Fire Engineering Research Articles

Smart fire detection analysis in complex building floorplans powered by GAN

Ceiling-mounted fire service systems are the most widely used provisions to ensure building fire safety. Current design distribution of fire detectors is based on semi-empirical correlations derived from open-floor fire experiments, but building floorplan affects their activation. This work develops a generative adversarial network (GAN) model to achieve accurate and real-time fire detection analysis for buildings with complex floorplans. A numerical fire database with hundreds of floorplans, fire locations and ceiling heights is established to train the GAN model. The pre-trained model can recognize geometric characteristics and reveal hidden fire dynamics laws. Given any building floorplan and fire detector distribution, the model can predict ceiling temperature, velocity and soot density fields with an accuracy of 88% in a second and detection time with 95% accuracy. The proposed GAN model enables a smart fire detection analysis, reduces the fire engineering design cost, and improves fire safety for complex buildings.

Cost-benefit analysis in fire safety engineering: State-of-the-art and reference methodology

Cost-effectiveness is a key consideration within fire safety engineering. Currently, different approaches are being applied in literature. These approaches differ in how cost-effectiveness is evaluated, which costs are considered, and how the preferred design solution is defined. Recognizing this issue, the Fire Protection Research Foundation enrolled an international team of researchers, supported by a broad stakeholder panel, to develop a reference methodology. In this paper, this reference methodology for cost-benefit analysis in fire safety engineering is presented following an extensive literature review. The methodology clarifies the minimum requirements for assessing cost-effectiveness, and highlights that only a present net value evaluation can be used to compare design alternatives. Commonly used cost-benefit ratios should only be used when deciding on the effectiveness of a single package of fire safety measures. An illustrative case study demonstrates the application of the methodology and shows how designs based on cost-benefit ratios can be sub-optimal when evaluating multiple possible fire safety measures.

Comparative pyrolysis characteristics and kinetics of agricultural food grains by thermogravimetric analysis

Pyrolysis precedes the development of smouldering or flaming fires in storage and processing facilities. Understanding this process and determining the parameters that characterise it is essential for controlling fires. This study analysed the pyrolysis of African food grains that are important for food security but historically have received limited attention. Cowpeas, lentils, millet, soybeans, unshelled peanuts, flax, sunflowers, shelled peanuts, and sesame were subjected to thermogravimetry in a nitrogen atmosphere at heating rates of 5, 10, 20, and 40 °C/min from ambient to 600 °C. All grains were completely dehydrated at 170 °C and started decomposing at about 180 °C. The decomposition patterns varied with the relative proportion of hemicellulose, cellulose, protein and, particularly, lipids (oil content). Pyrolysis rates peaked at lower temperatures of about 300 °C for non-oil grains but at higher temperatures of 400 °C for oil grains. Friedman and Coats-Redfern methods were used to determine activation energies (130–355 kJ/mol), preexponential factors (8.1 × 107–1.0 × 1031 s−1) and the numerical values of the complex, multistep reaction models. Oil grains (or their powder) generally have lower activation energies, are thus more reactive than non-oil grains, and therefore constitute critical consideration for fire safety in processing facilities. The work is important for developing fire engineering solutions for food facilities based on quantitative fire behaviour data.

Experimental study on fire characteristics of sidewall fires in a long-narrow compartment with multiple lateral openings

This experimental study delves into the fire characteristics within a long and narrow compartment equipped with multiple lateral openings. The investigation encompasses aspects such as radiant heat flow, temperature distribution, and smoke layer height. The presence of lateral openings introduces asymmetry in suction, resulting in augmented radiative heat flow on the rear side of the fire source compared to the front and left sides. Smoke stratification remains stable, with minimal temperature influence from the fire source power at one opening and negligible impact at the other. Employing a customized two-dimensional method for thermal estimation, our experimental data display lower results than previous predictions due to structural disparities. The utilization of the N-percentage rule unveils two discernible regions in smoke layer height behavior: stable and decreasing, a pattern consistent across varying heat release rates. These insights offer valuable predictive tools for discerning fire characteristics in elongated, restricted compartments with multiple lateral openings. Consequently, this study enhances comprehension and informs safety measures within such configurations, contributing to the broader field of fire safety engineering.

Scaling laws of plume-induced granular cratering.

