Search Results (4,793)

In the context of sustainable development, improving the durability of engineering materials and the service life of engineering projects is an important path to address engineering sustainability and low-carbon development. This study addresses the durability issues of steel fiber-reinforced cementitious materials (SFRCMs) under the combined action of stray current and chloride ions in metro engineering. Through simulated stray current-accelerated corrosion tests, combined with compressive strength tests and X-ray computed tomography (X-CT) analysis, the effects of steel fiber volume content (0.5%, 1.0%, 1.5%) and electrification duration (0–72 h) on the mechanical properties and corrosion mechanisms were systematically investigated. The results indicate that steel fiber content significantly influences corrosion rate and strength degradation. Specimens with 1.5% fiber content exhibited the highest initial compressive strength (58.43 MPa), but suffered a severe strength loss rate of 37.67% after 72 h of electrification. In contrast, specimens with 1.0% fiber content demonstrated balanced performance, achieving both high initial strength and superior corrosion resistance (19.66% strength loss after 72 h). X-CT analysis revealed that corrosion products initially filled pores during early stages but later induced microcracks in the matrix. Higher fiber content specimens exhibited increased large-pore ratios due to fiber agglomeration, accelerating chloride ion penetration. Furthermore, digital volume correlation (DVC) analysis demonstrated that steel fibers effectively dispersed loads and reduced stress concentration. However, post-corrosion fiber volume loss weakened their crack resistance capacity, highlighting the critical role of fiber integrity in structural durability. Full article

This study incorporates a nonlinear seepage relationship into Biot’s consolidation theory and simulates the consolidation of a single vertical drain under vacuum preloading using the finite element method. The model, simplified via the equal-strain assumption, is validated against theoretical predictions. Under the axisymmetric Biot’s framework, consolidation behavior is analyzed in detail. The results show that in the early stages of consolidation, excess pore water pressure in the vicinity of the prefabricated vertical drain (PVD) does not fully dissipate and may even increase, indicating the occurrence of the Mandel–Cryer effect. As the consolidation process advances, the consolidation front gradually extends outward, and the void ratio near the PVD decreases rapidly, leading to the formation of a clogging zone. In contrast, the reduction in the void ratio in the non-clogging region is relatively slow. The progressive development of the clogging zone significantly impedes the overall consolidation rate. Furthermore, this study explores the influence of key parameters—including the compression index, permeability coefficient, well diameter ratio, smear effect, and well resistance—on the formation of the clogging zone and the Mandel–Cryer effect. Full article

Wind fields on tropical islands are among the most complex systems in atmospheric science, simultaneously influenced by large-scale monsoons, tropical cyclones, local sea-land circulation, and island topography. These interactions result in extremely complex responses to climate change, posing significant challenges for detailed assessment. This study examines how multi-scale processes have shaped the long-term evolution of the near-surface wind speed over Hainan, China’s largest tropical island. We developed a new high-resolution (5 km, hourly) regional climate reanalysis spanning 1961–2022, based on the WRF model and ERA5 data. Our analysis reveals three key findings: First, the long-term trend of wind speed over Hainan exhibits significant spatial heterogeneity, characterized by “coastal stilling and inland strengthening.” Wind speeds in coastal areas have decreased by −0.03 to −0.09 m/s per decade, while those in the mountainous interior have paradoxically increased by up to +0.06 m/s per decade. This pattern arises from the interaction between the weakening East Asian Winter Monsoon and the island’s complex terrain. Second, the frequency of extreme wind events has undergone seasonal reorganization: days with strong winds linked to the winter monsoon have significantly decreased (−0.214 days per decade), whereas days linked to warm-season tropical cyclones have increased (+0.097 days per decade), indicating asynchronous evolution of climate extremes. Third, the risk from 100-year extreme wind events is undergoing geographical redistribution, shifting from the coast to the mountainous interior (with an increase of 0.4–0.7 m/s in inland areas), posing a direct challenge to existing engineering design standards. Taken together, these findings demonstrate that local topography can significantly influence large-scale climate change signals, underscoring the critical role of high-resolution modeling in understanding the climate response of such complex systems. Full article

