Search Results (1,812)

A utility tunnel is a complex underground facility that serves as a critical infrastructure integrating and operating systems such as electricity, telecommunications, and drainage within a city. However, various hazard events such as fire, flooding, condensation, damage, and intrusion can occur within utility tunnels, posing risks not only to the degradation of facility functions but also to potential human casualties and economic losses. Therefore, it is crucial to establish prompt and effective response measures for these hazard events. Unlike previous studies that focused on individual hazard types, this study proposes an integrated and standardized multihazard response framework for utility tunnels. Through case analysis, fire, flooding, condensation, damage, and intrusion were defined as representative hazard events, and the response stages for each were classified into attention, caution, warning, and critical levels. Appropriate response scenarios were developed for each stage, providing prompt and efficient response measures tailored to different situations. The proposed framework offers a unique contribution by presenting a unified structure that supports stage-based management and can be directly applied to smart monitoring and control systems in underground infrastructure. This study is expected to contribute to improving the disaster prevention and response systems of utility tunnels and enhancing overall facility safety. Full article

Despite tremendously valuable work on the T-stub, its safety and reliability in post-fire conditions remain a major concern. It is well known that steel is sensitive to high temperatures. Material degradation at high temperatures is likely to cause the T-stub to yield or gradually collapse, potentially leading to the failure of the entire structure. Recent studies have shown that steel joints exhibit a significant change in moment-rotational response post-fire, as the joint’s load–displacement behavior and failure modes change with increasing exposed temperature. However, studies on T-stubs at high post-fire temperatures are very limited. In this study, the aim is to investigate the post-fire load–displacement curves, ductility, plastic, and ultimate capacities of the unstiffened T-stub connected to a rigid base as a function of the exposed temperature. Of the 36 unstiffened T-stubs tested, 30 were subjected to high temperatures. The selected temperature values were 400 °C, 600 °C, 800 °C, 1000 °C, and 1200 °C. A thin plate of 10 mm was selected for the flange of the T-stub in order to obtain mode 1 behavior. Bolts of M16 and M24 were utilized in order to investigate the effects of bolt diameter on the behavior due to the change in distance of plastic hinges. Furthermore, the distances from a T-stub stem to bolt row (p_f) of 40 mm, 60 mm, and 80 mm were selected. As p_f values decrease, the plastic capacity increases, while the ultimate displacement capacity and the ductility decrease. A direct relation between p_f and yield displacement, and between pf and ultimate capacity, was not detected. As the applied temperature increases, the yield displacement increases and the ductility decreases. No significant change in either the plastic or ultimate capacity was observed up to 400 °C. At higher exposed temperatures, the plastic and ultimate capacity decrease as the applied elevated temperature increases. A significant reduction in the plastic and ultimate capacity was especially observed after post-fire exposure to 1000 °C and 1200 °C. The effects of elevated temperature are more pronounced for the plastic capacity of materials. Reduction factors for both plastic and ultimate capacities were proposed to account for the post-fire effects. The proposed reduction factors can predict the effects of a post-fire environment with high accuracy. The results were compared with AISC 358 and Eurocode 3, and it was revealed that the current standards underestimate the actual capacities. A modified calculation, including a reduction factor, is proposed to obtain more accurate results of unstiffened T-stubs for post-fire conditions. Full article

This paper constructs a numerical simulation model for the fire and fire-fighting system of an all-electric vehicle ro-ro passenger ship to study the influence of fire characteristics and fire-fighting system layout parameters on the fire-extinguishing system. The simulation results show that the fire can spread to the upper deck within 52 s, and the smoke will fill the main deck within 57 s. The study found that the battery capacity has a super-linear relationship with the fire hazard, and the fire thermal spread radius of a 240 Ah battery can reach 3.5 m. The high-expansion foam system has a low applicability in quickly suppressing battery fires due to its response delay and limited cooling capacity for deep-seated fires; the fire-extinguishing efficiency of fine water mist has spatial dependence: 800 µm droplets achieve effective cooling in the core area of the fire source with stronger penetrating power, while 200 µm droplets show better environmental cooling ability in the surrounding area; at the same time, the large-angle nozzles with an angle of 80–120° have a wider coverage range and perform better in overall temperature control and smoke containment than small-angle nozzles. The study also verified the effectiveness of fire curtains in forming fire compartments through physical isolation, which can reduce the heat radiation range by approximately 3 m. This research provides an innovative solution for improving the fire safety level of transporting all-electric vehicles on ro-ro passenger ships. Full article

