Fire Risk Assessment Methods

risk assessment has always been a challenging issue. Furthermore, performance based approaches to fire engineering showed that risk based decisions and fire scenarios are a fundamental element of the fire safety strategy assurance. In particular, a correct assessment of the risk allows all the involved stakeholders to identify a specific strategy among a pool of possibilities. Risk assessment is the perfect tool to identify comparable fire protection strategies and to measure fire risk reduction associated to the single specific prevention and protection measures composing each different fire strategies. This approach implies the need to abandon a classic, not even conservative approach, that in many cases linked the total fire load to the fire risk level, despite specific dynamics, layouts, prevention measures and risk management issues during time. During the years, a number of different methodologies have been developed: for specific cases, for industrial or civil buildings, to adopt a method enforced by the local law and regulations acts, etc. Methods have been based on matrices, indexes, check-lists, etc. Present paper illustrates a method developed by the authors taking into account several international recognized methods; even coming back to methodologies developed in early seventies. The Method is named (Fire risk Assessment Method for Enterprises), it goes back to the fire safety fundamentals against a generalized approach to fire safety engineering based on complex and time-consuming methods like CFD that deals only with the ‘consequences' aspect of the fire risk (that is indeed characterized also by frequency estimation) using as reference scheme the Fire Safety Concept Tree explained in detail in the NFPA 550 Standard. In order to identify the most appropriate fire safety strategy it is important to identify the associated fire risk that the strategy is intended to mitigate to a certain level. Alternative solutions can be evaluated considering the risk reduction operated by different strategies and by different elements composing the fire strategies themselves and also costs with a modern ALARP approach. A clear advantage is the possibility to get an overview of the whole fire risk as the cumulative risk assessed by the model and not solely related with the consequences evaluation of a limited number of fire scenarios (usually the most obvious ones). Risk level assessment leads to the identification of the fire scenario (or a pool of) that governs and limits the specific situation, declined for both humans and structures (assets) considering that the two vulnerabilities could be linked to different fire risk scenarios. The method has been tested against different buildings occupancies. In the present case results of the FLAME method application to hospitals and health-care facilities are reported. A fire compartment-based risk estimation has been conducted on an overall of about 300 compartments (overall size of about 60000 m 2 ). Coherence has been found among risk estimation by FLAME parametric code and prescriptions of the Italian fire code. There is good agreement when assessing the RSET with the method proposed in FLAME, dealing with the occupants' behaviour and the actual characteristics of occupants in clinics or hospitals and difficulties due to poor mobility or incapacity to understand emergency cues.

In this investigation, we developed a methodology for inclusion of fire protection and used a methodological approach for fire risk assessment. Present practice of fire risk assessment and prevention measures in the Republic of Serbia is not systematic. To develop a methodological approach of fire risk assessment, a modified matrix for fire risk factors was set up that combines the implementation of modified Delphi and checklist methods into a risk matrix based on the Allgemeine Unfall Versicherungs Anstalt and Berufs Genossenschaften methods. An efficient and rapid fire risk assessment was enabled by the application of our fire protection project solution software of SAFOFP. The results of the investigation were validated by the concrete timber warehouse case study. This fire risk assessment method is applicable to other branches of industry as well as other places aside from Republic of Serbia where the study was conducted.

A fire risk assessment has always been a challenging task. Performance-based approaches to fire engineering have shown that risk-based decisions and fire scenarios are fundamental elements that must be considered in fire safety strategies. A correct assessment of the fire risk allows all the involved stakeholders to identify a specific strategy from among a variety of possibilities. A risk assessment is the best tool to identify comparable fire protection strategies and to measure the reduction in fire risk that can be obtained with each specific prevention and protection measure, i.e., by means of different fire safety strategies. The present paper illustrates a method that takes into account several well-known methods, even some that were developed as far back as in the early seventies. The method is named “FLAME” (Fire Risk Assessment Method for Enterprises). FLAME considers fundamental fire safety aspects instead of making use of sophisticated and time-consuming methods like CFD. FLAME uses the “Fire Safety Concept Tree”, which is explained in detail in the NFPA 550 Standard, as a reference scheme. The method allows the risk to the occupants to be evaluated separately from the risk to the building. Over the years, we have tested the method considering different kinds of buildings and occupancies. We here report the results of an application of the FLAME method to hospitals and health-care facilities. Overall, about 300 compartments (overall size of about 60,000 m2) were analysed, including two hospitals of about 200,000 m2 each. The results of the risk estimation with the FLAME code have been found to be coherent with Italian fire code prescriptions. About 44% of the compartments were defined as being at a Medium risk and 39% as being at a high risk (according to the Italian Fire Code). More than 60% of the hospital compartments were defined as being at a High risk. A good agreement was obtained between the RSET results with those of the method proposed in FLAME when using the current performance-based regulation criteria. The RSET estimation in FLAME considers the occupants’ behaviour and the actual characteristics of the occupants in clinics or hospitals, who often have difficulties due to reduced mobility or an incapacity to understand emergency instructions.

