Search Results (1,467)

Nowadays, the potential of hydrokinetic turbines as a sustainable alternative to complement traditional hydropower is widely recognized. This study presents a comprehensive numerical analysis of twin straight-bladed Darrieus hydrokinetic turbines, characterizing their hydrodynamic interactions and performance characteristics. The influence of turbine configuration spacing and flow parameters on efficiency and wake dynamics are investigated. The employed 3D computational approach combines the overset mesh technique, used to capture the unsteady flow around the turbines, with the URANS k-ω Shear Stress Transport (SST) turbulence model. Results show that turbine spacing improves power coefficients and overall efficiency, albeit at the cost of slower wake recovery. A noticeable performance increase is observed when the turbines are spaced between 1.5 and 2 diameters apart, which is predicted to reach up to 40% regarding the single turbine. Furthermore, the effect of flow interaction between the turbines is examined by analyzing the influence of turbine spacing on flow structures as well as pressure and skin friction coefficients on the blades. The performed analysis reveals that vortex detachment is delayed in the twin-turbine configuration compared to the isolated case, which partially explains the observed performance enhancement. The insights gained from this work are expected to contribute to the advancement of renewable hydrokinetic energy technologies. Full article

Fault slips induced by hydraulic fracturing are the primary mechanism of casing de-formation during deep shale gas development in Sichuan’s Luzhou Block, where de-formation rates reach 51% and severely compromise productivity. To address a critical gap in existing research on quantitative risk assessment systems, we developed a probabilistic model integrating pore pressure evolution dynamics with Monte Carlo simulations to quantify slip risks. The model incorporates key operational parameters (pumping pressure, rate, and duration) and geological factors (fault friction coefficient, strike/dip angles, and horizontal stress difference) validated through field data, showing >90% slip probability in 60% of deformed well intervals. The results demonstrate that prolonged high-intensity fracturing increases slip probability by 32% under 80–100 MPa pressure surges. Meanwhile, an increase in the friction coefficient from 0.40 to 0.80 reduces slip probability by 6.4% through elevated critical pore pressure. Fault geometry exhibits coupling effects: the risk of low-dip faults reaches its peak when strike parallels the maximum horizontal stress, whereas high-dip faults show a bimodal high-risk distribution at strike angles of 60–120°; here, the horizontal stress difference is directly proportional to the slip probability. We propose optimizing fracturing parameters, controlling operation duration, and avoiding high-risk fault geometries as mitigation strategies, providing a scientific foundation for enhancing the safety and efficiency of shale gas development. Full article

Severe snowstorms pose multiple threats to high-speed rail systems, including sudden drops in track friction coefficients, icing of overhead contact lines, and reduced visibility. These conditions can trigger dynamic risks such as train speed restrictions, cascading delays, and operational disruptions. Addressing the limitations of traditional scheduling methods in spatio-temporal modeling during blizzards, real-time multi-objective trade-offs, and high-dimensional constraint solving efficiency, this paper proposes a collaborative optimization approach integrating temporal forecasting with deep reinforcement learning. A dual-module LSTM-PPO model is constructed using LSTM (Long Short-Term Memory) and PPO (Proximal Policy Optimization) algorithms, coupled with a composite reward function. This design collaboratively optimizes punctuality and scheduling stability, enabling efficient schedule adjustments. To validate the proposed method’s effectiveness, a simulation environment based on the Lanzhou-Xinjiang High-Speed Railway line was constructed. Experiments employing a three-stage blizzard evolution mechanism demonstrated that this approach effectively achieves a dynamic equilibrium among safety, punctuality, and scheduling stability during severe snowstorms. This provides crucial decision support for intelligent scheduling of high-speed rail systems under extreme weather conditions. Full article

