Objective: Understanding the pyrolysis characteristics of tobacco powder is crucial to controlling the formation of harmful substances and enhancing the safety and quality of heated cigarettes, thus providing a scientific basis for optimizing the design of heated cigarettes. Although the extant studies mainly explored the pyrolysis characteristics and product distributions of some tobacco powders, they barely considered the development of a reliable, component-specific kinetic model for the pyrolysis of tobacco powder in heated cigarettes. To address this research gap, we explored the pyrolysis process and the kinetic parameters of tobacco powder in heated cigarettes, followed by the development of a reliable model. Methods: First, employing thermogravimetric (TG) analysis, the thermal weight loss of the sample (tobacco powder, 10±0.02 mg) was studied under a purge gas (nitrogen) at a flow rate (50.0 mL/min). Following a pre-dehydration step (heating to 100 ℃, holding for 30 min, and cooling to room temperature), the sample was heated from 50 ℃ to 500 ℃ at four heating rates: 5, 10, 15, and 20 ℃/min. Next, the resulting TG and derivative TG (DTG) curves were recorded. Second, we calculated the apparent activation energy for the pyrolysis of tobacco powder using three model-free fitting methods: the Kissinger-Akahira-Sunose (KAS), Friedman (FR), and Flynn-Wall-Ozawa (FWO) methods. Finally, we proposed a four-step pseudo-component kinetic model covering the four-stage pyrolysis of tobacco powder: water evaporation, hemicellulose pyrolysis, cellulose pyrolysis, and lignin pyrolysis. Additionally, a genetic algorithm was employed to optimize 19 kinetic parameters (e.g., activation energy, pre-exponential factor, reaction order, and stoichiometric coefficient) in the model to considerably minimize the error between calculated and experimental DTG values. Results: Tobacco powder pyrolysis proceeded in four stages, illustrated using the 20℃/min heating rate: 1) dehydration (50—208 ℃), where the mass loss (8.73%) was mainly due to the evaporation of bound water in the tobacco powder; 2) hemicellulose pyrolysis (208—291 ℃), where the mass loss reached 19.20% owing to hemicellulose decomposition; 3) cellulose pyrolysis (291—372 ℃), where the mass loss was 22.50%, accounting for the maximum weight-loss rate (0.381 wt%/℃) at 325 ℃; 4) lignin pyrolysis (372—500 ℃), where the mass loss was 14.40%, marking a gradual decrease in the weight-loss rate owing to the complex structure and high thermal stability of lignin. Notably, the 10 ℃/min heating rate yielded the highest weight-loss rate (0.390 wt%/℃) and lowest residual mass (35.0%). Furthermore, the apparent activation energy calculations were highly reliable, with the correlation coefficients (R2) of all three model-free fitting methods exceeding 0.97. Particularly, the KAS, FWO, and FR methods yielded activation energy ranges of 200.89—519.66, 198.11—505.40, and 198.17—505.53 kJ/mol, respectively, exhibiting high correlation throughout the process. As the conversion rate increased, the activation energy exhibited a "first up, then down, then up again" trend. In detail, the activation energy stabilized at approximately 200 kJ/mol when the conversion rate was less than 0.1 (the dehydration stage), then increased rapidly to 249 kJ/mol as the conversion rate increased from 0.1 to 0.3 (hemicellulose pyrolysis). It stabilized again at approximately 250 kJ/mol at a conversion rate of 0.3—0.5 (cellulose pyrolysis) before decreasing to 219 kJ/mol as the conversion rate reached 0.6 (initial lignin pyrolysis). Afterward, it increased rapidly as the conversion rate exceeded 0.6 (lignin decomposition into phenols and aromatic compounds). The kinetic model, optimized using the genetic algorithm, converged after 120 iterations (with a deviation of 5.00%). Notably, the optimized activation energies for the four pseudo-components were 62.00 kJ/mol (water), 118.83 kJ/mol (hemicellulose), 217.31 kJ/mol (cellulose), and 192.13 kJ/mol (lignin). Further, the model accurately simulated the experimental data, with the TG and DTG curves achieving high R2 values (>0.94) for all four heating rates. Conclusions: We clarified the four-stage pyrolysis characteristics of tobacco powder in heated cigarettes. We established that the three model-free fitting methods can be used to reliably calculate the conversion-rate-dependent apparent activation energies for the pyrolysis of tobacco powder, reflecting the differences in energy requirements across the pyrolysis stages. Furthermore, our kinetic model can accurately simulate the pyrolysis of tobacco powder, providing key theoretical support for improving the quality of heated cigarettes.
Objective: Forest fires play a crucial role in the replacement of plant communities. However, climate change may significantly affect tree regeneration after severe wildfires, transform ecosystems and cause huge economic losses. Pneumatic fire extinguishers have become the primary portable firefighting equipment in China's mountainous and roadless regions due to their high mobility and simple operation. However, prolonged operation often leads to engine overheating, which reduces rotational speed, resulting in lower jet velocity, increased air outlet temperatures, and decreased firefighting efficiency. Extensive studies examine the interactions between air flow and gas-phase combustion, but mainly focus on the effects of ambient wind on pool fire combustion. The understanding of their dynamic mechanisms during engine overheating, which causes reduced air jet velocity and elevated air flow temperature, is still poorly understood. To address these gaps, this study numerically investigates the suppression effect of high-speed air jets from pneumatic fire extinguishers on gas-phase combustion, aiming to provide methodological references and data support for optimizing pneumatic fire extinguisher design and improving pneumatic firefighting strategies. Methods: This study employed the scale-adaptive simulation (SAS) turbulence model and eddy dissipation model to simulate the gas-phase combustion of n-heptane pool fires under the influence of air jets. The SAS turbulence model, based on the modifications of the k-L turbulence equation, blends the advantages of the Reynolds-averaged Navier-Stokes (RANS) and large-eddy simulation (LES) models. It can dynamically adjust its turbulence length scale to balance the modeling and resolution of turbulence stress transport. In this study, the SAS turbulence model was used to simulate n-heptane pool fires in air jets. The oil pan height was increased by 100 mm to minimize the gap between the simulation and experimental results. The simulation of high-speed jet interaction with gas-phase combustion involves two methods: computational domain coupling of the pneumatic fire extinguisher and n-heptane combustion for data transfer, and boundary condition transfer from the fan outlet to serve as the jet inlet conditions in the n-heptane combustion computational domain. For computational efficiency, the second method was chosen. The stable n-heptane gas-phase combustion simulation results were used as the initial flow field, and the RANS results at the fan outlet (average velocity of approximately 80 m/s) were extracted and implanted into the interaction computational domain inlet. Results: The height increases of the oil pan improved model accuracy, keeping the SAS temperature error within an acceptable range. Results showed that high-speed airflow effectively suppressed gas-phase combustion. As the jet velocity increased, the flame shape underwent remarkable changes. At low velocities, the flame maintained a stable and continuous structure within a concentrated combustion area. However, as the velocity of the jet exceeded a certain threshold, it strongly impacted and disrupted the flame, which was stretched, distorted and ultimately extinguished. Furthermore, within the studied range, changes in the jet temperature had minimal impact on the gas-phase combustion of n-heptane. Regardless of the temperature, the flame structure and combustion efficiency remained similar at the same jet velocity. This is likely because physical dilution of the jet masks the sensitivity of the gas-phase combustion rate to the temperature. When the jet velocity dominates, minor temperature fluctuations cannot significantly alter the combustion process. Conclusions: This study presents a simulation approach for analyzing gas-phase combustion suppression of n-heptane pool fires using high-speed airflow. The key findings are as follows: (1) jet velocity is the dominant factor in flame suppression. As the velocity increases, the kinetic energy of a jet increases, effectively diluting combustible gases and disturbing the flow field. This hinders fuel-oxidizer mixing and leads to flame breakup and suppression. However, increased jet velocities may cause fuel splashing in actual firefighting, so an optimal jet velocity range needs to be determined. (2) Within the studied range, the jet temperature exerts minimal impact on combustion. At the same velocity, jets with different temperatures produce similar flame structures and efficiencies, thus indicating that temperature regulation is not critical for suppression under these conditions. (3) The SAS turbulence model is effective for simulating air jet-gas-phase combustion interactions as it balances computational accuracy and cost, outperforming the RANS and LES models. Thus, it is suitable for further firefighting simulation studies. Overall, this study provides simulation methods and data references for optimizing pneumatic fire extinguishers. Future studies should focus more on combustion suppression effects under complex conditions and refine simulation methods to better suit actual firefighting scenarios.