Swelling in pouch batteries poses reliability issues and safety hazards, resulting in product damage, fires, and explosions. This study examines swelling based on the impact of C-rate and temperature during charge–discharge tests, and upper voltage limit and temperature during constant voltage/float charging tests. Internal cell dynamics related to swelling are analyzed using equivalent circuit model parameters from electrochemical impedance spectroscopy tests, and correlations with thickness are established. Constant voltage charging experiments show that swelling follows an initial increase, a plateau, and then a rapid escalation. The onset of rapid swelling accelerated with temperature and voltage, thereby reducing the time to the knee point. A double-exponent swelling model is developed to predict the evolution of thickness under various stress conditions. The results demonstrate that monitoring swelling rate and magnitude can serve as an effective diagnostic for identifying abnormal cell behavior. Full article

Wildfires pose a growing threat to ecosystems, infrastructure, and public safety, particularly in the province of British Columbia (BC), Canada. In recent years, the frequency, severity, and scale of wildfires in BC have increased significantly, largely due to climate change, human activity, and changing land use patterns. This study presents a comprehensive, data-driven approach to wildfire prediction, leveraging advanced machine learning (ML) and deep learning (DL) techniques. A high-resolution dataset was constructed by integrating five years of wildfire incident records from the Canadian Wildland Fire Information System (CWFIS) with ERA5 reanalysis climate data. The final dataset comprises more than 3.6 million spatiotemporal records and 148 environmental, meteorological, and geospatial features. Six feature selection techniques were evaluated, and five predictive models—Random Forest, XGBoost, LightGBM, CatBoost, and an RNN + LSTM—were trained and compared. The CatBoost model achieved the highest predictive performance with an accuracy of 93.4%, F1-score of 92.1%, and ROC-AUC of 0.94, while Random Forest achieved an accuracy of 92.6%. The study identifies key environmental variables, including surface temperature, humidity, wind speed, and soil moisture, as the most influential predictors of wildfire occurrence. These findings highlight the potential of data-driven AI frameworks to support early warning systems and enhance operational wildfire management in British Columbia. Full article

Fire hazard presents a critical challenge to the structural reliability of underground modular infrastructure. This study examines the fire resistance performance of prefabricated monolithic utility tunnels featuring longitudinal threaded connections. A series of fire exposure tests was conducted on assembled utility tunnel specimens using different bolt materials and thermal conditions, enabling evaluation of fire behavior, deformation behavior, and residual capacity. The observed thermal properties revealed significant temperature gradients across tunnel sections, with the peak internal–external differential reaching 536.8 °C. Post-fire mechanical degradation was evident in reduced stiffness and ductility, and the residual load-bearing capacity declined by up to 12.28% compared to unexposed specimens. Specimens using high-strength threaded bolts demonstrated superior performance compared to stainless steel bolt specimens, exhibiting a 4.67% higher residual capacity and 13.87% less residual deformation. A sequential thermal–mechanical finite element model was developed and calibrated based on experimental results, offering a reliable simulation framework for investigating fire-induced damage and residual strength in modular utility tunnel systems. These findings provide a quantitative basis for fire safety assessment. Full article

Fires in underground mines pose significant risks to worker safety. In this study, a digital twin of an underground mine was created, and the heat, gas distribution, and airflow dynamics were investigated during and after the fire using computational fluid dynamics (CFDs) methods at three different locations. While traditional methods did not indicate any problems, the results from the CFDs analyses revealed some important findings. One of the key findings of the study was the change in airflow direction caused by the changing thermodynamic conditions caused by the fire. The digital twin allows us to demonstrate how a fire at any point within the mine can affect the entire mine under these changing thermodynamic conditions. The digital twin enables the real-time monitoring of underground events. Additionally, it facilitates strategic planning to anticipate potential incidents during a fire in an underground mine, allowing for necessary precautions to be implemented. Full article

The aquaculture industry generates large amounts of shell waste, with limited recycling options at the industrial scale. This study explores the feasibility of substituting 20% of gypsum with seashell waste to produce sustainable, fire-resistant panels for non-load-bearing walls on a semi-industrial scale (2.4 × 2.2 × 0.1 m). The new composite exhibits high density (≈1500 kg/m³) and mechanical performance comparable to commercial gypsum. Thermal and fire tests confirmed its excellent insulation and stability: after 4 h of standard fire exposure, the non-exposed surface temperature remained below 80 °C, meeting European fire-resistance criteria. The incorporation of shell waste slightly reduced density and thermal conductivity (0.23 W/mK at 500 °C) without affecting strength or surface hardness. Environmental characterization revealed leaching and radionuclide levels well below regulatory limits, confirming its safety for building use. Overall, this work demonstrates, for the first time at a semi-industrial scale, the technical and environmental feasibility of reusing seashell waste as a gypsum substitute for fireproof materials. The proposed approach advances circular-economy strategies for aquaculture residues, providing an innovative pathway toward sustainable and low-impact construction products. Full article