Extraterrestrial landing often requires firing a high-speed plume towards a planetary surface, and the resulting gas-granular interactions pose potential hazards to the lander. To investigate these jet-induced cratering dynamics, an experiment campaign covering a range of gas and granular properties relevant to the lunar and Martian environments was conducted in a large-scale vacuum chamber. Despite the variations in jet Mach number, mass flow rate, and composition of the granular phase investigated in this work, the observed time evolution of crater depth displays a consistent transition from an early-stage linear to a late-stage sublinear growth. To explain these scaling relations, a model that relates the kinetic energy gained by the particles per unit time to the power of the impinging jet is introduced. From this model, erosion rates and the critical depth at which the transition occurs can be extracted, and they are shown to depend on the gas impingement pressure, which was varied by changing ambient pressure, jet Mach number, mass flow rate, and nozzle height above the surface. These results highlight key mechanisms at work in the dynamics of plume-induced cratering and help to develop an understanding of optimal rocket engine firing times for future landings.

ALGORITHM FOR APPLICATION OF METHODS FOR DETECTING CENTRAL SIGNS OF AN EMERGENCY SITUATION DUE TO FIRE AT CRITICAL INFRASTRUCTURE FACILITIES

The work is devoted to the solution of an actual scientific task in the field of civil protection, namely, the development of an algorithm for the application of the technique of detecting focal signs of an emergency situation due to a fire at critical infrastructure facilities. Recommendations for the practical application of the methodology as the basis of the method of non-destructive control of the processes of preventing emergency situations due to a fire of a terrorist nature at the objects of critical infrastructure of Ukraine are given. the algorithm for the application of the method of detecting focal signs of an emergency situation due to a fire at critical infrastructure facilities consists of three procedures, namely: procedures for conducting measurements at a critical infrastructure facility, procedures for statistical processing of measurement results, fire reconstruction procedures. The received general recommendations of the fire reconstruction procedure can be reduced to the following. In particular, we note that the value of the electrical resistance of soot is related to the mode of combustion in one or another zone. If this value, which was measured directly above the investigated area, exceeds 10101011 Ohm, then this indicates that there was no intense flame burning in this area, but the burning took place in the form of smoldering. Long-term smoldering of a fire load in conditions of insufficient air exchange can lead to the formation of a thick layer of greasy soot on the ceiling and in the upper part of the walls, sometimes with clear drops of the liquid phase or drop-like spots. This can be observed in small rooms and other volumes that are not ventilated. If the combustion moves from such premises to a larger space with better air exchange, and a flaming combustion occurs, then the formed electrical resistance pattern will mainly reflect the development of flaming combustion. The source of the fire may appear in the form of soot burning or extremely low values of its electrical resistance, or vice versa, in a rather thick layer of soot with a high content of extractive substances. Thus, the interpretation of the results of the measurement of electrical resistance must be accompanied by an analysis of the specifics of the volume-planning decisions of the building (room), the conditions of air exchange, and the distribution of the fire load. The obtained results of the soot research can be used within the framework of fire engineering expertise to reconstruct the process of the occurrence and development of combustion, including to establish the center of the fire. Keywords: emergency situation, critical infrastructure object, technique, focal signs, thermal damage.

Acoustic sources identified using a microphone phased array during a rocket engine test

A new phased array of microphones, suitable for the harsh environment of a rocket launch, was built and tested during a static firing of an RS-25 engine. It uses 70 piezo-resistive, dynamic pressure sensors, optimally distributed on a 10.5-ft diameter open frame dome structure and has a 200-ft long cable bundle to carry the signals to a weather-protected cabinet containing the data systems. The test stand was imaged using an infra-red camera and a visible wavelength camera, and the beamformed noise maps were superimposed on the photographs. The first-time data from a full-scale engine test stand showed that the plume deflector at the bottom of the engine was the primary noise source. The openings of the test stand around the nozzle exit were also found to be noise sources particularly at higher frequencies. The final goal is to utilize the array during NASA’s Artemis-II launch at Kennedy Space Center.

