterogeneity. Grounded in unsaturated effective stress theory, the framework explicitly incorporates matric suction into the Mohr–Coulomb failure criterion via suction stress and apparent cohesion. By employing a horizontal two-layer nonhomogeneous soil model and solving the one-dimensional vertical Richards’ equation, an analytical solution for the face drainage boundary is derived to quantify the spatiotemporal evolution of suction stress and apparent cohesion. Subsequently, the critical support pressure is evaluated using the upper bound theorem of limit analysis, incorporating a horizontal layer-discretized rotational failure mechanism and the power balance equation. The validity of the proposed framework is confirmed through comparative analyses. Parametric studies reveal that in the upper hard and lower soft strata, the critical support pressure decreases and converges over time, indicating that unsaturated transient seepage exerts a significant influence in the short term that stabilizes over the long term. Additionally, sand–silt stratum exhibits lower overall stability and higher sensitivity to groundwater levels and temporal factors compared to silt–clay stratum. Conversely, silt–clay stratum displays a non-monotonic evolution with increasing cover-to-diameter ratios (C/D), reaching a minimum critical support pressure at approximately C/D = 1.1. Regarding heterogeneity, the internal friction angle of the lower layer exerts dominant control over the critical support pressure compared to seepage velocity, while the influence of other strength parameters remains secondary. These findings provide a theoretical basis for the time-dependent design of tunnel face support pressure under excavation drainage conditions. Full article

To address the increasing demands for faster response and higher control accuracy in the braking systems of electric and intelligent vehicles, a novel brake-by-wire actuation unit and its braking force control methods are proposed. The braking unit employs a permanent-magnet linear motor as the driving actuator and utilizes the lever-based force-amplification mechanism to directly generate the caliper force. Compared with the “rotary motor and motion conversion mechanism” configuration in other electromechanical braking systems, the proposed scheme significantly simplifies the force-transmission path, reduces friction and structural complexity, thereby enhancing the overall dynamic response and control accuracy. Due to the strong nonlinearity, time-varying parameters, and significant thermal effects of the linear motor, the braking force is prone to drift. As a result, achieving accurate force control becomes challenging. This paper proposes a model-free adaptive control method based on compact-form dynamic linearization. This method does not require an accurate mathematical model. It achieves dynamic linearization and direct control of complex nonlinear systems by online estimation of pseudo partial derivatives. Finally, the proposed control method is validated through comparative simulations and experiments against the fuzzy PID controller. The results show that the model-free adaptive control method exhibits significantly faster braking force response, smaller steady-state error, and stronger robustness against external disturbances. It enables faster dynamic response and higher braking force tracking accuracy. The study demonstrates that the proposed brake-by-wire scheme and its control method provide a potentially new approach for next-generation high-performance brake-by-wire systems. Full article

This paper investigates whether intelligent workplace technologies improve firm-level productivity and, if so, under what conditions, with particular attention to their implications for the economic and social sustainability of firms. This investigation occurs in a context where firms increasingly combine automation, artificial intelligence (AI), and work-from-home (WFH) practices to sustain performance under structural shocks such as the COVID-19 pandemic. Despite evidence that firms adopt these technologies jointly and reorganize work accordingly, existing research typically examines them in isolation. We develop a micro-founded, task-based production model in which firms allocate tasks between on-site and remote labor and automated capital in an optimal manner. This model allows both automation technologies and remote work collaboration tools to affect productivity and coordination costs that are central to long-term organizational sustainability. Using firm-level survey data from nearly 4000 large firms across industries and countries (2018–2021), we show that working from home (WFH) exhibits diminishing productivity returns when scaled in isolation, reflecting rising coordination frictions. In contrast, firms that combine WFH with automation and digital collaboration tools experience significantly higher labor productivity growth. These integrated technology systems support sustainable productivity by enabling capital deepening, resilient task reallocation, and more efficient use of labor resources over time. Overall, the findings suggest that productivity gains—and by extension sustainable firm performance—stem from integrated workplace technology systems rather than isolated investments, highlighting the importance of coherent technology strategies for organizing work in the post-pandemic economy. Full article

This paper presents a fault-tolerant control (FTC) strategy for a six-degree-of-freedom (DoF) anthropomorphic manipulator operating under actuator faults and complex friction dynamics. The proposed framework integrates a backstepping control methodology with LuGre friction modeling and a feedforward neural network (FFNN) for friction estimation. Actuator faults are considered in the form of multiplicative efficiency losses and additive disturbances. An adaptive control law is developed to estimate and compensate for both friction and actuator faults in real time. The stability of the closed-loop system is guaranteed through Lyapunov theory. The simulation results validate the effectiveness and robustness of the proposed approach in ensuring precise trajectory tracking despite faults and friction uncertainties. Full article

