Firing Time Research Articles

Study on Aqueous Film Forming Foam Extinguishing Agents Based on Perfluorobranched Short-Chain Fluorocarbon-Hydrocarbon Surfactant Complex Mixtures.

Aqueous film-forming foam (AFFF) is a targeted product for liquid fuel fires and has the benefits of a long storage period and high fire extinguishing efficiency. However, because of the toxicity and bioaccumulation of the core raw material's long-chain fluorocarbon surfactant, traditional AFFF is being phased out. For this reason, three efficient AFFFs (F-1, F-2, and F-3; more details in Table 2) were designed using anionic surfactants (PBAF) with branched C6 perfluorinated chains, hexadecyltrimethylammonium bromide (CTAB), and dodecyl dimethyl betaine (BS-12) as core materials. Through comparison, F-1 shows excellent foaming ability (initial foam height is 86 mm) and foam stability (25% drainage time is 234 s). Moreover, F-1 exhibited excellent fire extinguishing and fire resistance performance: the fire extinguishing time was 33 s, and the fire resistance time was 831 s. This means that F-1 has enormous firefighting potential and can serve as a potential alternative to traditional AFFF.

Fuel accumulation shapes post-fire fuel decomposition through soil heating effects on plants, fungi, and soil chemistry.

Forty percent of terrestrial ecosystems require recurrent fires driven by feedbacks between fire and plant fuels. The accumulation of fine fuels in these ecosystems play a key role in fire intensity, which alters soil nutrients and shapes soil microbial and plant community responses to fire. Changes to post-fire plant fuel production are well known to feed back to future fires, but post-fire decomposition of new fuels is poorly understood. Our study sought to quantify how pre-fire fuel loading influenced post-fire fuel decomposition through soil abiotic properties, as well as plant and soil fungal communities. Prior to spring prescribed burns, we manipulated fine fuel loads in plots, both near (<10m) and away (>10m) from overstory pines, to modify soil heating in an old-growth longleaf pine savanna. We then assessed how fuel load and soil heating influenced post-fire plant fuel decomposition through changes to soil chemistry, vegetation, and fungi. Burning larger fuel loads made fires hotter, burn longer, and more completely combusted fuels. In these plots, decomposition of newly deposited fine fuels was slower in the eight months following fire. Decomposition changes from greater soil heating were mediated by greater shifts to postfire plant (2 and 4months postfire) and fungal communities (4 and 6months postfire). Soil properties (C: N ratios, soil pH, and P) controlled postfire decomposition throughout the year, but weakly responded to soil heating differences from fuels. Since the mechanisms for fuel effects on decomposition change over time, fire timing may be a future target for understanding fire feedbacks to fuel decomposition. Integrating these feedbacks with fuel production responses across fire-dependent ecosystems can help managers better set prescribed fire intervals and predict responses to reintroducing burning in fire-suppressed ecosystems.

Polyester/cotton fabrics fire alarm sensors with sensitive fire warning response and excellent flame retardancy

Intelligent fire alarm textiles are beneficial for prevent the occurrence of fire. However, the sensitivity and sustained response time of intelligent fire alarm textiles will directly affect fire losses. In this study, intelligent fire alarm polyester/cotton blend fabrics (PCFs) with excellent flame retardancy were prepared by construction of GO@PA/CNTs@CS organic and inorganic composite coating containing phytic acid (PA), chitosan (CS), graphene oxide (GO) and carbon nanotubes (CNTs). GO@PA/CNTs@CS coating greatly enhanced the flame retardancy of PCFs to obtain a LOI value of 30%, and it also endowed PCFs with self-extinguishing property. The fire hazard of PCF coated with GO@PA/CNTs@CS was significantly reduced with 40.5% reduction of peak heat release rate (pHRR) and 72.3% reduction of total heat release (THR). The fire alarm trigger time of GO@PA/CNTs@CS coated PCF was 1.5s, showing the super-fast fire warning response. The fire alarm response signal can still be sent out even when the coated PCF was burnt in a fire for over 600s, showing the long-term fire alarm response property. This study provides the experimental basis to prepare intelligent fire alarm textiles with sensitive fire warning response property and excellent flame retardancy.