LOCALISED FIRE ASSESSMENT OF A STEEL STRUCTURAL SOLUTION IN A PILOT BUILDING

AbstractMany tragic fires in the past decades have highlighted the importance of fire safety engineering and its meaningful application in the engineering field. With a constant and significant growth of the research the classical approach based on prescriptive time‐temperature curve, where the gas temperature is assumed to be constant within the entire compartment and always increasing on time has been challenged by a performance‐based one. Performance‐based approach is aiming to represent the fire accounting for more physics than the prescriptive approach, considering ignition, fire growth burning and cooling phase. Nowadays practitioners facing the design stage of a project have to face the choice between designing with prescriptive or performance‐based approach. In this work a comparison between design using performance based and a prescriptive approach will be provided. In particular, the building is under development in the framework of a demonstration RFCS (Research Found for Coal and Steel) project called DREAMERS, founded by the European Commission. The chosen structure for this example is an 800 m2 steel building, which will be built in the Campus of the University of Salerno (Italy). The main peculiarity of the building is the implementation of all the most advanced technologies for the construction of a resilient structure in terms of seismic, robustness and fire safety. The building is designed in steel and steel composite solutions, following a holistic design approach and foreseeing a life time monitoring of its behavior. The flooring system is made of Asymmetric Floor Beams (AFB) and Cofradal® 260, whereas vertical elements are hot rolled HEB sections. The work here presented is showing some of the main challenges related to the fire design as well as application of next generation localised fire models.

Experiments on the Application of Class A and B Fires to Derive the Optimum Air Ratio of Compressed Air Foam Systems

This experiment was designed to increase the utilization of fire engines equipped with compressed air foam systems (CAFS) at the scene of a fire. The purpose of this experiment was to determine the optimum air ratio for the CAFS. Wood crib fires (class A) and steel pan fires (class B) were both extinguished using synthetic surfactant CAFS installed in a fire engine. According to the temperature drop rate (°C/s), the optimum air ratio was thirteen and five in the class A and B fires, respectively. The results derived from this experiment can be used to strengthen fire scene response capabilities.

Investigation on the temperature variation of novec-1230 and halon 1301 in a discharge system

The flow inside the aviation engine fire extinguishing system is complicated due to its transient, two-phase and compressible nature. Temperature is one of the important variables of the flow, because it reflects the thermal respect of the physics. However, detailed analysis on the temperature variation during the discharge process is in absence. In this article, factors influencing temperature were analyzed, based on experimental experiments using halon1301 and novec1230. The temperature variation is found to be mainly influenced by the following factors: (1) the pressure gradient in pipe and gas fraction of the flow, (2) the relative magnitude of pressure work rate and convection, (3) pressure undershoot. The negative pressure gradient in the pipe, combined with the raising of gas fraction, leads to a sharp temperature drop of about 50 °C/s in the pipe. This process stops when the magnitude of pressure work is diminished, then heat convection from the pipe wall starts to dominate. Pressure undershoot is observed only in experiments using halon1301. The temperature drops of 6.1–9.8 °C in 0.01 s during the pipe pressure undershoot, and drops 12–14.2 °C in 1 s during bottle pressure undershoot.

Perancangan dan Analisis Konstruksi Mekanik pada Robot Pemadam Api Hexapod Menggunakan Metode Finite Element Analysis dan Inverse Kinematics

Perancangan dan Analisis Konstruksi Mekanik pada Robot Pemadam Api Hexapod Menggunakan Metode Finite Element Analysis dan Inverse Kinematics

A primer and success stories on performance-based fire design of structures

PurposeThe extreme nature of fire makes structural fire engineering unique in that the load actions dictating design are intense and neither geographically nor seasonally bound. Simply, fire can break out anywhere, at any time and for any number of reasons. Despite the apparent need, the fire design of structures still relies on expensive fire tests, complex finite element simulations and outdated procedures with little room for innovation. This paper aims to discuss the aforementioned issues.Design/methodology/approachThis primer highlights the latest state of the art in this area with regard to performance-based design in fire structural engineering. In addition, this short review also presents a series of examples of successful implementation of performance-based fire design of structures from around the world.FindingsA comparison between global efforts clearly shows the advances put forth by European and Oceanian efforts as opposed to the rest of the world. In addition, it can be clearly seen that most performance-based fire designs are related to steel and composite structures.Originality/valueIn one study, this paper presents a concise and global view to performance-based fire design of structures from success stories from around the world.

Multi-sensor signals multi-scale fusion method for fault detection of high-speed and high-power diesel engine under variable operating conditions

Detecting faults in high-speed and high-power diesel engines under complex variable operating conditions is highly challenging. Online vibration monitoring systems have been used in such diesel engines in key fields, in which vibration sensors are installed on each cylinder to enable comprehensive monitoring. In this paper, a fault detection method for diesel engines under variable operating conditions is proposed based on multi-sensor signal multi-scale fusion. Firstly, a preprocessing framework is established for the raw vibration signals collected from each cylinder to eliminate random interference and system noise. Then, the resulting signals are phase-aligned based on the engine firing sequence and analyzed using a signal correlation algorithm to produce a multi-sensor multi-scale similarity matrix (MSMSSM). Finally, a multi-branch residual convolutional neural network (MBRCNN) model is constructed with the MSMSSM as the input to detect abnormal health states of the diesel engine. Fault simulation experiments are conducted on a 12-cylinder V-type high-speed and high-power diesel engine test rig. The comparative test results indicate that the proposed MSMSSM-MBRCNN method shows both the highest accuracy of 95.28% and the lowest standard deviation of 3.57% compared to other typical methods. The multi-sensor signals multi-scale fusion method proposed in this paper fully utilizes the key information that remains basically consistent in the synchronous acquisition signals of multiple sensors under different operating conditions. This can effectively reduce the interference of operating condition changes and improve the accuracy and robustness of fault detection.

