Fire Incidents Research Articles

Wildfire management decisions outweigh mechanical treatment as the keystone to forest landscape adaptation

BackgroundModern land management faces unprecedented uncertainty regarding future climates, novel disturbance regimes, and unanticipated ecological feedbacks. Mitigating this uncertainty requires a cohesive landscape management strategy that utilizes multiple methods to optimize benefits while hedging risks amidst uncertain futures. We used a process-based landscape simulation model (LANDIS-II) to forecast forest management, growth, climate effects, and future wildfire dynamics, and we distilled results using a decision support tool allowing us to examine tradeoffs between alternative management strategies. We developed plausible future management scenarios based on factorial combinations of restoration-oriented thinning prescriptions, prescribed fire, and wildland fire use. Results were assessed continuously for a 100-year simulation period, which provided a unique assessment of tradeoffs and benefits among seven primary topics representing social, ecological, and economic aspects of resilience.ResultsProjected climatic changes had a substantial impact on modeled wildfire activity. In the Wildfire Only scenario (no treatments, but including active wildfire and climate change), we observed an upwards inflection point in area burned around mid-century (2060) that had detrimental impacts on total landscape carbon storage. While simulated mechanical treatments (~ 3% area per year) reduced the incidence of high-severity fire, it did not eliminate this inflection completely. Scenarios involving wildland fire use resulted in greater reductions in high-severity fire and a more linear trend in cumulative area burned. Mechanical treatments were beneficial for subtopics under the economic topic given their positive financial return on investment, while wildland fire use scenarios were better for ecological subtopics, primarily due to a greater reduction in high-severity fire. Benefits among the social subtopics were mixed, reflecting the inevitability of tradeoffs in landscapes that we rely on for diverse and countervailing ecosystem services.ConclusionsThis study provides evidence that optimal future scenarios will involve a mix of active and passive management strategies, allowing different management tactics to coexist within and among ownerships classes. Our results also emphasize the importance of wildfire management decisions as central to building more robust and resilient future landscapes.

Implementation of fire incident response time service policy in Manado City Fire Service

The purpose of the research is to find out, analyze and describe the Implementation of Response Time Service Policy for Fire Incident Management in Manado City Fire Service and the determinant factors. The method used in this research is qualitative research method. The results showed that in the implementation of the Fire Event Response Time Service Policy in Manado City Fire Service, there are six important indicators, namely (1) Media call center which plays an important role in fire handling as the main link between the community and fire handling officials, (2) Implementing apparatus consisting of various roles with complementary responsibilities, from fire fighting to fire prevention, (3) Fire fighting facilities in this case facilities and infrastructure which are important elements in fire management efforts, (4) The situation of the fire location which greatly affects the response and fire management activities, (5) The distance and limitations of hydrants which affect the speed and effectiveness of fire management, and (6) Coordination between agencies in fire management plays an important role in ensuring a fast, effective, and coordinated response to fire situations. The determinant factor in fire incident management efforts is Human Resources (HR) which is the main driving factor in the implementation of fire management. The Human Resources referred to here are the number of fire fighting personnel. Next is the facilities or facilities and infrastructure supporting firefighting activities which include vehicles and other extinguishing aids used in extinguishing activities, then the limited budget both in terms of the budget for operations and the budget for procurement and repair of facilities and infrastructure supporting extinguishing activities.

Numerical Simulation of Fire Smoke Transport in Underground Spaces of a Pumped Storage Power Station

The present study employs numerical simulation to investigate the transportation of fire smoke within the underground powerhouse of a Pumped Storage Power Station. The obtained results reveal the spatial variation of fire smoke under the smoke exhaust effect inside the facility. For an 8 MW fire occurring on the generator, busbar, and turbine layer floors of the main powerhouse, recommended evacuation times are 86 seconds, 242 seconds, and 298 seconds respectively when utilizing a mechanical exhaust capacity of 85000 m3/h. In case three simultaneous fires occur at these three floor levels, the evacuation time is reduced to 45 seconds. Comparatively, when compared to situations without mechanical smoke exhaust systems, our simulations indicate that escape times for different fire scenarios were extended by only 6 seconds and 91 seconds respectively. These findings underscore the urgent need for optimizing the mechanical smoke exhaust system in order to provide valuable time for personnel evacuation during fire incidents.

