Search Results (1,277)

With the increasing penetration of distributed generation (DG), integrated main-distribution networks (IMDNs) face challenges in rapidly and effectively performing comprehensive operational risk assessments under multiple uncertainties. Thereby, using the traditional hierarchical economic scheduling method makes it difficult to accurately find the optimal scheduling operating point. To address this problem, this paper proposes a multi-objective dispatch decision-making optimization model for the IMDN with static security region (SSR) constraints. Firstly, the non-sequential Monte Carlo sampling is employed to generate diverse operational scenarios, and then the key risk characteristics are extracted to construct the risk assessment index system for the transmission and distribution grid, respectively. Secondly, a hyperplane model of the SSR is developed for the IMDN based on alternating current power flow equations and line current constraints. Thirdly, a risk assessment matrix is constructed through optimal power flow calculations across multiple load levels, with the index weights determined via principal component analysis (PCA). Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. A membership matrix of the solution set is then established using fuzzy comprehensive evaluation to identify the optimal compromised operating point for dispatch decision support. Finally, the effectiveness and superiority of the proposed method are validated using an integrated IEEE 9-bus and IEEE 33-bus test system. Full article

Background: Off-label nebulization of tranexamic acid (TXA) solution is common practice for the treatment of hemoptysis. However, data regarding nebulization protocols, resulting aerodynamic parameters of the generated aerosol, and corresponding biopharmaceutical parameters are missing. The aim of this in vitro study was to investigate the aerosol characteristics of nebulized sterile, aqueous TXA solution. Methods: TXA solution 100 mg/mL was nebulized for 2 min by a multi-dose vibrating mesh nebulizer using 15 L/min and 30 L/min air flow rates. The generated aerosol was analyzed by a Next Generation Cascade Impactor. For each air flow rate, the mean Fine Particle Dose (FPD), Fine Particle Fraction (FPF), the Mass Median Aerodynamic Diameter (MMAD), and Geometric Standard Deviation (GSD) were quantified. Results: Nebulization at 15 L/min air flow rate resulted in a MMAD of 6.68 ± 0.23 µm and GSD of 2.02 ± 0.16. The FPD < 5 µm was 16.56 ± 0.45 mg, the FPF < 5 µm 28.91 ± 3.40%. Nebulization at 30 L/min air flow rate revealed a MMAD of 5.18 ± 0.12 µm and GSD of 2.14 ± 0.10. The FPD < 5 µm was 16.30 ± 1.38 mg, the FPF < 5 µm 35.43 ± 0.59%. Conclusions: Nebulization of TXA 100 mg/mL solution by a specified vibrating mesh nebulizer generated an aerosol particle distribution and deposition pattern suitable for the treatment of hemoptysis with bronchial origin. Full article

Considering the serious hazard of respiratory dust in underground coal mines and the low efficiency of traditional dust-reduction technology, this study optimizes the atomisation parameters of the gas–liquid two-phase flow nozzle through numerical simulation and experimental testing, and designs an on-board dust-reduction system. Based on the Fluent software (version 2023 R2), a flow field model outside the nozzle was established, and the effects of the air supply pressure, gas-phase inlet velocity, and droplet mass flow rate on the atomisation characteristics were analyzed. The results show that increasing the air supply pressure can effectively reduce the droplet particle size and increase the range and atomisation angle, and that the dust-reduction efficiency is significantly improved with the increase in pressure. The dust-reduction efficiency reached 69.3% at 0.6 MPa, which was the economically optimal operating condition. Based on the parameter optimization, this study designed an annular airborne gas–liquid two-phase flow dust-reduction system, and a field test showed that the dust-reduction efficiency of this system could reach up to 86.0%, which is 53.5% higher than that of traditional high-pressure spraying, and that the dust concentration was reduced to less than 6 mg/m³. This study provides an efficient and reliable technical solution for the management of underground coal mine dust and guidance for promoting the development of the coal industry. Full article