To accommodate the high penetration of intermittent renewable energy sources like wind and solar power into the grid, coal-fired units are required to operate with enhanced deep peak-shaving and variable load capabilities. This study develops a dynamic model of the boiler–turbine coordinated control system (BTCCS) for ultra-supercritical once-through boiler (OTB) coal-fired units operating under wet conditions. A mechanistic model framework is established based on mass and energy conservation. In case of missing steady-state data, this work proposes a mechanism-integrated parameter identification method that determines model parameters using only dynamic running data while incorporating physical constraints. Model validation demonstrates that the proposed approach accurately reproduces the variable-load operation of the BTCCS within the range of 50–350 MW. Mean relative errors of output variables are all less than 7.5%, and root mean square errors of output variables are less than 0.3 MPa, 1.4 kg/s, 0.25 m, and 20.7 MW, respectively. Open-loop simulations further confirm that the model captures the essential dynamic characteristics of the system, making it suitable for simulation studies and control system design aimed at improving operational flexibility and safety of OTB coal-fired units under wet conditions. Full article

Joint overheating in low-voltage distribution cabinets presents a major safety risk, often leading to insulation failure, accelerated aging, and even fires. Conventional threshold-based inspection methods are limited in detecting early temperature evolution and lack predictive capabilities. To address this, a short-term temperature prediction method for electrical joints based on deep learning is proposed. Using a self-developed sensing device and Raspberry Pi edge nodes, multi-source data—including voltage, current, power, and temperature—were collected and preprocessed. Comparative experiments with ARIMA, GRU, and LSTM models demonstrate that the LSTM achieves the highest prediction accuracy, with an RMSE, MAE, and MAPE of 0.26 °C, 0.21 °C, and 0.54%, respectively. Furthermore, a lightweight version of the model was optimized for edge deployment, achieving a comparable accuracy (RMSE = 0.27 °C, MAE = 0.21 °C, MAPE = 0.67%) while reducing the inference latency and memory cost. The model effectively captures temperature fluctuations during 6 h prediction tasks and maintains stability under different cabinet scenarios. These results confirm that the proposed edge-enabled lightweight LSTM model achieves a balanced trade-off between accuracy, real-time performance, and efficiency, providing a feasible technical solution for intelligent temperature monitoring and predictive maintenance in low-voltage distribution systems. Full article

Urban underground spaces, including tunnels, subways, and underground commercial buildings, have grown quickly as urbanization has progressed. Fires frequently break out following industrial accidents and multi-hazard natural disasters, and they can severely damage human health. Fire smoke is a major contributor and a major hazard to public safety. The flow patterns of fire smoke in underground spaces, the risks to human casualties, and engineering and personal protective technologies are all thoroughly reviewed in this work. First, it analyzes the diffusion characteristics of fire smoke in underground spaces and summarizes the coupling effects between human behavior and smoke spread. Then, it examines the risks of casualties caused by toxic gases, particulate matter, and thermal effects in fire smoke from both macroscopic case studies and microscopic toxicological viewpoints. It summarizes engineering protection strategies, such as optimizing ventilation systems, intelligent monitoring and early warning systems, and advances in the application of new materials in personal respiratory protective equipment. Future studies should concentrate on interdisciplinary collaboration, creating more precise models of the interactions between people and fire smoke and putting life-cycle management of underground fires into practice. This review aims to provide theoretical and technical support for improving human safety in urban underground space fires, thereby promoting sustainable urban development. Full article

Energy-intensive sectors in emerging nations have the simultaneous difficulties of trying to diminish greenhouse gas emissions while maintaining a stable and cost-effective energy supply. Rooftop solar photovoltaic (PV) systems offer a viable solution, especially in tropical areas like Indonesia that have elevated solar irradiance. This study employs a comprehensive methodology to evaluate the structural, economic, and safety viability of rooftop photovoltaic adoption in the Fast-Moving Consumer Goods (FMCG) sector. Structural analysis utilizing the PMM Ratio verified that industrial rooftops can support a 599 kWp photovoltaic system with minimal reinforcements. The economic assessment revealed substantial feasibility, featuring a Levelized Cost of Energy (LCOE) of Rp 261.40/kWh (about USD 0.016/kWh), yearly savings of Rp 1.36 billion (approximately USD 89,000), a Return on Investment (ROI) of 570%, and a payback duration of 3.73 years. The safety evaluation utilizing the Hazard Identification and Risk evaluation (HIRA) technique found significant hazards—working at height, electrical faults, and fire risks—and recommended mitigation measures in accordance with IEC and Indonesian standards. The findings establish a replicable paradigm for assessing rooftop photovoltaic systems in energy-intensive sectors and furnish actionable recommendations for policymakers and industry executives to expedite the adoption of renewable energy in tropical emerging economies. Full article