Study on Public Perceptions and Disaster Prevention Framework of Tunnel Fires Based on Social Media and Artificial Intelligence

To investigate public perceptions regarding tunnel fire disasters and optimize the tunnel fire disaster prevention framework, this study takes the emerging social media platform Douyin as a case study, conducting an in-depth analysis of 2133 short videos related to tunnel fires on the platform. A computational communication method was used for analysis, Latent Dirichlet Allocation was used to cluster the discussion topics of these tunnel fire short videos, and a spatiotemporal evolution analysis of the number of videos posted, user comments, and emotional inclinations across different topics was performed. The findings reveal that there is a noticeable divergence in public opinion regarding emergency decision making in tunnel fires, related to the complexity of tunnel fire incidents, ethical dilemmas in tunnel fire escape scenarios, and insufficient knowledge popularization of fire safety practices. The study elucidates the public’s actual needs during tunnel fire incidents, and a dynamic disaster prevention framework for tunnel fires based on social media and artificial intelligence is proposed on this basis to enhance emergency response capabilities. Utilizing short videos on social media, the study constructs a critical target dataset under real tunnel fire scenarios. It proposes a computer vision-based model for identifying critical targets in tunnel fires. This model can accurately and in real-time identify key targets such as fires, smoke, vehicles, emergency exits, and people in real tunnel fire environments, achieving an average detection precision of 77.3%. This research bridges the cognitive differences between the general public and professionally knowledgeable tunnel engineers regarding tunnel fire evacuation, guiding tunnel fire emergency responses and personnel evacuation.

Vulnerability assessment of major urban tunnel subjected to fire induced by traffic incidents - a case study

As a type of critical transportation infrastructures, safety of major tunnels in urban transportation corridors has become unprecedentedly crucial. In various fire incidents with high temperature environment, the ceiling and wall of a tunnel would risk spalling, strength reduction, and even structural failure. In addition to risks of structural damage, high temperature and thick smoke in fire incidents will increase the risk of severe injury and even death due to burning, lack of oxygen, inhaling smoke and reduced visibility for people inside the tunnel. Limited mobility of evacuees would delay the evacuation process by endangering the safety of both evacuees and first responders. A comprehensive simulation-based case study is conducted to look into the fire and smoke simulation as well as potential threats to structural integrity and human health caused by fire in typical traffic incidents of three types of vehicles. Fire and smoke simulation are conducted using the Fire Dynamics Simulator (FDS), followed by the thermal and structural analyses with ANSYS. The comprehensive parametric study provides insights in terms of the impacts of different parameters including various typical traffic fire incidents on the structural performance and potential threats to evacuees.

Vision-Based Prediction of Flashover Using Transformers and Convolutional Long Short-Term Memory Model

The prediction of fire growth is crucial for effective firefighting and rescue operations. Recent advancements in vision-based techniques using RGB vision and infrared (IR) thermal imaging data, coupled with artificial intelligence and deep learning techniques, have shown promising solutions to be applied in the detection of fire and the prediction of its behavior. This study introduces the use of Convolutional Long Short-term Memory (ConvLSTM) network models for predicting room fire growth by analyzing spatiotemporal IR thermal imaging data acquired from full-scale room fire tests. Our findings revealed that SwinLSTM, an enhanced version of ConvLSTM combined with transformers (a deep learning architecture based on a new mechanism called multi-head attention) for computer vision purposes, can be used for the prediction of room fire flashover occurrence. Notably, transformer-based ConvLSTM deep learning models, such as SwinLSTM, demonstrate superior prediction capability, which suggests a new vision-based smart solution for future fire growth prediction tasks. The main focus of this work is to perform a feasibility study on the use of a pure vision-based deep learning model for analysis of future video data to anticipate behavior of fire growth in room fire incidents.