Fatigue crack propagation in friction stir welded joints significantly affects aircraft structural integrity. This study investigates the influence of welding speed, rotational speed, specimen thickness, loading frequency, and stress ratio on the fatigue crack growth rate. Four classical machine learning models with different structures—Deep Back-Propagation Network, Random Forest, Support Vector Regression, and K-Nearest Neighbors—were employed to predict fatigue crack growth behavior. The results show that all models achieve strong predictive performance. For FSWed joints, Deep BP and KNN exhibit comparable performance (R² > 0.98) on the training data, indicating similar learning capabilities with sufficient data coverage. Notably, KNN achieves the fastest training time (<0.3 s), while all models require less than 5 s of computation time. These results demonstrate that machine learning-based models provide an efficient and reliable alternative for rapid fatigue crack growth evaluation, supporting damage-tolerant design and structural integrity assessment in aircraft engineering. Full article

We investigate the impact of the vortex state of ultralight dark matter (ULDM) on the dynamical friction acting on moving globular clusters. Comparing this force with that for the solitonic ground state, it is shown that the internal structure and rotation of the ULDM core strongly affect the orbital decay of globular clusters. In particular, co-directional rotation in a vortex state can lead to significant suppression of dynamic friction at certain distances where globular clusters and ULDM velocities match. Applying these findings to the Fornax dwarf galaxy, it is found that the Fornax timing problem is naturally alleviated. Full article

Steel wire ropes are key load-bearing components in systems such as mine hoisting, bridge cableways, elevators, and cranes, and frictional wear is among the earliest occurring and most easily accumulated form of damage. Under actual working conditions, micro-relative sliding occurs both along the internal wires of the rope and at the contact surfaces with sheaves and ropes, leading to frictional wear, crack propagation, and fatigue failure. Frictional wear, a complex phenomenon influenced by structural layout, contact load, vibration conditions, lubrication, and environmental corrosion, critically determines the service life and load-bearing capacity of steel wire ropes. Recent experimental and numerical studies have significantly clarified the fundamental mechanisms and patterns of internal and external frictional wear in steel wire ropes, offering theoretical support for the distribution of wear, fatigue evolution, and fracture behavior. Meanwhile, non-destructive testing techniques have emerged as a vital tool for the real-time monitoring of wear conditions in steel wire ropes. This review summarizes the research progress on the generation, characteristics, effects, and protection of frictional wear in steel wire ropes, and proposes future directions for tribology and service safety research of steel wire ropes. Full article

During the discharge process of a salt cavern compressed air energy storage (CAES) system, high-speed air flow may entrain salt slag from the cavern floor, posing a threat to pipeline safety. Currently, there is a lack of in-depth research into the transient mechanisms of the entrainment process, particularly the influence of particle shape. This study employs a CFD-DEM coupling approach to conduct, for the first time, a high-fidelity simulation of slag entrainment dynamics during the initial discharge phase of a salt cavern CAES system, with a focus on the motion patterns of three particle shapes: spherical, conical, and square. Results show that: (1) during the initial discharge stage, the flow field rapidly forms vortex structures that migrate toward the wellhead, which is the core mechanism driving particle mobilization; (2) particle shape significantly affects entrainment efficiency through frictional characteristics—spherical particles are most easily entrained (maximum entrainment rate of 0.42 kg/h), while non-spherical particles tend to accumulate below the wellhead; and (3) the entrainment process exhibits strong transient characteristics: the entrainment rate peaks rapidly (approximately 0.82 kg/h) within a short time and then declines sharply, and it is sensitive to particle size, with the most entrainable particle size being around 5 mm. This study reveals the coupling mechanism between transient vortices and multi-shape particle entrainment during discharge, providing a theoretical basis for the design of filtration systems, operational risk prevention, and slag removal strategies in salt cavern CAES power plants. Full article

To address the high bending stresses and potential structural failure risks caused by differential settlement at expansion joints during bridge widening projects of straight bridges, this paper proposes an “Adaptive Rebound Displacement Compensation Device”. Existing research primarily focuses on analyzing settlement patterns and passive control standards, with limited attention to active dynamic regulation. Notably, the bending stress induced by new pier settlements can reach 3–5 times that of vehicle loads, posing serious safety concerns. Through theoretical derivation, this study clarifies the relationship between superstructure loss of strength and factors such as pier settlement, device stiffness, friction coefficient, and L-shaped baffle angle, and a comprehensive design framework is established accordingly. Combining numerical simulations, laboratory tests, and field measurements from engineering practices, multiple validation approaches are employed. The simulation results demonstrate that the proposed device can limit deck subsidence to 10–20% of pier settlement height, and experimental outcomes align closely with theoretical predictions. This device has been successfully implemented in a bridge widening project on a highway section in Jiangxi Province. It should be noted that all data presented in the paper are derived from finite element method (FEM) numerical simulations, and there are currently no on-site measurements of the device’s performance. FEM analysis indicates that the device demonstrates certain feasibility for practical engineering applications. Compared to scenarios without the installation of this device, bridge deck displacements can be reduced by approximately 16.5%. By enabling adaptive rebound through self-adjustment mechanisms for settlement compensation, this device significantly alleviates bending stresses at expansion joints, breaking through traditional passive control limitations. This study provides an innovative approach for actively controlling settlement differences in the widening of straight bridges, offering significant implications both at the theoretical and practical levels. Full article

