Search Results (1,799)

This research presents a comprehensive methodology for calibrating Discrete Element Method (DEM) parameters governing rice grain interactions with biodegradable Polylactic Acid (PLA) components in agricultural bucket elevator systems. Rice grains, a critical global food staple requiring efficient post-harvest handling, were modeled as three-sphere clusters to accurately represent their physical dimensions (6.5 mm length), while the Hertz–Mindlin contact model provided the theoretical framework for particle interactions. The calibration process employed a multi-phase experimental design integrating Plackett–Burmann screening, steepest ascent method, and Face Central Composite Design to systematically identify and optimize critical micro-mechanical parameters for agricultural material handling. Statistical analysis revealed the coefficient of static friction between rice and PLA as the dominant factor, contributing 96.49% to system performance—significantly higher than previously recognized in conventional agricultural processing designs. Response Surface Methodology generated predictive models achieving over 90% correlation with experimental results from 3D-printed PLA shear box tests. Validation through comparative velocity profile analysis during bucket elevator discharge operations confirmed excellent agreement between simulated and experimental behavior despite a 20% discharge velocity variance that warrants further investigation into agricultural material-specific phenomena. The established parameter set enables accurate virtual prototyping of sustainable agricultural handling equipment, offering post-harvest processing engineers a powerful tool for optimizing bulk material handling systems with reduced environmental impact. This integrated approach bridges fundamental agricultural material properties with sustainable engineering design principles, providing a scalable framework applicable across multiple agricultural processing operations using biodegradable components. Full article

A solar air heater (SAH) converts solar energy into heated air without causing environmental pollution. It features a low initial cost and easy maintenance due to its simple design. However, owing to air’s poor thermal conductivity, its thermal efficiency is relatively low compared to that of other solar systems. To improve its thermal performance, previous studies have aimed at either enlarging the heat transfer surface or increasing the convective heat transfer coefficient. In this study, a novel SAH with fins and sequentially placed obstacles on the fin surface—designed to achieve both surface extension through a finned channel and enhancement of the heat transfer coefficient via the obstacles—was investigated using computational fluid dynamics analysis. The results confirmed that the obstacles enhanced heat transfer performance by up to 2.602 times in the finned channel. However, the obstacles also caused a pressure loss. Therefore, the thermo-hydraulic performance was discussed, and it was concluded that the obstacles with a relative height of 0.12 and a relative pitch of 10 yielded the maximum THP values among the investigated conditions. Additionally, correlations for the Nusselt number and friction factor were derived and predicted the simulation values with good agreement. Full article

To elucidate the key material parameters governing the tribological performance of ceramic composites under dry sliding against steel, this study presents a comprehensive comparative assessment of the microstructural characteristics, mechanical performance, and tribological behavior of two alumina–zirconia (Al₂O₃–ZrO₂) ceramic composites, each reinforced with a 42 vol.% carbide phase: zirconium carbide (ZrC) and tungsten carbide (WC). Specifically, tungsten carbide (WC) was selected for its exceptional bulk mechanical properties, while zirconium carbide (ZrC) was chosen to contrast its potentially different interfacial reactivity against a steel counterface. ZrC and WC were selected as reinforcing phases due to their high hardness and distinct chemical and interfacial properties, which were expected to critically affect the wear and friction behavior of the composites under demanding conditions. Specimens were consolidated via spark plasma sintering (SPS). The investigation encompassed macro- and nanoscale hardness measurements (Vickers hardness HV₁, HV₁₀; nanoindentation hardness H), elastic modulus (E), fracture toughness (K_IC), coefficient of friction (COF), and specific wear rate (W_s) under unlubricated reciprocating sliding against 100Cr6 steel at normal loads of 10 N and 25 N. The Al₂O₃–ZrO₂–WC composite exhibited an ultrafine-grained microstructure and markedly enhanced mechanical properties (HV₁₀ ≈ 20.9 GPa; H ≈ 33.6 GPa; K_IC ≈ 4.7 MPa·m^½) relative to the coarse-grained Al₂O₃–ZrO₂–ZrC counterpart (HV₁₀ ≈ 16.6 GPa; H ≈ 27.0 GPa; K_IC ≈ 3.2 MPa·m^½). Paradoxically, the ZrC-reinforced composite demonstrated superior tribological performance, with a low and load-independent specific wear rate (W_s ≈ 1.2 × 10⁻⁹ mm³/Nm) and a stable steady-state COF of approximately 0.46. Conversely, the WC-reinforced system exhibited significantly elevated wear volumes—particularly under the 25 N regime—and a higher, more fluctuating COF. Scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDX) of the wear tracks revealed the formation of a continuous, iron-enriched tribofilm on the ZrC composite, derived from counterface material transfer, whereas the WC composite surface displayed only sparse tribofilm development. These findings underscore that, in steel-paired tribological applications of Al₂O₃–ZrO₂–based composites, the efficacy of interfacial tribolayer generation can supersede intrinsic bulk mechanical attributes as the dominant factor governing wear resistance. Full article