Research on Determining the Weights of Key Influencing Factors Based on Multi-Grained Binary Semantics

To effectively address the complexity of the environment, information uncertainty, and variability among decision-makers in the event of an enterprise emergency, a multi-granularity binary semantic-based emergency decision-making method is proposed. Decision-makers use preferred multi-granularity non-uniform linguistic scales combined with binary semantics to represent the evaluation information of key influencing factors. Secondly, the weights were determined based on the proposed method. Finally, the proposed method’s effectiveness is validated using a case study of a fire incident in a chemical company.

Investigating Post-fire Critical Area of ship base on Numerical Fire Simulation

Abstract Ship fires are recognized as significant maritime incidents that can lead to substantial losses, including loss of life. In events where fires severely compromise a vessel’s structural integrity, the costs associated with comprehensive repairs can be exorbitant, placing considerable pressure on shipowners. Ensuring post-fire structural integrity is paramount. Therefore, it is essential to provide technical considerations that aid shipowners and classification societies in identifying critical areas of a ship’s structure that require replacement. This study aims to investigate the post-fire critical areas of ship structures through numerical fire simulations. By leveraging the properties of steel, which can undergo microstructural changes when subjected to high temperatures and rapid cooling, critical structural areas can be identified based on fire-induced heat exposure. A specific case study involving a fire incident aboard a 7,500 GT bulk carrier, triggered by the failure of an auxiliary engine, is examined. The simulations utilize on-site data and actual post-fire conditions to draw robust conclusions. The insights derived from this research are expected to enhance the understanding of the impacts of fire on ship construction and facilitate more efficient and accurate post-fire inspections.

Forest fire emission estimates over South Asia using Suomi-NPP VIIRS-based thermal anomalies and emission inventory

Emission estimates of carbon-containing greenhouse gases (CO2, CH4) and aerosols (PM2.5) were made from forest fire across South Asia using Visible Infrared Imaging Radiometer Suite (VIIRS) based thermal anomalies and fire products. VIIRS 375 m I-band active fire product was selectively retrieved for the years 2012 to 2021 over forest cover across South Asia. Annual incidence of fire events across South Asia was 0.17 (±0.05) million (M) with robust spatio-temporal heterogeneity. Fire occurrences were mainly concentrated over the forest across Hindu Kush Himalayan region (HKH; 56%), Deccan Plateau (DP) and Central Highlands (CH; 34%). Monthly mean fire incidences emphasize February to May as a typical forest fire season, accounting 90% of annual fire counts. The highest fire pixel density (>1.5 km -2 yr-1) was noted over the tropical dry/moist deciduous and tropical semi-evergreen forests. Strong diurnal nature of fire radiative power (FRP) was evident with >85% of FRP linked to daytime retrieval. VIIRS based Fire Emission Inventory (VFEI, Version 0) was followed to constitute regional emissions from biomass-based fire. Forest fire accounted a yearly emission of 91.58 (±14.76) and 0.25 (±0.04) Tg yr-1 CO2 and CH4 respectively, with 25.14 (±3.94) Tg of cumulative carbon release per year, i.e., roughly 1.3% of global fire-related carbon emission. Fire associated PM2.5 emission rate was 0.60 (±0.10) Tg yr-1, 95% of which emitted during peak fire season as was the case for carbon-containing gases. Forest fire across HKH (75%) and DP+CH (20%) predominately contribute to the regional carbon emission, while also accounting 68% (HKH) and 27% (DP+CH) of fire associated PM2.5 emission budget. With >70% of forest fires within South Asia being typically anthropogenic, forest fire appears to be a major sector of greenhouse gas and aerosols emissions, and necessitate planning and strict legalities to reduce emission load.

Automated Fire Sensing and Fire Extinguisher Module

The Hazard of fire and fire explosions poses significant risks to both property and human safety, necessitating immediate action to minimize damage. Conventional fire detection methods that rely on human observation may result in delays, particularly in unattended areas. To address these challenges, a specialized fire detection and extinguishing system is being developed with the capability to autonomously detect and extinguish fires. This system will also promptly notify individuals through messages and phone calls upon fire detection, improving response times and ensuring immediate awareness of fire incidents. Equipped with Arduino microcontrollers, the system integrates advanced sensors for precise detection of heat and smoke, allowing accurate pinpointing of fire locations. The use of Arduino technology provides adaptable functionality in various environments, ranging from residential to commercial settings. Effective communication of fire alerts is essential for promptly notifying firefighters and occupants, facilitating timely intervention and safe evacuations. The objective is to create an efficient system that harnesses modern technology to enhance fire safety measures, ultimately reducing fire related risks and effectively protecting lives.

