Search Results (1,591)

Heat-treatable aluminum alloys are widely used in aerospace and automotive industries for high-performance structural applications. However, their processing through conventional fusion-based additive manufacturing is limited by solidification-related defects, such as hot cracking, porosity, and elemental segregation. To overcome these limitations, friction-based additive manufacturing (FBAM) has emerged as a promising solid-state alternative. FBAM primarily includes friction stir additive manufacturing (FSAM), additive friction stir deposition (AFSD), friction screw extrusion additive manufacturing (FSEAM), and friction rolling additive manufacturing (FRAM), which differ in feedstock form and process configuration. In these processes, feed material is consolidated through frictional heat generated below the melting temperature, enabling the formation of refined equiaxed microstructures while minimizing solidification defects. Despite these advantages, significant challenges persist in processing heat-treatable aluminum alloys, particularly the 2xxx, 6xxx, and 7xxx series. These include non-uniform microstructure and mechanical properties along the build direction; precipitation instability; process-induced defects, such as tunnel formation; and mechanical properties that are often inferior to those of the corresponding base materials (BMs). Reported FBAM builds generally exhibit equiaxed ultrafine grains below 1 μm; however, the strength and microhardness of heat-treated alloy builds commonly remain around 70–75% of the corresponding BM. Following post-heat treatment, microhardness can be nearly fully recovered, whereas UTS typically reaches about 80–85% of BMs, often with an associated ductility reduction of nearly 50%. This review critically analyzes research reported over the past decade on FBAM processing of heat-treatable aluminum alloys, covering FSAM, AFSD, FSEAM, and FRAM. The key challenges related to microstructural evolution and mechanical performance are systematically discussed for each alloy series. Furthermore, mitigation strategies proposed in the literature, including process parameter optimization, in-process cooling, post-heat treatment, and nanoparticle reinforcement (e.g., SiC, TiC, Ni and ZrO₂), are evaluated. Finally, existing research gaps are identified, and future directions are proposed to support the development of robust, scalable, and high-performance FBAM processes for heat-treatable aluminum alloys. Full article

Friction at the cold rolling interface is affected jointly by the surface roughness, lubrication state, local pressure, and relative sliding. A constant friction coefficient is therefore insufficient to describe its non-uniform distribution along the contact arc. Accordingly, this study proposes a macro–micro two-scale mixed-lubrication and dynamic friction model based on the measured roll roughness. First, the measured roll roughness profile was represented within a finite effective scale interval by a scaled and truncated Weierstrass–Mandelbrot (W–M) function. The parameters D and G were obtained as finite-scale W–M roughness parameters and were introduced into a mixed-lubrication load-sharing model to calculate the local mixed-lubrication friction coefficient. The pressure distribution along the contact arc was calculated using the Karman equation, and the local macroscopic pressure was mapped to a representative microscopic contact load. Finally, the mixed-lubrication friction coefficient was used to calibrate the dynamic friction factor separately in the forward-slip and backward-slip zones, and the friction stress distribution along the contact arc was calculated. For the selected effective scale interval and preprocessing procedure, the fitted W–M roughness parameters were D = 1.528 and G = 9.15 × 10⁻⁸ m. The W–M parameter D had a more significant influence on the mixed-lubrication friction coefficient and load-sharing behavior than the scale parameter G. Increasing the rolling speed strengthened the oil-film load-carrying effect and reduced the equivalent interfacial friction coefficient. The friction stress was positive in the backward-slip zone and negative in the forward-slip zone, with a direction reversal near the neutral point. Field forward-slip inversion showed that both the simulated and measured equivalent friction coefficients decreased with increasing rolling speed, with a difference of approximately 0.009~0.017. The proposed model can capture the main trend of cold rolling interfacial friction with variations in the rolling speed and contact state. Full article