Objective: Conventional photoelectric smoke detectors frequently present challenges in complex environments owing to their reliance on single-angle and single-wavelength scattering signals, which can result in high false alarm rates and limited accuracy. To address these limitations, this study proposes an advanced method for distinguishing between fire smoke and interference sources by leveraging multi-angle and multi-wavelength scattering spectral analysis. The primary objective of this study is to enhance the reliability of detection, reduce the occurrence of false alarms, and improve generalization capability in real-world scenarios. These contributions will facilitate the development of next-generation intelligent fire detection systems. Methods: The system incorporated a broadband LED light source with controlled illumination characteristics and an AS7341 multi-channel spectral sensor capable of simultaneous detection across eight discrete wavelength channels (415, 445, 480, 515, 555, 590, 630, and 680 nm). Scattering signals were systematically acquired at 10 discrete angles ranging from 40° to 85°, with an interval of 5°. Spectral data were synchronously captured across all channels at each angle, forming a comprehensive wavelength-versus-angle feature matrix. The experimental design encompassed five types of standard fires (smoldering cotton, wood, polyurethane, heptane flame, and paper fire) and five typical interference sources (water mist, cooking fumes, cement dust, loest dust, and A2 test dust). The model's capacity for generalization was subsequently assessed using a set of five non-standard fire categories. A range of machine learning algorithms were utilized to construct classification models, including random forest, XGBoost, support vector machine, k-nearest neighbors (KNN), and logistic regression. The feature selection and hyperparameter tuning steps were implemented to enhance the model's performance and interpretability. Results: Under controlled chamber conditions, the 50° scattering angle consistently yielded optimal performance across all tested scenarios. At this angle, the XGBoost model demonstrated an accuracy of 100% in discriminating standard fires from interference sources. For non-standard fires, the KNN model demonstrated an accuracy of 97.2%, with a recall rate exceeding 95%, suggesting robust generalization capability and minimal false negatives. Within the 40°~55° angular range, all models demonstrated accuracy levels exceeding 85% and recall rates surpassing 80%, thereby substantiating the resilience of the proposed spectral feature representation. A comparative analysis revealed that models utilizing multi-angle spectral features significantly outperformed conventional single-angle methods across all evaluation metrics, including precision, F1-score, and AUC. The system's performance demonstrated stability across a series of experimental trials, thereby substantiating its capacity for consistent detection under controlled conditions. Conclusions: The integration of angle-resolved scattering spectroscopy and machine learning has proven to be a highly effective and reliable solution for accurate fire smoke detection amidst diverse interference sources. The proposed method offers significant advantages in reducing false alarms and enhancing detection sensitivity, particularly in challenging operational conditions. This research establishes a robust framework for intelligent fire detection systems with stronger generalization abilities and higher operational precision. Subsequent endeavors will concentrate on real-world validation, system miniaturization, and the development of adaptive learning mechanisms for continuous performance enhancement in dynamic environments. The findings of this study bear significant implications for practical applications in smart buildings, industrial fire safety, and public infrastructure protection.
Objective: The leakage of liquid fuel onto high-temperature components, such as aircraft engine nozzles, poses an ignition hazard, particularly under sudden conditions arising from fuel system aging, mechanical impact, or structural damage. Given that it is a critical issue for aviation fire safety, this study investigates the ignition characteristics of fuel droplets on high-temperature surfaces. Titanium alloys, widely used in modern aircraft for their high strength-to-weight ratio and thermal stability, were selected as the substrate to systematically examine the effects of droplet diameter, surface temperature, and fuel composition on ignition probability and ignition delay time. Methods: An experimental platform was established using a TC4 titanium alloy heating plate to simulate a high-temperature hot surface. RP-3 aviation kerosene and n-heptane droplets with diameters of 3.62-9.49 mm were generated using a precision pipette and released from a height of 30 mm onto the heated surface. Surface temperatures were controlled between 200 ℃ and 800 ℃ with a PID system, and ignition events were recorded with a high-speed camera. Ignition probability was defined as the ratio of successful ignitions to the total number of trials, while the ignition delay time was defined as the time interval from droplet contact to sustained flame appearance. A physics-based logistic model and an energy conservation-Arrhenius model were developed to predict ignition behavior and incorporate dimensionless parameters, such as the Bond and Weber numbers, to account for droplet impact dynamics. Results: The minimum ignition temperatures for RP-3 aviation kerosene and n-heptane droplets on titanium alloy surfaces are approximately 590 ℃ and 580 ℃, respectively. Ignition probability increased monotonically with surface temperature but displayed nonmonotonic variation with droplet diameter, peaking at a critical diameter of 7.26 mm. For smaller droplets, ignition probability increases with diameter because of enhanced heat transfer and vapor concentration, whereas larger droplets exhibit reduced ignition probability due to weaker internal thermal gradients and limited oxygen diffusion. Ignition delay time decreases with increasing surface temperature and is the shortest at the critical diameter. Under equivalent conditions, RP-3 droplets show a 5%-15% lower ignition probability and a 20%-30% longer ignition delay time than n-heptane. These changes are attributable to RP-3's complex composition, high boiling point, antioxidant additives, and smoke formation. Titanium alloys exhibit ignition temperatures 50-70 ℃ lower than stainless steel because of their lower thermal conductivity, diffusivity, and catalytic activity. The logistic model accurately predicted ignition probability with < 1% error, while the energy conservation-Arrhenius model predicted ignition delay with < 2 s error. Conclusions: Droplet diameter and surface temperature are the principal factors controlling thermal surface ignition on titanium alloys. The identified critical diameter serves as a useful parameter for monitoring and mitigating fire risks. The developed models offer reliable predictive capability, supporting fire prevention design in aircraft engines. For risk reduction, monitoring droplets 5-9 mm in diameter is recommended, and surface temperatures should be maintained below 600 ℃. Future research should consider additional factors, such as low-oxygen conditions at high altitudes, droplet impact velocity, vibration frequency, and surface characteristics, to further optimize the model and enhance aviation fire safety.