To address the issue of surface glazing that occurs during prolonged polishing with gel tools, this study employs a triethanolamine (TEA)-based polishing fluid system to enhance the self-sharpening capability of the gel polishing disc. The inhibitory mechanism of TEA concentration on disc glazing is systematically analyzed, along with its impact on the gel disc’s frictional wear behaviour. Furthermore, the synergistic effects of process parameters on both surface quality and material removal rate (MRR) of SiC are examined. The results demonstrate that TEA concentration is a critical factor in regulating polishing performance. At an optimal concentration of 4 wt%, an ideal balance between chemical chelation and mechanical wear is achieved, effectively preventing glazing while avoiding excessive tool wear, thereby ensuring sustained self-sharpening capability and process stability. Through orthogonal experiment optimization, the best parameter combination for SiC polishing is determined: 4 wt% TEA concentration, 98 N polishing pressure, and 90 rpm rotational speed. This configuration delivers both superior surface quality and desirable MRR. Experimental data confirm that TEA significantly enhances the self-sharpening performance of gel discs through its unique complex reaction. During the rough polishing stage, the MRR increases by 34.9% to 0.85 μm/h, while the surface roughness S_a is reduced by 51.3% to 6.29 nm. After subsequent CMP fine polishing, an ultra-smooth surface with a final roughness of 2.33 nm is achieved. Full article

The strength parameters of fault gouge are critical factors that influence sealing capacity and fault reactivation in underground gas storage reservoirs. This study investigates the shear characteristics of remolded fault gouge under varying hydro-mechanical conditions, focusing on the coupled influence of water content and cementation. Sixty fault gouge samples are prepared using a mineral mixture of quartz, montmorillonite, and kaolinite, with five levels of water content (10–30%) and three cementation degrees (0%, 1%, 3%). Direct shear tests are conducted under four normal stress levels (100–400 kPa), and microstructural characteristics are examined using SEM. The results show that shear strength and cohesion exhibit a non-monotonic trend with water content, increasing initially and then decreasing, while the internal friction angle decreases continuously. Higher cementation degrees not only enhance shear strength and reduce the softening effect caused by water but also shift the failure mode from ductile sliding to brittle, cliff-type rupture. Moreover, clay content is found to modulate the degree—but not the trend—of strength parameter responses to water and cementation variations. Based on the observed mechanical behavior, a semi-empirical shear strength prediction model is developed by extending the classical Mohr–Coulomb criterion with water–cementation coupling terms. The model accurately predicts cohesion and internal friction angle as functions of water content and cementation degree, achieving strong agreement with experimental results (R² = 0.8309 for training and R² = 0.8172 for testing). These findings provide a practical and interpretable framework for predicting the mechanical response of fault gouge under complex geological conditions. Full article