The growing demand for precision and consistency in the forging industry has heightened the need for predictive simulation tools. While extensive research has focused on parameters such as flow stress, die wear, billet fracture, and residual stresses, the phenomenon of billet buckling, especially during cold upset forging, remains underexplored. Most existing models address only elastic buckling for slender billets using classical approaches like Euler and Rankine-Gordon formulae, which are not suitable for inelastic deformation in shorter billets. This study presents a numerical model developed to analyze inelastic buckling during cold forging and to determine associated stresses and deflection characteristics. The model was validated through finite element simulations across a range of billet geometries (10–40 mm diameter, 120 mm length), materials (aluminum, stainless steel, and copper), and friction coefficients (µ = 0.12, 0.16, and 0.35). Stress distributions were evaluated against die stroke, with particular emphasis on the influence of strain hardening and geometry. The results showed that billet geometry and strain-hardening exponent significantly affect buckling behavior, whereas friction had a secondary effect, mainly altering overall stress levels. A nonlinear regression approach incorporating material properties, geometric parameters, and friction was used to formulate the numerical model. The developed model effectively estimated buckling stresses across various conditions but could not precisely predict buckling points based on stress differentials. This work contributes a novel framework for integrating material, geometric, and process variables into stress prediction during forging, advancing defect control strategies in industrial metal forming. Full article

Static mixers are commonly used for process intensification in a wide range of industrial applications. For the design and selection of a static mixer, an accurate prediction of the hydraulic performance, particularly the pressure drop, is essential. This experimental study examines the pressure drop for turbulent single-phase and gas–liquid two-phase flows through a Komax triple-action static mixer placed on a horizontal pipeline. New values of friction factor and z-factor are reported for fully turbulent liquid single-phase flow (11,700 ≤ Re_L ≤ 18,700). For two-phase flow, the pressure drop for stratified and intermittent flows (0.07 m/s ≤ U_L ≤ 0.28 m/s and 0.46 m/s ≤ U_G ≤ 3.05 m/s) is modeled using the Lockhart–Martinelli approach, with a coefficient, C, correlated to the homogenous void fraction. Conversely, the analysis of power dissipation reveals a dependence on both liquid and gas superficial velocities. For conditions corresponding to intermittent flow upstream of the mixer, flow visualization revealed the emergence of a swirling flow in the Komax static mixer. It is interesting to note that an increase in slug frequency leads to an increase, followed by stabilization of the pressure drop. The results offer valuable insights for improving the design and optimization of Komax static mixers operating under single-phase and two-phase flow conditions. In particular, the reported correlations can serve as practical tools for predicting hydraulic losses during the design and scale-up. Moreover, the observed influence of the slug frequency on the pressure drop provides guidance for selecting operating conditions that minimize energy consumption while ensuring efficient mixing. Full article

Vibration loads during deep drilling are one of the main causes of reduced service life of drilling tools and emergency failure of downhole motors. This work investigates the adaptive operation of an original elastic element based on an open cylindrical shell used as part of a drilling shock absorber. The vibration protection device contains an adjustable radial clearance between the load-bearing shell and the rigid housing, which provides the effect of structural nonlinearity. This allows effective combination of two operating modes of the drilling shock absorber: normal mode, when the clearance does not close and the elastic element operates with increased compliance; and emergency mode, when the clearance closes and gradual load redistribution and increase in device stiffness occur. A nonconservative problem concerning the contact interaction of an elastic filler with a coaxially installed shaft and an open shell is formulated, and as the load increases, contact between the shell and the housing, installed with a radial clearance, is taken into account. Numerical finite element modeling is performed considering dry friction in contact pairs. The distributions of radial displacements, contact stresses, and equivalent stresses are examined, and deformation diagrams are presented for two loading modes. The influence of different cycle asymmetry coefficients on the formation of hysteresis loops and energy dissipation is analyzed. It is shown that with increasing load, clearance closure begins from local sectors and gradually covers almost the entire outer surface of the shell. This results in deconcentration of contact pressure between the shell and housing and reduction of peak concentrations of equivalent stresses in the open shell. The results confirm the effectiveness of the adaptive approach to designing shell shock absorbers capable of reliably withstanding emergency overloads, which is important for deep drilling where the exact range of external impacts is difficult to predict. Full article