EVALUATING THE FIRE PROTECTION SYSTEM AT LAMPUNG CITY MALL USING FAULT TREE ANALYSIS

This study evaluates the fire incident that occurred in the kitchenware storage area on the ground floor of Lampung City Mall, caused by an LPG gas cylinder. The studys objective is to identify the root causes of the fire, assess the adequacy of active fire protection systems, compare them to the applicable regulations and standards, and evaluate the communication hazard in Lampung City Mall. Recommendations for improving safety communication are provided. The findings indicate that the active fire protection system meets 88% of the required standards, which falls under the GOOD category, meaning all elements are functioning properly and in accordance with regulations. As for evacuation safety, the system meets 85% of the requirements, which also falls under the GOOD category. However, the study concludes that there are still several fire safety symbols that urge to be added in order to improve the safety communication at Lampung City Mall.

Fire behavior of composite steel truss bridge girders: numerical investigation and design strategies

Fire pose more severe threat to steel truss bridge girders as compared to common steel plate and box bridge girders. To deeply clarify failure mechanism of fire exposed steel truss bridge girders, this paper presents an investigation on fire performance of composite steel truss bridge girders simultaneously subjected to structural loadings and hydrocarbon fires. A numerical model, developed using the computer program ANSYS, is validated dependent on fire test to trace fire behavior of a typical through-type composite steel truss bridge girders under different hydrocarbon fire exposure conditions. The analysis is applied to evaluate influence of potential fire exposure scenarios occurred in bridge structures, including fire exposure lanes on bridge deck and fire exposure length beneath bridge, on temperature and structural response in steel truss bridge girders. The results shows that fire exposure lanes on bridge decks and fire exposure length beneath bridge has a significant influence on fire performance of steel truss bridge girders. Fire exposure on all lanes and side lanes can cut down fire resistance highly as compared to fire exposure on mid-lanes. The composite steel truss bridge girders exhibit special multi-hinge failure modes when fire exposure under bridge. Further, the composite steel truss bridge girders exposed to side-lane fire exhibit significant transverse torsional deformation. The established failure criteria dependent on structural deflection limit states, chord deformation and strength can be applied to evaluate fire resistance of actual composite steel truss bridge girders under realistic fire exposure scenarios. Limiting the minimum clearance of passage on bridge deck and increasing fire protection measures in upper portion of trusses can effectively improve fire resistance of through-type composite steel truss bridge girders. Some predominant design strategies closely related to oil tanker trucks traversing composite steel truss bridge girders are proposed to minimize probability of fire incidents on bridge and keep integrity of structure in the case of fire to the maximum extent possible.

Web-based spatial decision support system for optimum route to forest fires: A case of Viphya plantations

Efficient access to fire incidents is crucial for successful firefighting operations. This study aimed at developing a web-based spatial decision support system (SDSS) to determine optimal routes to forest fires and risk zones in the Viphya Plantations, Malawi. The system integrates remote sensing analysis to identify fire risk zones and a web-based SDSS to suggest optimal response routes. Remote sensing data was used to map areas prone to forest fires based on factors such as land use/cover type, terrain, and anthropogenic activities. These risk zones were incorporated into the GIS routing decision support system, enabling the generation of optimal routes from fire stations to fire risk zones and reported fire cases. System testing demonstrated the SDSS's capability to provide optimum routing options targeting fire risk hotspots and reported incidents within the plantations. The SDSS facilitated the identification of optimal routes to mitigate transportation costs and provided insights into spatial patterns of fire vulnerability, revealing areas that may be inaccessible within the optimal timeframe. This highlighted the necessity of establishing additional fire stations in high-risk regions to enhance rapid response times. The web-based SDSS proved to be an effective decision support tool for optimizing resource allocation and improving emergency response coordination for fighting forest fires in the Viphya Plantations.

Vapor Pressure Deficit Controls the Extent of Burned Area Over the Himalayas

AbstractGlobally, increasing occurrences of forest fires are major threats to the ecosystem. The rich forests in the Himalayas also suffer from high incidents of forest fires in the pre‐monsoon summer months, March to June. Research studies are limited in identifying the meteorological factors governing the spatiotemporal distribution of forest fires. Using three satellite‐based data sets of monthly burned area (BA) for March to June, we found higher BA in the Eastern Himalayas (EH) compared to the Central (CH) and Western Himalayas (WH). Using statistical methods, we found Vapor Pressure Deficit (VPD) to be the most dominating variable controlling BA in the Himalayas. Precipitation, soil moisture and temperature, with their relative variability, control VPD that governs the interannual and intraseasonal variations of BA. Our results imply that a good forecast of VPD will facilitate alert generation for the Himalayan forest fires.

Health benefits of reduced deforestation in the Brazilian Amazon

The conversion of tropical forests in the Amazon region for agriculture and other land uses is associated with health risks linked, for example, to air and water pollution from forest fires and agrochemical use. Several conservation policies introduced in the 2000s aimed at reducing deforestation in the Brazilian Amazon. Here we exploit variations in the regional targeting of these policies to measure human health externalities of conservation policy enforcement using a double-difference approach at close distance to the Amazon biome border. We find that the change in deforestation pressure reduces forest fire incidence. As a consequence, fine particulate matter concentrations in the air—a main vector for adverse health effects of fire smoke—also decrease. This leads to a reduction in the hospitalization and death prevalence rate due to respiratory health problems and other health benefits for the local population.

Evaluation of the Domino Effect Caused by Pool Fires in a Tank Farm

Major hazard installations (MHIs), such as oil refineries, petrochemical plants, and terminals, use large-capacity storage tanks for storing crude oil and by-products. Pool fire is one of the most common types of storage tank fire incidents. This technical article aims to investigate the domino effect resulting from a pool fire in a tank farm consisting of eight large floating-roof storage tanks, with a focus on four specific tanks. A crude oil storage tank was selected as the primary tank (source tank). Point source and plume solid models were used to estimate the thermal radiation. It has been noted that the thermal radiation from the source tank to the adjacent tank in the same dike exceeds the threshold heat radiation level and might result in a domino effect; however, the thermal radiation from the source tank alone does not reach the threshold level for the tanks in the other dike. Additionally, it was found that the thermal radiation from both the primary and secondary tanks just reaches the threshold level for the farther-away tank in the other dike. The domino effect occurs provided that the firefighting system is not activated and the emergency response team does not intervene within ten minutes.

Fire Fighter Robot Using IOT and Mobile Application

In today's fast-paced world, fire hazards pose significant risks to life, property, and the environment. Traditional fire detection systems often rely on human intervention, leading to delays in response time and exacerbating the damage caused by fire incidents. Our project, the IoT-Based Automatic Fire Detection and Extinguisher Robot, addresses this challenge by utilizing a combination of modern sensor technology, robotics, and IoT to provide an autonomous and real-time solution. The robot is equipped with flame and temperature sensors that allow it to detect fires at an early stage. Once a fire is detected, the robot activates its movement mechanism using DC motors to navigate toward the fire while the integrated servo-controlled water pump precisely sprays water to extinguish the fire. In addition to automatic firefighting, the robot features obstacle detection using ultrasonic sensors, ensuring safe navigation in complex environments. The system includes Bluetooth and Wi-Fi communication, allowing for remote control via an Android mobile app. This app provides both manual and automatic control options and sends real-time fire alerts when the robot detects a fire. This autonomous system minimizes human intervention, speeds up response times, and reduces fire damage effectively. The robot is powered by an ESP32 microcontroller, which processes data from the sensors and controls the motors and water pump. The rescue pod feature allows the robot to perform additional operations like transporting sensitive materials during emergencies. The system's IoT functionality enables real-time alerts and remote monitoring, enhancing its capability as a scalable and cost-effective solution for residential, commercial, and industrial fire safety.

