Search Results (375)

Accurate wildfire prediction increasingly determines whether emergency resources arrive before a disaster becomes uncontrollable, yet the dominant paradigm reduces the problem to binary occurrence, offering no estimate of the severity that drives suppression planning. This study develops a machine-learning framework for four-class wildfire severity prediction, conditional on ignition, from weather-station observations and calendar terms alone. We construct a composite severity index (CSI) by applying principal component analysis to five damage dimensions (burned area, suppression equipment, personnel, duration, and property loss) recorded for 868 wildfires in Gangwon Province, South Korea (2011–2022) and pair standard observations with effective humidity and six indices of the Canadian Forest Fire Weather Index (FWI) System. Under a leakage-safe protocol, the strongest tree ensembles reach a macro F1 of 0.46 to 0.50 (recommended configuration: 0.41 ± 0.03 across 20 repeated splits) against a four-class chance level of 0.25, and the recommended Random Forest attains an extreme-class recall of 0.474; the CSI target outperforms burned area by 5.5 macro-F1 points under identical inputs. A weather-only screen separates extreme from non-extreme events with an ROC AUC of 0.758, capturing 47% of extreme events at a 20% alert budget. We also quantify how oversampling misplaced before the train-test split inflates the macro F1 to 0.65–0.83, a cause for caution for the severity-prediction literature. Full article

This study investigates how O₂ concentration affects the combustion performance and kinetic response of Changji and Fushun oil shales under CO₂-based oxy-fuel atmospheres. Coupled TGA–DSC–MS analysis was performed to characterize thermal decomposition, heat release and absorption, gaseous product evolution, and apparent kinetic parameters. The results show that raising the O₂ concentration facilitates oil shale combustion. The TG–DTG and heat flow profiles move to lower-temperature regions as O₂ concentration increases. At 20 °C·min⁻¹, increasing the O₂ concentration from 35% to 100% reduced T_p1 and T_p2 from 357.3 and 519.7 °C to 331.2 and 491.5 °C for CJ oil shale, and from 352.3 and 484.0 °C to 326.6 and 429.7 °C for FS oil shale, respectively. These shifts were accompanied by decreases in ignition and burnout temperatures and an increase in the comprehensive combustion index. Fushun oil shale shows a more concentrated main mass-loss and heat-release region than Changji oil shale. It also exhibits lower ignition and burnout temperatures, indicating stronger overall combustion reactivity. By contrast, Changji oil shale displays more evident mass loss and thermal responses at high temperatures, suggesting a greater contribution from carbonate mineral decomposition in the later reaction stage. MS results further show that CO₂, H₂O, SO₂, and NO₂ release mainly occurs within 300–600 °C. Their release peaks shift toward lower temperatures as the O₂ concentration increases, indicating that oxygen-enriched atmospheres promote the oxidative conversion of organic carbon, hydrogen-containing structures, and S- and N-containing functional groups. The Vyazovkin nonlinear iso-conversional analysis provides conversion-dependent apparent activation energies rather than a single global kinetic parameter. The substantial variation in E_α with conversion highlights the overlapping and multi-stage nature of oil shale combustion. When the O₂ concentration is raised from 21% to 75%, E_α generally follows an upward trend; under pure O₂, however, it drops sharply. This non-monotonic variation suggests that O₂ concentration changes not only the combustion rate but also the dominant reaction routes at different conversion stages. These findings provide experimental support for selecting suitable oxy-fuel combustion conditions and improving the clean and efficient utilization of oil shale. Full article

This study numerically investigates the combustion characteristics of four catalytic micro-burners with different channel geometries: a straight-channel burner (Burner 1), a symmetric U-bend burner (Burner 2), and two asymmetric U-bend burners with either a wider inlet channel (Burner 3) or a wider recirculating channel (Burner 4). A steady-state, two-dimensional mathematical model accounting for gas-phase and catalytic reactions of propane on Pt/Al₂O₃ is employed. The results show that U-bend configurations significantly reduce the ignition equivalence ratio compared to the straight-channel design, with Burner 4 exhibiting the lowest value of 0.45. At an equivalence ratio of 0.85, Burner 4 achieves the highest maximum temperature and the most upstream flame location, attributed to enhanced heat recirculation and prolonged residence time in the wider recirculating channel. Temperature and propane mass fraction distributions reveal strong thermal coupling between the inlet and recirculating channels in asymmetric designs. The contribution of catalytic reactions to total heat release remains within a narrow range across the examined equivalence ratios for all U-bend burners, whereas Burner 1 shows a much higher catalytic contribution (~87%) due to suppressed gas-phase reactions. The U-bend geometries also exhibit lower heat loss ratios than the straight channel. The maximum wall temperature gradient increases with equivalence ratio, and the ranking among the three U-bend burners varies with operating conditions, indicating that geometry-specific thermal stress should be considered in practical design. Full article