This study, in response to the optimization needs of fall risks for the elderly in the context of cultural and tourism integration in Hebei Province, China, established a quantitative correlation system between ten gait parameters and ten types of spatial risk factors. By collecting gait data (Qualisys infrared motion capture system, sampling rate 200 Hz) and spatial parameters from 30 elderly subjects (with mild, moderate, and severe functional impairments), a multi-level regression model was established. This study revealed that step frequency, step width, and step length were nonlinearly associated with corridor length, door opening width, and step depth (R² = 0.53–0.68). Step speed, ankle dorsiflexion, and foot pressure were key predictive factors (OR = 0.04–8.58, p < 0.001), driving the optimization of core spatial factors such as threshold height, handrail density, and friction coefficient. Step length, cycle, knee angle, and lumbar moment, respectively, affected bed height (45–60 cm), switch height (1.2–1.4 m), stair riser height (≤35 mm), and sink height adjustment range (0.7–0.9 m). The prediction accuracy of the ten optimized values reached 86.7% (95% CI: 82.1–90.3%), with Hosmer–Lemeshow goodness-of-fit x² = 7.32 (p = 0.412) and ROC curve AUC = 0.912. Empirical evidence shows that the graded optimization scheme reduced the fall risk by 42–85%, and the estimated fall incidence rate decreased by 67% after the renovation. The study of the “abnormal gait—spatial threshold—graded optimization” quantitative residential layout optimization provides a systematic solution for the data-quantified model of elderly-friendly residential renovations. Full article

Slope stability analysis is conventionally performed using the strength reduction method with the proportional reduction in shear strength parameters. However, during actual slope failure processes, the attenuation characteristics of rock mass cohesion ($c$) and internal friction angle ($\phi$) are often inconsistent, and their reduction paths exhibit clear nonlinearity. Relying solely on proportional reduction paths to calculate safety factors may therefore lack scientific rigor and fail to reflect true slope behavior. To address this limitation, this study proposes a novel approach that considers the non-proportional reduction of $c$ and $\phi$, without dependence on predefined reduction paths. The method begins with an analysis of slope stability states based on energy dissipation theory. A Bayesian Gaussian Mixture Model (BGMM) is employed for intelligent interpretation of the dissipated energy data, and, combined with energy mutation theory, is used to identify instability states under various reduction parameter combinations. To compute the safety factor, the concept of a “reference slope” is introduced. This reference slope represents the state at which the slope reaches limit equilibrium under strength reduction. The safety factor is then defined as the ratio of the shear strength of the target analyzed slope to that of the reference slope, providing a physically meaningful and interpretable safety index. Compared with traditional proportional reduction methods, the proposed approach offers more accurate estimation of safety factors, demonstrates superior sensitivity in identifying critical slopes, and significantly improves the reliability and precision of slope stability assessments. These advantages contribute to enhanced safety management and risk control in slope engineering practice. Full article

Variable-speed reciprocating compressors (VSRCs) have been increasingly used in domestic refrigeration due to their ability to modulate cooling capacity and reduce energy consumption. A detailed understanding of performance-limiting factors such as volumetric and exergetic inefficiencies is essential for optimizing their operation. An experimentally validated simulation model was developed using GT-SUITE to analyze a VSRC operating with R-600a across speeds from 1800 to 6300 rpm. Volumetric inefficiencies were quantified using a stratification methodology, while an exergy-based approach was adopted to assess the main sources of thermodynamic inefficiency in the compressor. Unlike traditional energy analysis, exergy analysis reveals where and why irreversibilities occur, linking them directly to power consumption and providing a framework for optimizing design. Results reveal that neither volumetric nor exergy efficiency varies monotonically with compressor speed. At low speeds, exergetic losses are dominated by the electrical motor (up to 19% of input power) and heat transfer (up to 13.5%). Conversely, at high speeds, irreversibilities from fluid dynamics become critical, with losses from discharge valve throttling reaching 5.8% and bearing friction increasing to 6.5%. Additionally, key volumetric inefficiencies arise from piston–cylinder leakage, which causes up to a 4.5% loss at low speeds, and discharge valve backflow, causing over a 5% loss at certain resonant speeds. The results reveal complex speed-dependent interactions between dynamic and thermodynamic loss mechanisms in VSRCs. The integrated modeling approach offers a robust framework for diagnosing inefficiencies and supports the development of more energy-efficient compressor designs. Full article