Accurate prediction of gas pipeline incidents through risk factor interdependencies is critical for proactive safety management. This study develops a hybrid SARIMA–association rule mining (ARM) framework integrating time-series forecasting with causal pattern decoding, using 60-month U.S. pipeline incident records (2010–2024) from the Pipeline and Hazardous Materials Safety Administration (PHMSA) database, covering leaks, mechanical punctures, and ruptures. Seasonal Autoregressive Integrated Moving Average (SARIMA) modeling with six-month rolling-window validation achieves precise leak forecasts (MAPE = 14.13%, MASE = 0.27) and reasonable mechanical damage predictions (MAPE = 31.21%, MASE = 1.15), while ruptures exhibit pronounced stochasticity. Crucially, SARIMA incident probabilities feed Apriori-based ARM, revealing three failure-specific mechanisms: (1) ruptures predominantly originate from natural force damage, with underground cases causing economic losses (lift = 3.70) and aboveground class 3 incidents exhibiting winter daytime ignition risks (lift = 2.37); (2) leaks correlate with equipment degradation, where outdoor meter assemblies account for 69.7% of fire-triggering cases (108/155 incidents) and corrosion dominates >50-year-old pipelines; (3) mechanical punctures cluster in pipelines <20 years during spring excavation, predominantly occurring in class 2 zones due to heightened construction activity. These findings necessitate cause-specific maintenance protocols that integrate material degradation laws and dynamic failure patterns, providing a decision framework for pipe replacement prioritization and seasonal monitoring in high-risk zones. Full article

Aircraft cargo compartment fires represent a major threat to aviation safety due to their rapid development, concealment, and the challenges associated with suppression in confined spaces. This study analyzes the 2019 A330 cargo compartment fire at Beijing Capital International Airport as a representative case. Based on flight crew statements, ECAM alerts, surveillance footage, and firefighting records, the event timeline was reconstructed and the emergency response process examined. The analysis identified four defining characteristics of cargo fires: rapid escalation, interacting hazards, restricted accessibility, and prolonged suppression duration. To address these challenges, a three-stage investigation framework—comprising timeline reconstruction, evidence analysis, and experimental verification—is proposed to systematically determine the causes of fires. In addition, a portable penetrating fire-suppression device was designed and experimentally validated. Results confirm its effectiveness in achieving rapid agent delivery, enhanced structural cooling, and prevention of re-ignition. The findings demonstrate that comprehensive cargo fire investigations require the integration of multi-source data and experimental validation, while tactical and equipment innovations are critical for improving suppression efficiency in confined environments. This research provides practical insights for optimizing cargo fire investigation methodologies and emergency response strategies, thereby contributing to the advancement of aviation safety management systems. Full article

The development of halogen-free flame-retardant formulations for wood-based panels is a promising strategy to improve both fire safety and environmental performance. In this study, oriented strand boards (OSB) were impregnated with aqueous solutions of sodium borate (SBo) and sodium bicarbonate (SBi) to evaluate their combined effects on fire resistance and mechanical properties. Fire performance was assessed using the ASTM D3806 small-scale tunnel test, while mechanical and physical properties were measured according to ASTM D1037. Significant improvements in fire performance were observed: mass loss (ML) during flammability testing decreased by 38% (from 6.9% to 4.3%), flame spread speed (FSS) was reduced by more than 50% (from 6.8 to 3.3 mm/s), and after-flame times (AFT) dropped from 17.2 s to 0 s. Thermogravimetric analysis (TGA) further confirmed enhanced thermal stability, with increased char residue (from 16.9% in untreated boards to 31.5% in treated ones). Mechanical testing revealed a 16% increase in internal bond (IB) strength (from 0.44 to 0.51 MPa), while modulus of rupture (MOR) and modulus of elasticity (MOE) were only slightly affected (decreased by up to 4.2% and 3.6%, respectively). Interestingly, the two additives exerted contrasting effects: SBo reduced strength and bonding performance, whereas SBi improved internal bond strength and dimensional stability. The optimal balance was obtained with treatment P250-50 (250 g SBi and 50 g SBo), which combined enhanced fire resistance with acceptable mechanical integrity. Overall, the results demonstrate that the synergistic use of SBo and SBi offers an effective halogen-free approach to simultaneously enhance the fire resistance and mechanical performance of OSB panels, highlighting its potential for industrial applications. Full article