Human-in-the-loop (HIL) immersive simulators integrate a human operator into the simulation loop, enabling real-time interaction with virtual environments. To expose users to controlled acceleration fields, they employ parallel kinematic machines (PKMs), including reduced-degree-of-freedom (DoF) configurations when compact and cost-effective systems are required. These reduced-DoF platforms frequently exhibit kinematic crosstalk, whereby motion along one axis causes unintended displacements or rotations along others. Among compact PKMs, the four-legged, three-DoF platform is widely used, particularly in driving simulators. However, to the best of the authors’ knowledge, its kinematics have never been systematically analyzed in the literature. It is an over-actuated system with specific constraint conditions characterized by actuators that are not fully grounded. As a result, kinematic crosstalk accelerations are not fully determined by kinematic relationships. They also depend on friction at the constraints; thus, they are also determined by the dynamic behavior of the machine, which is difficult to predict during operation. To address this issue, this paper introduces a simplified modeling approach to estimate kinematic crosstalk whose usability is evaluated experimentally both with mono-harmonic, combined DoF tests and in a real-world engineering application on an actual driving simulator. Results show that kinematic crosstalk on the platform is likely to generate acceleration levels up to 4 $\mathrm{m}/{\mathrm{s}}^2$, exceeding the vestibular perception threshold of 0.17 $\mathrm{m}/{\mathrm{s}}^2$ defined by Reid and Nahon. This result is relevant with respect to enabling a comprehensive assessment of the acceleration field to which the user is actually subjected, which determines the actual quality and immersiveness of the simulation. Full article

Three sizes of copper nanoparticles (1.7 nm, 2.8 nm, 3.4 nm) were synthesized using N902 as a surface-modifying ligand and diesel as the solvent. These nanoparticles were incorporated into biodiesel at volume fractions ranging from 0.005% to 0.20%, and their impacts on the lubrication performance, combustion characteristics, and thermal behavior of biodiesel were systematically investigated. The results indicated that the addition of copper nanoparticles significantly reduced the friction coefficient and wear scar diameter. Specifically, the 1.7 nm Cu nanoparticle sample achieved the most remarkable friction-reducing and anti-wear effects, with the friction coefficient and wear scar diameter decreasing by 16.07% and 20.1%, respectively. The combustion heat value of biodiesel showed a “first increase and then decrease” trend with the increase in nanoparticle addition, with the most significant improvement observed at an addition level of 0.01%. Among the three particle sizes, the 2.8 nm Cu nanoparticle sample effectively promoted the pyrolysis of biodiesel, while the 1.7 nm Cu nanoparticle sample exhibited optimal performance in reducing the oxidation induction time (OIT) and achieving complete combustion—characterized by lower CO emissions and minimal O₂ residue after combustion. Overall, the incorporation of copper nanoparticles realizes a synergistic enhancement, where lubricity improvement and combustion promotion occur concurrently, reflected by reduced OIT, lower CO emissions, and lower O₂ residue. Full article

Al-Cu-Fe quasicrystalline coatings were prepared using detonation spraying, followed by heat treatment at 450 °C for varying durations. Reciprocating sliding wear tests were conducted using an MTF-5000 tribological tester to investigate the tribological behavior of the coatings with varying phase compositions and contents. The results show that heat treatment significantly influences the phase composition and tribological behavior of the quasicrystalline coating. Regarding the phase composition, as the heat treatment duration increased, the phase constitution of the coating evolved from the initial three phases to five phases. The content of the quasicrystalline I phase remained essentially constant with increasing heat treatment time, but exhibited a notable decrease at 241 h mark. For the friction coefficient, shorter heat treatment times resulted in a relatively low range (0.35–0.37), while excessively long heat treatment times led to a significant increase in the friction coefficient (0.44–0.48). Regarding the wear rate, it decreased approximately linearly with increasing heat treatment time, reaching a minimum value after 136 h of treatment. At this point, it is the optimal heat treatment time. In essence, heat treatment modifies the wear mechanism and wear resistance of the coating by altering its phase composition and mechanical properties. Full article