The safe and efficient capture of CO₂ in confined environments such as coal mine goafs remains a significant challenge, posing both environmental and safety risks. To address this issue, this study developed a novel biomass-based aerogel adsorbent using CNF-C and CS through sol–gel synthesis and freeze-drying. A series of composite aerogels with varying mass ratios were systematically characterized by SEM, BET, FTIR, and TG-DSC to analyze their microstructure, specific surface area, pore characteristics, chemical properties, and thermal stability. A constant temperature and humidity experimental setup was specially designed to explore the effects of various temperatures, humidity, and material ratios on CO₂ adsorption performance. FTIR analysis confirmed that -NH₂ served as the primary adsorption site, with its density increasing with higher chitosan content. The 1:3 ratio exhibited the optimal specific surface area (7.05 m²/g) and thermal stability, withstanding temperatures up to 350.0 °C, while the 1:1 ratio demonstrated the highest porosity (80.74%). Adsorption experiments indicated that 35.0 °C and 50% humidity were the optimal conditions, under which the 1:2 ratio biomass aerogel achieved an 18% increase in CO₂ adsorption capacity compared to room temperature. The sample with a 1:1 high cellulose ratio is primarily dominated by physical adsorption, making its performance susceptible to environmental fluctuations. The sample with a 1:3 high chitosan ratio is predominantly governed by chemical adsorption, exhibiting more stable adsorption characteristics. The 1:2 ratio achieved the best balance under 35.0 °C and 50% humidity. The biomass aerogel synergistically combined physical barriers from its three-dimensional network structure and chemical adsorption via active functional groups, enabling efficient CO₂ capture and stable sequestration. This study demonstrates the feasibility of biomass-derived aerogels for CO₂ adsorption under complex conditions and provides new insights into the design of sustainable materials for environmental remediation and carbon reduction applications. Full article

Lithium-ion batteries (LIBs) have garnered extensive application across various domains. However, frequent safety incidents associated with these LIBs have emerged as a significant impediment to their further advancement. Consequently, there is an urgent necessity to develop a novel fire extinguishing agent that possesses both rapid fire suppression and efficient cooling capabilities, thereby effectively mitigating the occurrence and propagation of fires in LIBs. This study pioneers the development of an adaptive thermosensitive microcapsule (TM) fire extinguishing agent synthesized via in situ polymerization. The TM encapsulates a ternary composite core—perfluorohexanone (C₆F₁₂O), heptafluorocyclopentane (C₅H₃F₇), and 2-bromo-3,3,3-trifluoropropene (2-BTP)—within a melamine–urea–formaldehyde (MUF) resin shell. The TM was prepared via in situ polymerization, combined with FE-SEM, FTIR, TG–DSC, and laser particle size analysis to verify that the TM had a uniform particle size and complete coating structure. The results demonstrate that the TM can effectively suppress the thermal runaway (TR) of LIBs through the synergistic effects of physical cooling, chemical suppression, and gas isolation. Specifically, the peak TR temperature of a single-cell LIB is reduced by 14.0 °C, and the heating rate is decreased by 0.17 °C/s. Additionally, TM successfully blocked the propagation of TR thereby preventing its spread in the dual-LIB module test. Limitations of single-component agents are overcome by this innovative system by leveraging the ternary core’s complementary functionalities, enabling autonomous TR suppression without external systems. Furthermore, the TM design integrates precise thermal responsiveness, environmental friendliness, and cost-effectiveness, offering a transformative safety solution for next-generation LIBs. Full article

