European Heart Journal, Supplement

Square steel tube (SST) columns are widely applied, and fire resistance is a critical issue in its design. Current research on the fire resistance of the SST column predominantly assumes that it is uniformly exposed to fire, ignoring the thermal insulation of the surrounding walls under actual fire conditions. The heat transfer and mechanical finite element model (FEM) for SST columns embedded in walls under an ISO 834 standard fire are established in this study, and the accuracy of the FEM is verified by existing experimental results. Subsequently, the wall effect on the temperature distribution and fire resistance of the SST columns exposed to fire is analyzed, the stress mechanisms of the SST column embedded in walls is investigated and further parametric analyses are performed. The results show that, for SST columns embedded in walls, the temperature rise rate of the wall-embedded region is significantly reduced, and the fire resistance is improved by 25.3% compared with the case of uniform exposure to fire. Under two fire conditions, the SST columns exhibit compressive bending failure, and when considering the wall effect, the uneven temperature distribution induces material strength eccentricity, causing the buckling direction to deviate toward the wall-thickness direction. Reducing the fire-resistive coating thickness of the wall-embedded region can mitigate the uneven stress distribution, thereby lowering construction costs while concurrently preserving fire resistance. Increasing the steel tube thickness can significantly improve the fire resistance, but the high steel strength and slenderness ratio result in the accelerated failure of the SST column when exposed to fire.

This study investigates innovative surface coatings’ effectiveness in enhancing spruce wood’s fire resistance (Picea abies spp.). Spruce wood samples were treated with various agents, including oils, waxes, boric acid, commercial coatings, and fire-retardant agents. The evaluation was conducted using the small flame method (EN ISO 11925-2:2020), surface roughness analysis, hyperspectral imaging (HSI), and contact angle measurements. The results demonstrated significant improvements in fire resistance for samples treated with specific coatings, particularly the Burn Block spray and Caparol coating, which effectively prevented flame spread. The analysis revealed that the Burn Block spray reduced the average flame height to 6.57 cm, while the Caparol coating achieved a similar effect with an average flame height of 6.95 cm. In contrast, untreated samples exhibited a flame height of 9.34 cm, with boric acid-treated samples reaching up to 12.18 cm. Char depth measurements and the surface roughness analysis revealed a clear correlation between the type of treatment and the thermal stability of the wood. Hyperspectral imaging enabled a detailed visualisation of surface degradation, while contact angle measurements highlighted the impact of hydrophobicity on flammability. This research provides in-depth insights into the fire-retardant mechanisms of spruce wood and offers practical guidelines for developing safer and more sustainable wood materials for the construction industry.

This study was conducted to precisely map burned areas in fire-prone forest regions of İzmir and analyze the spatial distribution of wildfires. Using Sentinel-2 satellite imagery, burn severity was first classified using the dNBR and dNDVI indices. Subsequently, machine learning (ML) algorithms—RF, XGBoost, LightGBM, and AdaBoost—were employed to classify burned and unburned areas. To enhance model performance, hyperparameter optimization was applied, and the results were evaluated using multiple accuracy metrics. This study found that the RF model achieved the highest performance, with an overall accuracy of 98.0% and a Kappa coefficient of 0.960. In comparison, classification based solely on spectral indices resulted in overall accuracies of 86.6% (dNBR) and 81.7% (dNDVI). A key contribution of this study is the integration of Explainable Artificial Intelligence (XAI) through SHapley Additive exPlanations (SHAP) analysis, which was used to interpret the influence of key spectral and environmental variables in burned area classification. SHAP analysis made the model decision processes transparent and identified dNBR, dNDVI, and SWIR/NIR bands as the most influential variables. Furthermore, spatial analyses confirmed that variations in spectral reflectance across fire-affected regions are critical for accurate burned area delineation, particularly in heterogeneous landscapes. This study provides a scientific framework for post-fire ecosystem restoration, fire management, and disaster strategies, offering decision-makers data-driven and effective intervention strategies.