Objective: The rapid expansion of high-rise buildings globally presents notable challenges for firefighting, as traditional methods are often ineffective at that altitude. To resolve this issue, unmanned aerial vehicles (UAVs) offer a promising solution, with tactics centered on glass curtain wall demolition to inject fire suppressants. However, this action drastically alters interior ventilation, potentially triggering flashover and a rapid transition to full-room fire involvement. In this study, the mechanisms and influencing factors of flashover, specifically those induced by glass curtain-wall demolition, are investigated through a series of meticulously designed full-scale experiments. Methods: Experiments were conducted in a 3.0 m (length) × 7.0 m (width) × 2.5 m (height) steel compartment, thereby simulating a standard office or residential room. Additionally, the target glass curtain wall for demolition was simulated using controllable gypsum board opening. Further, fire loads were created using fir wood cribs (moisture content: ~12%), with quantities varying between 6, 12, 15, and 18 cribs. Additionally, a square n-heptane pool fire served as the ignition source. Demolition timing systematically varied between 630, 750, and 870 s, post-ignition, thereby creating six distinct test scenarios. A comprehensive data acquisition system comprising the following components was deployed: The strategically positioned thermocouple arrays (e.g., R1-R5) inside the compartment were used to capture the evolution of the three-dimensional temperature field, especially vertical thermal stratification; an oxygen sensor that monitored volume fraction changes at breathing height (1.5 m); thermal imaging cameras that recorded flame and smoke dynamics; and a high-precision balance that tracked combustible mass loss. Results: The findings revealed distinct fire development patterns after demolition in the ventilation-controlled regime. Particularly, the temperature rise rate of the hot smoke layer exhibited a characteristic dual-peak trend: "initial peak → decayed oscillation → secondary peak." The combustible mass-loss process was segmented into five stages: initial pyrolysis, accelerated pyrolysis, fluctuating stability, sudden increase, and decay. Furthermore, the indoor oxygen concentration demonstrated a complex seven-stage dynamic evolution: "rapid decrease → slow decrease → accelerated decrease → fluctuating decrease → local recovery → fluctuating increase → stable recovery." This evolution was governed by the interplay of combustion intensity and ventilation. A key finding pertains to the influence of fire load: increasing the load (from 12 to 18 cribs) linearly enhanced the maximum post-demolition temperature rise rate (from 18.7 C/s to 56.2 C/s) but nonlinearly shortened the flashover initiation time (~75 s earlier for a 50% load increase). Crucially, a critical load threshold was identified. Beyond this threshold (between 15 and 18 cribs), the sensitivity of flashover initiation time to load diminished (a reduction of only 19 s), indicating a shift to the oxygen-replenishment rate as the dominant control factor of flashover triggering. Demolition timing was equally a critical factor: delaying demolition (from 630 to 870 s) increased the accumulation of unburned pyrolyzates, which rapidly increased the post-demolition temperature (peak rate up from 13.9 C/s to 51.9 C/s, drastically reduced flashover initiation time (from 93 s to 22 s post-demolition), increased the maximum temperatures, and prolonged high-temperature duration. However, beyond a critical demolition time threshold (~750 s in this setup), the ventilation capacity of the opening became the limiting factor. The oxygen supply rate constrained further intensification, stabilizing the flashover time around a fixed value despite additional delay. Conclusions: To the best of our knowledge, this study represents the first full-scale quantitative analysis of flashover behavior induced by glass curtain-wall demolition. The results definitively establish the profound, nonlinear influences of fire load and demolition timing, thereby identifying critical thresholds that control flashover dynamics. These results provide valuable insights into key parameters for designing realistic fire experiments related to structural demolition. More importantly, the findings offer a crucial scientific basis for refining fire safety strategies for high-rise buildings, optimizing tactical decision-making regarding UAV-driven window demolition operations, and improving risk assessment protocols.
Objective: Pumped storage power stations pump water to upper reservoirs when the electricity load is low; they release water to lower reservoirs to generate electricity when the electricity load is high. In these stations, cable tunnels, which connect underground transformers and ground switch stations, usually have high-fall, long-distance, and large-slope attributes. These affect the cable flame spread characteristics. Methods: This paper studies the effect of slope (0°-45°) on cable flame morphology, flame front distance, average flame spread rate, cable surface temperature, and ceiling temperature by conducting cable flame spreading experiments in a 1/10 small-scale cable tunnel. Thermocouples are used to measure the cable surface temperature and tunnel ceiling temperature. A camera is used to record the cable flame morphology, while a computer is used to record data from the camera and thermocouples. Results: The flame front distance and the average flame spread rate increase with the tunnel slope. When the tunnel slopes are 0°, 15°, 30°, and 45°, the cable flame front distances are 539, 783, 1076, and 1 300 mm, respectively, with average cable flame spread rates of 0.43, 0.92, 1.28, and 1.53 mm/s. With increasing slope, the first peak of the cable surface temperature moves upward, and so does the first peak of the tunnel ceiling temperature. When the slope is 0°, the first peak temperature and position of the cable surface and the ceiling are 650 ℃ and -0.25 m, respectively. When the slope is 15°, the first peak temperature and position of the cable surface and the ceiling are 400 ℃ and -0.50 m, respectively. When the slope is 30°, the cable surface's first peak temperature and position are 200℃ and -0.25 m, respectively, whereas those of the ceiling are 250 ℃ and -0.50 m, respectively. When the slope is 45°, the cable surface's first peak temperature and position are 200 ℃ and -1.00 m, respectively, whereas those of the ceiling are 250 ℃ and -1.50 m, respectively. The peak position of the tunnel ceiling temperature is farther than the peak position of the cable surface temperature. Conclusions: First, in the inclined cable tunnel, the Coandǎ and stacking effects increase the flame inclined angle and the preheating area of the unburned cable, with the unburned cable's heating rate and the average cable flame rate increasing. Second, the cable ceiling heating has little effect on cable flame spreading. However, the copper core inside the cable acts as a "heater" and a "radiator, " affecting the cable's burning behavior. The high-temperature core heats the unburned cable zone, increasing the preheating area and cable flame spread rate. Third, in the inclined tunnel, the stacking effect enhances the heat dissipation of cable burning. In the horizontal tunnel, the high-temperature ceiling heats the cable and increases the cable's burning time. Fourth, under the combined effects of longitudinal airflow inertia and thermal buoyancy forces, the peak position of the tunnel ceiling temperature is farther than the peak position of the cable surface temperature.
