Search Results (552)

Fractured coal in the residual-strength stage is a primary medium for gas migration and drainage in deep mining areas. To investigate the hydro–mechanical seepage response of post-peak fractured coal under constant-pressure-difference conditions, triaxial CO₂ seepage tests were conducted on coal specimens collected from the Xinyuan Coal Mine. A Weibull-based damage constitutive model was established to characterize the confining-pressure-induced hysteresis in the damage-evolution path. The flow-rate evolution and Reynolds number analysis indicated that gas flow remained within the linear Darcy regime. A controlled-variable analysis was used to examine the competing effects governing permeability evolution. Mechanical compaction induced an exponential decrease in permeability, whereas the decrease in permeability with increasing pore pressure was interpreted, within the proposed model framework, as the combined effect of possible adsorption-induced matrix swelling and weakened gas slippage. To address the limitations of conventional constant-slip-factor models, a pressure-dependent slip modulation coefficient was introduced into a composite permeability equation incorporating effective stress, adsorption-related deformation, and dynamic gas slippage. Global nonlinear fitting yielded R² = 0.97 and an RMSE of 0.1909, with the residuals generally distributed around zero, supporting the fitting reliability of the model within the investigated stress–pressure range. Response-surface analysis identified mechanical compaction as the dominant controlling mechanism, while adsorption-related deformation and gas slippage acted as secondary correction mechanisms. The proposed framework provides a quantitative basis for distinguishing the mechanical and fluid-related effects governing permeability evolution in post-peak fractured coal. Full article

With global warming continuously worsening drought hazards, the Fuhe River Basin urgently requires insight into drought evolution laws to support resilient water resources management. However, traditional univariate indices such as the Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) are limited by their inability to capture the coupled meteorological-agricultural drought process and the time-lag effects between precipitation and soil moisture response. Therefore, a multivariate drought index—which integrates both precipitation and soil moisture information—is needed as a core tool for drought early warning and precise regulation. In this study, the calibrated SWAT model was used to simulate monthly soil moisture content in the Fuhe River Basin over the past 60 years. On a 3-month time scale, a Multivariate Standardized Drought Index (MSDI) was established by coupling the Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) using the Copula function. The main findings are as follows: (1) The Nash–Sutcliffe efficiency coefficient (NS) of the SWAT (Soil and Water Assessment Tool) model during the validation period reached above 0.70, indicating favorable performance in monthly runoff simulation. (2) The MSDI revealed frequent drought events in two periods, namely 1960–1979 and 2000–2019, demonstrating the periodic fluctuation pattern of droughts in the basin. (3) Wavelet analysis showed that compared with the previous two periods, the frequency of droughts in the basin increased significantly after 2000, with weakened periodic characteristics, intensified extreme drought events, and a further rise in drought risks. This study deepens the understanding of drought dynamics in the Fuhe River Basin and provides a scientific basis for regional sustainable water resource management and the formulation of climate adaptation strategies. Full article

Agricultural supply chains operating under rural infrastructure constraints face persistent logistical inefficiencies that reduce producer income and weaken territorial sustainability. This paper assesses how collaborative and coordinated distribution architectures reshape economic performance, efficiency, and equity in dispersed networks of cocoa producers in El Carmen de Bolívar, Colombia. The unified optimization framework compares three regimes: decentralized non-collaborative individual shipments, collaborative consolidation based on distribution centers, and coordinated distribution with time-window synchronization. The findings show a reduction in average logistics costs from $0.688/kg in decentralized distribution to $0.323/kg with collaborative distribution centers, and even further to $0.282/kg in coordinated distribution, representing an overall reduction of approximately 59%. A sensitivity analysis across 64 accessibility configurations shows that the advantage of coordination increases as time rigidity increases. These structural improvements translate into a 13.97% increase in total producer utility, raising average utility from $278 to $317 per producer. In addition, the distributional assessment based on Lorenz curves and Gini coefficients indicates that inequality remains stable despite gains in welfare. These results demonstrate that spatial consolidation combined with temporal synchronization is a decisive lever for resilient and inclusive rural supply systems. Full article