Driven by the increasing energy density of battery energy storage systems, immersion cooling (IC) has emerged as a promising approach for mitigating thermal runaway (TR) hazards. In this study, overcharge-induced TR tests were conducted on commercial 314 Ah lithium iron phosphate batteries in an accelerating rate calorimeter to compare their thermal, pressure, mass loss, and gas venting responses under air cooling (AC) and static ester-based immersion cooling. For the two cells tested, internal short circuit onset occurred at 1150 s under AC and 1377 s under IC, while TR was triggered at 1232 and 1404 s, respectively. The peak surface temperature decreased from 422.4 °C under AC to 302.4 °C under IC, and the maximum surface temperature difference was reduced by approximately 31%. The maximum chamber pressure rise rate decreased from 3.12 to 1.68 kPa/s, although a higher late-stage cumulative pressure was observed under IC within the sealed ARC chamber. Battery mass loss decreased from 1014.2 g (18.27%) under AC to 845.2 g (15.24%) under IC. In addition, the CO₂ fraction in the post-cooling gas mixture increased from 30.4% to 38.4%, while the H₂ fraction decreased from 43.6% to 36.9%. Based on the modified Le Chatelier calculation, the estimated lower explosive limit increased from 6.16% to 7.18%, suggesting lower composition-based ignitability under the adopted assumptions. Overall, the tested static ester-based immersion cooling configuration delayed TR evolution, reduced peak thermal response and mass loss, and moderated the transient pressure rise under the present experimental conditions. These findings provide experimental reference data for the thermal-safety design of large-capacity battery energy storage systems. Full article

After ignition, fire behavior is governed by a complex interaction of fuel, weather and topography. In practice, fire behavior is labeled as wind, topography or fuel-driven depending on the dominant driver. These labels are typically assigned through expert judgment and post-fire analysis rather than real-time classification. In this paper, we propose a model based on the ConvNeXtV2 convolutional neural network (CNN), capable of detecting the dominant wildfire driver directly from high-resolution surveillance images. The model is trained using 16 labeled sequences with targeted augmentation, class-balanced sampling and loss weighting to counter strong class imbalance and heavy repetition within sequences. The network shows good results in both fuel- and wind-driven situations but struggles with topography-driven wildfires, even when trained on full-resolution images. Despite the small dataset, our approach illustrates how modern CNNs can complement expert predictions. Full article

The study investigated and quantified the feasibility of using waste derived from shea tree fruit shells (Vitellaria paradoxa) as an organic multifunctional additive for building ceramic bodies, focusing on its influence on thermal behavior, pore formation, and mechanical performance. The scope of the research included sieve analysis, chemical analysis (WDXRF), phase composition analysis (XRD), thermal analysis coupled with evolved gas analysis (DTA–TG–EGA), and the evaluation of the physical and mechanical properties of the obtained ceramic materials. The analyses demonstrated that the shea waste was characterized by a high content of organic matter, a loss in ignition of 93.84%, and a calorific value of 19.421 kJ/g. The incorporation of biomass resulted in increased porosity and reduced apparent density of the ceramic materials. The relative porosity increased from 27.00% for the reference sample to 34.98% for the sample containing 30% shea waste. Simultaneously, the compressive strength decreased from 23.67 MPa to 10.10 MPa, while the flexural strength decreased from 8.96 MPa to 4.76 MPa. Partial replacement of conventional mineral additives and, in particular, partial substitution of fossil-derived kiln fuel demand with high-calorific biomass enabled a reduction in overall CO₂ emissions associated with ceramic production. This includes both process-related emissions from raw material decomposition and fuel-related emissions generated in the tunnel kiln. In addition, a reduced contribution of carbon originating from inorganic mineral sources (including carbonates) to total emissions covered by emission trading systems (ETSs) was observed. Despite the reduction in mechanical parameters, samples containing up to 20% shea waste retained properties suitable for application in the production of ceramic building materials. Full article