Objective: Densified wood (DW) is a novel functional material that has garnered significant attention in recent years owing to its exceptional mechanical properties. In comparison with natural wood (NW), DW exhibits a more compact structure, which augments its strength and confers enhanced fire resistance. These advantages position DW as a promising candidate for utilization as a structural material in mid-and high-rise timber buildings, where strength and fire safety are paramount. Nevertheless, despite its potential, the current understanding of the flammability of DW and its fire spread characteristics under real fire scenarios remains limited; this dearth of knowledge imposes substantial constraints on its large-scale implementation in the construction sector. However, a paucity of research has emerged on the coupled effects of wood density and thickness on fire spread in DW. Concurrently, the regulatory influence of external thermal radiation on the fire spread characteristics of DW remains to be fully investigated. Addressing these gaps is imperative for developing a comprehensive theoretical foundation for the safe and reliable use of DW in modern building design. Methods: This study integrates theoretical analysis with systematic experimental testing to explore these issues. The fire spread behavior of DW was investigated under an external radiant heat flux of 8 kW/m2. The specimens' grain direction was maintained parallel to the anticipated fire spread direction, and samples were meticulously prepared to ensure the absence of visible knots, thereby mitigating potential irregular burning effects. Each specimen measured 600 mm in length and 30 mm in width, with two distinct thicknesses: 2 mm and 8 mm. DW specimens with varying density gradients (281.53-973.61 kg/m3) were obtained by compressing NW of different initial thicknesses to these unified final thicknesses. A multiparameter fire spread testing platform was designed and constructed, consisting of three main components: a radiant heating system, specimen support system, and multiparameter data acquisition system. The initiation of the combustion process was facilitated by the application of a linear butane flame to the surface of the DW samples, thereby ensuring uniform ignition conditions across all experimental iterations. During the experiments, flame morphology, solid-phase temperature, and gas-phase temperature were recorded in real time. The analysis of flame images was conducted using digital image processing techniques to extract key parameters, such as the flame front position and flame height, thereby facilitating qualitative and quantitative assessment of combustion behavior. Results: Distinct fire spread behaviors were observed to depend on specimen thickness and density. When the specimen thickness was minimal, the fire spread rate initially increased and subsequently decreased with increasing density, and a critical turning density of 573 kg/m3 was identified. Conversely, as specimen thickness increased, the fire spread rate exhibited a monotonic decrease with increasing density. Flame height exhibited a variation trend that was consistent with the fire spread rate. Preliminary theoretical analyses indicated a positive correlation between wood density and the release of combustible gases during the combustion process, which in turn resulted in taller flames. However, with further increases in density and thickness, a decrease in flame height was observed owing to the growth of the material's thermal inertia, which inhibited rapid heat transfer. Furthermore, wood density was found to influence the rate of fire spread by affecting gas-phase and solid-phase heat transfer mechanisms. In the case of thin specimens, the initial stage of fire propagation was predominantly characterized by gas-phase heat transfer, while as density increased, the mechanism transitioned toward a combined effect of gas and solid phases. In the case of thick specimens, solid-phase heat transfer emerged as the predominant factor influencing the propagation of fire. Thermal thickness was employed as a classification criterion for the specimens, in accordance with heat transfer theory principles. Theoretical fire spread rates were subsequently calculated. The theoretical values exhibited a strong correlation with the experimental results, as evidenced by a correlation coefficient of R2=0.88, thereby substantiating the model's predictive capacity. Conclusions: The present study offers a comprehensive understanding of the fire spread behavior and heat transfer mechanisms of DW under external radiation. The findings reveal the complex interplay between density, thickness, and heat transfer mode; they also highlight the critical role of external radiation in shaping fire dynamics. This research contributes to the advancement of knowledge in the field by enriching the theoretical framework of fire spread and offering valuable guidance for the safe design and application of DW in modern construction. The findings of this study can assist in overcoming the current barriers to the large-scale adoption of DW, thereby promoting its use as a sustainable, high-performance, and fire-safe material. This, in turn, will contribute to the green development of the construction industry.
Objective: The fire resistance of cable sheaths, a critical property for safe operation, can be significantly affected by various environmental factors during service. The resultant degradation compromises cable reliability and poses risks to electrical systems and public safety. Low-smoke halogen-free flame-retardant (LSHFR) cable sheaths are widely used for their environmentally friendly and efficient fire-resistant characteristics. However, their long-term performance under complex environmental conditions remains insufficient understood. This study aims to systematically investigate the fire-resistant degradation mechanism of LSHFR under coupled environmental exposures. Methods: To simulate long-term service conditions, multifactor accelerated aging tests were performed using thermal, salt-spray, and hygrothermal treatments. The fire-resistance performance of the cable sheaths was evaluated through cone calorimetry, limiting oxygen index (LOI) testing, thermogravimetric analysis (TGA), smoke density measurement, and contact angle analysis. Key fire-resistance parameters—including total heat release (THR), LOI, specific optical density, and char residue—were compared before and after accelerated aging treatments. Results: Complex environmental conditions markedly weakened the fire resistance of LSHFR cable sheaths. The coupling effects of different environmental factors varied significantly. Among all treatments, the coupled aging of 240 h hygrothermal exposure and 120 h salt-spray exposure (CACS5) produced the most pronounced adverse effects. Compared with unaged samples, this treatment increased THR by 8.8%, decreased LOI by 6.3%, and reduced char residue at 800 ℃ by 32.3%. Smoke suppression performance also deteriorated severely: total smoke production increased by 83.8%, light transmittance decreased by 72.5%, and maximum specific optical density rose by 124.1%. The fire hazards of the cable sheaths intensified with increasing proportions of hygrothermal aging time in the total aging period. Conclusions: This study comprehensively analyzed the degradation mechanisms of the fire resistance of low-smoke halogen-free flame-retardant cable sheaths under complex environmental conditions. The coupled hygrothermal-salt-spray aging treatment had the most detrimental effect on the fire resistance of LSHFR cable sheaths. Deterioration was mainly attributed to the decomposition of key flame-retardant components, reduced thermal stability, and impaired charring ability, leading to increased heat release and smoke production and decreased char residue. The experimental results highlight that exposure to complex environments significantly elevates the fire risk of LSHFR cable sheaths, and the proportion of hygrothermal aging time is a critical factor. These findings offer valuable insights for the development of precise maintenance, evaluation, and design strategies for flame-retardant, and weather-resistant cables with enhanced long-term fire safety.
Objective: Corrugated cardboard, a cellulosic material consisting of flat and wavy layers, is widely used in warehouses and packing factories. When a fire occurs in these environments, flame spreading over the wavy surfaces poses significant risks to firefighters' health and the local environment, and can result in substantial economic penalties for building owners and insurance companies. Thus, a detailed understanding of flame spreading on wavy surfaces is crucial for preventing and mitigating fire hazards. Methods: This study developed a simplified model of high-precision direct numerical simulation for flame spreading, utilizing the open-source code Fire Dynamics Simulator version 5.5.3. The model incorporates one-step finite-rate gas-phase combustion, one-step first-order pyrolysis, and gray gas radiation applicable to all gas species. The sample was a cellulose-based material modeled as a "B" flute corrugated cardboard measuring 20.4 cm in length and 2.0 cm in width, with each flute being 8.24 mm long and 3.93 mm high. We hypothesized that the thickness of the flat layer matched that of the wavy layer, with layer thickness ranging from 0.083 to 0.414 mm. The sample was assumed to produce 10% chemically inert char residue and liberate 90% combustible gas vapor. The computational domain is a cuboid measuring 0.10×0.640 8×0.02 m, with a time step set at 1 × 10-4 s prior to simulation. Flame is defined as a heat release rate exceeding 15, 000 kW/m2, with the pyrolysis front identified as the position where the local burning rate exceeds 001 kg/s/m2. Results: The flame characteristics on the corrugated and flat surfaces were compared across five aspects: flame shape, fire spreading speed, flame stationary distance, net heat flow distribution, and local combustion rate. The results indicated that: 1) the flame on the wavy surface split into more flamelets, whereas that on the flat surface tended to remain more cohesive. The flame base on the wavy surface moved more rapidly, reaching the fuel's top end sooner and, consequently, self-extinguishing earlier than the flame on the flat surface. 2) In thermally thin samples of layer thickness less than 0.414 mm, the flame base and pyrolysis front movement rates decreased with increasing thickness. 3) Compared with the flat surface, the wavy surface exhibited a lower peak flame temperature and shorter flame standoff distance, resulting in a larger net heat flux imposed on the wavy surface and an increased pyrolysis rate. 4) Correlations were established between the flame net heat flux and the pyrolysis rate relative to the normalized distance, both showing a decaying trend. Conclusions: Through the development of a simplified high-precision direct numerical simulation model for flame spreading, the mechanisms behind flame splitting on corrugated surfaces were explored, and the relationship between net heat flow and local combustion rate was analyzed, providing valuable insights for understanding fire behavior on irregular surfaces.