This work proposes a novel design configuration for an elasto-poro-hydrodynamic damper (EPHD damper) that consists of an imbibed, soft, elastic, porous material enclosed by a rubber membrane. The core innovation lies in the device’s ability to collect and re-imbibe expelled fluid during decompression, ensuring potential functionality and durability across repetitive loading cycles. Damping is achieved through the synergy of three mechanisms: friction of the membrane and of the piston with solid boundaries, squeeze flow inside the porous layer, and compression of the poro-elastic structure. The EPHD damper’s behavior was evaluated both theoretically and experimentally through quasi-static, low-speed compression tests, with dynamic evaluation being reserved for future work. A numerical model successfully validated stress-deformation behavior against experimental data, with a simplified analytical model providing a good approximation. The study also identifies that the piston–membrane friction coefficient significantly influences the EPHD damper’s performance. These findings provide a valuable framework for optimizing the design and expanding its potential application to repetitive damping systems. Full article

This study evaluates the tribological properties of poly-DL-lactic acid (PDLLA) nanosheets attached to shark-skin surfaces with varying textures. The main goal was to assess friction reduction in samples with different surface textures and investigate the influence of PDLLA nanosheets on tribological behaviors. Biomimetic shark skin was created using a polydimethylsiloxane (PDMS)-embedded stamping method (PEES) that replicates shark skin’s unique texture, which reduces friction and drag in aquatic environments. PDLLA nanosheets, with a controlled thickness of several tens of nanometers, were fabricated and attached to the PDMS surfaces. The morphological characteristics of the materials were analyzed before and after attaching the PDLLA nanosheets using scanning electron microscopy (SEM), revealing the uniformity and adherence of the nanosheets to the PDMS surfaces. Friction tests were conducted using force transducers to measure the friction coefficients of biomimetic shark skin, biological models, and flat PDMS and silicon substrates, allowing a comprehensive comparison of frictional properties. Additionally, sliding tests with human fingers were performed to assess friction coefficients between various fingerprint shapes and sample surfaces. This aspect of the study is critical for understanding how human skin interacts with biomimetic materials in real-world applications, such as wearable devices. These findings clarify the relationship between surface texture, nanosheets, and their tribological performance against human skin, thereby contributing to the development of materials with enhanced friction-reducing properties for applications such as surface coatings, substrates for wearable devices, and wound dressings. Full article

Control of the friction process in stretch-forming conditions, when creating sheet metal, is essential for obtaining components of the quality required. This paper presents an approach to modelling the friction phenomenon at the rounded edges of stamping dies. The aim of the study is to compare the coefficient of friction (CoF) determined from numerous analytical models available in the literature. Experimental studies were conducted using self-developed bending under tension friction testing apparatus. The test material was low-carbon DC01 steel sheeting. Tests were conducted under lubricated conditions, using industrial oil intended for deep drawing operations. The surfaces of countersamples made of 145Cr6 substrate were modified using the ion implantation of Pb (IOPb) and electron beam melting processes. Variation in the CoF in BUT tests was related to continuous deformation-induced changes in surface topography and changes in the mechanical properties of sheet metal due to the work-hardening phenomenon. Under friction testing with a stationary countersample, the largest increase in average roughness (by 19%) was found for the DC01/IOPb friction pair. The friction process caused a significant decrease in kurtosis values. The results show that the difference between the highest and lowest CoF values, determined for the analytical models considered, was approximately 40%. Full article

