Search Results (4,315)

The escalating intensity and depth of coal mining operations have exacerbated underground strata pressure, resulting in fracture-induced air leakage channels that heighten risks of coal spontaneous combustion and gas explosions. These challenges necessitate enhanced flexibility and strength in cementitious materials used for roadway support. This study investigated the mechanical properties of fiber-reinforced polymer concrete (FRPC) for mining applications through response surface methodology (RSM) using Design Expert software. Three critical factors: styrene–acrylic emulsion content (5–15 wt.%), polypropylene fiber length (9–15 mm), and fiber content (0.7–1.1 kg/m³), were systematically investigated to establish factor-performance correlations via 3D response surfaces. This study experimentally investigated the effects of styrene–acrylic emulsion content, polypropylene fiber length, and fiber content on the mechanical properties of fiber-reinforced polymer concrete for mining roadway support. Response surface methodology was used as an empirical statistical tool to describe the response trends and factor interactions within the selected experimental range. The regression models developed in this study should therefore be interpreted as local empirical models rather than mechanics-based predictive equations. Using the flexural-to-compressive strength ratio as an index, the optimal formulation of FRPC was 10% emulsion, 12 mm fibers, and 1.1 kg/m³ fiber content. Microstructural characterization indicated that polypropylene fibers effectively inhibited crack propagation through bridging effects, while styrene–acrylic emulsion formed continuous film-like network structures on cement surfaces. Synergistically, both components enhanced matrix densification, achieving concurrent improvements in flexibility and strength. Field applications demonstrated that FRPC significantly reduced air leakage channels, decreased the risk of coal spontaneous combustion, and improved the safety of coal mine production. Full article

Background/Objectives: Spirometry is essential for objective asthma assessment in children with sickle cell disease (SCD), but technically uninterpretable examinations may reduce the effectiveness of systematic screening. This study aimed to determine their frequency and identify associated demographic, clinical, social, disease-related, and center-level factors in French Guiana. Methods: We conducted a prospective multicenter observational study involving children and adolescents with confirmed SCD who underwent systematic asthma screening at Cayenne, Kourou, and Saint-Laurent-du-Maroni hospitals between January 2025 and May 2026. Spirometry technical quality was assessed according to the 2019 American Thoracic Society/European Respiratory Society technical standards and classified as interpretable or technically uninterpretable according to the acceptability, usability, and repeatability of the recorded maneuvers. Across the three sites, spirometry was performed on the recorded MicroLab platform using GLI-2012 reference equations. Salbutamol was delivered by pressurized metered-dose inhaler with a valved holding chamber when bronchodilator testing was technically feasible; the exact device submodel/manufacturer metadata, center-specific software versions, and administered salbutamol dose were not retained in the exported analytical dataset. Participant characteristics were compared between groups, and associated factors were examined using univariable and multivariable logistic regression. Results: After removal of duplicate records, 143 unique children were included. Spirometry was technically uninterpretable in 34 participants (23.8%). Children with uninterpretable examinations were significantly younger than those with interpretable spirometry (8.9 ± 3.0 vs. 10.5 ± 4.0 years; p = 0.015). In univariable analysis, each additional year of age was associated with a 12% reduction in the odds of uninterpretable spirometry (OR 0.88, 95% CI 0.78–0.99; p = 0.036). After adjustment for sex, recruitment center, and health-insurance status, the inverse association persisted in direction and magnitude but did not reach conventional statistical significance (adjusted OR 0.89, 95% CI 0.79–1.01; p = 0.075). Given the limited number of outcome events, this attenuation may reflect reduced statistical power. No other investigated factor was independently associated with non-interpretability. Conclusions: Nearly one-quarter of children had technically uninterpretable spirometry. Younger children may benefit from enhanced preparation, age-adapted coaching, experienced operators, and planned repeat testing to improve asthma-screening yield and reduce missed respiratory disease. Full article