Agricultural biomass ashes are increasingly used as sustainable supplementary cementitious materials (SCMs) to reduce cement-related carbon emissions and improve concrete performance. However, their effects on compressive strength depend on the SCM type, replacement level, and physical and chemical properties. These variables are often overlooked in machine learning studies focused on single SCM types and absolute strength prediction, limiting transferability across heterogeneous SCM datasets. This study develops an interpretable machine learning framework using a compiled dataset covering 18 agricultural biomass ash SCMs (bio-SCMs) used in concrete. Input features include concrete mixture proportions, the SCM replacement level, chemical composition, and specific surface area (SSA), while the target variable is the 28-day compressive-strength ratio relative to the companion control mixture. Among the five evaluated models, XGBoost achieved the best performance, with weighted 10-fold cross-validation R² values around 0.80. SHapley Additive exPlanations (SHAP) results were interpreted as model associations rather than causal mechanisms. Higher SCM SiO₂ content, pozzolanic oxide content, superplasticizer dosage, and baseline control mixture strength were associated with more favorable strength ratios; SCM SSA showed a mild positive tendency, whereas a higher SCM replacement level, water-to-binder ratio, and loss on ignition were associated with less favorable strength ratios. SCM-specific response analysis further identified literature-derived screening ranges based on observed and interpolated replacement levels rather than machine learning extrapolation. Full article

This study compares the response of five coal-derived post-mining waste streams from Poland and the Czech Republic to dry electrostatic and magnetic separation, with emphasis on rare earth element (REE) enrichment, product yield, and material variability. The materials included dump-derived wastes and process-derived streams from beneficiation operations. Electrostatic separation was performed on the <45 µm fraction, whereas magnetic separation was performed on the <3 mm fraction. Chemical composition was determined by ICP–MS, and process response was evaluated using enrichment factor (EF), product yield, and mass distribution. The ΣREE content of the feeds ranged from 109.33 to 250.54 ppm, while loss on ignition varied from 12.5% to 50.8%, confirming substantial heterogeneity. Electrostatic separation produced only moderate and material-specific enrichment, with EF ΣREE values generally close to unity and reaching a maximum of 1.26 for the Haldex K conductive product. Magnetic separation was less favourable, as most magnetic products showed ΣREE depletion or very low yields. Although the Haldex K paramagnetic product reached EF ΣREE = 1.30, its yield was only 0.2%. Overall, no tested configuration combined high REE enrichment with high product yield, indicating limited standalone beneficiation potential for the investigated materials. This study provides a comparative process-response assessment of low-grade, heterogeneous coal-derived post-mining waste streams and shows that dry electrostatic and magnetic separation can reveal material-dependent REE partitioning behaviour under laboratory conditions. Full article

Homogeneous Charge Compression Ignition (HCCI) combustion has been widely reported to offer high efficiency and ultra-low nitrogen oxide emissions compared to conventional spark-ignited (SI) combustion. However, reported efficiency benefits strongly depend on boundary conditions, engine hardware, and the chosen reference concept. This study presents a systematic experimental comparison between HCCI and SI combustion using gasoline and ethanol on the same single-cylinder research engine under unthrottled and otherwise identical operating conditions. Combustion stability, indicated efficiency, combustion phasing, and gaseous emissions are evaluated. The results show that HCCI combustion provides substantially reduced CO (ethanol: −61.1%; gasoline: −80.6%) and NO_x (ethanol: −96.1%; gasoline: −86.3%) emissions and superior combustion stability for both fuels. Ethanol further improves efficiency and emissions compared to gasoline. Contrary to common expectations reported in the literature, no universal efficiency advantage of HCCI combustion over SI operation is observed under the specific boundary conditions and with the investigated engine configuration of this study. A detailed loss analysis shows that, for the present setup, increased gas exchange and heat transfer losses offset the higher working cycle efficiency (without gas exchange) of HCCI combustion. Full article