Selecting a reasonable mesoscopic contact model and corresponding contact parameters is a key problem in discrete element simulation. In order to characterize the mesoscopic contact characteristics between particles in cohesive soil–rock mixture (CSRM), a set of laboratory consolidated and undrained triaxial tests were conducted on remolded samples of clay and CSRM collected in situ. Based on the experiments, 2D discrete element models of clay and CSRM were established, respectively. Considering the difference in the mechanical characteristics between soil particles and between soil and rock particles, different types of contact model were applied. The effects of the contact stiffness, bond strength, and friction coefficient between soil particles and between soil and rock particles on the stress–strain curves of both clay and CSRM numerical samples were sequentially studied by parameter sensitivity analysis. Results show that the contact stiffness and friction coefficient between soil particles affect the initial tangent modulus, the peak stress and the post-peak residual stress of the clay sample, while the bonding strength only affects its peak stress and residual stress. However, the mesoscopic contact parameters between soil and rock particles have little effect on the initial tangent modulus of CSRM sample but have a certain impact on the development of stress in the plastic stage, among which the influences of normal bonding strength and friction coefficient between soil and rock particles are more obvious. Finally, according to the comparison between the laboratory test results and the corresponding numerical simulation results in both clay and CSRM samples, mesoscopic contact parameters in CSRM were calibrated. Full article

Basalt fiber-reinforced polymer (BFRP) composites are increasingly utilized in photovoltaic mounting systems due to their excellent mechanical properties and durability. Bolted connections, valued for their simplicity, ease of installation, and effective load transfer, are widely employed for joining composite components. An orthogonal experimental design was adopted to investigate the effects of key parameters—including bolt end distance, number of bolts, bolt material, bolt diameter, preload, and connection length—on the load-bearing performance of three bolted BFRP plate configurations: lap joint (DJ), single lap joint (DP), and double lap joint (SP). Test results showed that the DJ connection exhibited the highest average tensile load capacity, exceeding those of the SP and DP connections by 45.3% and 50.2%, respectively. This superiority is attributed to the DJ specimen’s longer effective shear length and greater number of load-bearing bolts. Conversely, the SP connection demonstrated the largest average peak displacement, with increases of 29.7% and 52.9% compared to the DP and DJ connections. The double-sided constraint in the SP configuration promotes more uniform preload distribution and enhances shear deformation capacity. Orthogonal sensitivity analysis further revealed that the number of bolts and preload magnitude significantly influenced the ultimate tensile load capacity across all connection types. Finally, a calculation model for the tensile load capacity of bolted BFRP connections was established, incorporating a friction decay coefficient (α) and shear strength (τ). This model yields calculated errors under 15% and is applicable to shear slip-dominated failure modes, thereby providing a parametric basis for optimizing the tensile design of bolted BFRP joints. Full article

One of the key issues in vehicle sustainability is their energy efficiency. The article concerns the complex issue of predicting the tractive efficiency of heavy off-road vehicles depending on the parameters of the transfer case. As part of the research, a mathematical model of an off-road truck with simplified drive system was developed and implemented in MATLAB/Simulink environment. Multiple simulations for various parameters were performed. Based on the simulation results, efficiency maps were plotted depending on parameters such as the friction coefficient in the differential mechanism, torque bias of the differential, load distribution and drawbar pull of the vehicle. The results showed that the vehicle generally achieves the highest traction efficiency with the differential operating in locked condition and confirmed that the optimal torque bias is close to the load ratio. However, taking into account the multipass effect shifts this value towards the front wheel, while taking into account the bulldozing effect shifts it towards the rear wheel. Simulated vehicle showed higher efficiency when heavily loaded at higher differential friction, while when lightly loaded, higher efficiency at lower friction. Thanks to its high degree of parameterization, this model can be used to help optimize the drive train of off-road vehicles traveling in various terrains from the energy consumption point of view, leading to more sustainable operation. Full article