Carbon dioxide-enhanced oil recovery (CO₂-EOR) in ultra-low-permeability reservoirs requires a reliable understanding of CO₂–oil phase behavior and minimum miscibility pressure (MMP), particularly where multiple stratigraphic members are co-developed. In this study, recovered live-oil samples from the Chang 4 + 5-producing Well 272 and the Chang 6-producing Well 651 of the Yanchang Formation in the Ordos Basin were compared using compositional analysis, conventional PVT tests, CO₂-swelling experiments, slim-tube displacement tests, and Peng–Robinson equation-of-state (PR-EOS) characterization. The PR-EOS model used pseudo-component characterization, grouped binary interaction parameters and CO₂-swelling saturation-pressure constraints to support the interpretation of EOS-predicted phase behavior and the evaluation of internal consistency. The two recovered samples have similar measured bubble-point pressures and dead-oil densities, whereas the Well 651 sample has a lower live-oil viscosity and a slightly higher C₂–C₁₂ hydrocarbon fraction. Slim-tube tests gave approximate MMPs of 17.8 MPa for the Well 272 sample at 59.94 °C and 16.1 MPa for the Well 651 sample at 69.30 °C. Because the samples were tested at their respective reservoir temperatures, temperature and composition varied simultaneously and their independent contributions cannot be separated using the present dataset. Accordingly, the comparison is limited to the two sampled well-fluid systems under the documented sampling and test conditions; the results should not be generalized to interval-wide Chang 4 + 5 or Chang 6 fluid properties without additional representative sampling. Full article

In situ nondestructive continuous monitoring of plant water status coupled with online data analysis is a core technical prerequisite for developing intelligent irrigation decision-making systems. The LPCP (leaf patch clamp pressure probe, ZIM-probe) sensor can detect leaf turgor pressure and shows promising application prospects. In this paper, the LPCP was used to monitor the leaf turgor pressure of maize during the silky growth stage cultivated in the North China Plain. The experiment was arranged in a randomized block design with two treatments: full irrigation (CK) and natural drought (ND). The results showed that the probe output pressure (P_p) underwent three stages: P_{p min} increasing stage, P_{p max} early-occurring stage, and P_p curve inversion stage, along with soil water decreasing, which correspond to mild, moderate, and severe water stress, respectively, and the ranges of soil and leaf water content of each stage were identified. As water stress intensified, the peak times of transpiration rate and stomatal conductance occurred earlier than normal, and the values decreased; meanwhile, the relationships between P_p, sap flow (SF), and leaf physiology indicators were quadratic parabolic, but the parabola opening directions, determination coefficients of regression equations, and model significance differed under different water stress stages. Under mild and moderate water stress, P_p positively correlated with SF, vapor pressure deficit (VPD), photosynthetically active radiation (PAR), and air temperature (T), while negatively correlated with relative humidity (RH), and path analysis results revealed that PAR and T exerted direct effects on P_p variations, whereas SF and VPD influenced P_p indirectly through other variables, and RH exhibited a negative effect on P_p changes. However, these correlations reversed under severe water stress. A regression model including PAR, T and VPD was established to simulate the P_p values of maize under full irrigation conditions, and by comparing the variation trend of P_p curves between the predicted and the measured values, whether maize was under water stress could be determined. Full article

Compression packers are widely used in oil and gas well operations for zonal isolation, yet the large-deformation mechanical behavior of their rubber sealing elements lacks a closed-form analytical solution. This paper presents a complete theoretical analysis of the axisymmetric compression of an annular rubber cylinder based on the incompressible Mooney–Rivlin hyper-elastic model. The deformation process is divided into three successive stages: free expansion, casing-constrained deformation, and fully constrained deformation. Analytical expressions for the principal stretches, stress fields, and axial force are derived for each stage by integrating the radial equilibrium equation with proper treatment of the Lagrange multiplier. The frictionless analytical results are validated against axisymmetric finite element simulations, showing excellent agreement for all stress components. The applicability of the frictionless theory to frictional conditions is then examined. Results show that although friction introduces non-uniform axial deformation and end bulging, the average contact pressure on the rubber–mandrel interface agrees closely with the theoretical prediction, especially at higher axial forces (150–250 kN). A linear relationship between the average contact pressure and the axial force is confirmed, providing a simple design tool. The theoretical solution offers a computationally efficient alternative to finite element analysis for preliminary packer design and parametric studies. Full article