A daily-scale flux variance (FV) method, which employs low-frequency air temperature measurements, was assessed against eddy covariance (EC) measurements of sensible and latent heat fluxes at four sites representing grassland and cropland ecosystems. The sensible heat flux was estimated using two daily-scale FV approaches: M1 (separating daytime and nighttime data) and M2 (integrating daily data), both derived from conventional formulations. The latent heat flux was extracted as a residual of the energy balance closure with the FV-estimated sensible heat flux and additional measurements of net radiation and soil heat flux. The results showed that the FV method performed poorly in estimating sensible heat flux across all four sites, primarily due to the negative flux values from cropland sites. In contrast, latent heat flux estimation showed reasonable agreement with EC measurements. Notably, upscaling the FV method from a half-daily (M1) to a daily (M2) scale did not improve the accuracy of sensible and latent heat flux estimations for most sites. The best performance for latent heat flux was achieved with M1 at a cropland site (YF), yielding a slope of 0.98, determination coefficient of 0.88, and root mean square error of 13.13 W m⁻². Overall, the daily-scale FV method—requiring only low-frequency air temperature data from microclimate systems—offers a promising approach for evapotranspiration monitoring, particularly at basic meteorological stations lacking high-frequency instrumentations. Full article

To address the issues of traditional linear inversion methods, such as their dependence on initial models and the high computational cost of Jacobian matrix calculations, this study conducts inversion research on vertical electrical sounding data based on the backpropagation (BP) neural network combined with the Particle Swarm Optimization (PSO) algorithm. First, two-layer and three-layer horizontally layered geoelectric models were constructed to generate the sample data required for neural network training. Secondly, the PSO-BP neural network model was employed to perform test inversions. The inversion results demonstrate that both neural network methods can successfully invert apparent resistivity data into corresponding geoelectric model parameters, thereby validating the correctness of the PSO-BP neural network inversion approach. Finally, the PSO-BP neural network method was applied to training and inversion of field-measured apparent resistivity data. A comparison between the inversion results of the PSO-BP neural network and those of the conventional BP neural network revealed that the PSO-BP neural network yields superior inversion results. This further confirms the reliability, effectiveness, and practical applicability of the proposed inversion method. The work presented in this study provides a novel approach and perspective for the inversion of vertical electrical sounding data. Full article

Background/Objectives: Cancer is a major public health burden in Serbia and a factor influencing long-term disaster readiness by straining health system capacity. This study examined spatial and temporal trends in incidence and mortality for eight major cancers among women in Central Serbia (1999–2021) to inform targeted prevention and preparedness strategies. Methods: Standardised rates from national datasets were analysed using the Mann–Kendall trend test and Sen’s slope estimator. Geographic disparities were mapped in ArcGIS Pro 3.2. Mortality trends were assessed only for statistically reliable series. Results: Breast cancer incidence increased in six counties, while cervical cancer declined in several areas, likely reflecting screening success. Colorectal, bladder, pancreatic, and lung and bronchus cancers showed rising incidence; lung and bronchus cancer mortality increased in 16 counties, indicating growing demand for chronic respiratory care. These shifts may reduce surge capacity during disasters by increasing the baseline burden on healthcare infrastructure. Regional disparities highlight uneven system resilience. Conclusions: Aligning cancer control measures—especially for high-burden cancers like lung—with emergency preparedness frameworks is essential to strengthen health system resilience, particularly in resource-limited regions. Full article

Improving tropical cyclone (TC) track forecasts is critical for enhancing disaster prevention and mitigation efforts. This study evaluates the effectiveness of the spectral nudging (SN) technique in simulating TC tracks with diverse path patterns over the Western North Pacific using the Weather Research and Forecasting (WRF) model. The results show that the SN technique is remarkably effective in improving tropical cyclone track forecasts for all types of regular track patterns, except for irregular tracks. Specifically, spectral nudging reduced simulated mean track position errors by approximately 60%, 67%, and 77% on average for curving, northwestward-, and westward-moving tracks, respectively. Better simulations of large-scale flow dynamics contributed to these improvements, particularly in scenarios where the subtropical high underwent rapid changes in its circulation patterns. For irregular tracks, applying the SN technique showed mixed results, ranging from 75% error reduction to 20% error increase. This implies that the effectiveness of spectral nudging on the simulation of irregular tracks is case dependent. Since the effectiveness of spectral nudging depends on the scales (spectrum) of the underlying processes creating the irregularities of the tracks, when such irregularities were caused by local and regional-scale factors, spectral nudging became ineffective. Full article