In metal fused deposition modeling (FDM), performance is governed by feedstock formulation, most critically the metal solid loading, while binder selection is constrained by environmental impacts and limited recyclability. This study investigates the development and performance of highly filled 17-4PH stainless steel (17-4PH) feedstocks formulated with a low-molecular-weight polymer binder system, specifically designed for FDM in metal additive manufacturing (AM). The binder system, composed of low-cost, recyclable paraffin wax and stearic acid, was used to prepare feedstocks containing 93.0–96.0 wt.% metal powder. Rheological analysis indicated that intermediate powder loadings (95.0–95.5 wt.%) yielded optimal shear-thinning behavior, essential for stable extrusion during printing. Printing trials identified 95.5 wt.% as the critical powder loading, delivering superior print fidelity and structural integrity relative to both under-filled (93.0–94.5 wt.%) and overfilled formulations. Green part characterization revealed increased density and flexural modulus with rising powder content, while thermal debinding and sintering trials indicated enhanced thermal stability and dimensional retention at higher loadings. The as-sintered specimens from the 95.5 wt.% feedstock achieved a relative density (RD) of 96.5% and significantly improved mechanical performance, including an ultimate tensile strength (UTS) of 758 MPa and 5.2% elongation, clearly outperforming the 95.0 wt.% variant. Tribocorrosion testing further validated these improvements, with the higher-density samples showing a lower coefficient of friction and a reduced wear coefficient of 2.1 × 10⁻⁵ mm³·(N·m)⁻¹ in 3.5% NaCl solution. Full article

This paper presents a novel methodology for predicting the tire–road friction coefficient in real-time under challenging climatic conditions based on a fuzzy logic inference system. The core innovation of the proposed approach lies in the integration and probabilistic weighting of a diverse set of input data, which includes signals from ambient temperature and precipitation intensity sensors, activation events of the anti-lock braking system (ABS) and electronic stability control (ESP), windshield wiper operation modes, and road marking recognition via a front-facing camera. This multi-sensor data fusion strategy significantly enhances prediction accuracy compared to traditional methods that rely on limited data sources (e.g., temperature and precipitation alone), especially in transient or non-uniform road conditions such as compacted snow or shortly after rainfall. The reliability of the fuzzy-logic-based predictor was experimentally validated through extensive road tests on dry asphalt, wet asphalt, and wet basalt (simulating packed snow). The results demonstrate a high degree of convergence between predicted and actual values, with a maximum modeling error of less than 10% across all tested scenarios. The developed methodology provides a robust and adaptive solution for enhancing the performance of Advanced Driver Assistance Systems (ADASs), particularly Automatic Emergency Braking (AEB), by enabling more accurate braking distance calculations. Full article

To meet the demand for simulative materials exhibiting suitable hydraulic characteristics in geomechanical model tests, this research developed a type of simulative material using iron powder, quartz sand, and barite powder as aggregates, white cement as binder, and silicone oil as additive. An orthogonal experimental design L₁₆(4⁴) was employed to prepare 16 distinct mix proportions. Advanced statistical methods, including range analysis, residual analysis, Pearson correlation analysis, and multiple regression performed with SPSS 27.0.1, were applied to analyze the influence of four factors—aggregate-to-cement ratio (A), water–cement ratio (B), silicone oil content (C), and moisture content (D)—on physical and mechanical parameters such as density, uniaxial compressive strength, elastic modulus, angle of internal friction, and permeability coefficient. Range analysis results indicate that the aggregate-to-cement ratio serves as the primary controlling factor for density and elastic modulus; moisture content exerts the most significant effect on compressive strength and permeability; while the water–cement ratio is the dominant factor influencing the internal friction angle. Empirical formulas were established through multiple regression to quantitatively correlate mix proportions with material properties. The resulting similitude materials cover a wide range of mechanical and hydraulic parameters, satisfying the requirements of large-scale physical modeling with high similitude ratios. The proposed equations allow efficient inverse design of mixture ratios based on target properties, thereby supporting the rapid preparation of simulative materials for advanced model testing. Full article