Accurate hemodynamic assessment is essential for characterizing vascular function and pathology. While computational fluid dynamics (CFD) provides the means to simulate blood flow, each anatomical variation requires its own dedicated simulation, which in turn demands substantial computational resources and domain expertise. Accelerating blood flow simulations to enable real-time or near real-time predictions could significantly enhance clinical decision-making and personalized treatment planning. We evaluated single and multi-case physics-informed neural networks (PINNs) in predicting steady-state blood flow in parameterized two-dimensional (2D) stenotic vascular geometries. The PINN was trained without the use of labeled data, utilizing the parameterized incompressible steady state continuity and Navier–Stokes equations. The degree of stenosis was set to vary from 20% to 60% and the Reynolds number ($Re$) from 500 to 1750. To measure the accuracy, CFD ground truth data were generated using COMSOL Multiphysics^® version 6.4. Results show that PINNs accurately predict both axial and vertical velocity fields, with low global and localized errors. Pressure predictions were generally insufficient, particularly in mild to moderate stenoses at low $Re$, with the median throat-pressure error reaching 38.8%. Pressure is anchored by a single outlet condition, and its non-dimensional scale varies by a factor of 142 across cases, so a few dominate the training objective; hard boundary-condition enforcement improved the field but not the pressure drop. These findings highlight that while current PINNs can reliably reproduce velocity fields, their ability to capture localized pressure dynamics remains limited, indicating the need for more robust formulations. Full article

To shorten the gas control period in low-permeability coal seams, the effectiveness of microbial gas dissolution technology for gas control was investigated through a combination of field tests and numerical simulations. First, three groups of injection boreholes were constructed, and the microbial gas-dissolving solution was injected into the coal seam, followed by an evaluation of the treatment effect after three days. Furthermore, based on a multiphysics-coupled modeling framework, the conventional borehole drainage process was simulated using the Partial Differential Equation (PDE) module of COMSOL Multiphysics to compare the evolution of coal seam gas pressure under conventional drainage with the field performance of the gas dissolution treatment. The results showed that the injected bioactive solution promoted methane oxidation and rapidly reduced the gas content and pressure in the treated region. After 3 days of gas dissolution treatment, the average gas content and gas pressure within the overlapping influence zones between the injection borehole groups decreased by 38.0% and 80.7%, respectively, relative to their initial values. However, the treatment effect gradually weakened with increasing distance from the injection zone, indicating spatial attenuation of the effective influence of the bioactive solution in the low-permeability coal seam. Comparatively, conventional drainage required approximately 68 days to reduce the gas pressure to the same level achieved by the gas dissolution treatment within 3 days, demonstrating that gas dissolution technology can drastically accelerate the gas control cycle. Nevertheless, further large-scale application requires consideration of economic feasibility and continued optimization of injection parameters and field implementation procedures. Full article

The widespread adoption of unmanned agricultural machinery has transformed modern agricultural production. In unstructured farmland scenarios, variations in soil conditions and operational loads induce large perturbations to system dynamic parameters, leading to degraded tracking accuracy and insufficient robustness in fixed-parameter path tracking controllers. Additionally, conventional single-structure observers cannot simultaneously achieve fast convergence and smooth steady-state output. This study constructs a mixed preview error state-space equation, which aggregates parameter perturbations, unmodeled dynamics, and external disturbances into a unified lumped disturbance term of the system. A composite observer architecture is designed by parallelly combining an adaptive generalized super-twisting observer and a nonlinear extended state observer, where observation weights are continuously and smoothly scheduled via online identification of field operation conditions. Furthermore, a gain-power dual-adaptive super-twisting sliding mode control strategy is proposed, and the closed-loop stability of the system is rigorously proven. Co-simulation and field experiments covering powered rotary tillage, high-speed unloaded transfer, and variable tire pressure conditions verify that, under parameter perturbation, the increase in tracking error remains within 10%. Compared with the conventional PID controller used as a benchmark, the proposed controller reduces the root mean square error (RMSE) of lateral deviation by 40–50%, and maintains centimeter-level tracking accuracy in field operations. The proposed method provides technical support for high-precision operation of agricultural machinery in unstructured farmland environments. Full article