A framework for performance-based assessment in post-earthquake fire: Methodology and case study

Post-earthquake fire (PEF) is a threatening hazard triggered immediately after an earthquake, resulting in extensive destruction and casualties. It is important to evaluate structural performance in this typical cascading hazard to develop mitigation strategies and improve multi-hazard resilience. However, existing research mainly focuses on the structural response in PEF scenarios, while there is still a lack of knowledge on other critical parts of performance evaluation. In contrast, there has been a well-established methodology for performance-based assessment in earthquake engineering (PBEE), which can be regarded as the basis for extension to PEF scenarios. Based on that, a comprehensive framework has been proposed in this study for performance-based assessment in post-earthquake fire engineering (PB-PEF-E). To demonstrate the feasibility of the proposed methodology, an illustrative example of a realistic multi-storey steel frame is presented with specific details. The overall procedure considering the hazard, structure, damage, and loss domains is utilised for step-by-step PEF performance evaluation. Firstly, a dual-cause PEF ignition model is used to capture the probabilistic causation among the earthquake-fire sequence, considering ignition related to utility system damage and ignitable contents overturning. Then, structural demands with respect to both earthquake and fire intensities are obtained by a series of nonlinear analyses via numerical modelling, and uncertainties that significantly influence the responses are included. Finally, the structural capacity in different performance levels is estimated with PEF fragility development, and the consequences are measured using quantitative indicators for decision-making. The proposed methodology provides important benefits in evaluating the performance of alternative solutions thus facilitating robust decision-making in PEF scenarios, and it can be further extended to performance-based assessment in other multi-hazard scenarios with cascading effects.

The impact of people with mobility limitations on exit choice

Demographic trends and advances in accessibility have led to more heterogeneous populations in public buildings. While providing accessible evacuation, it may be necessary to direct evacuees to different evacuation paths depending on functional capacity. The presence of people with mobility limitations (e.g., wheelchair users) may affect the evacuation of others, possibly influencing the decision making of neighbouring evacuees. This study investigates how exit choice of people is influenced by the functional capacity of other evacuees and the design of the exit. Virtual Reality was used to design a discrete choice experiment in which participants were exposed to multiple choice situations and a mixed logit model was fitted to the data. Results from 40 participants indicate that exit choice was positively influenced by other people choosing the exit, and a larger effect was found when the other person was a wheelchair user. The design of the exit also influenced the exit choice of the participants. Large inter-person differences existed. Strategies reported by the participants in the subsequent questionnaire included altruistic behaviour. These results can inform fire safety engineers when outlining evacuation strategies and evacuation model users in their assumptions concerning exit choice in building evacuation.

An open-source software framework for the integrated simulation of structures in fire

The traditional methods to understand the development of elevated temperature in a structure, and also the associated structural response, are not representative of realistic fire scenarios. To provide a more accurate and realistic reflection of the fire development, the current paper develops a generic middleware which interfaces between the computational fluid dynamics (CFD) software Fire Dynamics Simulator (FDS) and the finite element (FE) analysis software OpenSees. This framework enables a fully integrated simulation of a realistic fire scenario including the heat transfer through the structure and the resulting thermo-mechanical response. The proposed framework is open-source and freely available and therefore can be used and further developed by researchers and practicing engineers and customised to their requirements. This paper shows validation against two sets of experimental results and one real fire incident. A number of different types of thermal boundary conditions such as gas temperatures and heat fluxes, are obtained from the CFD analysis and are then used in the subsequent heat transfer and thermo-mechanical analysis. The primary advantage of this computational tool is that it provides consultants and designers with the means to undertake large-scale projects requiring performance-based fire engineering solutions.