Under the “dual carbon” goals and rapid clean energy development, power grids face challenges including rapid load growth, uneven power flow distribution, and limited transmission capacity. This paper proposes a novel FACTS device with fault tolerance and switchable topology that maintains power flow control over multiple lines during N-1 faults, enhancing grid safety and economy. The paper establishes a steady-state mathematical model based on additional virtual nodes and provides power flow calculation methods to accurately reflect the device’s control characteristics. An entropy-weighted TOPSIS method was employed to establish a quantitative evaluation system for assessing the grid performance improvement after FACTS device integration. To address interaction issues among multiple flexible devices, an optimization planning model considering th3e coordinated effects of UPFC and VSC-HVDC was constructed. Multi-objective particle swarm optimization obtained Pareto solution sets, combined with the evaluation system, to determine the optimal configuration schemes. Considering wind power uncertainty and fault risks, we propose a system-level coordinated operation strategy. This strategy constructs probabilistic risk indicators and introduces topology switching control constraints. Using particle swarm optimization, it achieves a balance between safety and economic objectives. Simulation results in the Jiangsu power grid scenarios demonstrated significant advantages in enhancing the transmission capacity, optimizing the power flow distribution, and ensuring system security. Full article

To reveal the meso-mechanical essence of deep rock mass failure and capture precursor information, this study focuses on soft rock failure mechanisms. Based on the discontinuous medium discrete element method (DEM), we employed digital image correlation (DIC) technology, acoustic emission (AE) monitoring, and particle flow code (PFC) numerical simulation to investigate the failure evolution characteristics and AE quantitative representation of soft rocks. Key findings include the following: Localized high-strain zones emerge on specimen surfaces before macroscopic crack visualization, with crack tip positions guiding both high-strain zones and crack propagation directions. Strong force chain evolution exhibits high consistency with the macroscopic stress response—as stress increases and damage progresses, force chains concentrate near macroscopic fracture surfaces, aligning with crack propagation directions, while numerous short force chains coalesce into longer chains. The spatial and temporal distribution characteristics of acoustic emissions were explored, and the damage types were quantitatively characterized, with ring-down counts demonstrating four distinct stages: sporadic, gradual increase, stepwise growth, and surge. Shear failures predominantly occurred along macroscopic fracture surfaces. At the same time, there is a phenomenon of acoustic emission silence in front of the stress peak in the surrounding rock of deep soft rock roadway, as a potential precursor indicator for engineering disaster early warning. These findings provide critical theoretical support for deep engineering disaster prediction. Full article

Accurate calibration of mesoscopic contact model parameters is essential for ensuring the reliability of Particle Flow Code in Three Dimensions (PFC3D) simulations in geotechnical engineering. Trial-and-error approaches are often used to determine the parameters of the contact model, but they are time-consuming, labor-intensive, and offer no guarantee of parameter validity or simulation credibility. Although conventional machine learning techniques have been applied to invert the contact model parameters, they are hampered by the difficulty of selecting the optimal hyperparameters and, in some cases, insufficient data, which limits both the predictive accuracy and robustness. In this study, a total of 361 PFC3D uniaxial compression simulations using a linear parallel bond model with varied mesoscopic parameters were generated to capture a wide range of rock and geotechnical material behaviors. From each stress–strain curve, eight characteristic points were extracted as inputs to a multi-objective Automated Machine Learning (AutoML) model designed to invert three key mesoscopic parameters, i.e., the elastic modulus (E), stiffness ratio (k_s/k_n), and degraded elastic modulus (E_d). The developed AutoML model, comprising two hidden layers of 256 and 32 neurons with ReLU activation function, achieved coefficients of determination (R²) of 0.992, 0.710, and 0.521 for E, k_s/k_n, and E_d, respectively, demonstrating acceptable predictive accuracy and generalizability. The multi-objective AutoML model was also applied to invert the parameters from three independent uniaxial compression tests on rock-like materials to validate its practical performance. The close match between the experimental and numerically simulated stress–strain curves confirmed the model’s reliability for mesoscopic parameter inversion in PFC3D. Full article

This study establishes a multiphysics coupling model of acoustics, mechanics, and electrostatics through COMSOL, systematically explores the sound field distribution and stress–strain characteristics of tailing particles in sand silos under different frequencies of ultrasonic radiation, and proposes an optimization scheme for the sound field. The simulation results show that under 28 kHz ultrasonic radiation, the amplitude of sound pressure in the sand silo (173 Pa) is much lower than that at 40 kHz (1220 Pa), which can avoid damaging the original settlement mode of the tail mortar. At the same time, the periodic fluctuation amplitude of its longitudinal sound pressure is significantly greater than 25 kHz, which can promote settlement by enhancing particle tensile and compressive stress, achieving the best comprehensive effect. The staggered placement scheme of the transducer eliminates upward disturbance in the flow field by changing the longitudinal opposing sound field to oblique propagation, reduces energy dissipation, and increases the highest sound pressure level in the compartment to 130 dB. The sound pressure distribution density is significantly improved, further enhancing the settling effect. This study clarifies the correlation mechanism between ultrasound parameters and tailings’ settling efficiency, providing a theoretical basis for parameter optimization of ultrasound-assisted tailing treatment technology. Its results have important application value in the optimization of tailings settling in metal mine tailing filling. Full article