The continuous rise in turbine inlet temperatures to maximize engine efficiency makes highly integrated composite cooling schemes essential, but their intricate thermal interactions pose formidable challenges for parameter optimization. In this study, an impingement–pin-fin–film configuration is extracted as a representative composite cooling unit from a double-wall blade and subjected to 3D steady-state RANS simulations under realistic engine conditions. The numerical results are then used to construct quadratic polynomial response surface surrogate models for multi-objective optimization. It is revealed that the blowing ratio dictates overall thermal performance primarily through internal cooling, and excessively high ratios weaken the film coverage. Geometrically, insufficient control over the spanwise ratio disrupts film coverage and breaks the continuity of internal cooling, thereby degrading both cooling effectiveness and structural thermal compatibility. Additionally, a critical region is located upstream of the film hole exit; the combination of an extremely thin solid wall and high heat transfer coefficients creates a localized over-cooled zone, severely constraining temperature uniformity. Ultimately, the optimization framework clarifies the coupled flow and heat transfer behaviors of the double-wall unit. It simultaneously maximizes area-averaged overall cooling effectiveness and temperature uniformity while minimizing coolant mass flow, revealing the key mechanism behind induced thermal stress concentrations. Full article

This study investigates the synergistic regulation mechanism of water–heat–salt transport in the black soil of cold regions in Northeast China by combining field monitoring with HYDRUS-2D simulations. Four tillage treatments were evaluated: control group (CK), no-tillage with flat straw mulching (NM), ridge tillage with flat straw mulching (RM), and straw return with rotary tillage (RR). Monitoring data indicated that all straw incorporation treatments significantly improved soil moisture retention capacity. Compared with CK, soil water content under RM increased by 63.93% correspondingly; soil salinity in CK was 5.75–13.68% higher than that in straw-amended treatments. In addition, RM exerted a more prominent regulatory effect on soil temperature fluctuations relative to CK. Simulation results reveal that straw incorporation effectively reduces surface runoff, thereby substantially weakening the driving force for upward salt migration. Structural equation modeling (SEM) quantified path coefficients, revealing that straw incorporation optimizes the soil microenvironment. This integrated approach provides a mechanistic basis for black soil conservation in seasonally frozen regions, identifying RM as the optimal management practice to balance water retention and salt inhibition. Full article

Aiming at the characteristics of high viscosity and poor fluidity of high waxy ordinary heavy oil, a Janus silica-based nanosheet composite viscosity reducer was designed and prepared in this paper. The viscosity reducer was assembled by asymmetric Gemini viscosity reducer and silica nanosheets through dehydration condensation reaction, and its structure was verified by FT-IR, ¹HNMR, XPS and DLS. The viscosity reduction performance, emulsion stability, interfacial tension and flow performance of the viscosity reducer were systematically evaluated by taking heavy oil with wax content of 35.7% and viscosity of 237 mPa·s at 30 °C as the research object. The results showed that, at an oil-to-viscosity-reducer-solution volume ratio of 3:7 and a viscosity reducer mass fraction of 0.3%, the maximum viscosity reduction rate reached 94.5% at 30 °C, calculated relative to the viscosity of the dehydrated original heavy oil. The oil–water interfacial tension was significantly reduced, and the 24 h bleeding ratio, defined as the volume percentage of separated water relative to the initial aqueous phase volume, was only 7.3%, indicating good emulsion stability. The core flow experiment shows that the resistance coefficient is reduced to the lowest at 0.3% concentration, and the seepage capacity is significantly improved. The analysis of total hydrocarbon gas chromatography showed that the content of high-carbon wax components in the C₂₃-C₃₀ range decreased by 4.79 percentage points after treatment, indicating that the viscosity reducer preferentially interacted with high-carbon wax molecules and promoted wax-crystal dispersion, thereby weakening the three-dimensional wax-crystal network. The viscosity reducer has the synergistic effect of dispersing wax crystals, reducing interfacial tension and stabilizing emulsification, which provides a low-cost and high-performance technical approach for the efficient exploitation of high waxy ordinary heavy oil. Full article