This study investigates a risk-based approach to evaluate the effectiveness of sprinklers in residential buildings to offset the risk premium imposed by combustible cladding (expanded polystyrene and aluminium composite panels) installed on such buildings in Victoria, Australia. This approach builds upon the Initial Fire Spread in Cladding Assessment Number (IF-SCAN), a concept pioneered by Cladding Safety Victoria as a triage tool in their rectification program. The analysis uses published data from real fires in buildings with and without sprinkler systems installed. It considers three criteria: death rates, injury rates, and construction cost. The construction cost was determined using an existing costing model currently employed in Victoria. The results of this study suggest a higher risk tolerance can be accepted for combustible cladding on buildings equipped with sprinkler systems over that set out in government policy. More specifically, it was found that a building fully protected by sprinklers can generally counterbalance the fire risk posed by combustible cladding spanning up to seven apartments, while a span of up to ten apartments could be considered for buildings without balconies or a private courtyard.

Some of the most catastrophic fire events that have occurred in the western US in recent decades, such as the 2018 Camp Fire in California, were ignited by electric utility infrastructure. As wildfires and fire seasons intensify across the western United States, policymakers and utilities alike are working to mitigate the risk of wildfire as it relates to utility infrastructure. We pose the following research question: Is there an association between risk factors such as wildfire hazard potential and social vulnerability, and the inclusion of various strategies in mitigation planning by public or cooperative electric utilities in Washington, such as PSPS provisions and non-expulsion fuse installation? By applying statistical tools including t-tests and logistic regression modeling to test these potential associations, our analysis reveals statistically significant relationships between risk factors and the inclusion of specific wildfire mitigation strategies. We find that the inclusion of PSPS provisions in mitigation planning is significantly and nonlinearly associated with wildfire hazard potential, while social and socioeconomic vulnerability in the utility service area are negatively associated. Additionally, the installation of non-expulsion fuses is negatively associated with socioeconomic vulnerability in service populations. Overall, understanding the factors associated with wildfire mitigation planning can assist policymakers and state agencies in the prioritization of resources and practical support for utilities that may have limited capacity to mitigate wildfire risk.

For computational fluid dynamic (CFD) modeling of advanced combustion engines, the cylinder is usually considered a closed system in which the initial conditions are estimated based on the experimental data. Most of these approximations hinder observing the effect of design parameters on engine performance and emissions accurately, and most studies are limited to a few design parameters. An approach is proposed based on the combination of a 1D gas dynamic and a 3D CFD model to simulate the whole engine with as few simplifications as possible. The impact of changing the in-cylinder initial conditions, injection strategy (dual direct injection or multiple pulse injections), and piston bowl geometry on a reactivity controlled compression ignition (RCCI) engine’s performance, emissions, and fuel stratification levels was investigated. It was found that applying the dual direct injection (DDI) strategy to the engine can be promising to reach higher load operations by reducing the pressure rise rate and causing stronger stratification levels. Increasing the number of injection pulses leads to lower Soot/NOx emissions. The best reduction in the pressure rise rate was found by the dual direct strategy (38.36% compared to the base experimental case) and higher exhaust gas recirculation (EGR) levels (41.83% reduction in comparison with the base experimental case). With the help of a novel piston bowl design, HC and CO emissions were reduced significantly. This resulted in a reduction of 54.58% in HC emissions and 80.22% in CO emissions.

To investigate the propagation of explosion shock waves within a ship’s engine room, a two-story engine room of a cargo ship was selected as the research object. The BlastFOAM solver in OpenFOAM-9 software was utilized to conduct numerical simulations of the explosion dynamics in the engine room. The results demonstrate that the explosion impact force escalates with the quantity of explosives. Following a liquefied natural gas (LNG) explosion, the shock waves exerted on the ventilation duct and control room are significantly stronger in terms of maximum pressure and intensity compared with those generated by a naphtha explosion. Comprehensive analyses of shock wave pressure distribution, structural damage, and energy absorption reveal that the centralized control room sustains the most severe damage from shock waves, while the ventilation ducts are also significantly impacted. The mechanical equipment absorbs the majority of the shock wave impact while reflecting a minor portion, leading to the intersection of direct and reflected waves. This study provides valuable insights for enhancing the explosion resistance of ship engine rooms, optimizing equipment layout within cabins, and improving the structural resilience of cabin designs.