Shooting Simulator “Inhibitor”: Special Effect Mathematical Support of Target Behaviour

Mathematical support and algorithms for implementing special effects oftarget active behavior and local subjects along with result analysis of performing exercise scenario for the optical-electronic shooting simulator «Inhibitor» developed at Institute of mechanics UdmFRC UB RAS and at Computer facilities department of Kalashnikov ISTU jointly with JSC «Kalashnikov» Concern», is described. A tactical and technical task is given for displaying wind-dependent local objects and fumes, to provide the realism of the targetbehavior (motion angles, defeats, return fire, evading close misses, occurrence, crawling, etc.), andarmored vehicleburning. In addition, the manager must receive complete information about the course of firing (time of firing and damage with respect totarget materialization, number of shots and errors, sight adjustment, points on target No. 4, etc.) and assess each student with control onexercise completion (magazine - shutter - fuse). It is necessary to calculate the aiming point at the moment of shooting and apply the projection of the rear sight and front sight to the target for each shot in order to control the grip, hold, aim and smooth descent skills. Theconducted studies of chromatic aberrations of special effects revealed factors affecting distortions and showed that the target situation meets the TTT requirements. The targetrealism with motion phases and angles, defeat (fall or burning), evasion of near misses, occurrence and return fire and reaction to the wind of local objects, as well as the completeness of operational informing of the leader was confirmed by military acceptance. The literature review showed the prospects for further research and development of electronic shooting simulators due to the improvement of computing tools and the development of software libraries in order to increase the accuracy of behavior simulation of the target environment and analyzing shooting results. It is necessary to expand the possibilities of special effectrealism of goals and reduce the cost, and, therefore, increase the competitiveness of electronic shooting simulatorsconstantly.

Numerical Study on Fire Suppression by Water Mist in Aircraft Cargo Compartments: Effects of Spray Pattern, Droplet Size, and Nozzle Layout

Aircraft cargo compartment fires are one of the main threats to the safety of civil aircraft. In this study, a series of numerical simulations on the fire suppression performance of water mist in cargo compartments was carried out to examine the effects of the spray pattern, droplet size, and nozzle layout. The fire dynamics simulator (FDS) code was used to construct a fire suppression scenario in a full-scale aircraft cargo compartment. The results show that the extinguishment time of a corner fire was longer compared with center and sidewall fires due to the relatively larger distance from the nozzle and, therefore, a lower effective number of droplets reaching the flame area. Solid and hollow spray patterns showed significant differences in the spray coverage area. For a fixed flow rate, the hollow spray showed better fire suppression performance than solid spray. When the droplet size varied from 50 to 400 µm, the fire extinguishment time first increased and then decreased, corresponding to the dominant mechanism of the smothering effect of small droplets and the cooling effect of large droplets. In addition, the nozzle layout affected the water coverage on the ground of the cargo compartment. With an increase in nozzle number, the water mist flux was more evenly distributed and the fire extinguishment effect also increased.

Complex Battery Storage Fire Propagation Translational Forensic Study Using Cellular Automata

The surge in lithium-ion battery (LIB) use, essential for mass-scale renewable energy storage, raises concerns about fire hazards. However, to date, there is a lack of industry-wide understanding of large-scale LIB fire propagation. This paper suggests a translational forensic approach to promote fire safety awareness and introduces the cellular automata (CA) model coupled with the Monte Carlo (MC) approach to address the complex fire propagation simulation within an energy storage system (ESS). The objective is to demonstrate that the CA-MC model can provide a flexible and scalable connection for all levels of battery fire studies. The numerical model is coupled with experimental tests which have been performed to establish the actual timing of fire propagation from a single source. Cellular automata simulation, conducted through hybrid modeling and an applied risk analysis approach to evaluate fire hazards associated with LIBs, offers crucial insights into potential risks. The results demonstrate that, with fire incident initiation at a probability of 0.1 (10%), 33% of batteries will burn, and at a probability of 0.6 (60%) and beyond, the entire battery module will face complete burndown. Achieving full combustion of the entire module will take only approximately 42 timesteps on average, indicating rapid fire propagation. The actual time for a complete fire to occur in the battery module has been estimated to be 304 s per timestep, or 3.5 h total. Using this example, it is shown that the CA-MC approach can be extended to many other aspects of battery fire studies and is ideal as a translational tool, spanning all domains of the LIB industry.