With the expansion of ammonia energy applications, long-distance liquid ammonia pipelines are expected to support large-scale cross-regional ammonia transport. In the liquid ammonia pipeline commissioning process, gaseous ammonia purging involves ammonia–nitrogen mixing and possible liquefaction, while liquid ammonia injection may induce flashing and severe local cooling, all of which can affect commissioning safety. To characterize these thermodynamic phenomena, a transient gas–liquid two-phase flow model was established and validated using OLGA 2022.1.0 software for simulating the long-distance liquid ammonia pipeline commissioning. The model adopts the cross-sectionally averaged one-dimensional approach. A volume-corrected Soave–Redlich–Kwong (SRK) equation of state for ammonia was adapted, validated, and used to generate OLGA-compatible thermodynamic property tables. The results show that, during gaseous ammonia purging, a higher flowrate shortens the displacement time by accelerating nitrogen removal, and this effect is more pronounced at higher ambient temperatures due to enhanced molecular diffusion. Along the pipeline, pressure gradually decreases from frictional resistance, with a steeper drop near the outlet caused by gas acceleration, and temperature gradually approaches ambient through heat exchange with the pipe wall and surrounding soil. A high gaseous ammonia flowrate can cause partial liquefaction, regasification, and temperature fluctuations. During liquid ammonia injection, local condensation and slight liquid accumulation occur before the liquid front arrives, and the low-temperature region moves with the liquid front. The liquid ammonia mass flowrate has the strongest influence on the injection process, as it reduces the completion time but increases the outlet temperature, outlet pressure, and the low-temperature risk downstream of the valve. Therefore, it should be controlled within an appropriate range to balance efficiency and low-temperature safety risks. This work provides a rapid and efficient prediction model for key thermo-hydraulic parameters during liquid ammonia pipeline commissioning, and the overall analyses offer insights for on-site process design and safety control. Full article

Al 6061 is widely used in the automotive, aerospace, railway and shipbuilding industries due to its excellent mechanical and metallurgical properties. Friction stir welding is a solid-state method preferred in the welding of Al6061 alloy. In this study, Al 6061 plates with a thickness of 3 mm were joined at tool rotational speeds of 900 and 1120 rpm, feed rates of 50 and 80 mm.min⁻¹, and tilting angles of 0° and 2° by friction stir welding using a tapered pin tool in the Universal Milling Machine. To examine the mechanical properties of welded specimens, tensile tests and microhardness tests were applied to them. The microstructural evolution of the welded zones was studied using an optical microscope and scanning electron microscope, and energy-dispersive X-ray spectroscopy analysis. The tensile test results demonstrate that the specimen welded at 900 rpm tool rotational speed, 2° tilting angle, and 80 mm.min⁻¹ feed rate exhibited the highest welding strength of 243.77 MPa and welding performance of 82.93%, while specimen welded at 1120 rpm tool rotational speed, without tilting angle, and 50 mm.min⁻¹ feed rate exhibited the lowest welding strength of 105.76 MPa and welding performance of 36%. Full article

Optimizing the structural stability of foundations is challenging in modern geotechnical engineering. This study investigated the mechanism of geocell-reinforced foundations through discrete element modeling based on transparent soil model tests. A three-dimensional particle flow code (PFC^3D) model was developed to investigate the micromechanical soil–geocell interactions in both unreinforced and geocell-reinforced foundations under strip loading. Particle displacement, contact force distribution, and structural deformation within the foundation system were analyzed to quantify the performance of geocell reinforcement. The results show that geocell inclusion enhances structural performance by 2.1 times compared to an unreinforced foundation, increasing the bearing capacity from 60.6 to 126.8 kPa at a defined bearing capacity criterion. The geocell walls act as rigid physical boundaries that microscopically intercept the lateral migration and horizontal extrusion of soil particles. The kinematic trajectories of soil particles beneath the loading plate are forced into a downward realignment, decreasing the displacement vector rotation angle from 42° in the unreinforced soil to 27° in the reinforced soil and effectively mitigating the heave of adjacent surfaces. Furthermore, the quasi-rigid three-dimensional network completely interrupts the continuous steep contact force chains inherent in unreinforced foundations. Concentrated vertical stresses are converted into horizontal components through interfacial friction and mechanical interlocking, resulting in the lateral redistribution of the applied load by a distance of approximately 0.06 m. The geocell–soil composite considered as a flexible raft foundation extends load dispersion and reduces average subsoil pressure. A coupled tension and compression stress state in the horizontal plane is developed within the geocell structure. Forces are channeled along rigid paths by elevated bending moments and stress concentrations at the cell junctions. These findings provide micromechanical insights into the performance of geocell-reinforced-foundation systems. Full article