We prove a complete moment convergence criterion for weighted maximal partial sums of extended negatively dependent (END) random variables under slowly varying weights. For every $r>1$, and for triangular weight arrays that are uniformly bounded, quadratically non-degenerate, and uniformly non-degenerate on their active coefficients, we show that the summability of $n^{r-1}l\left(n\right)E\left[{(S_n^{*}/n-\epsilon )}_{+}\right]$ for all $\epsilon >0$ is equivalent to the weighted moment condition ${E\left[\right|X|}^{r+1}l\left(\right|X\left|\right)]<\infty$. The slowly varying factor l gives a refined borderline scale: it weakens the pure $(r+1)$-moment condition when $l\left(t\right)\to 0$, strengthens it when $l\left(t\right)\to \infty$, and recovers the classical scale when l is bounded away from zero and infinity. The proof uses weight-dependent monotone clipping, a Rosenthal-type maximal inequality for END sequences, Potter bounds and Karamata-type estimates for slowly varying functions, and a Bonferroni lower-bound argument based on a linear set of significant coefficients. Particular attention is paid to the preservation of the END structure under clipping, centering, and signed weights. Several corollaries and borderline heavy-tail examples are included, and possible modeling interpretations are briefly discussed without claiming finite-sample risk bounds beyond the theorem. Full article

This study examines the moderating effect of firm attributes on the value relevance of accounting information in Saudi Arabia. Using a sample of 630 firm-year observations from 126 Saudi listed firms over 2018–2022, the research evaluates whether audit quality, size, leverage, growth potential, board diversity, and profitability complement the valuation role of earnings per share (EPS) and book value per share (BVPS) and if so then which direction of the attribute gave greater value relevance. Results reveal that all the firm attributes tested have a significant moderating effect on value relevance. Lower leverage, higher growth potential, greater board diversity, and profitability all lead to higher predicted market value for given EPS and BVPS. Big 4 audit quality and larger firm size are found to moderate the value relevance of accounting information rather than to influence share price directly. Both attributes strengthen the value relevance of earnings per share (EPS)—the EPS coefficient is significantly higher for firms audited by a Big 4 firm and for larger firms—while weakening the value relevance of book value per share (BVPS), with the BVPS coefficient being significantly lower in both cases. The combined effect is that earnings carry greater pricing weight, and book values carry lesser pricing weight, when audit quality is high and when firms are larger. Results also reveal that cohorts with Big 4 auditor, larger size, lower leverage, higher growth potential, more diverse boards, and profitability all have greater value relevance (higher R²) than cohorts with the alternative for each attribute. Hence, tests provide evidence that these attributes strengthen the association between selective accounting figures (EPS and BVPS) and share prices. The findings contribute to agency, information asymmetry, and value-relevance theory by showing that firm attributes condition the EPS and BVPS pricing weights rather than affecting price directly. The results have implications for regulators and firms seeking to improve financial reporting credibility and usefulness amid concentrated ownership. This study contributes timely empirical evidence on the multifaceted drivers of value relevance in an under-researched Middle Eastern emerging market. Full article

A 660 MW coal-fired unit was investigated to clarify the combustion behavior over a wide load range and the effects of static mixers on selective catalytic reduction (SCR) performance. A full-process CFD model covering the furnace, rear pass duct, and SCR system was established, and the combustion characteristics, NO_x formation, and SCR performance were analyzed over a boiler load range of 25–100%. The results showed that, as the boiler load decreased, the furnace heat release weakened, the high-temperature zone contracted, and the flame center shifted downward, with more pronounced flame maldistribution at 25% load. The average NO_x concentration at the SCR inlet first decreased and then increased with decreasing boiler load, reaching a minimum at 75% load. Without a static mixer, the NO_x concentration at the SCR inlet increased from 238 mg/Nm³ at 100% load to 312 mg/Nm³ at 25% load. After a static mixer was installed, the distance required for NH₃ homogenization downstream of the ammonia injection grid was markedly shortened, and the uniformity of the velocity, NH₃ concentration, and temperature fields at the SCR catalyst inlet was improved. In particular, the coefficient of variation in NH₃ concentration decreased from about 4–5% to about 2–3%, while the denitrification efficiency increased by about 1–5 percentage points compared with the case without a static mixer. The variation in denitrification efficiency among different boiler loads was also significantly reduced, indicating improved adaptability of the SCR system to wide-load operation. Among the tested configurations, the static mixer with small blades and a larger blade angle relative to the vertical plane showed the best overall performance. These results provide useful guidance for SCR system improvement in coal-fired units operating over a wide load range. Full article