Aerosol uniformity in the mixing chamber is one of the key factors in evaluating performance of aerosol samplers and accuracy of aerosol monitors which could output the direct reading of particle size or concentration. For obtaining high uniformity and a stable test aerosol sample during evaluation, a portable mixing chamber, where the sample and clean air were dual-vortex turbulent mixed, was designed. By using computational fluid dynamics (CFD), particle motion within the mixing chamber was illustrated or explained. By adjusting critical structure parameters of chamber such as height and diameter, the flow field structure was optimized to improve particle mixing characteristics. Accordingly, a novel portable aerosol mixing chamber with length and inner diameter of 0.7 m and 60 mm was developed. Through a combination of simulations and experiments, the operating conditions, including working flow rate, ratio of carrier/dilution clean air, and mixture duration, were studied. Finally, by using the optimized parameters, a mixing chamber with high spatial uniformity where variation is less than 4% was obtained for aerosol particles ranging from 0.3 μm to 10 μm. Based on this chamber, a standardized testing platform was established to verify the sampling efficiency of aerosol samplers with high flow rate (28.3 L·min⁻¹). The obtained results were consistent with the reference values in the sampler’s manual, confirming the reliability of the evaluation system. The testing platform developed in this study can provide test aerosol particles ranging from sub-micrometers to micrometers and has significant engineering applications, such as atmospheric pollution monitoring and occupational health assessment. Full article

This study employs Particle Image Velocimetry (PIV) technology to investigate the statistical properties and flow structures of the turbulent boundary layer over smooth walls and riblet walls with yaw angles of 0, ±30° in both clear water and liquid–solid two-phase flow fields. The results indicate that, compared to the smooth wall, streamwise riblet walls and 30° divergent riblet walls can reduce the boundary layer thickness, wall friction force, comprehensive turbulence intensity, and Reynolds stress, with the divergent riblet wall being more effective. In contrast, convergent riblet walls have the opposite effect. The addition of particles leads to an increase in boundary layer thickness and a reduction in wall friction resistance, primarily by reducing turbulence fluctuations and Reynolds stress in the logarithmic region of the turbulent boundary layer. Moreover, the two types of drag-reduction riblet walls can decrease the energy content ratio of near-wall streak structures and suppress their motion in the spanwise direction. Their impact on burst events is mainly characterized by a reduction in the number of ejection events and their contribution to Reynolds shear stress. In comparison, convergent riblet walls have the complete opposite effect and also enhance the intensity of burst events. The addition of particles can fragment streak structures and suppress the intensity and number of burst events, acting similarly on drag-reduction riblet walls and further strengthening their drag reduction characteristics. Full article

The dynamic non-equilibrium effect (DNE) describes the non-unique character of saturation–capillary pressure relationships observed under static, steady-state, or monotonic hydrodynamic conditions. Macroscopically, the DNE manifests as variations in soil hydraulic characteristic curves arising from varying hydrodynamic testing conditions and is fundamentally governed by soil matrix particle size distribution. Changes in the DNE across porous media with discrete particle size fractions are investigated via stepwise drying experiments. Through quantification of saturation–capillary pressure hysteresis and DNE metrics, three critical signatures are identified: (1) the temporal lag between peak capillary pressure and minimum water saturation; (2) the pressure gap between transient and equilibrium states; and (3) residual water saturation. In the four experimental sets, with the finest material (Test 1), the peak capillary pressure consistently precedes the minimum water saturation by up to 60 s. Conversely, with the coarsest material (Test 4), peak capillary pressure does not consistently precede minimum saturation, with a maximum lag of only 30 s. The pressure gap between transient and equilibrium states reached 14.04 cm H₂O in the finest sand, compared to only 2.65 cm H₂O in the coarsest sand. Simultaneously, residual water saturation was significantly higher in the finest sand (0.364) than in the coarsest sand (0.086). The results further reveal that the intensity of the DNE scales inversely with particle size and linearly with wetting phase saturation (Sw), exhibiting systematic decay as Sw decreases. Coarse media exhibit negligible hysteresis due to suppressed capillary retention; this is in stark contrast with fine sands, in which the DNE is observed to persist in advanced drying stages. These results establish pore geometry and capillary dominance as fundamental factors controlling non-equilibrium fluid dynamics, providing a mechanistic framework for the refinement of multi-phase flow models in heterogeneous porous systems. Full article