In recent years, pneumatic stages have attracted attention as stages for semiconductor manufacturing equipment due to their low cost and minimal maintenance requirements. However, pneumatic stages include nonlinear elements such as friction and air compressibility, making precise control challenging. To address this issue, this paper aims to achieve high-precision positioning by applying a nonlinear position control method to pneumatic stages. To achieve this, we propose a control method that combines filtered right coprime factorization and Prescribed Performance Control–Sliding Mode Control (PPC-SMC). Filtered right coprime factorization not only stabilizes and simplifies the plant but also reduces noise. Furthermore, PPC-SMC enables safer and faster control by constraining the system state within a switching surface that imposes limits on the error range. Through experiments on the actual system, it was confirmed that the proposed method achieves dramatically higher precision and faster tracking compared to conventional methods. Full article

The compressive capacity of helical anchors constitutes a pivotal performance parameter in geotechnical design. To precisely predict the compressive bearing behavior of helical anchors in aeolian sand, this study integrates in situ testing with finite element numerical analysis to systematically elucidate the non-linear evolution of its load-bearing mechanisms. The XGBoost algorithm enabled the rigorous quantification of the governing geometric features of compressive capacity, culminating in a computational framework for the bearing capacity factor (N_q) and lateral earth pressure coefficient (K_u). The research findings demonstrate the following: (1) Compressive capacity exhibits significant enhancement with increasing helix diameter yet displays limited sensitivity to helix number. (2) Load–displacement curves progress through three distinct phases—initial quasi-linear, intermediate non-linear, and terminal quasi-linear stages—under escalating pressure. (3) At embedment depths of H < 5D, tensile capacity diminishes by approximately 80% relative to compressive capacity, manifesting as characteristic shallow anchor failure patterns. (4) When H ≥ 5D, stress redistribution transitions from bowl-shaped to elliptical contours, with ≤10% divergence between uplift/compressive capacities, establishing 5D as the critical threshold defining shallow versus deep anchor behavior. (5) The helix spacing ratio (S/D) governs the failure mode transition, where cylindrical shear (CS) dominates at S/D ≤ 4, while individual bearing (IB) prevails at S/D > 4. (6) XGBoost feature importance analysis confirms internal friction angle, helix diameter, and embedment depth as the three parameters exerting the most pronounced influence on capacity. (7) The proposed computational models for N_q and K_u demonstrate exceptional concordance with numerical simulations (mean deviation = 1.03, variance = 0.012). These outcomes provide both theoretical foundations and practical methodologies for helical anchor engineering in aeolian sand environments. Full article

The optimization and control of the wellbore trajectory is one of the important technologies to improve drilling efficiency, reduce drilling cost, and ensure drilling safety in the process of modern oil and gas exploration and development. In this paper, a multi-objective wellbore trajectory optimization mathematical model is established, which takes into account the five factors of wellbore trajectory length, friction, torque, trajectory complexity, and target accuracy. A DR-NSGA-III-MGA algorithm (dynamic reference NSGA-III with multi-granularity adaptation) is proposed. By introducing multi-granularity reference vector generation and an information entropy-guided search direction adaptation mechanism, the performance of the algorithm in the complex target space is improved, and the three-stage wellbore trajectory is optimized. Simulation experiments show that the DR-NSGA-III-MGA algorithm is stable in a variety of complex problems, while maintaining good convergence, and has good generalization ability and practical application value. Full article

With the evolution of hydroelectric generators toward larger capacity and higher rotational speeds, the significa++nt increase in power density has rendered rotor cooling technology a critical bottleneck restricting performance enhancement. Addressing the need for feasibility verification and thermodynamic characteristic analysis of evaporative cooling applied to rotors, this study innovatively proposes an internal-cooling-based evaporative cooling architecture for rotor windings. By establishing a single-channel experimental platform for a rotor evaporative cooling system, the key parameters of the system circulation flow under varying centrifugal accelerations and thermal loads are obtained, revealing the flow mechanism of the cooling system. The experimental results demonstrate that the novel architecture has outstanding heat dissipation performance. Furthermore, the experimental findings reveal that the flow characteristics of the medium are governed by the coupled effect of centrifugal acceleration and thermal load; the flow rate decreases with increasing centrifugal acceleration and increases with rising thermal load. Centrifugal acceleration reduces frictional losses in the heating pipe, leading to a decrease in the inlet–outlet pressure difference. Through the integration of experimental data with classic formulas, this study refines the friction factor model, with the modified formula showing a discrepancy of −10% to +5% compared with the experimental results. Finally, the experiment was rerun to verify the universality of the modified friction factor. Full article