While artificial intelligence (AI) can improve energy efficiency in carbon neutrality applications, its high energy consumption and rebound effect weaken the actual emission reduction effect. To address the issues of high energy consumption and the rebound effect of AI weakening emission reduction, this paper proposes a green AI-driven environmental economic computing framework. First, an energy consumption perception index is introduced, and carbon emissions are monitored in real time using Carbontracker version 2.4.2. Second, multi-task learning is used to predict energy demand and emissions based on multi-source data. Third, the rebound effect is quantified and corrected using an elasticity coefficient model. Finally, resource allocation is optimized under environmental constraints through reinforcement learning, and a closed-loop feedback mechanism is constructed. Experimental results show that the carbon emissions from GPT-3 training are as high as 590 kgCO₂, while the emissions from YOLOv5 are only 59 kgCO₂. Dynamic batch processing improves energy efficiency by 45%, and the knowledge distillation rebound index is 0.75, but the net energy-saving rate is only 9.1%. The information technology industry achieved a synergy index of 0.88 through AI optimization, but the response time of dedicated hardware is 1.5 s (three times faster than the cloud), indicating that large-scale models have high energy consumption and need optimization to prevent rebound. Real-time feedback and hardware scheduling are key to achieving carbon neutrality. Full article

Weak-bus identification is a key task for online security assessment, preventive control, maintenance verification, and resilience-oriented dispatch of interconnected power grids. In large-scale grids, conventional full-graph graph neural networks preserve the complete network topology but may become inefficient when many operating scenarios must be screened repeatedly. Direct graph partitioning improves computational tractability, but it may cut tie-line channels and weaken the boundary evidence that determines cross-area risk propagation. To address this trade-off, this paper proposes a boundary-compensated partition-based parallel graph neural network for weak-bus identification. The method first constructs a scenario-aware weighted power-grid graph and divides it into electrically coherent subgraphs under coupling-strength and partition-size constraints. Local graph encoders are then executed in parallel to learn intra-partition vulnerability representations. A boundary compensation module further restores cross-partition information by weighting tie-line neighbors according to electrical coupling, branch loading, and cross-area association. Standardized partition scores are finally fused into a whole-grid weak-bus ranking, and a composite learning objective jointly considers node-score regression, boundary consistency, and pairwise ranking stability. The method is evaluated on the IEEE 57-bus benchmark with mechanism-based node and branch vulnerability labels. Compared with the original full-graph GNN, the proposed method reduces the mean square error from 0.0359 to 0.0147, improves the Spearman rank coefficient from 0.248 to 0.446, and increases Hit@10 from 30% to 70%. Topological interpretation further shows that the identified weak buses are concentrated around high-risk branches such as 8-12, 12-14, 0-14, and 7-8, indicating that the proposed framework captures local aggregation, boundary transmission, and corridor-driven vulnerability propagation. The IEEE 57-bus benchmark is used as a focused validation case because it provides aligned node- and branch-level vulnerability evidence for evaluating weak-bus ranking behavior. Because the available aligned vulnerability evidence is concentrated in this medium-scale benchmark, the results should be interpreted as a focused validation of the proposed ranking mechanism rather than as a complete large-system scalability study. Full article

This paper presents a performance analysis of a hybrid tilting pad journal bearing (TPJB) for reusable liquid methane (LCH₄) turbopumps. The numerical model incorporates temperature- and pressure-dependent density and viscosity of LCH₄ using fourth-order polynomial correlations based on the National Institute of Standards and Technology (NIST) data. A bulk-flow thermohydrodynamic analysis solves the Reynolds and energy equations considering turbulence, compressibility, recess inertia effects, and thermal mixing. The model calculates the pressure and temperature fields using the finite element and finite difference methods, respectively. The results of the static load and length-to-diameter ratio identify the available load range for the present bearing geometry. The cryogenic LCH₄ supplied through the recess locally suppresses temperature rise and produces spatial variations in its density and viscosity. The preload and radial clearance design can compensate for the limited load-carrying capacity of low-viscosity LCH₄, while they also can increase friction coefficient and temperature rise. The supply pressure ratio is the dominant parameter because it strengthens hydrostatic support and compensates for the weak hydrodynamic effect of LCH₄. In contrast, larger recess area weakens hydrostatic support and reduces dynamic coefficients. These results provide bearing-level design guidance for reusable LCH₄ turbopumps. Full article