Substation-level carbon-emission factors (CEFs) are operationally relevant because substations concentrate transformer losses, auxiliary consumption, and sulfur hexafluoride (SF6) leakage at the interface between transmission and distribution. However, static or annual emission-factor methods average over heterogeneous operating regimes and cannot capture the pronounced non-stationarity of substation CEFs driven by seasonal loads, stochastic maintenance events, cooling-system switching, and extreme weather. To support high-frequency dynamic carbon tracing, dispatch optimization, and audit compliance, this study proposes a physics-guided fusion framework integrating a temporal foundation model, MOIRAI-2, with a Uniform Physics-Informed Neural Network (UPINN). A 15-dimensional physically constrained feature vector is constructed from IEEE C57.91 thermal-circuit equations and ideal-gas state equations, including transformer top-oil/hot-spot temperature, SF6 pressure/density estimation, and oil-forced/air-forced (OFAF) or oil-directed/water-forced (ODWF) cooling status. MOIRAI-2 uses Any-Variate Attention with binary attention bias to model intra-variate temporal dependencies and cross-variate physical couplings, whereas UPINN embeds thermal-balance, SF6 leakage-kinetics, and CEF conservation residuals as soft constraints. An adaptive gating network balances data-driven pattern recognition and physics-driven smoothness across steady-state, extreme-event, and maintenance regimes. Validation on a 220 kV substation dataset achieves a mean absolute error (MAE) of 0.352 gCO₂e/kWh, outperforming random forest (RF), gradient boosting machine (GBM), long short-term memory (LSTM), and a Pure Transformer by 24.0%, 19.1%, 23.0%, and 14.4%, respectively. Ablation studies show that the 15-dimensional physical-feature expansion improves accuracy by 8.8%, whereas physics-loss regularization reduces prediction variance by 37%. UPINN decomposition further indicates that transformer total loss, ambient temperature, and load factor dominate CEF dynamics, and rainfall cooling reduces CEF by 0.04 gCO₂e/kWh per 20 mm increment. The framework provides a physically consistent and intrinsically interpretable basis for dynamic substation carbon accounting and low-carbon operation. Full article

To address the inherent limitations of traditional resonant underwater sound sources—specifically their excessive size and the sharp decline in sound pressure level (SPL) at frequencies below resonance—a blade-type extremely low frequency (<30 Hz) underwater sound source system was developed. The structure of the system and the principles of its coupled rotational and oscillatory motions are elucidated. The kinematic equations of the blade oscillation driven by a combined crank-connecting rod-slider-connecting rod-rocker mechanism are established, and the effects of the impeller rotational speed and the blade oscillation speed on the SPL are analytically evaluated. The prototype was tested in both air and underwater environments. The experimental results show that the blade-type sound source can emit acoustic waves of extremely low frequency ranging from 2 Hz to 7 Hz, with the fundamental frequency of the acoustic waves perfectly aligned with the blade oscillation frequency. Increasing rotational speed more strongly affects the SPL of harmonics, while changing the oscillation frequency has a greater effect on the fundamental. Notably, a steady increase in the SPL in this paper is maintained even when the oscillation-to-rotation frequency ratio exceeds 2, while the existing blade sound source gradually decreases when the ratio exceeds 1/2. With blade dimensions as small as 13 cm in length and 9 cm in width, the SPL at 10 Hz reaches 131.77 dB (re 1 μPa), highlighting its potential for high-performance acoustic radiation applications at an extremely low frequency. Full article