Heated crude oil pipelines transporting high-pour-point, high-viscosity, and high-wax-content crude oil are increasingly operated under small-batch and multi-condition scenarios. Under such conditions, fixed-parameter models and experience-based operating strategies may fail to accurately describe the evolving thermo-hydraulic state, resulting in inaccurate temperature-safety assessment and conservative energy use. To address this problem, this study develops a hybrid modelling and simulation framework for the energy-efficient operation of heated crude oil pipelines. The framework integrates operating-state perception, online parameter inversion, transient thermo-hydraulic simulation, data assimilation, and rolling optimization. First, an online parameter inversion method based on inverse problem solving is established to dynamically identify the overall heat-transfer coefficient and friction correction factor from Supervisory Control and Data Acquisition (SCADA) measurements. Second, a transient thermo-hydraulic simulation and data-assimilation model is constructed to predict pressure, temperature, and safety margins under changing boundary conditions. Third, a constraint-aware rolling optimization strategy is introduced to coordinate heating and pumping operations while satisfying temperature and pressure constraints. The proposed framework is validated using a practical crude oil pipeline. Under a representative low-flow-rate condition, online parameter inversion corrects the overestimation of the thermo-hydraulic state by the fixed-parameter model: the total temperature drop along the pipeline is revised from 33.12 °C to 35.65 °C, and the minimum station-inlet oil temperature is revised from 24.77 °C to 21.61 °C. After optimization is introduced, the total operating energy consumption decreases from 11,715.65 kW to 11,287.43 kW, corresponding to a reduction of 3.66%, while all temperature and pressure constraints remain satisfied. Under time-varying boundary conditions, the rolling optimization strategy further adjusts heating-furnace operation according to variations in inlet flow rate, inlet oil temperature, and ambient temperature, thereby reducing cumulative heating energy consumption while maintaining safe operation. The results demonstrate that the proposed framework provides an implementable modelling and simulation approach for online state assessment, transient prediction, and energy-efficient operation of heated crude oil pipelines under variable operating conditions. Full article

This review explicitly focuses on agricultural attachments and executing components that interact directly with soil and crops, rather than the tractor vehicle itself. Operating within complex and variable farmland media environments, the key components of agricultural machinery have long been constrained by bottlenecks such as high-energy draught resistance, severe solid–liquid interfacial adhesion, and intense abrasive wear. Bionic functional surfaces, based on the coupling of micro-geometric morphology and surface-interface physical chemistry, provide a scientific approach to overcoming traditional tribological limitations by reconstructing the contact mechanics and fluid dynamics boundaries at the interface. This paper presents a comprehensive review of the latest research progress regarding bionic functional surfaces in the fields of friction reduction, wear resistance, and anti-adhesion in agricultural machinery. The article systematically categorises typical biological prototypes, such as soil-burrowing animals, aquatic organisms, and plant leaves, alongside their multidimensional feature extraction methods. It provides an in-depth analysis of core interaction mechanisms, ranging from static air cushion effects and dynamic wetting evolution to active electro-osmotic soil detachment, interfacial stress redistribution, and microscopic wear debris capture. Furthermore, it evaluates the efficacy of cross-scale coupled numerical simulation technologies in resolving interfacial interactions. At the engineering application level, this review extensively discusses the field performance of bionic structures in typical operational scenarios, including draught reduction in tillage and land preparation, blockage prevention in seed-metering channels, and low-damage harvesting in agricultural machinery. Finally, countermeasures are proposed to address the fatigue degradation of bionic surfaces under alternating field loads and the barriers to the large-scale fabrication of large-sized components. The paper further highlights the development trend towards the deep integration of bionic tribology with digital twins and intelligent wear-state perception technologies, aiming to provide systematic underlying theoretical and technical references for the research and development of the next generation of intelligent agricultural equipment characterised by low energy consumption and a prolonged service life. Full article