Decontamination robots are becoming more common in environments where reducing human exposure to hazardous substances is essential, including healthcare settings, laboratories, and industrial cleanrooms. Designing terrain-capable decontamination robots quickly is challenging due to varying operational surfaces and mobility limitations. To tackle this issue, a structured recommendation framework is proposed to automate selecting optimal locomotion types and track configurations, significantly cutting down design time. The proposed system features a two-stage evaluation process: first, it creates an annotated compatibility score matrix by validating locomotion types against a robust dataset based on factors like friction coefficient, roughness, payload capacity, and slope gradient; second, it employs a weighted scoring model to rank wheel/track types based on their appropriateness for the identified environmental conditions. User needs are processed dynamically using a large language model, enabling flexible and scalable management of various deployment scenarios. A prototype decontamination robot was developed following the proposed algorithm’s guidance. This framework speeds up the configuration process and establishes a foundation for more intelligent, terrain-aware robot design workflows that can be applied to industrial, healthcare, and service robotics sectors. Full article

The thermal error caused by the temperature rise in the service condition of the hydrostatic turntable system has a significant impact on the accuracy of the machine tool. The temperature rise is mainly caused by the friction heat of the bearing and the heat of the oil pump. The amount of heat mainly depends on the working parameters, such as the oil supply pressure and the oil film gap. The unreasonable parameter setting will cause the reduction in the internal flow of the hydrostatic bearing and the increase in the oil pump power, which makes the heat of the lubricating oil increase and the heat dissipation capacity decrease during the movement. Based on the established hydrostatic turntable system, in order to explore the main influencing factors of its thermal error, the temperature field model of the component is established by calculating the thermal balance of the key components of the system. The thermal coupling analysis of the component is carried out by using the model, and the temperature rise, deformation and strain curves of the hydrostatic turntable system under different service conditions are obtained. The results show that with the increase in the temperature, the deformation and strain of the bearing increase monotonously. For every 1 °C increase, the total deformation of the bearing increases by about 0.285 $\mathsf{\mu }\mathrm{m}$. The higher the oil supply pressure, the higher the temperature rise in the system. The larger the oil film gap, the lower the temperature rise in the system. The oil supply pressure has a greater influence on the temperature rise and thermal deformation than the oil film gap. This study provides a valuable reference for reducing the thermal error generated by the hydraulic turntable of the ultra-precision lathe. Full article

To establish a fundamental property database for discrete elements targeting long-fiber materials and address the issue of response surface methodology (RSM) being prone to local optima in high-dimensional nonlinear optimization, this study conducted parameter calibration experiments and validated the calibrated parameters through a combined approach of simulation and physical testing. The Plackett–Burman design and steepest ascent test were employed to screen significant factors. Using the angle of repose (42.3°) obtained from physical experiments as the response value, response surface methodology (RSM) and a particle swarm optimization–back propagation (PSO-BP) neural network model were independently applied to optimize and compare the critical parameters. The results demonstrated that the dynamic friction coefficient between wheat straw particles, the static friction coefficient between wheat straw and steel plate, and the JKR surface energy were the most influential factors on the simulated angle of repose. The PSO-BP model exhibited superior optimization performance compared to RSM, yielding an optimal parameter combination of 0.17, 0.46, and 0.03. The simulated repose angle under these conditions was 41.67°, exhibiting a relative error of only 1.5% compared to the physical experiment. These findings provide a robust theoretical foundation for discrete element simulations of wheat straw feedstock. Full article