The effect of a surface coating with an aqueous solution containing a synthetic diammonium hydrogen phosphate fire retardant and vacuum pressure impregnation with a synthetic diammonium hydrogen phosphate fire retardant, potassium acetate, and a natural polymeric retardant, arabinogalactan, to improve the fire resistance and selected properties of structural fir (Abies alba L.) wood was investigated in this article. The combustion characteristics were investigated, and the heat of combustion reflects the effect of the presence of fire retardants. Changes in the content of cellulose, hemicelluloses, holocellulose, lignin, and extractives characterize the chemical changes in wood caused by these factors. The relationship between the combustion characteristics and chemical changes in chemically modified wood as a consequence of the presence of flame retardants were assessed using Fourier transform infrared spectroscopy. The results showed that the effectiveness of the fire retardants against ignition and burning when applied by vacuum pressure impregnation was always higher than in the case of surface coating, even when using impregnation solutions of low concentrations. In the case of diammonium hydrogen phosphate, a low 5% concentration of retardant was sufficient to provide suitable flame retardancy. Further, degradation by depolymerization of cellulose occurred only at temperatures between 460 and 470 °C. Low concentrations of retardant limit the loss to the environment and consequent ecological impact.

Wildfires pose severe threats to terrestrial ecosystems by causing loss of biodiversity, altering landscapes, compromising ecosystem services, and endangering human lives and infrastructure. Chile, with its diverse geography and climate, faces escalating wildfire frequency and intensity due to climate change. This study employs a spatial machine learning approach using a Random Forest algorithm to predict wildfire risk in Central and Southern Chile under current and future climatic scenarios. The model was trained on a time series dataset incorporating climatic, land use, and physiographic variables, with burned-area scars as the response variable. By applying this model to three projected climate scenarios, this study forecasts the spatial distribution of wildfire probabilities for multiple future periods. The model’s performance was high, achieving an Area Under the Curve (AUC) of 0.91 for testing and 0.87 for validation. The accuracy, True Positive Rate (TPR), and True Negative Rate (TNR) values were 0.80, 0.87, and 0.73, respectively. Currently, the prediction of wildfire risk in Mediterranean-type climate areas and the central Araucanía are most at risk, particularly in agricultural zones and rural–urban interfaces. However, future projections indicate a southward expansion of wildfire risk, with an overall increase in probabilities as climate scenarios become more pessimistic. These findings offer a framework for policymakers, facilitating evidence-based strategies for adaptive land management and effective mitigation of wildfire risk.

This study aimed to shorten firefighter search times during indoor fires, allowing more people to be rescued, by enhancing disaster-prevention capabilities using building technologies. In indoor fires, fatalities are often caused by the failure of firefighters to rescue individuals in a timely manner. The question of how to effectively increase the probability of survival while waiting for rescue behind closed doors warrants in-depth research and analysis. Therefore, to ensure that people live in safe environments, there is an urgent need to develop a building door panel material with an emergency call function to prevent such incidents from occurring. Utilizing the PRISMA method, we conducted a comprehensive review of the existing literature to identify the key issues and limitations associated with the current search-and-rescue techniques. Subsequently, the identified primary factors were analyzed using the TRIZ method to determine the key factors that influence the success of rescuing trapped individuals, and a notification system was designed to address this issue. Based on the premise that it is advisable to wait for rescue during a fire, we utilized a smartphone to scan a QR code and transmit the exact location information to the fire department. Through extensive participation and feedback from firefighters, we developed a rescue notification door panel and obtained a patent for it. This system can significantly reduce the time required for search-and-rescue operations in fire incidents. The experimental results show a reduction of one-third in search times.