To investigate the evolution trend of the extraction zone above the drawbell in block caving, an experimental apparatus incorporating the drawbell structure was designed. Ore drawing experiments were conducted using materials with varying particle size gradations. The results demonstrate that the extraction zones for all three gradations exhibit an ellipsoidal shape in the vertical direction, with elliptical cross-sections. As the draw height increases, both the major and minor axes of the extraction zone’s maximum cross-section continuously enlarge, stabilizing beyond a draw height of 80 cm. The ore fragment size significantly influences the extraction zone dimensions. Gradation I, characterized by the smallest average particle size, yielded the largest extraction zone, whereas Gradation III, with the largest average particle size, resulted in the smallest. Numerical simulations of ore drawing for the different particle sizes were performed using PFC3D. The extent of the extraction zone in the numerical results was determined by reconstructing the initial positions of the drawn particles. The simulations show good agreement with the experimental findings, particularly regarding how the major and minor axes of the extraction zone cross-section vary with increasing draw height. Moreover, the simulations confirm that smaller average particle sizes enhance particle flowability, leading to larger extraction zones, as anticipated. Full article

The overtopping-induced lateral erosion breaching of tailings dams represents a critical disaster mechanism threatening structural safety, particularly in reinforced fine-grained tailings dams where erosion behaviors demonstrate pronounced water–soil coupling characteristics and material anisotropy. Through physical model tests and numerical simulations, this study systematically investigates lateral erosion failure patterns of reinforced fine-grained tailings under overtopping flow conditions. Utilizing a self-developed hydraulic initiation test apparatus, with aperture sizes of reinforced geogrids (2–3 mm) and flow rates (4–16 cm/s) as key control variables, the research elucidates the interaction mechanisms of “hydraulic scouring-particle migration-geogrid anti-sliding” during lateral erosion processes. The study revealed that compared to unreinforced specimens, reinforced specimens with varying aperture sizes (2–3 mm) demonstrated systematic reductions in final lateral erosion depths across flow rates (4–16 cm/s): 3.3–5.8 mm (15.6−27.4% reduction), 3.1–7.2 mm (12.8–29.6% reduction), 2.3–11 mm (6.9–32.8% reduction), and 2.5–11.4 mm (6.2–28.2% reduction). Smaller-aperture geogrids (2 mm × 2 mm) significantly enhanced anti-erosion performance through superior particle migration inhibition. Concurrently, a pronounced positive correlation between flow rate and lateral erosion depth was confirmed, where increased flow rates weakened particle erosion resistance and exacerbated lateral erosion severity. The numerical simulation results are in basic agreement with the lateral erosion failure process observed in model tests, revealing the dynamic process of lateral erosion in the overtopping breach of a reinforced tailings dam. These findings provide critical theoretical foundations for optimizing reinforced tailings dam design, construction quality control, and operational maintenance, while offering substantial engineering applications for advancing green mine construction. Full article