Objective: In recent years, gas-fueled burners have been widely used to emulate real fires of condensed fuels (e.g., solid polymers and liquid hydrocarbons) in key fields such as fire research, fire safety testing, and fire-fighting training. However, gas-fueled burners differ from real fires in key aspects such as fuel combustion mechanisms, flame stability, and heat release. These differences may result in deviations in simulating flame behaviors and radiation effects. Therefore, exploring the effect of fuel mixing (specifically ethylene-propane blends) on flame shapes and radiation characteristics of buoyant diffusion flames is of great significance. This paper not only clarifies the correlation between fuel composition and flame performance but also establishes a foundation for an equivalent model that matches the burning rate, flame shape, and flame radiation characteristics between gas-fueled burners and real fires, thereby improving the accuracy of fire simulations. Methods: This work examined the combustion characteristics of buoyant turbulent diffusion flames fueled by ethylene-propane gaseous mixtures, including flame shapes, axial temperature distributions, and flame radiation intensities. An experimental burner with a circular nozzle design and a diameter of 0.08 m was adopted to ensure uniform fuel injection. Different ethylene-propane mixing ratios (0%—100% propane by volume, with 10% intervals) were achieved by separately controlling the flow rates of ethylene and propane using mass flow controllers. The total volume flow rate of the mixed fuel was adjusted within the range of 1—6 L/min to vary the heat release rate. Flame shape was analyzed using video footage captured by a high-resolution charge-coupled device camera. Images were converted to grayscale and binarized using the maximum interclass variance method. Subsequently, morphological parameters, including flame height (Lf) and width (Df), were determined using the intermittent rate distribution characteristics of the binary images, referencing a previously proposed flame height definition. In addition, axial flame temperatures were measured using a thermocouple tree, whereas radiant heat flux was measured using a water-cooled Schmidt-Boelter radiant heat flux meter. Results: The experimental results were as follows. 1) The flame height, flame width, flame surface area, and flame volume increased with increasing heat release rate within a total volume flow rate range of 1—6 L/min. 2) The axial temperature of the flames first increased and then decreased with height, and the maximum axial temperature was maintained at 700—900 ℃. 3) For a given propane volume fraction, the average flame radiation power increased with the heat release rate of buoyant turbulent diffusion flames. As the propane volume fractions increased, the flame radiation fractions first increased and then decreased. 4) When the gas-fueled flames were controlled to achieve a heat release similar to that of liquid pool fires, pure propane gas flames better simulated the flame height and radiation characteristics of n-heptane pool fires, whereas pure ethylene gas flames were more suitable for simulating the flame height and radiation characteristics of aviation kerosene pool fires. Conclusions: By integrating theoretical equations and analyzing datasets, this paper established prediction models for the flame shape and radiation fraction of ethylene/propane turbulent diffusion flames and proposed an equivalent method for gaseous flames and liquid pool fires; this equivalent method provides theoretical guidance for real-fire simulation technologies in fire research, fire safety testing, and fire training.
Objective: More than half of fire accidents happen in confined spaces. When a fire source is close to a solid wall, the wall may significantly restrict air entrainment, leading to flame attachment to the wall and even igniting the combustibles on it. However, studies on the effect of wall restrictions on the combustion and pulsation behaviors of near-wall fires remain notably limited. Methods: This study employed a self-designed experimental setup to investigate the influence of heat release rate (Q and fire-wall separation distance (S) on the global and local pulsation frequencies and attachment length of near-wall flames with different aspect ratios (r). Simulations of the combustion behaviors of near-wall fires were also conducted using ANSYS Fluent, yielding the associated flow fields and temperature distributions. Results: Experimental results show that near-wall fires exhibit unstable attachment behavior. Vertical walls impede air entrainment on the near-wall side of the flame, creating asymmetric air entrainment; meanwhile, horizontal walls primarily exacerbate flow-field deformation. The flame exhibits two burning patterns due to the restriction imposed by the wall: a varicose mode at larger values and a sinuous mode at smaller ones. Fast Fourier transform analysis of the flame width and correlation coefficient shows that the pulsation frequency is significantly influenced by Qand S. For attached flames (S=0 cm), the local pulsation frequency remains stable at varying Qvalues and normalized heights. At small S, low-frequency pulsation is pronounced under conditions of high Q. Rectangular fire sources (r=4 and 8) and the square fire source (r=1) show significant differences in global pulsation behavior. With increasing S, the global pulsation frequency for rectangular fire sources gradually decreases, while that for the square fire source decreases at large Qvalues (≥11.4 kW). Conclusions: (1) The flame evolution pattern of near-wall fires can be categorized as either varicose or sinuous mode, depending primarily on S. (2) Flame attachment probability and length increase with increasing Qand decreasing S. (3) For the square fire source with high Q(≥11.4 kW) and rectangular fire sources with r values of 4 and 8, the global pulsation frequency decreases with increasing S. (4) The characteristic diameter of near-wall fires is modified with the flame attachment probability and normalized flame attachment length to account for the effect of unstable flame attachment on air entrainment. Strong asymmetric entrainment causes significant spatial and temporal flame attachment, which increases the characteristic diameter of near-wall fires and reduces the global pulsation frequency. A unified correlation between the normalized flame pulsation frequency (Strouhal number) and the inverse of Froude number is proposed, which reasonably predicts the global pulsation frequency of near-wall fires with different S and Qvalues. Overall, the findings of this study lay a foundation for the reasonable prediction of flame evolution and spread in confined spaces.
Objective: Forest fires can be triggered by the failure of overhead power lines, especially in forests that are prone to wildfires and have dense power transmission networks. The spread of such fires can, in turn, endanger the safety and stability of nearby power infrastructure. Understanding the evolution of forest fires and the mechanisms behind secondary and derivative accidents is essential for implementing risk control at key nodes within the disaster chain. This is crucial in reducing the likelihood of disaster occurrence and the severity of its consequences. However, research on secondary and derivative disaster chains related to forest fires remains limited, and no existing studies have addressed the coupling induction between forest fires and overhead line failures. This gap may lead to risk control measures that are inadequately targeted. Methods: In this study, a secondary and derivative disaster chain network of overhead line failures and forest fires is built based on complex network theory, and the effect of the coupling induction of forest fires and overhead line failures on the formation mechanism of the disaster chain is investigated. First, indicators such as degree centrality and closeness centrality are calculated to evaluate the role and influence degree of each disaster node in the disaster chain network from multiple perspectives. Subsequently, the key nodes in the failure and secondary and derivative disaster chains between overhead lines and forest fires are determined. Second, the transmission probability of each evolution path in the disaster chain is used as the assessment criterion, and the Jaccard index is employed to identify the key evolution paths. Results: First, 92 related accident cases are analyzed, and experts are consulted to determine the inducing relationships among various disaster nodes. Based on this, a disaster chain evolution model is constructed to investigate the failure and secondary and derivative accident chains of the overhead lines and forest fires. This model has 21 disaster nodes, 46 edges, and 60 disaster evolution paths. Four indicators are calculated: degree centrality, closeness centrality, betweenness centrality, and disaster node hub count. The top five disaster nodes are forest fires, casualties, overhead line failure, forest resource destruction, and toxic gas leakage. The transmission probabilities of different disaster evolution paths are calculated based on the frequency of the disaster chain nodes in statistics and the Jaccard index. To confirm the validity of the model and its conclusions, a sensitivity analysis is conducted at the node of overhead line failures, which verifies the relevance of risk management for overhead lines in reducing the risk of the disaster chain. Conclusions: Based on theory of chain-cutting disaster mitigation, how to cut off the evolution paths of the disaster chain or the control key disaster nodes and how to prevent the occurrence of secondary and derivative accidents are clarified in this paper to provide decision support for the actual prevention and control of forest fires and the operation and maintenance of forest power grids.