To further improve the high-temperature dry sliding performance of Si₃N₄ ceramics, a CrAlN transition layer was introduced to improve interfacial stability, while Ag was incorporated as a solid lubricant into the CrAlN matrix. The effects of Ag content on the microstructure and mechanical properties of the coatings were systematically examined, and the tribological performance was evaluated from 25 °C to 550 °C under dry sliding conditions. The Ag concentration increased with increasing Ag target power and affected the morphology, nanoparticle distribution, surface roughness, and mechanical properties of the coatings. Among the tested samples, the coating containing 9.6 at.% Ag exhibited a comparatively favorable combination of mechanical properties within the investigated composition range, with a hardness of 11.5 GPa, an H/E ratio of 0.0913, and an H³/E² value of 0.096 GPa. Tribological tests showed that the average coefficient of friction decreased from 0.32 at 25 °C to 0.12 at 550 °C. This reduction may be associated with temperature-assisted Ag redistribution toward the worn surface and the possible development of Ag-rich surface features at elevated temperatures. However, the wear rate increased with temperature, reaching 3.6 × 10⁻⁵ mm³/(N·m) at 550 °C, suggesting that friction reduction was accompanied by increased material removal and possible near-surface weakening. These results indicate that controlling Ag content is important for balancing friction reduction and wear resistance in ceramic-based self-lubricating coatings. Full article

Injecting CO₂ into gas reservoirs is a crucial approach for enhancing natural gas recovery and achieving CO₂ geological storage, where the gas–gas diffusion behavior between CO₂ and CH₄ directly influences gas mixing efficiency. Direct observation of the spatiotemporal evolution of concentration fields during diffusion remains insufficient. In this study, a gas–gas diffusion experimental system capable of multi-time and multi-space stratified sampling within a high-temperature high-pressure PVT cell was established based on real reservoir fluid compositions. Non-equilibrium diffusion experiments were conducted under different pressures, different initial CO₂ mole fractions, and different diffusion times. A diffusion model was developed according to Fick’s second law. The results suggest that the gas column can be divided into a natural gas zone, a transition zone, and a CO₂ zone by the dimensionless concentration gradient threshold. At 5 MPa, the transition zone width expands rapidly within the first 4 h (dimensionless width increases from 0 to 0.6902), after which growth slows. Increasing pressure significantly inhibits diffusion, reducing transition zone width and prolonging equilibration time. Rising initial CO₂ concentration also suppresses diffusion mixing, particularly in the later stage. Component profile analysis confirms that, under high pressures and high CO₂ concentrations, the diffusion flux across the interface is weakened. Compared to CH₄, the diffusion equilibration time of CO₂ is shorter and more sensitive to pressure changes. The obtained diffusion coefficients (CH₄: 2.92 × 10⁻⁸ to 4.79 × 10⁻⁸ m²/s; CO₂: 3.91 × 10⁻⁸ to 6.08 × 10⁻⁸ m²/s) are on the order of 10⁻⁸ m²/s, consistent with bulk-phase PVT literature data, validating the reliability of the experimental method and inversion model. This study lays an experimental foundation for predicting multi-component gas mass transfer under conditions of CO₂-enhanced gas recovery and CO₂ geological storage. Full article

In hot and humid regions, urban underground utility tunnels are susceptible to high temperature and humidity due to moist inlet air, cable heat dissipation, and limited ventilation jointly affecting the internal environment. To address this issue, an alternating ventilation strategy, in which fan operation is periodically reversed to switch between air supply and exhaust, is proposed. Compared to conventional mechanical ventilation, this strategy overcomes the constraints of unidirectional airflow and mitigates thermal and humidity stratification, with low retrofit requirements and good adaptability. Ventilation performance was evaluated using non-guarantee rates for temperature and relative humidity, i.e., the ratio of the number of measurement points where the temperature/relative humidity exceeds 40 °C/65% to the total number of measurement points in the utility tunnel (TNGR and RHNGR), non-uniformity coefficients (K_T and K_RH), and mean temperature (T_m). The alternating mode outperformed the conventional mode, reducing TNGR by 6.0% and Tm by 0.3 °C while improving temperature and humidity distributions and lowering cable temperatures. Although the reduction in T_m appears modest, it is practically meaningful because it helps weaken thermal stratification and local overheating, improves cable operating conditions, and may reduce the need for high-airflow operation when tunnel temperatures approach the permissible limit. Response surface methodology was further used to optimize the alternating ventilation parameters, indicating that the recommended fan commutation frequency is 2 under different inlet air temperatures. CFD validation confirmed the effectiveness of the optimized scheme. At an inlet air temperature of 35 °C, KRH decreased from 11.9% to 11.0% and Tm decreased from 37.5 °C to 36.9 °C. Full article