Surface subsidence induced by underground mining in mining areas significantly alters surface topography and hydrogeological conditions, forming depressions and fissures, thereby affecting regional runoff-ponding processes and groundwater infiltration patterns. Accurate assessment of infiltration volumes in subsidence zones under heavy rainfall is crucial for designing underground drainage systems and evaluating water-inrush risks in open-pit to underground transition mines. Taking the surface subsidence area of the Dahongshan Iron Mine as a case study, this paper proposes a rainfall infiltration calculation method based on the precise delineation of surface ponding-infiltration zones. By numerically simulating the subsidence range, the study divides the area into two distinct infiltration characteristic zones under different mining states: the caved zone and the water-conducting fracture zone. The rainfall infiltration volume under storm conditions was calculated separately for each zone. The results indicate that high-intensity mining-induced subsidence leads to a nonlinear surge in stormwater infiltration, primarily due to the significant expansion of the highly permeable caved zone. The core mechanism lies in the area expansion of the caved zone as a rapid infiltration channel, which dominates the overall infiltration capacity multiplication. These findings provide a scientific basis for the design of mine drainage systems and the prevention of water-inrush disasters. Full article

This study investigates the fracture behavior of recycled aggregate concrete by integrating fractal theory and empirical modeling to quantify how recycled coarse aggregates (RCAs) and recycled fine aggregates (RFAs) influence crack complexity and maximum crack width under varying content and loads. The results reveal distinct scale-dependent behaviors between RCA and RFA. For RCA, moderate dosages enhance fractal complexity (a measure of surface roughness) by promoting micro-crack proliferation, while excessive RCA reduces complexity due to matrix homogenization. In contrast, RFA significantly increases both fractal complexity and crack width under equivalent loads, reflecting its susceptibility to micro-scale interfacial transition zone (ITZ) degradation. Non-linear thresholds are identified: RCA’s fractal complexity plateaus at high loads as cracks coalesce into fewer dominant paths, while RFA’s crack width growth decelerates at extreme dosages due to balancing effects like particle packing. Empirical models link aggregate dosage and load to fractal dimension and crack width with high predictive accuracy (R² > 0.85), capturing interaction effects such as RCA’s load-induced complexity reduction and RFA’s load-driven crack width amplification. Secondary analyses further demonstrate that fractal dimension correlates with crack width through non-linear relationships, emphasizing the coupled nature of micro- and macro-scale damage. These findings challenge conventional design assumptions by differentiating the impacts of RCA (macro-crack coalescence) and RFA (micro-crack proliferation), providing actionable thresholds for optimizing mix designs. The study also advances sustainable material design by offering a scientific basis for updating standards to accommodate higher recycled aggregate percentages, supporting circular economy goals through reduced carbon emissions and waste diversion, and laying the groundwork for resilient, low-carbon infrastructure. Full article

The frequent occurrence of sandstorms on the Mongolian Plateau has become a critical factor influencing the stability of regional ecosystems and social activities. In this study, a deep learning framework was developed for predicting sandstorm paths on the Mongolian Plateau. A spatio-temporal feature dataset was established using remote sensing imagery and meteorological observations. Spatial features were extracted through a convolutional neural network (CNN), while the temporal evolution of sandstorms was modeled using a bidirectional long short-term memory (BiLSTM) network. A random forest algorithm was employed to assess the relative importance of meteorological and geographical factors. The results indicate that the proposed CNN-BiLSTM model achieved strong performance at prediction intervals of 1, 6, 12, 18, and 24 h, with overall accuracy, F1-score, and AUC all exceeding 0.80. The 24 h prediction yielded the best results, with evaluation metrics of 0.861, 0.878, and 0.898, respectively. Compared with the individual CNN and BiLSTM models, the CNN-BiLSTM model demonstrated superior performance. The findings suggest that the model provides high predictive accuracy and stability across different time steps, thereby offering strong support for dust storm path prediction on the Mongolian Plateau and contributing to the reduction of disaster-related risks and losses. Full article