Objective: Hydrocarbons and their oxygen-containing derivatives are often used as fuels or fuel substitutes, most of which are prone to spontaneous combustion. During combustion, high-temperature flames and toxic gases (e.g., carbon oxides and nitrogen oxides) are produced, causing irreversible damage to the surrounding organisms, water bodies, soil, and air. Therefore, quickly and accurately assessing the consequences of accidents caused by their decomposition is a common practical problem in engineering. Methods: This study aimed to characterize the combustion properties of hydrocarbon oxygen-containing derivatives in flammable and explosive hazardous chemicals. A substitute model incorporating multiple components of small molecules was proposed. Based on the ratio of enthalpy changes, the components and proportion coefficients for each multicomponent substitution model were determined, and a library of 120 models was constructed. The following combustion characteristic parameters were selected as indicators: the maximum net heat release rate difference of gas phase reactions, the highest temperature difference of the adiabatic flame, the flame propagation speed difference, the mean square error (MSE) of the H mole fraction, and the MSE of the O2 mole fraction. The combustion characteristic difference library was comprehensively evaluated using the G1 and TOPSIS methods, along with an improved CRITIC comprehensive weighting approach. The index matching accuracy between small-molecule hydrocarbon substitution models and complex molecular substances was calculated. From this, the optimal substitution schemes and substitution model sets of the same type of substances were selected. Furthermore, the intersection components of the alternative model sets were used as a simple alternative to simulate the combustion reaction kinetics of complex molecular substances. The rationality of these alternative models was verified through high-temperature pyrolysis experiments. Eventually, an alternative model for the combustion reactions of large-molecule complex substances was constructed, characterizing the consequences of hazardous chemical accidents. Results: (1) Using the selected combustion characteristic indicators effectively identified the best alternative models. (2) The substitution models for alcohols and ethers shared essentially the same components, including: CH4, C2H6, C3H8, and C4H10, and exhibited a very high degree of overlap in their best alternative solutions. (3) The multicomponent substitution model for furan compounds included CH4, i-C4H8, and C4H10. The analysis results are in agreement with the high-temperature pyrolysis tests. (4) The best alternative model demonstrated low sensitivity to the weights of each indicator. Therefore, the intersection of the alternative models serves as a mandatory and highly reliable component. Conclusions: The multicomponent, small-molecule hydrocarbon substitution model adopted does not yet encompass all categories of hydrocarbon oxygen-containing derivatives. Some results need further experimental validation. Nonetheless, the research results provide new ideas for constructing combustion reaction kinetic models of hydrocarbons and their oxygen-containing derivatives. This approach enables highly accurate prediction of the consequences of an accident involving complex mixed components (such as gasoline and diesel derived from petroleum).
Objective: Neural network models have shown strong performance in fault arc detection. However, these models often relied on fragmented, single-modality features—such as time-domain, frequency-domain, or time-frequency representations of one-dimensional time series—making it difficult to capture transient high-frequency oscillations at the microsecond level. This resulted in the loss of critical detail, limiting the ability to predict arc occurrence precursors and weakening emergency response. To address this issue, this paper proposed a fault arc detection method based on multi-modality feature fusion. Methods: An experimental circuit simulating parallel breakdown arc induced by overcurrent was built, with 75 effective working conditions designed and over 100, 000 data points collected per scenario. Based on the typical characteristics of pre-fault and fault waveforms, 5, 456 one-dimensional time-series signal samples were constructed. Five conversion methods—Markov transition field (MTF), recurrence plot (RP), Gramian angular field (GAF), short-time Fourier transform (STFT), and continuous wavelet transform (CWT)—were used to convert the transient current signals into time-frequency-space feature maps (TFS-Maps). Each mapping method involved multiple parameters, and their effectiveness in feature extraction varied, necessitating the selection of optimal settings. For MTF, parameters such as the number of bins, interval division strategy, and color mapping scheme were chosen. For GAF, the visualization results of the summation and difference angular fields were compared. For STFT, window lengths of 16, 32, and 64 were tested. For CWT, the wavelet basis, scale, center frequency, and bandwidth were optimized. For RP, the signal's standard deviation was used. The resulting multi-modality dataset—containing original signals and their corresponding TFS-Maps—was split into training, validation, and test sets in a 7∶2∶1 ratio. A gated recurrent unit (GRU) was used to model sequence dependencies in the original signals. A Swin transformer integrated with the convolutional block attention module (Swin Transformer-CBAM) was applied to highlight key regions within the TFS-Maps. The outputs from GRU and Swin Transformer-CBAM were fused via cross-modality concatenation to perform arc detection. Accuracy, precision, recall, F1-score, and comprehensive evaluation visualization graphs were used to assess the algorithm's performance. Results: The experimental results showed that (1) among various TFS-Maps, GADF achieved the highest performance, with 98.07% accuracy, 97.52% F1-score, and 98.01% recall; 2) Swin Transformer-CBAM outperformed the convolutional neural network, with improvements of 0.37% in accuracy, 0.17% in F1-score, and an increase in recall from 97.67% to 98.01%; and (3) the confusion matrix indicated very few misclassifications, with over 98% agreement between predicted and actual labels. Conclusions: Time-frequency imaging enhanced sensitivity to high-frequency transient features. The attention mechanism effectively captured fault arc features by focusing on critical frequency bands and time-domain segments. The proposed detection method met expectations, improved detection efficiency, and provided a more reliable technical solution for identifying parallel breakdown arcs induced by overcurrent.
Objective: Developing a strong safety culture is a critical strategy for coal enterprises to address persistent safety challenges. However, existing approaches to safety culture construction face two major limitations: ambiguity in the conceptual definition of "safety culture" and a lack of clarity regarding its interaction mechanisms with other organizational safety elements. These limitations hinder the full realization of the safety culture's preventive role in accident reduction. To overcome these issues, this study proposes a safety culture construction method based on the 24Model, followed by an empirical investigation using data collected from coal enterprises. Methods: First, the theoretical framework of the 24Model was applied to clarify the connotation of safety culture and elucidate its interaction mechanisms with other organizational safety elements. Second, a safety culture analysis program was employed to collect and verify 3 482 valid questionnaires from 19 coal enterprises in China. Third, the influence of various factors on safety culture levels was systematically examined across three dimensions: individual characteristics (gender, years of service, and education level); industry-wide safety level; and four functional position groups (managers, professionals, team leaders, and frontline workers). Based on the empirical findings, targeted strategies for improving safety culture levels were proposed. Results: No statistically significant difference in safety culture scores was found between male and female employees. Employees with more than 10 years of service scored significantly higher than those with ≤2 years or 2-5 years of service, and those with higher education levels scored significantly higher than those with lower education levels. The overall safety culture score of the sampled enterprises was 78.19, which is slightly higher than the national average for other industries (77.74). A comparative analysis of the evaluation results of 32 safety culture elements across four functional position groups, benchmarked against enterprises with superior and poor safety performance, revealed the following: elements such as "role of the safety department" "approach to safety performance" and "role of safety organization" consistently scored low across three groups; elements including "community safety impact" "care for injured employees" "understanding of safety performance" "relationship between safety performance and human resources" and "overall safety expectation" showed deficiencies in two groups; and elements such as "importance of safety" "perception of safety investment" "formation of safety values" "leadership responsibility" "employee participation" "training needs" "quality of safety meetings" "implementation of safety procedures" "types of safety inspections" "safety management of subsidiaries and contractors" and "emergency response capability" fell below expectations in one group. Conclusions: The empirical results demonstrate that both years of service and education level are significantly and positively correlated with safety culture levels in coal enterprises. Furthermore, systematic differences were observed among the four functional position groups in their understanding of specific safety concepts. Based on these insights, a three-stage safety culture enhancement strategy and a dual-path improvement framework integrating reconstruction of the safety management system and enhancement of employee safety competence were proposed. This framework provides a systematic and practical approach for strengthening safety culture in coal enterprises.