Sustainable growth has become an increasingly important strategic objective for entrepreneurial firms facing resource constraints, technological change, and growing environmental and social pressures. Although previous studies have established a positive relationship between entrepreneurial orientation and firm performance, relatively limited attention has been paid to the economic resource allocation perspective through which entrepreneurial orientation contributes to sustainable growth. In particular, the role of efficient resource allocation as a mediating mechanism remains insufficiently examined. Therefore, this study investigates the relationship between entrepreneurial orientation and sustainable growth and examines whether resource allocation efficiency mediates this relationship. Entrepreneurial orientation is conceptualized in terms of innovativeness, proactiveness, and risk-taking, while resource allocation efficiency reflects the effective allocation and utilization of financial, human, and operational resources. Sustainable growth is considered from an integrated perspective encompassing economic, environmental, and social dimensions. A quantitative cross-sectional survey was conducted among startups and small and medium-sized enterprises (SMEs) in South Korea using purposive sampling. Data were collected from 1 June to 30 June 2026. A total of 375 questionnaires were distributed, of which 360 were returned. After excluding 10 questionnaires that did not meet the predefined data-quality criteria, 350 valid responses were retained for the final analysis. The response rate was 96.00%, and the valid response rate based on the distributed questionnaires was 93.33%. Structural equation modeling and bootstrap-based mediation analysis were employed to examine the proposed relationships among Entrepreneurial Orientation, Resource Allocation Efficiency, and Sustainable Growth. The measurement model was assessed through confirmatory factor analysis, composite reliability, convergent validity, and discriminant validity using the Fornell–Larcker criterion and heterotrait–monotrait ratio. Structural equation modeling was subsequently employed to test the hypothesized relationships, and the mediating effect was examined using bootstrapping procedures. The results indicate that entrepreneurial orientation has a significant positive effect on resource allocation efficiency and that resource allocation efficiency has a significant positive effect on sustainable growth. Entrepreneurial orientation also has a significant direct positive effect on sustainable growth. Furthermore, resource allocation efficiency significantly mediates the relationship between entrepreneurial orientation and sustainable growth, indicating a partial mediation effect. These findings suggest that entrepreneurial orientation contributes to sustainable growth not only by encouraging innovation, proactive market behavior, and calculated risk-taking, but also by improving how scarce organizational resources are selected, prioritized, and allocated. This study contributes to the entrepreneurship and sustainability literature by integrating an economic resource allocation perspective into the relationship between entrepreneurial orientation and sustainable growth. The findings suggest that entrepreneurial orientation should not be considered solely as a strategic posture for opportunity exploration; rather, its contribution to sustainability depends partly on the firm’s ability to allocate scarce resources efficiently. The study also provides practical implications for entrepreneurs, SME managers, and policymakers seeking to enhance sustainable growth through entrepreneurial activities and efficient resource utilization. Full article

The adoption of advanced three-dimensional Computational Fluid Dynamics (CFD) tools for the research and design of Rolling-Piston Compressors (RPCs) is severely constrained by the absence of efficient and reliable grid generation methods. To address this issue, this paper proposes a novel analytical grid generation method for the rotor fluid domain of RPCs based on the User-Defined Nodal Displacement (UDND). This method splits the rotor fluid domain into a vane region, a transition region and a core region according to geometric characteristics. The number of circumferential nodes in each region is adaptively determined based on the mapped lengths of the corresponding inner and outer boundaries, while node number normalization is employed to ensure precise control of the total number of nodes. Numerical tests demonstrate that the proposed method can generate O-type structured meshes with consistent topology and adaptive node allocation over the entire range of rotor rotation angles. The proposed method was verified by reference indicated pressure measurements on a small-scale RPC for refrigeration and air-conditioning applications, yielding mean absolute percentage errors of 6.30% and 7.42% and maximum pointwise relative errors of 12.70% and 20.99% at 80 and 120 Hz, respectively. The proposed method reduces the preprocessing time required for a typical CFD model of the machine from approximately 48 h to only 54 s. The improved quality and robustness of the generated mesh enhance the stability and convergence behavior of the solver, thereby enabling the use of advanced physical models, such as the real-gas equation of state, in the design and analysis of RPCs. This paper presents a rapid and reliable meshing strategy for CFD simulations of RPCs. Full article