Igneous intrusions significantly modify the distribution and mobility of elements in coal. In order to explore the influence of igneous intrusions on the elements in coals, the No. 2-2 coal seam of the Shanxi Formation of Juji Coal Mine was selected as the research focus. The No. 2-2 coal was investigated using X-ray fluorescence spectrometry and a high-resolution inductively coupled plasma mass spectrometer. The results show that the volatile gases accompanying the igneous intrusion, together with CO₂ generated by reaction between the intrusion and the coal seam, led to marginally higher MnO and MgO in the thermally altered coals compared to unaltered coal, and also promoted reprecipitation of carbonate and silicate minerals, which increased loss on ignition. The content of P₂O₅ initially rises with increasing distance from the intrusion, indicating that contact metamorphism can lead to a depletion of major elements in thermally altered coals. Meanwhile, the igneous intrusion caused reprecipitation of silicate minerals, but the high temperatures from the intrusion pyrolyzed some of these minerals, resulting in Li, Sb, and U contents that increase with distance from the intrusion. In contrast, Ge, Mo, Ba, Eu, and Pb, together with hydrothermal fluids, entered the thermally metamorphosed coal via fractures and migrated downward, gradually accumulating within it; their contents therefore decrease with increasing distance. Additionally, the intrusion and associated hydrothermal fluids also induced positive Eu, Gd, and Y anomalies and negative Ce anomalies in the thermally altered coals, whereas intermediate-felsic source rocks and oxidizing conditions produced negative Eu, positive Ce, and weakly negative Y anomalies in coals farther from the intrusion. Contact metamorphism results in a significant element depletion, exerting negative effects. Conversely, hydrothermal fluids and fluids from the host rocks promote the redistribution and enrichment of elements in coal, producing positive effects. Overall, the negative effects outweigh the positive ones. Full article

Skeletal kinetic mechanisms are essential for reducing the computational cost of ammonia combustion simulations while retaining the key chemical features governing ignition, flame propagation, and NO formation. This study extends the DRG-CSP-ANN reduction and optimization framework to ammonia combustion over a broader multi-condition parameter space, aiming to develop a compact skeletal mechanism applicable to different pressures, equivalence ratios, and temperatures. Sixteen detailed ammonia combustion mechanisms were first assessed against experimental data covering ignition delay time, laminar flame speed, and NOx species concentrations over wide ranges of pressure, temperature, equivalence ratio, and oxidizer composition. Based on the overall error evaluation, the detailed mechanism with the most balanced predictive performance was selected as the parent mechanism. The parent mechanism was then reduced using the Directed Relation Graph and Computational Singular Perturbation methods, yielding an initial skeletal mechanism, RA-Ori, with 20 species and 76 reactions. To compensate for the accuracy loss caused by mechanism reduction, an Artificial Neural Network surrogate was constructed to optimize the pre-exponential factors of selected sensitive reactions within their evaluated uncertainty ranges, leading to the final mechanism, RA-ANN. The validation results show that RA-ANN reasonably reproduces ignition delay times, laminar flame speeds, and NO concentrations under different ammonia combustion conditions. Quantitatively, RA-ANN reduces the overall error from 0.335 for RA-Ori to 0.206, corresponding to a 38.4% reduction, while maintaining the same compact size. Its overall error is close to that of the parent detailed mechanism and lower than that of several existing skeletal mechanisms considered in this work. These results demonstrate that the proposed DRG-CSP-ANN strategy can construct a compact ammonia skeletal mechanism that achieves a favorable balance between computational efficiency, predictive accuracy, and applicability over representative multi-condition ammonia combustion regimes. Full article

With the increasing frequency of desilting in urban drainage systems, the safe disposal and resource reuse of sewer sediments have become a prominent practical challenge. Screened sand, the most promising component for resource recovery from sewer sediments, still lacks systematic insight into its pollution risks and the necessity of pretreatment. In this study, 120 raw sewer sediment samples were collected from sanitary, storm, and illicitly connected (IC) storm sewers in Shanghai, alongside seasonal screened sand samples. We systematically characterized their physicochemical properties and heavy metal and antibiotic pollution profiles, and evaluated the purification performance of ultrasonic treatment, sodium hexametaphosphate (SHMP) washing, and their coupled processes. Results revealed significant differences in sediment properties across pipeline types. Screened sand, dominated by SiO₂ and CaO, shows preliminary potential for reuse as a low-grade bulk building material, but its organic loss on ignition (LOI) of 5.29–13.42% exceeded the reuse limit. Concentrations of heavy metals and antibiotics were generally higher in screened sand than in raw sediments, with further enrichment in the fine sand fractions, indicating that screening only redistributed contaminants rather than eliminated them. The coupled ultrasonic–SHMP process, applied for the first time to screened sand from sewer sediments, achieved optimal performance, with a maximum LOI reduction and over 85% removal of certain antibiotics, without damaging the sand’s mineral skeleton. This study provides a scientific basis for the safe resource reuse of screened sand. Full article