Objective: In today's increasingly interconnected world, risks—whether natural, technological, economic, or social—rarely exist in isolation. Instead, they often intertwine, which increases their impacts and complicates mitigation efforts. Such complex intertwining of risks poses significant challenges to emergency decision-making and public safety management. To address this issue, this study examines the mechanisms underlying risk intertwining to establish a scientific foundation for optimizing emergency response strategies. By enhancing the understanding of how risks interwine, this study seeks to improve the risk prevention, mitigation, and resilience-building for multifaceted crises. Methods: This study adopts a research methodology that combines qualitative and quantitative analysis. Through qualitative analysis, we examine (1) intertwining characteristics, analyzing interaction patterns between different risks; (2) root causes, investigating the fundamental driving mechanism of risk intertwining; and (3) forms of manifestation, identifying observable risk intertwining patterns, such as synchronous occurrence, secondary triggering, or latent correlations. Through quantitative analysis, we calculate (1) the time span, quantifying the duration of risk intertwining to assess its persistence and long-term impacts, and (2) the coupling intensity—computing the degree of interdependence between risks to establish quantifiable indicators of intertwining strength. This integrated approach enables a comprehensive investigation of both the qualitative and quantitative dimensions of risk intertwining. Results: This study investigates the intrinsic mechanisms of risk intertwining. By deconstructing the inherent patterns of risk intertwining, this study transcends the limitations of traditional descriptive analysis and reveals fundamental mechanism governing risk intertwining phenomena. An analytical framework is developed to assess real-time public safety risk intertwining utilizing open-source information such as news reports, social media data, and government bulletins for real-time monitoring and risk correlation assessment. A public safety risk intertwining model is proposed and empirically validated through case studies and testing using real-world data, demonstrating its practical applicability in real-life scenarios. The model's effectiveness is confirmed across multiple verification dimensions. Conclusions: This study proposes an open-source intelligence-based model that analyzes the intertwining mechanisms of public safety risks by integrating risk perception, identification, and mechanism exploration capabilities to evaluate complex risk composites. This study systematically elucidates the characteristics and underlying causes of risk intertwining while establishing a comprehensive evaluation index system to assess the degree of intertwining between different risk themes. Using 23 years of open-source data from websites, such as X, as a case study, the model's effectiveness in applications related to public safety and emergency management has been empirically validated. The study finds that (1) the proposed mixed methods model effectively reveals complex intertwining mechanisms, particularly in the public safety domain, where risks are high and information is abundant; (2) the risk perception model enables the prediction and generation of multiple risk topics through the contextual analysis of vast open-source information to promptly identify emerging risks and facilitates effective preventive measures; and (3) building on traditional qualitative descriptions, the risk intertwining model achieves a mathematical representation of risk intertwining by calculating the similarity between different risk topics. The model quantitatively assesses the evolving trends of risk intertwining over time, providing auxiliary decision-making support for preventing and mitigating public safety risks.
Objective: This study focuses on the critical task of predicting the number of people to be evacuated (i.e., relocation number) during flood disasters. Accurate predictions of relocation numbers are vital for ensuring timely resource allocation and efficient disaster management, particularly in flood-prone areas where rapid decision-making can drastically mitigate the adverse impacts of the disaster. Methods: This research developed a robust relocation number prediction framework that combines feature selection and data augmentation techniques using the extreme gradient boosting (XGBoost) model, a widely used gradient-boosting machine learning algorithm. The model was built using historical data from flood events across China between 2014 and 2018. These events included meteorological and geographical features and the relocation number during each disaster. Feature selection was accomplished using Shapley additive explanations (SHAP), a game theory method for measuring the contribution of each feature to the model predictions. The selected features were then fed into the XGBoost model for training. A data augmentation strategy was also introduced to handle the challenge of limited training samples. This strategy involved the injection of Gaussian noise using a weighted k-nearest neighbors method to generate synthetic data points that preserved the local structure of the data, thereby enhancing the model's robustness and generalization ability. Results: The study demonstrates that the XGBoost model performs well with the selected features and augmented data. Initially, the model is trained on a small dataset, leading to satisfactory accuracy but limited generalization ability. However, after applying data augmentation, the model's performance significantly improves, especially for extreme values in the data. The testing phase reveals that R2 improves from 0.854 to 0.967, indicating a substantial increase in the model's predictive accuracy. Additionally, the root mean square error decreases from 0.296 to 0.123, signifying a considerable reduction in prediction error. These results highlight the effectiveness of combining feature selection and data augmentation to enhance the predictive power of the model. The feature selection process, guided by SHAP, identifies several key predictors that play a dominant role in determining population relocation demand. Among the most influential features are the maximum 3-day cumulative rainfall (MCR) and the maximum cumulative rainfall over the 15 days prior to the event (MRPE). These features are the most important in predicting the relocation number during flood events. Conclusions: The proposed relocation number prediction framework, integrating feature selection through SHAP and data augmentation techniques, is a highly effective tool for forecasting the relocation number during flood disasters. The XGBoost model, after optimization through Bayesian hyperparameter tuning and data augmentation, demonstrates significantly improved prediction accuracy and robustness. This approach can be instrumental in supporting disaster management teams with more reliable forecasts, allowing for better planning and more timely deployment of resources. Improving the model's ability to generalize to unseen data ensures accurate predictions even in regions with limited historical data. Thus, this study provides a valuable decision-making support tool for emergency response teams, helping to streamline resource allocation and evacuation planning during flood disasters and thereby minimizing the impact of the disaster on human lives and infrastructure.