The occurrence of intelligent building fires causes huge economic losses to the country and society, and even people’s safety. It is necessary to accurately assess the degree of intelligent building fire risk so that the fire emergency management department can make scientific decisions. In this paper, a trustworthy classification model for intelligent building fire risk is proposed, which provides a scientific and reasonable model supporting the classification assessment of intelligent building fire risk. The model integrates Bayesian Network (BN) and software trustworthy computing approach. BN is used to calculate the risk value of attributes that describe the fire risk situation of the intelligent building from 7 profiles. Based on the fire risk attribute values, trustworthy computing is adopted to classify the fire risk into 5 ranks which indicates the severity degree of building fire risk: the higher the rank is, the greater the harm is. Taking the Shanghai Jing’an 11.15 fire as an example, the result confirms that the method proposed in this paper has good theoretical significance and practical value. In addition, we compare our method with 3 fire risk assessment methods in the reference. The comparisons illustrate that the trustworthy classification model proposed in this paper is more comprehensive, rational, and scientific.

Establishing fire historical data and index system is the key to solving the fire risk assessment problem. Based on this, this paper proposes a new fire risk assessment method. Firstly, aiming at the imbalance problem of fire history data, SMOTE algorithm is used to expand the small class of sample data and build an improved fire sample data set. Secondly, the improved fire data and expert knowledge are used to learn the structure and parameters of the Bayesian network. Finally, the risk assessment value is determined through the probabilistic inference of the Bayesian network. Applying this method to building fire risk assessment can effectively solve the problem of unbalanced fire data and improve the level of fire risk assessment.

Understanding and mitigating fire risks in healthcare settings are crucial for ensuring the safety of individuals, especially during the current pandemic, which has increased the use of oxygen-supply equipment and potentially raised fire hazards. This case study, conducted in two university hospitals in Semnan, Iran, examined fire risk factors in healthcare facilities using a developed fire risk assessment method. A total of 28 wards and 74 compartments were assessed. Data collection included topographical structure analysis, building usage evaluation, and process documentation review. The FRAME method, validated in previous studies, was used to calculate fire risk levels for buildings, contents, occupants, and activities. The fire risk assessment revealed varying risk levels across different wards and compartments in the two hospitals. Hospital A exhibited higher fire risk levels compared to Hospital B, with several wards in Hospital A classified as "High" or "Very High" risk. Factors contributing to higher risk levels included building design, occupancy density, and the presence of flammable materials. Occupants in certain wards, particularly those with high occupancy rates and limited evacuation routes, were identified as being at increased risk. Activities such as the storage and handling of flammable materials were also found to contribute to elevated risk levels in specific areas. The study emphasizes the importance of implementing targeted fire safety measures, especially regarding oxygen-supplying equipment, high-density ventilators, and limited escape routes, to mitigate risks effectively in healthcare settings. This comprehensive assessment can guide best practices in fire safety management in hospitals.

Precaution and preparation, as established in emergency plans, are the most effective means of disaster mitigation and heritage protection. Emergency plans should include evaluation of cultural heritage assets, including buildings, both contents and structures, as well as surroundings and landscapes. These frameworks are based on common experience and reflect viewpoints shared worldwide. However, due to regulations imposed in Taiwan, it is difficult to achieve the goal of preserving cultural and historical heritages. This project analyzes the fire risk assessment of historical architectures and develops a new fire risk assessment method, as well as improved protection recommendations for Lukang Lung–shan Temple, an important national heritage property in Taiwan. The survey techniques and assessment procedures used in this case study can also be modified and applied to all heritage buildings. This enables heritage property managers and supporting organizations to construct fire emergency preparation and damage control plans suitable to a specific case.

Fire risk assessment is an important part of fire science and system safety engineering. “FRAME” means Fire Risk Assessment Method for Engineering. It is a widely used and comprehensive building fire risk assessment method based on a fixed index system, and compared with other methods, FRAME method can avoid artificial subjective influence, and it is more convincing. The paper discusses the advantages and calculation methods of FRAME, and takes a commercial building in Shijiazhuang as an example. By using the method, the fire risk of the building is evaluated and the strengthened fire protection measures are proposed based on the method.

To resolve all kinds of fire emergencies in the ship's engine room, increase the ability of fire risk source rectification and emergency-disposal, improve the problem in current risk assessment method including the complexity and poor targeting, huge difference between the calculation results and expected goal, the analytic hierarchy process (AHP) was used to determine weights of a ship engine room fire risk source, in this work. Fuzzy comprehensive evaluation method was used to evaluate the current engine room fire risk. The results show that the order of fire control optimization for a certain type of ship is high temperature object, electrical equipment, chemical or mechanical heat energy. Through the study on fire risk assessment method of ship engine room, this work provides scientific basis for improving engine room fire control ability.