This study investigates the effectiveness of immersive audiovisual simulations in eliciting emotional responses and replicating the psychological and cognitive demands of high-risk operational environments, particularly in firefighting scenarios. Conducted in two successive phases, the research first employed a pilot study involving 90 participants (45 firefighters and 45 students) who were exposed to a controlled audiovisual simulation. Emotional responses were assessed using the Differential Emotion Scale (DES), the Emotion Regulation Questionnaire (ERQ), and the Perceived Stress Scale (PSS). The second phase involved an immersive room experiment with 36 firefighters, where the same audiovisual stimulus was presented in a fully immersive environment, integrating interactive decision-making tasks to enhance ecological validity. The findings indicate that both methods effectively elicited the targeted emotional responses, including stress, fear, anger, and serenity, with firefighters exhibiting greater emotional regulation and adaptive coping strategies compared to students. The immersive room environment significantly amplified emotional engagement, resulting in stronger emotional responses from the first scene onward. These results underscore the potential of immersive training tools in preparing emergency responders for high-stress situations by strengthening psychological resilience, improving emotional regulation, and optimizing decision-making under pressure. The study contributes to advancing evidence-based training methodologies in emergency response, public safety, and crisis management, emphasizing the importance of integrating immersive technologies into professional training programs.

Firefighters are vulnerable to opioid misuse given the adverse effects their occupation has on mental and physical health. Yet there are limited data on opioid misuse within this population. This study examined the prevalence of illicit prescription opioid use among a nationally representative sample of U.S. firefighters and factors related to opioid misuse. Data were collected through reliable questionnaires from 617 firefighters prior to participating in an intervention designed to mitigate the negative impacts of trauma. The lifetime prevalence of illicit prescription opioid use was 14% compared to 13% in the general U.S. population. The most commonly misused opioids were hydrocodones with trade names Vicodin, Lortab, and Lorcet (72% of those illicitly using opioids). Illicit prescriptions opioid use was not significantly correlated with any demographics examined. However, firefighters who engaged in illicit opioid use exhibited poorer mental health, more alcohol-related problems, and an increased likelihood of misusing other prescription medications. In a regression analysis, alcohol consumption issues, Post-Traumatic Stress Disorder (PTSD), and the illicit use of sedatives and tranquilizers emerged as significant predictors of illicit prescription opioid use. Illicit prescription opioid use by firefighters is a potential problem especially when considered along with other factors such as mental health. Longitudinal studies are needed to further deepen our knowledge about this issue.

Underground interconnected tunnels typically have a large curvature and multiple branching structures, which pose a higher fire risk than traditional single-tube tunnels. In this paper, experiments were performed on a reduced-scale tunnel to study the characteristics of temperature distribution and smoke propagation under coordinated ventilation. A total of 318 experimental cases were conducted, systematically varying fire location, ventilation scheme, and fire power. The results show that an increased heat release rate (HRR) significantly elevates both the maximum temperature (ΔTmax) and smoke spread range. The influence of ventilation on ΔTmax and smoke spread varies depending on fire locations. When fire occurs at the intersection of two tunnel central axes, increasing the velocity in either the branch tunnel (v1) or main tunnel (v2) reduces ΔTmax and smoke spread in tunnels. When fire occurs inside the branch tunnel, the main tunnel airflow obstructs downstream smoke movement, leading to a higher ΔTmax and expanded smoke spread upstream of the branch tunnel. A prediction model for ΔTmax under cooperative ventilation in underground interconnected tunnels was established, accounting for variations in fire position and the HRR. Meanwhile, the temperature distribution upstream of the branch tunnel was studied, revealing that the HRR has minimal impact on it. When fire occurs outside of the branch tunnel, v2 significantly affects temperature attenuation within the branch tunnel. When fire occurs at the branch tunnel entrance or inside, v2 has less effect. Combining the ventilation scheme and the HRR, dimensionless temperature decay models for different fire locations were proposed. These findings offer valuable insights for smoke control in underground interconnected tunnels.

Wildfire activity in the western U.S. has highlighted the importance of effective management to address this growing threat. The Lookout Mountain Thinning and Fuels Reduction Study (LMS) is an operational-scale, long-term study of the effects of forest restoration and fuel reduction treatments in ponderosa pine (Pinus ponderosa Dougl. ex Laws.) and mixed-conifer forests in central Oregon, U.S. The broad objectives of the LMS are to examine the effectiveness and longevity of treatments on wildfire risk and to assess the collateral effects. Treatments include four levels of overstory thinning followed by mastication of the understory vegetation and prescribed burning. Stands were thinned to residual densities of 50, 75, or 100% of the upper management zone (UMZ), which accounts for site differences as reflected by stand density relationships for specific plant communities. A fourth treatment combines the 75 UMZ with small gaps (~0.1 ha) to facilitate regeneration (75 UMZ + Gaps). A fifth treatment comprises an untreated control (UC). We examined the causes and levels of tree mortality that occurred 2–9 years after treatments. A total of 391,292 trees was inventoried, of which 2.3% (9084) died. Higher levels of tree mortality (all causes) occurred on the UC (7.1 ± 1.9%, mean ± SEM) than on the 50 UMZ (0.7 ± 0.1%). Mortality was attributed to several bark beetle species (Coleoptera: Curculionidae) (4002 trees), unknown factors (2682 trees), wind (1958 trees), suppression (327 trees), snow breakage (61 trees), prescribed fire (19 trees), western gall rust (15 trees), cankers (8 trees), mechanical damage (5 trees), dwarf mistletoe (4 trees), and woodborers (3 trees). Among bark beetles, tree mortality was attributed to western pine beetle (Dendroctonus brevicomis LeConte) (1631 trees), fir engraver (Scolytus ventralis LeConte) (1580 trees), mountain pine beetle (Dendroctonus ponderosae Hopkins) (526 trees), engraver beetles (Ips spp.) (169 trees), hemlock engraver (Scolytus tsugae (Swaine)) (77 trees), and Pityogenes spp. (19 trees). Higher levels of bark beetle-caused tree mortality occurred on the UC (2.9 ± 0.7%) than on the 50 UMZ (0.3 ± 0.1%) which, in general, was the relationship observed for individual bark beetle species. Higher levels of tree mortality were attributed to wind on the 100 UMZ (1.0 ± 0.2%) and UC (1.2 ± 1.5%) than on the 50 UMZ (0.2 ± 0.02%) and 75 UMZ (0.4 ± 0.1%). Higher levels of tree mortality were attributed to suppression on the UC (0.5 ± 0.3%) than on the 50 UMZ (0.003 ± 0.002%) and 75 UMZ + Gaps (0.0 ± 0.0%). Significant positive correlations were observed between measures of stand density and levels of tree mortality for most causal agents. Tree size (diameter at 1.37 m) frequently had a significant effect on tree mortality, but relationships varied by causal agent. The forest restoration and fuels reduction treatments implemented on the LMS increased resistance to multiple disturbances. The implications of these and other results to the management of fire-adapted forests are discussed.

This study investigates the buckling performance of built-up cold-formed steel (CFS) columns, with a focus on how different thermal exposures and cooling strategies influence their susceptibility to various failure mechanisms. Addressing the gap in the literature on the fire behavior of mild steel (MS)-based CFS columns, the research aims to provide new insights. Compression tests were conducted on MS-based CFS column specimens after they were exposed to fire, to assess their post-fire buckling strength. The columns were subjected to controlled fire conditions following standardized protocols and then allowed to cool to room temperature. The study examined axial load-bearing capacity and deformation characteristics under elevated temperatures. To improve fire resistance, protective coatings—gypsum, perlite, and vermiculite—were applied to certain specimens before testing, and their performance was compared to that of uncoated specimens. A comprehensive finite element analysis (FEA) was also performed to model the structural response under different thermal and cooling scenarios, providing a detailed comparison of the coating effectiveness, which was validated against experimental results. The findings revealed significant variations in axial strength and failure mechanisms based on the type of fire-resistant coating used, as well as the heating and cooling durations. Among the coated specimens, those treated with perlite showed the best performance. For example, the air-cooled perlite-coated column (MBC2AC) retained a load capacity of 277.9 kN after 60 min of heating, a reduction of only 6.0% compared to the unheated reference section (MBREF). This performance was superior to that of the gypsum-coated (MBC1AC) and vermiculite-coated (MBC3AC) specimens, which showed reductions of 3.6% and 7.9% more, respectively. These results highlight the potential of perlite coatings to enhance the fire resistance of CFS columns, offering valuable insights for structural fire design.