Prediction of ultimate bearing capacity of RC beams after fire: data-driven method

The ultimate bearing capacity of reinforced concrete (RC) beams after exposure to fire was investigated using numerical simulations, regression fitting and machine learning techniques to examine the thermal and mechanical properties of the beams after high-temperature exposure. A series of fire and static load tests was conducted on seven RC T-beams. Based on the experimental observations and considering the effects of high-temperature concrete spalling and steel–concrete bond degradation, a numerical model was developed to simulate the temperature distribution and structural behaviour of RC T-beams. The accuracy of the numerical model was validated by comparing the cross-sectional temperature profiles and ultimate bearing capacities after fire exposure with experimental results. A dataset of 500 samples was established, with variables including fire exposure time, depth of concrete spalling, spalling area ratio and loading conditions. Regression fitting and machine learning techniques were used to establish predictive formulas and models for estimating the ultimate bearing capacity of RC T-beams after fire exposure. The accuracy of both methods was found to be within 10%.

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.

Fire return intervals and recruitment affect population growth rate of canopy trees in tall open forest in humid savanna

AbstractSavannas are the major biome in tropical regions of the globe, defined as sparsely wooded regions with a continuous herbaceous layer of mainly C4 grasses where rainfall is distinctly seasonal. Fire is a common feature of most savannas. The largest protected areas of savannas are found in sparsely populated monsoonal northcentral Australia with strong annual wet and dry seasons. The most common vegetation type is relatively intact, tall (&lt;15 m), open forests where Eucalyptus canopy trees form the basic structure. Over the past half century, traditional indigenous fire regimes were largely replaced by contemporary fires where individual trees may experience fire as often as 3 out of 5 years. The potential for long‐term persistence of the canopy tree populations is an open question. A stage‐based population model of the canopy trees was previously developed to address this question, drawing on data from three decades of experimental field studies wherein the survival, growth, and reproduction of individual marked trees were recorded under different seasonal fires and understory types to produce transition matrices among eight life history stages, and used to calculate population growth rates (λ). Here, we apply that model to determine how λ varies across a range of fire return intervals from 1 to 12 years for both early and late dry season fires, in two different understory types. We also explore the sensitivity of λ to two key life history parameters: recruitment and seedling survival. Minimum fire return intervals of 2–5 years were generally required for λ ≥1 that would allow populations to persist; these were shorter with stochastic year‐to‐year timing of fires and with higher recruitment rates. Uniquely, under certain conditions, there was also a maximum fire return interval above which λ &lt;1, creating a “window” of fire return intervals that allowed canopy tree populations to persist. Mechanisms underpinning results as well as implications for savanna structure, alternate states, cyclical dynamics, future research, and management by fire are discussed.

MILP-MPC for Planned Maneuver station-keeping and Collision Avoidance of GEO Satellites Using On-Off Chemical Thrusters

GEO satellites require precise station-keeping and ensuring collision avoidance to maintain their desired orbital positions and ensure uninterrupted communication services. However, maneuvering these satellites poses significant challenges due to various geophysical factors and orbital perturbations. This work proposes a model predictive control for planned maneuver station-keeping and collision avoidance of GEO satellites using south, east, and west maneuvers. These maneuvers have been achieved using on/off chemical thrusters with a short firing time. The station-keeping problem is reformulated as an optimization problem using mixed-integer linear programming. MILP-MPC formulation simultaneously considers multiple objectives and constraints such as fuel consumption, maneuver planning, and collision avoidance for mitigating collision risks. Simulation results demonstrate the effectiveness of the proposed MILP-MPC framework compared to the real-time telemetry in achieving accurate station-keeping and collision-free operation while optimizing fuel consumption. The proposed controller increases the satellite lifetime by reducing the thruster firing time.

Residual compressive behaviour and CFRP strengthening of SRCFST columns after combined damage of fire and lateral impact

Composite structure may be subjected to impact and fire during its service life, and the damaged member face challenges in the performance evaluation and strengthening. This study conducted an experimental and numerical investigation into the residual compressive behaviour of steel-reinforced concrete-filled steel tubular (SRCFST) columns after combined damage of fire and lateral impact. Thirteen damaged specimens under axial loading were tested, with three specimens strengthened with carbon fiber reinforced polymer (CFRP). The failure modes of specimens, residual compressive capacity, deflection distribution, and strain development were discussed. The finite element analysis model on the residual compressive behaviour of damaged SRCFST columns was then developed and calibrated. The full-range analysis on the residual performance of damaged columns was carried out, included the temperature development, distribution of axial load and bending moment, degradation mechanism of bearing capacity, stress development, and effects of fire exposure time. The parameter study was finally conducted to investigate the effects of various factors on the residual compressive performance of damaged SRCFST columns. The results indicated that increasing the fire exposure time and impact height reduces visibly the residual compressive capacity of damaged specimens. As the two damages accumulate, the axial load of each component gradually reduces, while the axial compressive capacity proportion redistributes.