Electric cooktop fire incidents in Finland

Cooking related fires contribute to one-fourth of residential building fires in Finland. However, their prevalence is often underestimated in statistics due to underreporting when individuals manage situations without fire service assistance. Despite their significance, cooktop fires remain inadequately studied, impeding our understanding of residential fire safety and the advancement of effective prevention measures. This study aims to provide a comprehensive evaluation of electric cooktop safety in Finland. It explores factors undermining safety, analyses materials contributing to hazards, assesses financial damages, and scrutinizes typical cooktop fire scenarios and prevention methods. Utilizing data from statistics (2016–2022), Safety Investigation Authority reports (1998–2022), media reviews (1.7.2020–30.6.2023), and insurance data (2017–2020), supplemented by two survey studies, this research identifies consistent causative factors across multiple data sources. Common factors include excessive items left on cooktops, unattended cooking, and unintentional activation of cooktops. Approximately three-quarters of cooktop fires go unreported to fire services, suggesting a significantly higher prevalence than recorded in statistics. Moreover, minimal use of stove safety devices exacerbates the issue. According to insurance company data, the costs caused by cooktop fires are significantly higher than those reported in official statistics. Implementing existing technology is crucial for reducing the frequency and consequences of these fires.

Estimate of Fire Safety Management in Residential Buildings: A Structural Equation Modeling (SEM) Approach

The devastating consequences of fire incidents have brought global attention to the need for a thorough understanding of the factors responsible for this menace in order to provide a lasting solution. Poor fire safety management in buildings contributes to our societies’ increasing susceptibility to fire disasters. Nigeria, like every other nation in the world, has experienced a number of fire incidents over the years, most of them occurring in residential buildings. Thus, the study aimed to estimate fire safety management in buildings that provide accommodation and sleeping facilities for individuals and/or households, such as apartments, hotels, and hostels, which are referred to as residential buildings. The study was conducted to fill the gaps in the existing literature and provide relevant policy recommendations to address the challenges in fire safety management. The study employed a cross-sectional research design. Primary data were collected from a random selection of one hundred and eighty respondents, including one hundred and twenty (120) building occupants, twelve (12) hostellers, and forty-eight (48) hoteliers, using a well-structured questionnaire. Descriptive statistics and structural equation modeling (SEM) were used to analyze the dataset collected. The study’s findings indicate that fire safety awareness, households/management commitment to fire safety policies and standards, and fire safety practices have significant positive impacts on fire safety management in residential buildings. Conversely, the cause of fire incidents has a significant negative impact on fire safety management in residential buildings, with P-values less than 0.05 under the regression weights. Additionally, the study revealed that the majority of fire incidents in residential buildings stem from human carelessness, errors, poor human behaviors, and malfunctioning mechanical and electrical equipment. Furthermore, the study showed that achieving fire safety management objectives in residential buildings requires a greater awareness of fire safety, a commitment to fire safety policies and standards, and the implementation of fire safety practices among residents, hoteliers, and hostellers. The study thus recommends that residents, hostellers, and hoteliers should adopt a positive attitude towards fire safety management; prioritize fire safety training, fire risk assessment, and routine maintenance of fire safety equipment; ensure the use of surge protectors for electrical equipment; and establish a well-planned and organized emergency action plan and evacuation procedure, complete with proper documentation, to create a standardized system for preventing, mitigating, preparing for, and responding to fire emergencies. Similarly, the fire service should intensify public enlightenment on fire safety management with strict enforcement of fire safety policies and standards to ensure uncompromised fire safety practices and effective fire safety management in buildings.

Multi-Sensor Photoelectric Fire Alarm Device Implementation for Early Fire Detection in Campsites

With the growing popularity of leisure activities such as camping and glamping, the incidence of fires at camping sites has increased. This study focuses on improving the effectiveness of photoelectric fire alarm devices by incorporating temperature and humidity data for early fire detection in confined spaces, such as campsites. This study proposes a novel multi-sensor fire alarm system that dynamically adjusts fire detection threshold values based on temperature and humidity data collected by unmanned automatic weather observation systems. The prototype, which was implemented using Raspberry Pi and multiple sensors, demonstrated approximately 20% faster fire detection speed than existing photoelectric fire alarm systems, as verified through experiments in a simulated camping environment. The proposed approach is expected to advance fire alarm systems, enabling faster and more accurate fire detection in diverse environments, particularly at campsites.