Empty-vehicle repositioning is a persistent challenge in long-haul road freight because carriers must reduce empty mileage without sacrificing service reliability under lead times, appointment windows, and uncertain load realization. This paper formulates empty-vehicle repositioning on freight corridors as a stochastic control problem with explicit space–time feasibility and a stated within-epoch event order. Lead times couple current dispatch decisions to future capacity, pickup windows impose reachability constraints, and stochastic match feasibility captures information and market frictions. We develop dynamic lower bounds from time-expanded relaxations, showing that dual prices of inventory-balance constraints can be interpreted as space–time scarcity values. We further introduce an order-dependent nested friction decomposition that separates excess empty movement into spatial imbalance, temporal mismatch induced by lead times and time windows, and information frictions. Guided by this structure, we propose price-guided rolling-horizon and generalized-cost policies and evaluate them on synthetic corridor experiments organized around the three friction families. The results reveal service–empty-mileage trade-offs, a pronounced knee in the Pareto frontier, lower service loss under widened tight pickup windows, and strong sensitivity to match feasibility. The PG-RH policy reduces empty-distance exposure and total cost relative to static balancing in the main scenarios while maintaining comparable, but not uniformly dominant, service performance. The framework provides a diagnostic basis for identifying the sources of deadhead and for designing operational interventions that reduce empty mileage without undermining reliability. Full article

Nonlinear Model Predictive Control (NMPC) has garnered significant attention in autonomous systems due to its ability to predict future states and manage complex vehicle dynamics. However, the adaptability of existing NMPC methods is constrained by having to manually set the weight coefficients in the NMPC cost function. This study aims to explore a novel approach that integrates NMPC with Reinforcement Learning (RL), specifically employing Proximal Policy Optimization (PPO), to dynamically adjust NMPC weight matrices. The investigation begins by establishing a physics-based model for a two wheeled differential drive vehicle. A PPO model is then trained and deployed in real time to adapt to the NMPC weight matrices, achieving a 71% reduction in tracking error compared with the NMPC baseline. Importantly, the performance gain arises from PPO’s ability to reshape the NMPC cost function in real time, amplifying both orientation and lateral penalties in curves while relaxing them on straights, thereby enabling adaptive trade-offs between accuracy and control effort that static-weight NMPC cannot achieve. To enhance safety, the controller is integrated with a Control Barrier Function (CBF) layer for real-time obstacle avoidance, while PPO’s real-time weight adaptation contributes to improved tracking performance relative to NMPC+CBF. Finally, robustness evaluations under friction uncertainty, sensor noise, and path disturbances demonstrate that the PPO+NMPC+CBF method maintains reliable tracking accuracy and safety margins. Full article

Additive friction stir deposition (AFSD) is a solid-state additive manufacturing process that enables the fabrication of fully dense metallic components without common fusion-related defects. Inconel 718, widely used in aerospace and energy sectors, requires high structural reliability; therefore, evaluating its response to AFSD is essential for advanced applications. This study investigates the effects of AFSD on IN718 by comparing the mechanical properties and microstructure of the as-deposited material with the feedstock condition. Tensile testing showed that the ultimate tensile strength (UTS) increased by 5% along the traverse direction, whereas elongation was reduced compared to the feedstock. In contrast, build-direction tensile specimens exhibited lower UTS and substantially reduced elongation, revealing mechanical anisotropy. Microhardness increased by 20%, consistent with substantial grain refinement from 11 µm to 3 µm due to dynamic recrystallization during deposition. X-ray diffraction (XRD) revealed no clearly detectable secondary phase formation after AFSD within the resolution limits of conventional XRD, suggesting that the increased hardness and traverse-direction strength can be partly explained by grain refinement. Elemental mapping detected oxygen-enriched Al/Ti regions at interlayer boundaries, which may contribute to the reduced build-direction ductility. Overall, AFSD refined the microstructure, enhanced hardness, and improved traverse-direction strength, while build-direction tensile testing revealed anisotropic mechanical behavior. Full article

To elucidate the mechanisms responsible for high friction in micro-pillared soft tribo-contacts under wet conditions, this study investigates the liquid migration behavior across elasticity interfaces featuring bionic surface textures and examines the influence of this migration on interfacial friction properties. Micro-pillar bionic surface textures were fabricated on polydimethylsiloxane (PDMS) substrates. In situ observation of liquid migration and corresponding friction tests were systematically conducted using custom-built experimental setups on soft interfaces textured with micro-pillars of varying area densities. The results demonstrate that both geometrical shape and area density of surface textures play a critical role in regulating liquid migration behavior. Surface textures with circular and hexagonal geometries exhibit optimal migration rates, attributed to their smooth structural profiles, which reduce flow resistance within the microchannels. Liquid migration efficiency is effectively improved with increasing area density of the bionic surface texture owing to strengthened capillary forces. Correspondingly, bionic surface textures exhibiting superior liquid migration characteristics show the smallest relative reduction in friction force during transitions from dry to wet frictional states. This behavior is primarily attributed to the surface’s exceptionally rapid drainage capability, which effectively mitigates the adverse effects of interfacial liquid films on friction. Specifically, rapid liquid removal increases the effective solid–solid contact area and enhances mechanical interlocking at the interface. Consequently, these surfaces maintain outstanding frictional performance even under humid or wet conditions. These findings provide important theoretical support for the rational design of surface microstructures and the optimized regulation of friction and liquid film in wet contact conditions. Full article

Aiming to study the plastic behavior of expansion tubes, this paper presents experimental studies on Q420 and S2205 steel tubes and investigates the influence of key parameters on the responses of the expansion tube. A finite element model is established and validated by comparing the numerical results with experimental results. Based on both experimental and numerical approaches, the effects of the coefficient of friction, geometric parameters, tube material and impact velocity are revealed. The results show that the steady-state force increases linearly with increasing friction coefficient and tube thickness. As expansion value increases, the growth rate of steady-state force decreases, and local buckling and splitting become more likely. Numerical simulations examine the response and failure modes under low- to high-speed impacts. The steady-state force is insensitive to impact velocity and expansion angle, but the failure mode under high-speed impact is more severe than that under low-speed impact. Four failure modes and typical deformation stages of the failure process were obtained based on test observations and numerical simulations. The empirical formula for predicting the steady-state force of Q420 steel tubes under quasistatic and low-speed impact expansion is proposed based on similarity criteria and dimensional analysis. Full article