UAV Cruise Strategies Based on Initial Attack

Forest fires not only cause severe damage to ecosystems and biodiversity but also directly threaten the safety of human societies. Given the significant increase in both the frequency and intensity of forest fires worldwide, especially under extreme climate conditions, efficient fire detection and initial attack (IA) are particularly critical. The initial attack is a key stage in forest fire control, and the time taken for fire detection is a crucial factor influencing the success of the initial attack. In response to the challenges of forest fire prevention and control, this study explores Unmanned Aerial Vehicle (UAV) cruising strategies, aiming to develop appropriate approaches based on regional characteristics and provide efficient periodic monitoring solutions for areas with high ecological value and challenging accessibility. By optimizing UAV patrol routes, this research seeks to maximize coverage in areas with lower initial attack success rates and significantly reduce fire detection time, thereby improving detection efficiency. We developed and applied four optimization strategies, random search, high-risk first (HRF), nearest high-risk first (NHRF), and a genetic algorithm-based (GA-based) strategy, to compare different UAV flight routes. To evaluate the deployment effectiveness of the four UAV cruise strategies, we introduced two evaluation metrics: Average Grid Risk (AGR) and Average Distance Risk (ADR). Experimental results showed that the NHRF and GA-based strategies performed better. Specifically, NHRF achieved the highest high-risk coverage, ranging from 51.5% to 71.3%, significantly outperforming the random search strategy (4–7%) and the HRF strategy (23.1–37.5%). The GA-based algorithm achieved the highest grid coverage, ranging from 30% to 59.8%, far surpassing the random search strategy (4–6.6%) and the HRF strategy (10.2–19.1%). Additionally, the NHRF and GA-based strategies delivered the best AGR and ADR performance, respectively. The application of these innovative strategies and evaluation metrics enhances forest fire prevention through periodic monitoring and supports more efficient firefighting efforts.

Development of Superior-Performance, High-Durability and Low-Cost Reversible Solid Oxide Cell for Power Generation and Hydrogen Production

A superior-performance, high-durability and low-cost reversible solid oxide cell (RSOC) technology is under development for power generation and hydrogen production applications. This RSOC incorporates components made by sputtering which significantly enhance cell performance. Sputtering can be a cost-effective manufacturing process for making RSOC cells/components, especially thin-film components. This process eliminates the multiple cell thermal processing steps (with high heat treatment temperatures and lengthy firing times) commonly used in conventional processes, thus reducing cell fabrication cycle time and fabrication cost. This cell technology also includes non-strontium perovskite oxygen electrodes and/or nickel-substituted perovskite hydrogen electrodes. Non-strontium perovskite oxygen electrodes contains no strontium, thus unwanted strontium segregation and interactions with volatile chromium species to form strontium chromium oxides are avoided, resulting in increased electrode resistance to chromium poisoning. Nickel-substituted perovskite hydrogen electrodes, when exposed to reducing environment, will exsolve nickel to form fine particles imbedded in the oxide skeleton. For this embedded structure, volume changes upon reduction/oxidation (redox) are not significant. The hydrogen electrode based on this material is thus redox resistant. Nickel particles formed in this way have been shown to significantly reduce electrode polarization resistance, thus enhanced performance and exhibit high stability, thus increased durability. The paper discusses recent progress in the development and scaleup of the sputtering process and studies of oxygen electrodes based on lanthanum nickel cobalt perovskite (LNC) and hydrogen electrodes based on nickel-substituted lanthanum strontium cobalt iron perovskite (LSCFN).

Sensitivity of Spiking Neural Networks Due to Input Perturbation.

Background: To investigate the behavior of spiking neural networks (SNNs), the sensitivity of input perturbation serves as an effective metric for assessing the influence on the network output. However, existing methods fall short in evaluating the sensitivity of SNNs featuring biologically plausible leaky integrate-and-fire (LIF) neurons due to the intricate neuronal dynamics during the feedforward process. Methods: This paper first defines the sensitivity of a temporal-coded spiking neuron (SN) as the deviation between the perturbed and unperturbed output under a given input perturbation with respect to overall inputs. Then, the sensitivity algorithm of an entire SNN is derived iteratively from the sensitivity of each individual neuron. Instead of using the actual firing time, the desired firing time is employed to derive a more precise analytical expression of the sensitivity. Moreover, the expectation of the membrane potential difference is utilized to quantify the magnitude of the input deviation. Results/Conclusions: The theoretical results achieved with the proposed algorithm are in reasonable agreement with the simulation results obtained with extensive input data. The sensitivity also varies monotonically with changes in other parameters, except for the number of time steps, providing valuable insights for choosing appropriate values to construct the network. Nevertheless, the sensitivity exhibits a piecewise decreasing tendency with respect to the number of time steps, with the length and starting point of each piece contingent upon the specific parameter values of the neuron.

Numerical Investigations on the Enhancement of Convective Heat Transfer in Fast-Firing Brick Kilns

In order to reduce CO2 emissions in the brick manufacturing process, the effectiveness of the energy-intensive firing process needs to be improved. This can be achieved by enhancing the heat transfer in order to reduce firing times. As a result, current development of tunnel kilns is oriented toward fast firing as a long-term goal. However, a struggling building sector and complicated challenges, such as different requirements for product quality, have impeded developments in this direction. This creates potential for the further development of oven designs, such as improved airflow through the kiln. In this article, numerical flow simulations are used to investigate two different reconstruction measures and compare them to the initial setup. In the first measure, the kiln height is reduced, while in the second measure, the kiln cars are adjusted to alternate the height of the bricks so that every other pair of bricks is elevated, creating a staggered arrangement. Both measures are investigated to determine the effect on the heating rate compared to the initial configuration. A transient grid independence study is performed, ensuring numerical convergence and the setup is validated by experimental results from measurements on the initial kiln configuration. The simulations show that lowering the kiln height improves the heat transfer rate by 40%, while the staggered arrangement of the bricks triples it. This leads to an average brick temperature after two hours which is around 130 °C higher compared to the initial kiln configuration. Therefore, the firing time can be significantly reduced. However, the average pressure loss coefficient rises by 70% to 90%, respectively, in the staggered configuration.

FORECASTING FIRE RISK VALUES USING MACHINE LEARNING AND TIME SERIES ANALYSIS

The probability of occurrence of emergencies and their consequences can be minimized by predicting events that contribute to the emergence of such a situation. An optimal and useful tool for such prediction and forecasting can be modeling, which can be carried out on the basis of information technology using computer programs.The methods of modeling and forecasting emergencies related to fires are the same as for other emergencies, but there are some specifics. The forecast of emergencies related to fires is aimed at three main stages: 1. forecasting the probability of occurrence with the determination of the place of the highest probability of fire occurrence, time and factors contributing to it; 2. forecasting the development of the situation and the spread of the fire (direction, speed) when it occurs, the process itself; 3. forecasting the consequences of a fire at a specific facility.The forecast is made based on the analysis of all possible unfavorable factors, their fields of action, features of the facility, its fire hazard and other data.The use of machine learning methods and time series analysis for forecasting fire risk values is substantiated. The possibility of using statistical methods of mathematical modeling of fire occurrence as the basis of the machine learning model is noted. This approach enables the machine learning model to process and analyze a large amount of statistical information for specific time periods and issue forecasts.

A novel dynamic evacuation risk assessment model of healthcare facilities during fire scenarios

Evacuation is a critical procedure for safeguarding individuals during a fire incident within a healthcare facility. Assessing the risk associated with the evacuation process is instrumental in enhancing emergency decision-making and developing contingency strategies. Evacuation, a dynamic process, poses challenges in accurate risk evaluation using conventional static quantitative risk assessment (QRA) techniques. This study introduces a dynamic QRA approach to precisely evaluate the evacuation risk to individuals in healthcare settings during a fire. The dynamic event tree methodology is initially utilized to determine the evolving probabilities of various fire scenarios, considering the equipment failure and repair rates. Subsequently, data on fire products and the evacuation of individuals under different fire scenarios are gathered through simulations conducted with Fire Dynamics Simulator (FDS) and Pathfinder software. In addition, this research proposes a dynamic incapacitation model to calculate the consequences of fire, incorporating changes in individuals' locations and the fire products surrounding them during evacuation to accurately estimate the casualty risk. Lastly, the dynamic scenario probability was integrated with the average incapacitation probability for all individuals, introducing the concept of a fire evacuation safety time window to comprehensively assess hospital fire evacuation risk. The findings revealed that the dynamic quantitative risk analysis (DQRA) approach more effectively captures the influence of fire products on the evacuation risk compared to static methods. Specifically, the peak incapacitation probability in a hospital fire reached 0.85, with firefighting equipment, especially the sprinkler system, reducing this risk by over 97 % and decreasing evacuation time by 45 %. In addition, the risk of fire evacuation in hospitals reaches a critical threshold in the fourth year, enhancing the repair rate of the firefighting system postpones the risk's escalation to a critical threshold until the fourteenth year.