The wave train generated by a moving vessel remains a persistent challenge in ship hydrodynamics, particularly in stratified oceans where internal waves contribute significantly to drag. This research investigates steady interfacial wave generation by flow past a semi-infinite curved plate in a two-layer fluid where both layers are of finite depth. Previous studies were limited by flat-plate geometries and infinite-depth approximations, neglecting the critical role of applied pressure as a design variable. We address these limitations to facilitate the engineering goal of wave drag reduction through optimal hull and pressure configurations. Using a scalar Wiener–Hopf formulation, we construct an analytical solution where the kernel is factorized via Cauchy-type integrals, bypassing the technical constraints of traditional infinite-product expansions. We derive a closed-form far-field amplitude and a wave-free condition, $M\left(\mu \right)=0$. This condition is a single complex equation, i.e., two independent real constraints. A one-parameter hull design can therefore generally only minimise the downstream wave amplitude; exact cancellation at linear order generally requires a second, independent real design freedom, such as a jointly optimised applied pressure. We quantify both regimes explicitly. Our findings demonstrate that physical stern flow patterns exhibit spatial relaxation and advection scales essential for energy transfer. This result provides a mathematically sharp framework for wave drag minimisation, quantifying the explicit performance trade-off between hull curvature and dynamic pressure control in stratified environments, and we are careful throughout to distinguish the formal linear theory cancellation from what is achievable with a single physically realisable (real-valued) design parameter. Full article

Spacer wires are widely employed in lead-cooled fast reactor fuel assemblies to maintain rod positioning. The helical spacer structure induces rotational flow and enhances transverse mixing between subchannels, thereby significantly influencing thermo-hydraulic performance. To further regulate coolant mixing intensity and reconstruct internal flow structures, a double-wire configuration with variable radial phase differences is proposed. Three-dimensional steady RANS simulations of liquid lead–bismuth flow in a 19-pin double-wire fuel assembly are conducted using a four-equation turbulent heat transfer model. Results indicate that pressure and velocity fields exhibit periodic distributions along the helical direction, with a clear inverse correlation between high-pressure and high-velocity regions. Transverse secondary flow intensity shows pronounced axial periodicity and attains a maximum value of 0.32, with stronger mixing observed in the vicinity of the spacer wires. Peripheral and corner subchannels maintain lower average coolant temperatures, whereas peak temperatures are concentrated within internal subchannels. The overall convective heat transfer coefficient decreases gradually along the axial direction and presents a localized enhancement in the mid-axial region. The axially averaged convective heat transfer coefficient of DP60 is approximately 4.58% higher than that of DP90. This difference is a thermal comparison and does not establish overall thermo-hydraulic superiority. Peak modeled coolant temperature fluctuations are observed at the interface between peripheral and outer internal subchannels, while maximum turbulent Prandtl numbers are concentrated within internal subchannels. Full article

The development of oil and gas resources in global petroliferous basins has extended from shallow to deep reservoirs. Dew point pressure (Pd) is a vital parameter for fluid characterization and field development. Accurately and quickly obtaining Pd is crucial for the development of ultra-deep condensate gas reservoirs. The objective of this work is to predict the Pd of condensate gas by an artificial neural network (ANN) model. Ten ultra-deep condensate gas samples were analyzed using an experimental method and the Pd at reservoir temperature was obtained. A total of 113 datasets including 103 collected datasets and 10 measured datasets were adopted for ANN model training and testing. The results show that the average absolute percent relative error (AAPRE) of the developed ANN model between the measured and predicted values on the test set was 4.9589%. The predicted accuracy between the ANN model and widely used equations of state was compared. The results of statistical and graphical analysis show that the ANN model achieves the minimum prediction error. This ANN model can provide the necessary guidance for predicting the Pd for the development of different kinds of reservoirs. Full article