Objective: The electric drive axle is a big and complex flexible system composed of a planetary gear system, an axle system, bearings and housing, etc. The unavoidable excitation of gear eccentricity error and the time-varying meshing stiffness of gears cause signal modulation, which severely affects the vibration characteristics of the system. Although an equivalent dynamics model of the system established by using spatial beam units can effectively solve the vibration response, it requires a long computation time for large and complex systems. Methods: An efficient dynamics calculation method for electric drive axles is proposed herein. This method considers the excitation of gear eccentricity error. First, the beam element of each component in the driveline was used to reduce the dimensions of the stiffness and mass matrices using the modal synthesis method. Only the essential connection nodes and the main modal order were retained. Since the housing was not suitable for beam unit modeling due to its complex structure, the bearing connection nodes and test measurement nodes were retained on the basis of the housing finite element solid element to obtain the reduced housing stiffness matrix and mass matrix. Second, the magnitude of the eccentricity error for each gear in the planetary gear system was determined using the results of the gear detection accuracy. It was assumed that the magnitude of the eccentricity error of each planetary gear was consistent, but the direction was random; the eccentricity error state of the planetary gear was regarded as consistent when the same planetary gear was in the sun-planet and ring-planet gear pairs simultaneously. Accordingly, the detailed expression of eccentricity error excitation for sun-planet n and ring-planet n gear pair was deduced. Finally, using the reduced stiffness matrix and mass matrix of each component, which considered the eccentric error excitation of each gear pair of the planetary gear system, a combined modal integrated dynamics model of the electric drive axle system was obtained. The vibration response was solved by using the Newmark method. Results: The analysis results revealed the following: (1) Compared with the finite element model of the beam element with an unreduced system, the proposed model had fewer degrees of freedom—2 788×2 788 for the former model but only 1 515×1 515 for the latter model (an effective reduction of 45.7%)—and significantly higher computational efficiency. (2) Pronounced side-frequency phenomena were observed in the frequency-domain response of the system calculated by the proposed method. In addition, amplitude fluctuations were observed in the time-domain response. These phenomena are consistent with the experimental measurement results. These phenomena did not arise when the eccentricity error excitation was not considered. Conclusions: In summary, this study proposed an efficient dynamic modeling and analysis method for overcoming the problem of time-consuming dynamics solution and signal modulation in determining the dynamic response of large and complex systems, such as electric drive axles. The accuracy of the method was verified, and the necessity of considering the excitation of eccentricity error through numerical calculation and experimental measurement was established.
Objective: Existing point elasticity theories of the multinomial logit (MNL) model mainly focus on the forward application of the elasticity formula. However, the monotonic and extremum properties of the elasticity formula—critical for exploring the potential to regulate choice probabilities—have received limited attention. Currently, no analytical method exists for calculating attribute variables based on given point elasticity extreme values and thresholds. To address the limitations of reverse point elasticity solutions that depend on numerical methods and the unclear monotonicity of threshold intervals, this study applies differential theory and the properties of the Lambert W function to clarify the monotonic intervals and extreme point properties of the MNL model's point elasticity function. It also proposes generalized closed-form solutions for the reverse solutions of cross and self-point elasticity functions. Methods: The study performs derivative analyses of the cross and self-elasticity functions, introducing the Lambert W function to derive generalized closed forms for the extreme points, determine the monotonic intervals of elasticity functions, and specify the ranges of attribute variables under given elasticity thresholds. First, the derivative of the elasticity function is calculated, revealing that the elasticity functions have a discontinuity at the origin and exhibit a monotonically increasing and then decreasing trend, with only one maximum point. Limit analysis indicates that the elasticity functions have no lower bound. Next, by introducing the main branch theory of the Lambert W function, the generalized closed form of the stationary points is derived, along with a criterion for identifying intervals of positive elasticity based on whether the stationary point exceeds 1. Considering the marginal diminishing effect of adjusting attribute variables on choice probability, the study further calculates the effect's preservation intervals of attribute variables under given elasticity critical thresholds. Because the inverse solution involves double roots, the main and negative branches of the Lambert W function are used to comprehensively obtain the generalized closed analytical form of the double roots and identify the variation intervals of attribute variables with the potential to regulate choice probability. Finally, two transportation mode choice cases—bus fare discounts and bus travel subsidies as attribute independent variables—are analyzed to verify the practicality of the proposed theory in formulating attribute variable adjustment values while accounting for policy costs and marginal diminishing effects. Results: The theoretical derivation and case analysis of this study indicate that: (1) As attribute variables increase, both the cross and self-point elasticity functions of the MNL model exhibit a monotonic pattern—first increasing and then decreasing, and first negative and then positive—with a single maximum positive point; (2) Considering an alternative associated with attribute variable, when the absolute difference between the system utility of the remaining alternatives and that of the alternative without the attribute variable is not less than 2, the maximum value of the self- or cross-point elasticity is not less than 1; (3) Within the MNL model framework, the marginal effect of bus fare discounts decreases continuously as the discount amount increases, while that of bus ride subsidies first increases and then decreases as the subsidy amount grows. Therefore, to enhance the attractiveness of public transportation, relevant authorities should first perform the reverse quantitative elasticity analysis proposed in this paper to scientifically balance policy implementation costs and effectiveness. Conclusions: This study provides a theoretical foundation for scientific decision-making on target values of attribute variables by considering adjustment costs and the significance of expected effects. Using the discriminant for the existence of sensitive intervals, decision-makers can assess whether adjustments to specific attribute variables significantly affect choice probabilities and preclude unsuitable variables. Under a given elasticity threshold, the adjustment interval of an attribute variable with a non-decreasing marginal effect can be precisely calculated in reverse, improving the efficiency and accuracy of policymaking.
Objective: The Chinese government has emphasized the active promotion of steel-structure (SS) residential buildings as a key strategy in its 14th Five-Year Plan for the construction industry to support national carbon neutrality goals. Despite this policy support, a comprehensive understanding of the relative environmental advantages of SS housing compared with traditional reinforced concrete structure (RCS) buildings remains limited, particularly regarding embodied carbon emissions during the materialization stage. Thus, this study aims to systematically quantify and compare the embodied carbon emissions of SS and RCS residential buildings across three typical building heights (6, 18, and 32 stories) and evaluate their carbon reduction potential under current conditions and anticipated upstream technological improvements in material production. Our findings seek to offer scientific evidence to inform structural design choices and promote low-carbon residential construction in China. Methods: This study focused on embodied carbon emissions generated during the materialization stage, including raw material extraction and production, material and equipment transportation, and on-site construction activities. A process-based emission factor approach compliant with the Chinese national standard (GB/T 51366—2019) was employed. Structural designs for typical residential buildings at the three specified heights were developed through expert consultation, applying relevant Chinese codes for fire protection, seismic resistance, and elevator requirements, all of which influence material use intensity. The major construction materials considered were concrete, steel reinforcement, structural steel, and masonry blocks. The carbon emission factors for these materials were calculated under two scenarios: business-as-usual (BAU), reflecting current production technologies, and greener material (GM), which incorporates expected advances such as clinker substitution in cement, steel recycling, improved energy efficiency, and decarbonization of electricity generation. Embodied carbon from transportation and construction phases was estimated proportionally to material production emissions using empirically derived coefficients from prior studies. Results: Under the current BAU scenario, the embodied carbon emissions per unit floor area increased with the building height for both SS and RCS structures. For six-story buildings, SS structures showed a 4.3% reduction in embodied emissions compared with RCS structures, whereas the embodied emissions of SS structures exceeded those of RCS structures by 4.2% and 13.3% for 18 and 32-story buildings, respectively. These differences could be attributed to conservative design codes and the high carbon intensity of current steel production. In contrast, under the GM scenario, carbon emission factors for concrete and steel decreased by approximately 21.5% and 59%, respectively. This led to a 35% reduction in embodied carbon for RCS buildings and an even greater reduction of up to 46% for SS buildings. The enhanced mitigation effect for SS buildings was largely driven by the significant share of steel in their embodied emissions, which benefited disproportionately from upstream technological improvements in material production and energy systems. Conclusions: Embodied carbon emissions during the materialization stage are substantially influenced by technological advancements in upstream sectors such as energy and manufacturing. As these sectors transition toward greener production, SS residential buildings are projected to achieve substantially greater carbon reduction potential than RCSs, especially for high-rise buildings where steel usage is intensive. Effective collaboration between the construction industry and upstream material producers, along with optimized structural design codes without compromising safety, is essential to fully realizing the low-carbon advantages of steel structures.