Performance of RC beams strengthened using NSM FRP and cement based adhesives after exposure to elevated temperatures

A popular method for strengthening of reinforced concrete (RC) structures is the use of carbon fiber reinforced polymers (CFRP) bonded to the structural elements using the near surface mounted (NSM) techniques. While this method possesses many advantages, poor fire resistance as a result of the low glass transition temperatures (TG) of organic resins remains a significant drawback. Replacement of organic resins with cement based adhesives (CBA) could potentially improve the fire performance of NSM FRP systems and reduce the amount of insulation required to achieve the required fire endurance period. This paper presents an experimental program consisting of fifteen RC beams strengthened in flexure using NSM FRP bonded using CBA and subjected to the standard fire time temperature curve up to a target temperature of 600 °C. Twelve of the beams were strengthened using NSM-FRP laminates and bars including both smooth and rough FRP laminates and the remaining three specimens acted as control beams. Further, the use of plasterboard was explored as fire protection to further increase the residual strength of the specimens after heating. Results showed that the reinforced concrete beams strengthened with NSM CFRP retained 82 % to 61 % of their unheated strengthened ultimate load after heat exposure. This was a result of the superior performance of the cement-based adhesive at high temperature and the fire protection provided to the CFRP through embedment in the grooves. Moreover, the use of plasterboard as fire protection decreased the CFRP temperature by 42–24 %. The insulated beams behaved similarly to strengthened beams prior to fire exposure.

Effect of nano-aluminum hydroxide on the liquid phase properties and fire-fighting foam performance of the mixed surfactants solution

Short-chain fluorocarbon surfactants show synergistic effects with hydrocarbon surfactants in foaming and foam stability. Nano-aluminum hydroxide (nano-ATH) was added as an additive to the short-chain fluorocarbon surfactant mixture solution, which was found to increase the surface tension and viscosity of the surfactant mixture solution, and decrease the foaming properties of the solution, as measured by Wilhelmy method, Waring Blender method and viscometer. By measuring zeta potential experiments, surfactant molecules were found to be adsorbed on nano-ATH through charge gravity, which increased the desorption energy of nano-ATH. Measuring the visco-elastic modulus of the solution by rheometer, it was found that nano-ATH increased the visco-elastic modulus of the surfactant mixture solution, which improved the foam's resistance to the external disturbances. Observed by the image analysis system on the foam, the uniform distribution of nano-ATH in the liquid film reduced the coarsening and coalescence speed of foam. Through the self-developed oil resistance test, nano-ATH enhanced the oil resistance stability and inhibition of fuel vapor diffusion of the foam by about 12 %; through self-developed foam fire extinguishing and anti-burning tests, nano-ATH shortened the fire extinguishing time of the two-phase foam by 25 %, and showed better fire extinguishing and anti-burning performance than the foam.

Fire and smoke transport dynamics in a dead-end tunnel under heavy rainfall

Fire is one of the most common major accidents during tunnel construction and operation. This work conducted scale-model experiments to investigate the pool burning progress and flame characteristics in a dead-end tunnel with one end closed and the other open under heavy rainfall. The results show that, compared to opening both ends, the global burning time of fires is significantly decreased, and the quasi-stable burning phase is advanced under the combined effects of the closed end and heavy rainfall. The reason is that the increase in ceiling temperature, resulting from the accumulation of hot smoke, leads to an increase in radiative feedback of the fuel from the environment and an acceleration in the pool's burning rate. A coefficient (denoted by γ) is defined to evaluate the increase in the burning rate resulting from the dead-end. The enhancement ratio is found to be related to rainfall intensity, raindrop size, and pool size, and a correlation has been established based on the experimental results. The fire has an increased flame height and a reduced tilt angle under the impact of the dead-end. The changes in flame geometry parameters are mainly influenced by thermal buoyancy and the restriction of the dead-end. Prediction formulas for flame height and tilt angle under the combined effects of the dead-end and heavy rainfall have been proposed based on theoretical analysis. Under these combined effects, the tunnel space becomes eroded by dirty air.