In this paper, we address the problem of intelligent operation of Distribution Static Synchronous Compensators (D-STATCOMs) in power distribution systems to reduce energy losses and CO₂ emissions while improving system operating conditions. In addition, we consider the entire set of constraints inherent in the operation of such networks in an environment with D-STATCOMs. To solve such a problem, we used three master–slave methodologies based on sequential programming methods. In the proposed methodologies, the master stage solves the problem of intelligent D-STATCOM operation using the continuous versions of the Monte Carlo (MC) method, the population-based genetic algorithm (PGA), and the Particle Swarm Optimizer (PSO). The slave stage, for its part, evaluates the solutions proposed by the algorithms to determine their impact on the objective functions and constraints representing the problem. This is accomplished by running an Hourly Power Flow (HPF) based on the method of successive approximations. As test scenarios, we employed the 33- and 69-node radial test systems, considering data on power demand and CO₂ emissions reported for the city of Medellín in Colombia (as documented in the literature). Furthermore, a test system was adapted in this work to the demand characteristics of a feeder located in the city of Talca in Chile. This adaptation involved adjusting the conductors and voltage limits to include a test system with variations in power demand due to seasonal changes throughout the year (spring, winter, autumn, and summer). Demand curves were obtained by analyzing data reported by the local network operator, i.e., Compañía General de Electricidad. To assess the robustness and performance of the proposed optimization approach, each scenario was simulated 100 times. The evaluation metrics included average solution quality, standard deviation, and repeatability. Across all scenarios, the PGA consistently outperformed the other methods tested. Specifically, in the 33-node system, the PGA achieved a 24.646% reduction in energy losses and a 0.9109% reduction in CO₂ emissions compared to the base case. In the 69-node system, reductions reached 26.0823% in energy losses and 0.9784% in CO₂ emissions compared to the base case. Notably, in the case of the Talca feeder—particularly during summer, the most demanding season—the PGA yielded the most significant improvements, reducing energy losses by 33.4902% and CO₂ emissions by 1.2805%. Additionally, an uncertainty analysis was conducted to validate the effectiveness and robustness of the proposed optimization methodology under realistic operating variability. A total of 100 randomized demand profiles for both active and reactive power were evaluated. The results demonstrated the scalability and consistent performance of the proposed strategy, confirming its effectiveness under diverse and practical operating conditions. Full article

This study investigates cement–bentonite slurries with hydration accelerators for borehole backfilling applications in infrastructure reconstruction projects. Two formulations with different accelerator dosages (5 and 10 kg/m³) were evaluated through combined experimental testing and Moving Particle Semi-implicit (MPS) numerical modeling to optimize material performance. The research focuses on time-dependent rheological evolution and its impact on construction performance, particularly bleeding resistance and workability retention. Experimental flow tests revealed that both formulations maintained similar initial flowability (240–245 mm spread diameter), but the higher accelerator dosage resulted in 33% flow reduction after 60 min compared to 12% for the lower dosage. Bleeding tests demonstrated significant improvement in phase stability, with bleeding rates reduced from 2.5% to 1.5% when accelerator content was doubled. The MPS framework successfully reproduced experimental behavior with prediction accuracies within 3%, enabling quantitative analysis of time-dependent rheological parameters through inverse analysis. The study revealed that yield stress evolution governs both flow characteristics and bleeding resistance, with increases several hundred percent over 60 min while plastic viscosity remained relatively constant. Critically, simulations incorporating time-dependent viscosity changes accurately predicted bleeding behavior, while constant-viscosity models overestimated bleeding rates by 60–130%. The higher accelerator formulation (10 kg/m³) provided an optimal balance between initial workability and long-term stability for typical borehole backfilling operations. This integrated experimental–numerical approach provides practical insights for material optimization in infrastructure reconstruction projects, particularly relevant for aging infrastructure requiring proper foundation treatment. The methodology offers construction practitioners a robust framework for material selection and performance prediction in borehole backfilling applications, contributing to improved construction quality and reduced project risks. Full article

Linear die filling is currently widely employed in industries. However, there is no comprehensive and systematic model to describe the powder die filling process. This paper utilizes dimensional analysis to extract and analyze various factors that affect the flow characteristics of powder based on DEM-CFD simulations. Several dimensionless parameters including the ratio of particle size to die depth ($d_p{h}_D^{-1}$), solid density number (${\rho }_p{\rho }_g^{-1}$), shoe speed number ($v{\rho }_g{L}_D{\mu }^{-1}$), and force number ($G_p{F}_{Drag}^{-1}$) were proposed based on the Pi theorem. The results showed that the filling ratio δ increased with the increase in $d_p{h}_D^{-1}$ and ${\rho }_p{\rho }_g^{-1}$ due to $G_p{F}_{Drag}^{-1}$ rising. But it decreased with the increase in $v{\rho }_g{L}_D{\mu }^{-1}$ due to the shortening of effective filling time. Finally, a semi-empirical modeling of linear die filling was developed, taking the critical value ${(d_p{h}_D^{-1})}_{90}$ as the dependent variable and the solid density number (${\rho }_p{\rho }_g^{-1}$) and shoe speed number ($v{\rho }_g{L}_D{\mu }^{-1}$) as independent variables. Hence, this model provides a new approach to computing the smallest shoe speed and designing the sizes of dies based on measurable material properties under complete die filling. Full article