Real-time visualization of smoke for fire safety engineering applications

Visibility in smoke is a key aspect in terms of safe egress in various fire related situations. Due to the hazardous nature of fire induced smoke, it is hard to study human behaviour under such conditions, but recent development within the field of virtual reality (VR) has enabled exposure to many different hazardous conditions while remaining relatively safe. However, to obtain valid results from such studies a higher degree of visual realism is often required, therefore when studying effects of visibility, the rendering of smoke needs to be physically based and of high visual fidelity while still being computationally cheap in order to render the virtual environment at high framerates. This paper presents an approach for rendering smoke with a single in-scattering term which allows for smoke and light interaction over multiple wavelengths. The results highlight the importance of smoke characteristics as well as the influence the general lighting conditions can have on perceived visibility. The presented work intends to be of benefit for VR or similar applications where visibility is of key interest.

Experimental and machine learning studies of thermal impinging flow under ceiling induced by hydrogen-blended methane jet fire: Temperature distribution and flame extension characteristics

Hydrogen-blended natural gas has a winged used in such thermal and combustible systems, the ceiling thermal characteristics have important parameters of impinging jet configurations. In this paper, a series of experiments were carried out to study the ceiling flame extension characteristics and temperature profile in a thermal impinging flow of methane jet diffusion flame with hydrogen addition. It was found that: for the given volume flow rate of methane fuel, the ceiling temperature increases although ceiling flame extension area (length) decreases, with the volume flow of hydrogen mixing ratios increasing. Then, a physical and mathematical model, combined influence of flame shape hypothesis based on physically the unburnt fuel, hydrogen addition, heat release rate, the effects of source-ceiling height and nozzle diameter is estimated to predict the flame extension area of methane jet diffusion flames with different hydrogen mixing ratios. Moreover, the fire plume temperature between buoyant plume and intermittent flame increased with the increase in hydrogen addition due to the fire plume temperature increased. The temperature profile models of the ceiling jet are proposed for methane diffusion flames with different hydrogen mixing ratios. Furthermore, to perform the calculation quickly and facilitate rapid thermal engineering design, this paper used machine learning methods (GABP neural network) to derive the volume flow rate of gas leak from the temperature data of the ceiling detected by thermocouples. The results show that the AI prediction for the heat release rates has a good correlation with the verification experimental value. The results of this paper may demonstrate the potential for industrial combustion systems and fire safety engineering applications of methane jet diffusion flame with hydrogen addition.

Causal Network Topology Analysis (CaNeTA) as a tool for risk assessment in fire safety engineering

Risk assessment occupies an integral place in a wide range of areas regarding health and safety, and many risk assessment tools have been applied in the field of Fire Safety Engineering (FSE). However, FSE is facing a lack of diversity of risk methods, and they all have common drawbacks, particularly in those alike methods of generating fire scenarios that are relied upon in the fire safety design process. These drawbacks include the overlook of interdependencies between different fire safety systems, as well as the overreliance on the competence of the risk-analyst. As a result, we applied a novel methodology called the Causal Network Topology Analysis (CaNeTA) to the fire safety strategy for a multi-tenancy retail occupancy. The contributions include: 1) The causal network which interlinks the causalities between the status of individual fire safety systems. 2) The results from network analysis help analysts to observe and engage with overall system performance. 3) The suggestions on the criticality of the status of individual fire safety systems to optimise fire safety strategy. To conclude, the usage of CaNeTA reveals broader insights from the fire safety strategies objectively, to support fire safety design.

Machine learning driven smart fire safety design of false ceiling and emergency response

In modern buildings, false ceilings are widely used for building services systems and aesthetic purposes, but they also pose challenges in terms of fire safety. A fire accident typically results from the failure of multiple safety measures or components. In many fire accidents, fire and smoke reached the false ceiling and kept spreading in the interstitial space without any detection. This study first generates a numerical database of false ceiling fire scenarios by varying the room dimensions, false-ceiling leakage area, fire size and locations. Then, a smart model based on machine learning to predict the fire smoke motion below and above the false ceiling is developed. The trained model is capable to predict the activation time of fire detectors and sprinklers for any given false ceiling design and fire scenario. This methodology enables a designer to generate multiple fire scenarios and determine the available safe egress time (ASET) for performance-based fire engineering designs especially in terms of fire detection time. In case of a real fire, with the data feed from the fire sensor network, the trained machine learning model can further predict the critical building fire events with the false ceiling, such as multi-compartment fires, smoke in the evacuation path, and structural failures. This work proposes a smart framework for improving the building fire safety design of false ceilings and the sensor-driven fire forecast to support firefighting.It enhances the emergency response processes by enabling dynamic risk assessment through prediction of critical events.