To resolve the issue of state of charge (SOC) inconsistency among energy storage units under traditional equal-power allocation strategies, this paper proposes a multi-unit SOC balancing control strategy based on battery life degradation characteristics. Prior to system operation, the proposed strategy optimizes power distribution according to each unit’s state of health (SOH) and predefined depth of discharge (DOD), ensuring SOC balance at the end of each charge–discharge cycle. Simulation and experimental results demonstrate that, compared with traditional equal-power distribution control, the proposed strategy significantly improves capacity utilization and extends the overall system lifetime. For instance, in Simulation Scenario 1, the available capacity per cycle is increased by 8.14%, and the overall system lifetime is prolonged by 11.04%. Furthermore, the strategy eliminates the need for dynamic power redistribution, thus reducing communication overheads and effectively meeting engineering requirements for SOC balancing. This research provides valuable insights for the safe and economical operation of energy storage power stations. Full article

To address the challenges of predicting high-intensity water inflow in regional mine clusters, this study evaluates the reliability of three methods—hydrogeological analogy, dynamic water inflow prediction models, and numerical simulations—based on geological and hydrogeological conditions as well as measured water inflow data from the target mining area. The water inflow at various working faces of the target coal mine was back-calculated, and the reliability of the three methods was compared. The conclusions are as follows: (1) Under the hydrogeological conditions of high-intensity water inflow in regional mine clusters, the conventional hydrogeological analogy method exhibits high reliability in predicting water inflow at the first-mined working face, with a coefficient of determination (R²) as high as 0.95. However, its prediction error increases significantly for non-first-mined working faces, yielding R² values of only 0.72–0.85. (2) Compared to the hydrogeological analogy method, the dynamic prediction model based on groundwater dynamics more accurately characterizes the lateral runoff recharge process of aquifers, significantly improving the prediction accuracy for non-first-mined working faces (R² = 0.90–0.94). (3) The numerical simulation method for water inflow prediction demonstrates high reliability under various conditions, but its accuracy is highly dependent on model characterization and parameter calibration. Full article

The gas desorption behavior of coal is a key basis for guiding gas parameter determination, optimizing gas extraction, and preventing gas-related disasters. Coal in mine working faces typically exhibits a mixed particle size distribution. However, research on the gas desorption behavior of mixed-size coal samples and comparative studies with single-sized samples remains insufficient. This study employed a self-developed experimental system for the multi-field coupled seepage desorption of gas-bearing coal to conduct comparative experiments on gas desorption behavior between single-sized and mixed-size coal samples. Systematic analysis revealed significant differences in their desorption and diffusion patterns: smaller particle sizes and higher proportions of small particles correlate with greater total gas desorption amounts and higher desorption rates. The desorption process exhibits distinct stages: the initial desorption amount is primarily influenced by the particle size, while the later stage is affected by the proportion of coal samples with different particle sizes. The desorption intensity for both single-sized and mixed-size samples decays exponentially over time, with the decay rate weakening as the proportion of small particles decreases. The gas diffusion coefficient decays over time during desorption, eventually approaching zero, and increases as the proportion of small particles rises. Conversely, the gas desorption attenuation coefficient increases with a higher proportion of fine particles. Based on the desorption laws of coal samples with single and mixed particle sizes, this study can be applied to coalbed gas content measurements, emission prediction, and extraction design, thereby providing a theoretical foundation and technical support for coal mine operations. Full article