Rotor imbalance and abnormal vibration are classical operating conditions in rotating machinery and can often be identified by conventional vibration analysis. However, the development of low-power, self-powered, and distributed sensing nodes remains important for long-term condition monitoring, particularly in scenarios where external power supply, wiring, and maintenance are constrained. Existing vibration sensors, including piezoelectric and capacitive types, are constrained by power consumption and degraded performance under low-frequency and weak excitation. To address this issue, a magnetically repulsive cushion triboelectric nanogenerator (MRCT) is proposed to enable self-powered vibration sensing. The magnetic-repulsion cushion allows the upper friction layer to undergo stable contact–separation motion under a non-contact restoring force, while the microstructured strip electrode array (MSEA) enhances the triboelectric output and signal stability. A hybrid convolutional neural network–gated recurrent unit (CNN-GRU) deep-learning model is employed to extract time-domain and frequency-domain features from the collected signals, enabling real-time identification of rotor vibration amplitude, frequency, and imbalance weight. Experimental results show that the MRCT provides stable output, a high signal-to-noise ratio, and an identification accuracy above 98% for predefined rotor imbalance-weight states under laboratory conditions. In addition, a shaft-misalignment-related abnormal vibration condition was examined on the motor platform. The corresponding time-domain and frequency-domain analyses show that the MRCT voltage signal exhibits distinguishable signal variations under normal and misalignment-related conditions, including spectral changes around the 2× rotational frequency. A laboratory-scale AIoT-oriented demonstration further verifies the feasibility of integrating MRCT signal acquisition, CNN-GRU inference, wireless transmission, and GUI-based visualization. It should be noted that the present work mainly focuses on imbalance-state recognition, while the misalignment-related experiment provides an additional sensor-response verification. Broader validation involving mechanical looseness, bearing defects, variable-speed operation, cross-machine testing, and long-term industrial conditions remains necessary. Full article

Cementitious materials in the fresh state are commonly regarded as viscoplastic. That is, below a given yield stress, they exhibit solid-like behavior, whereas above this threshold, they behave as fluids. In this context, the shear strength of such materials has traditionally been analyzed from a rheological standpoint, considering them as fluids and using time as the primary state variable. From a structural perspective, however, relatively few studies have treated the material as a solid. With the advent of 3D printing technology, this trend has persisted. Within this framework, the present research aims to evaluate the shear strength of a structural mortar for 3D printing in its solid-like regime, by applying the Mohr–Coulomb failure criterion. Furthermore, in a novel approach, the degree of hydration of Portland cement is proposed as a state variable to replace time, enabling a more comprehensive and objective description of the material’s mechanical evolution. Thus, addressing this gap in the state of the art, a chemo-mechanical coupling is developed. To obtain the necessary data, direct shear, uniaxial compression, and isothermal calorimetry tests are performed. The results indicate that the friction angle remains constant, at approximately 33°, and that cohesion, the parameter governing strength gain, exhibits the same linear rate of increase with hydration in both mechanical tests, indicating an intrinsic relationship within the material. Full article

The growing demand for elderly and bedridden patient care in hospitals, nursing homes, and long-term care facilities has increased the need for safe and efficient repositioning methods. Repositioning immobile patients is essential for preventing pressure injuries and other complications associated with prolonged immobility. However, this task is still commonly performed manually using bed sheets, pillows, and similar support aids, making it physically demanding and increasing the risk of musculoskeletal injury among caregivers. This paper presents a two-stage soft growing robot for safe and assisted patient repositioning from a supine posture to a side-lying position. The proposed mechanism consists of two soft pneumatic chambers with distinct roles. The first chamber enables pressure-driven eversion, allowing the robot to deploy smoothly beneath the patient with minimal friction. The second chamber is then pressurized to generate the lifting and rolling motion required for repositioning. A first-principles dynamic model of the pressure-driven vine robot is developed by integrating pneumatic supply dynamics, internal pressure evolution, and tip-extension mechanics within a Lagrangian framework. Based on this model, a robust multi-stage nonlinear model predictive control strategy is formulated to regulate deployment beneath the patient under parameter uncertainty. The rolling dynamics of the second stage are also analyzed to determine the minimum pressure required for repositioning as a function of patient weight and roll angle. Simulation results show that the proposed controller achieves smooth and accurate deployment while satisfying input and state constraints under uncertainty. The rolling analysis further indicates that the required pressure increases with patient weight and decreases with roll angle. These findings demonstrate the potential of the proposed mechanism to reduce caregiver effort and enable safe, controlled patient repositioning. Full article