The Akseki–Kuyucak bauxite deposits, located in the Western Taurus Belt in southwestern Türkiye, represent karst-type bauxite mineralization derived from carbonate platform phases. This work integrates field observations, X-ray diffraction (XRD) analysis, and extensive geochemical data, including major, trace, and rare earth elements (REEs), to clarify the mineralogical characteristics, geochemical processes, and genetic implications of the deposits. Field and petrographic investigations indicate that the bauxite deposits occur as irregular fills and lens-shaped formations on paleokarstic surfaces of carbonate substrates. The XRD examination reveals that the major minerals in the bauxite samples are boehmite, hematite, and anatase, with some samples exhibiting a predominance of calcite, indicating a strong genetic relationship between the ore bodies and the carbonate host rocks. Major oxide analysis reveals a distinct compositional disparity between bauxitic and carbonate-dominated materials: bauxitic samples exhibit elevated Al₂O₃ and Fe₂O₃ levels, with reduced SiO₂ and CaO concentrations. In contrast, carbonate-rich samples show higher CaO and loss-on-ignition values. Ternary discrimination diagrams categorize most bauxitic samples into the ferritic bauxite and robust lateritization domains, indicating substantial weathering and residual enrichment processes. The trace element and REE studies reveal ΣLREE values ranging from 22.3 to 240.2 ppm, with a right-skewed distribution indicating heterogeneous enrichment. Correlation studies indicate that ΣLREE has a positive correlation with SiO₂ and K₂O, suggesting that the enrichment of REEs is more closely associated with silicate/clay minerals than with iron oxide phases. Furthermore, spider diagrams and the study of immobile components emphasize the significance of residual concentration processes in bauxitization. In contrast, modest TiO₂ levels indicate a composite source derived from both insoluble carbonate remnants and detrital siliciclastic materials. In summary, the Akseki–Kuyucak deposits are categorized as intricate karst bauxite systems, characterized by significant lateritization, regulated accumulation governed by paleokarst characteristics, and a complex geochemical evolution. The results demonstrate that integrating mineralogical, geochemical, and statistical methods provides a thorough framework for evaluating REE behaviors and the effects of source-related factors in karst bauxite deposits. Full article

Polyester resin biocomposites containing biochar have attracted attention for improving mechanical strength and thermal stability while promoting sustainability. The pyrolysis temperature of biochar and its proportion in the polymer matrix are key factors affecting biocomposite performance. This study examined how biochar pyrolysis temperatures (400, 600, 800 °C) and incorporation levels (10, 20, 30 wt.%) influence the physical, chemical, mechanical, flammability, and morphological properties of polyester-based biocomposites. The samples were analyzed for density, water absorption, FTIR, XRD, flexural and tensile strength, ignition time, structural degradation, volumetric loss, and SEM microstructure. Biocomposites with 30 wt.% biochar produced at 800 °C showed the best mechanical properties, with a flexural strength of 95.3 MPa and an elastic modulus of 4417.4 MPa, representing increases of 14.5% and 45.7%, respectively, over the control. FTIR and XRD results revealed decreased aliphatic groups and increased aromaticity at higher pyrolysis temperatures, improving interactions between the matrix and biochar. These biocomposites also demonstrated enhanced thermal stability, with an ignition time of approximately 963 s, delayed structural degradation, and reduced volumetric loss (~19.3%). Overall, pyrolysis temperature and biochar content significantly influence the structural, mechanical, and thermal properties of polyester biocomposites, showing that biochar serves as a sustainable, performance-enhancing component in thermoset polymer matrices. Full article

This paper analyzes the operation of a spark-ignition reciprocating engine fueled by purified landfill gas (LFG). The engine serves as the prime mover for an electric generator and a heat source within a Combined Heat and Power (CHP) unit. Experimental data is retrieved from the Engine Control Unit (ECU). The findings encompass 3000 operating hours (September–December), a period characterized by evolving spark plug conditions, during which various adjustments and service tasks are performed. This study primarily addresses operational strategies for spark plug maintenance to guarantee CHP system reliability, with a specific focus on electrode degradation and its subsequent effect on engine performance. A significant portion of the research analyzes the wear of eight OEM spark plugs installed during the observation period. Utilizing data from a specific interval (4044 to 4797 h), the study calculates the wear rates for both center and ground electrodes based on volume loss measurements obtained via digital microscopy. The results indicate varied electrode wear across the set. Furthermore, the correlation between spark plug condition, misfire counts, emergency shutdowns, and service intervals is examined. The misfires counter is proposed as a parameter for predicting emergency shutdowns and as an indicator for spark plug adjustment or replacement. Lastly, the paper describes potential causes of accelerated ground electrode wear and suggests probable methods for enhancing component longevity. Full article