Large spaces, such as warehouses where internal loads are stored, exhibit higher fire loads and faster fire growths than general fires. In addition, the volume of the internal load reduces the space required for the smoke to stay, thereby accelerating the decline in smoke height. To prevent fire hazards in such spaces, it is necessary to evaluate the fire risk during the design stage. However, it is difficult to evaluate various settings because the evaluation method using the existing computational fluid dynamics utilize considerable amount of time. In this study, an algorithm was developed to evaluate the internal loads by using formulas related to the existing fire risk assessment. The developed algorithm is designed to easily calculate the detection time of the detector, smoke fall time, and sprinkler operation time. This algorithm could be used to design an optimized fire protection system in the initial design stage.

According to the characteristics of fuzziness and uncertainty in fire risk assessment of urban Bridges, this paper proposes a fire risk assessment model of urban Bridges based on fuzzy bayesian network. First of all, the factors are summarized into three sub-networks: risk source, risk carrier and disaster prevention and reduction control state. Then, the prior probability of bayesian network is determined through data investigation and expert scoring. Finally, the use of bayesian network to evaluate example project, get the bridge highway to fire risk level for "III". The results of this paper are consistent with the actual situation, which verifies the practicability and effectiveness of fuzzy bayesian network risk assessment.

Using the statistical data on fires in Russia, the study concludes that it is necessary to assess fire risks for preschool and educational institutions. The factors influencing the occurrence of fires are considered. Tools and resources for predicting fire risks are described. The methodology of assessing fire risks for preschool and educational institutions is analyzed. A fire risk for the facility under study is caluclated. The calculation is based on the method of constructing “bounce” trees, successfully used in the graph theory. The key event is a fire, the risk of which is etermined. The logic elements “and”, “or” and “inverter” are used in the construction. The block diagram has several levels - from the key to the simplest failures. The advantage of this scheme is described. In addition to the main fire risk for the facility, the professional risk is caluclated. Taking into account the result, measures aimed to ensure fire safety at these facilities are suggested. The article concludes that it is necessary to use the fire risk assessment method.

The magnetohydrodynamics (MHD) model of the alternating current (AC) arc is complex, so a simplified equivalent heat source (EHS) model can be used to replace the complex model in studying the AC arc's thermal characteristics and cable fire risk. A 2D axisymmetric AC arc MHD simulation model in the short gap of a copper-core cable is established in this paper. The AC arc voltage and current obtained by the model are consistent with experiments. The AC arc's heat source distribution obtained by the MHD model is fitted to obtain the heat source function Q of the AC arc. Q is divided into 16 independent segmented heat sources, and a correction matrix is constructed to optimize the segmented heat sources. A neural network and a genetic algorithm give the prediction model and the optimal correction matrix of the segmented heat source. The EHS model optimized by the optimal correction matrix can obtain a minimum temperature error of 5.8/4.4/4.2% with the MHD model in different AC arc peak currents 2/4/6 A. The probability of a cable fire is calculated by using AC arc's optimized EHS model when different numbers of AC arcs are generated randomly in AC half-waves. The EHS model can replace the complex MHD model to study the thermal characteristics of AC arcs and quickly calculate the probability of a cable fire caused by random AC arcs.

This report documents an experimental program designed to investigate high energy arcing fault (HEAF) phenomena for medium-voltage, metal-enclosed bus ducts and switchgear. This report covers full-scale laboratory experiments using representative nuclear power plant (NPP) three-phase electrical equipment. Electrical, thermal, and pressure data were recorded for each experiment and documented in this report. This report covers experiments performed on two medium-voltage switchgear units and eight non-segregated phase bus ducts. The data collected supports characterization of the medium-voltage HEAF hazard, and these results will be used to complement the data used for HEAF hazard modeling tools and support potential improvements in fire probabilistic risk assessment (PRA) methods. The experiments were performed at KEMA Labs in Chalfont, Pennsylvania. The experimental design, setup, and execution were performed by staff from the NRC, the National Institute of Standards and Technology (NIST), Sandia National Laboratories (SNL) and KEMA Labs. These experiments were sponsored by member countries of the HEAF 2 international agreement under the auspices of the Organisation for Economic Co-operation and Development (OECD). The HEAF experiments were performed between August 22 and September 2, 2022. The HEAF experiments were performed on two near-identical units of General Electric metal-clad medium-voltage switchgear and eight units of non-segregated phase bus duct. A three-phase arcing fault was initiated on the equipment’s bus bars. These experiments used nominal system voltages of either 4.16 kV (AC) or 6.9 kV (AC). Arc durations in the experiments ranged from approximately 2 s to 4 s with fault currents ranging from approximately 28 kA to 32 kA. Real-time electrical operating conditions, including voltage, current, and frequency, were measured during the experiments. Heat fluxes and incident energies were measured with plate thermometers and slug calorimeters at various locations around the electrical enclosures. Particulate samples were taken for subsequent analysis. The experiments were documented with normal and high-speed videography, infrared imaging, and photography. Insights from the experimental series include timing information related to enclosure breach, event progression, mass loss measurements for electrodes and enclosures, peak pressure rise, along with visual and thermal imaging data to better understand and characterize the hazard. These results will be used to evaluate the adequacy of existing HEAF hazard modeling tools and for potential improvements to fire probabilistic risk assessment methods related to HEAF.

Fire Risk Assessment Method: