Smoke Obscuration Research Articles

Underground Evacuation and Smoke Flow Simulation in Guangzhou International Financial City during Fire

The underground space in the Starting Area in the Guangzhou International Financial City is being developed to save resources and improve land benefits. However, high-density development has increased the likelihood of fires. Therefore, PyroSim and Pathfinder were used in this study to investigate the fire smoke flow and personnel evacuation in the underground space in the Starting Area. Firstly, the 2D temperature cloud map and the temperature and visibility recorded by sensor A over time of Zone I in the Starting Area were analyzed. Then, the 3D smoke diffusion, the 3D temperature diffusion map, and the value of thermocouple and smoke obscuration recorded by sensors of Zone II were analyzed. Next, smoke flow of Zones III to V in the Starting Area under different fire source positions was simulated. Finally, the personnel evacuation model was established to simulate the personnel flow rate and density. The simulation results show that the available safe evacuation time for people is 530 s when all the firefighting facilities fail and fire breaks out in Zone I. For large public spaces, the overall spread speed of fire is fast, which requires the use of the fire control system in time to control the spread of fire. Fortunately, the space of evacuation time is relatively sufficient; it only takes 143 s to evacuate personnel safely in Zone II, which is sufficient compared to the time for the fire to completely spread. Suggestions were made for fire safety management, such as evacuating personnel to the safety exits of other adjacent areas during a fire and installing linkage fire alarm systems in large public space s.

Deep learning health management diagnostics applied to the NIST smoke experiments

Fire is one of the most important hazards that must be considered in advanced nuclear power plant safety assessments. The Nuclear Regulatory Commission (NRC) has developed a large collection of experimental data and associated analyses related to the study of fire safety. In fact, computational fire models are based on quantitative comparisons to those experimental data. During the modeling process, it is important to develop diagnostic health management systems to check the equipment status in fire processes. For example, a fire sensor does not directly provide accurate and complex information that nuclear power plants (NPPs) require. With the assistance of the machine learning method, NPP operators can directly get information on local, ignition, fire material of an NPP fire, instead of temperature, smoke obscuration, gas concentration, and alarm signals. In order to improve the predictive capabilities, this work demonstrates how the deep learning classification method can be used as a diagnostic tool in a specific set of fire experiments. Through a single input from a sensor, the deep learning tool can predict the location and type of fire. This tool also has the capability to provide automatic signals to potential passive fire safety systems. In this work, test data are taken from a specific set of the National Institute of Standards and Technology (NIST) fire experiments in a residential home and analyzed by using the machine learning classification models. The networks chosen for comparison and evaluation are the dense neural networks, convolutional neural networks, long short-term memory networks, and decision trees. The dense neural network and long short-term memory network produce similar levels of accuracy, but the convolutional neural network produces the highest accuracy.

Investigation of the performance of fire suppression systems in protection of mass timber residential buildings

The effectiveness of fire suppression systems in protecting mass timber construction are experimentally investigated for the objectives of life safety and property protection from fire and water damages. The performance of high- and low-pressure water mist systems was compared with sprinkler systems in a residential fire scenario involving exposed mass timber structures. The tested water mist systems and sprinkler systems successfully maintained the room temperature and gas concentrations tenable, but the smoke obscuration deteriorated rapidly. Although the tested systems resulted in fire damage on the exposed mass timber walls, a high-pressure water mist system with wide spray angle demonstrated rapid fire suppression and less damage to the walls. The performance of sprinkler systems was comparable, yet least effective due to the large amount of water used. A large water pool was formed on the floor in all tests with the size proportional to the total water discharged during the test. Also, the moisture contents of the mass timber panels indicated that water could penetrate the floor-wall interface in a typical assembly.

Attenuation of Microwaves Received From a Drone Owing to Smoke Obscuration

The objective of this study is to analyze the effect of smoke obscuration on the signal sensitivity of microwaves received from a drone. A spectrum analyzer and a directional antenna were employed for analyzing the received signal sensitivity and measuring the mean received power, both before and after the drone entered the smoke layer for one min in the fire training area. The drone operated in the range of 2.4 GHz to 2.48 GHz. It is found that the received power before entering the smoke layer is –39.3 dBm, at which signals and image data can be received. However, upon entering the smoke layer, the received power is reduced to –47 dBm, at which signals and image data cannot be received. Hence, the received power undergoes an attenuation of approximately 7.7 dBm (5.9 mW) owing to smoke obscuration, which causes communication outage. Based on this study, it can be concluded that the received power undergoes attenuation owing to smoke obscuration during fires. Furthermore, if a communication problem occurs due to microwave attenuation, it affects the drone’s operation.

Near-Field Radiant Heat Flux from Open-Air Gasoline and Diesel Pool Fires: Modified Point Source and Discretized Solid Flame Models

This paper proposes novel modifications to existing solid flame and point source models to better predict the spatial contour of near-field, steady-state radiant heat flux from large circular pool fires (with diameters ranging from 1 m to 20 m) with gasoline and diesel fuel. The proposed models account for partial smoke obscuration of the flames, and the emissive power of the visible flame layer is calculated via a radiative fraction of the fire’s heat release rate as a function of the pool size. The modified discretized solid flame model uses a cylinder + cone shape combination whose surfaces are discretized to enable a flexible summation of total radiative energy emission. The modified point source model places its radiating point at the mid-height of the visible flame layer to capture the location of maximum radiation intensity. Predictions from both proposed models are benchmarked against available data from pool fire experiments, calibrated against computational fluid dynamic simulations, and compared with existing analytical solutions for a range of pool fire diameters at varying standoffs and gauge heights. The results demonstrate that the proposed models can effectively predict the spatial contour and peak value of radiant heat flux on nearby targets (i.e., at distances less than 2.5 times the pool diameter) with low computational effort.

Experimental study on the effects of sprinkler activation on the stratified smoke layer inside a 36 m2 enclosure

Experiments have been carried out in a specially designed 36 m2 compartment. The experimental results show the main phenomena during the fire and smoke propagation in the compartment before sprinkler activation and additionally the interaction between the hot flue gases in the smoke layer and the water spray. The axial temperature profiles at three characteristic positions inside the compartment were measured. A comparison of a standard sprinkler and a High-Pressure Water Mist system (HPWM) revealed two different phenomena, which are flue gas scrubbing and recirculation motion, respectively – both eventually leading to an increased smoke obscuration inside the compartment.

In-situ measurement of water-vapor in fire environments using a real-time tunable diode laser based system

A robust tunable diode laser absorption spectroscopy (TDLAS) based system is developed and deployed to make real-time water-vapor concentration measurements in quasi-controlled live-fire experiments conducted in firefighter training props. This system targets the 1392.5 nm (7181.15 cm−1) water-vapor absorption line while employing a multi-tier detection sensitivity scheme that allows for measurements at multiple locations in fire environment through varying smoke obscuration levels. Temperature-corrected absorbance values are compared to HITRAN simulations to quantify water-vapor concentration. Upon validation in laboratory setting, the impact of firefighter hose stream application on water-vapor concentration is studied. Comparative effects of training structures (metal, concrete and drywall-lined) and fuel-loads (pallet/straw, lightweight furnishings and pallet/straw/oriented-strand-board (OSB)) on water-vapor concentration are characterized. Despite small increase in water-vapor concentration due to suppression, the post-suppression concentrations are found to be comparable or lower than the corresponding maximum pre-suppression concentrations in all scenarios except the metal structure. Irrespective of the structure, highest temperature and water-vapor concentrations are measured with pallet/straw/OSB fuel-load. Under identical fuel-loads, the drywall structure scenarios generate highest water-vapor concentration. Peak water-vapor concentrations are measured post-suppression in typical training structures (near-floor and crawling levels), but prior to suppression in the structure/fuel package combination that simulated a typical residential fire scenario.

Smoke suppression performance of polyurethane composites containing microencapsulated melamine polyphosphate

A novel microencapsulated flame retardant containing melamine polyphosphate (MPP) and 4,4[Formula: see text]-oxydianiline-formaldehyde (OF) resin as a core–shell material was synthesized using in situ polymerization. The flame retardant was added to polyurethane (PU) to improve the fire suppression performance of resulting materials. Polyurethane was modified by silane, which was called as Si–PU and MPP was microencapsulated by OF resin, which was OFMPP. The results indicated that the smoke obscuration index (SOI) values of Si–PU, Si–PU/MPP 30% and Si–PU/OFMPP 30% were 6.59, 3.04 and 1.16, respectively, which indicated that the addition of flame retardants causes a significant downward trend in SOI values. The SOI value of Si–PU/OFMPP 30% was lower than that of Si–PU/MPP 30%, indicating that the microencapsulated OFMPP achieved smoke suppression.

Smoke Obscuration Measurements in Reduced-Scale Fire Modelling Based on Froude Number Similarity.

A common method for investigating various fire- and smoke-related phenoma is a reduced-scale fire modelling that uses the conservation concept of Froude number as its primary similarity criterion. Smoke obscuration measurements were not commonly used in this approach. In this paper, we propose a new type of optical densitometer that allows for smoke obscuration density measurements on a reduced-scale. This device uses a set of mirrors to increase the optical path length, so that the device may follow the geometrical scale of the model, but that still measures smoke obscuration as if it were in full scale. The principle of operation is based on the Bougher-Lambert-Beer law, with modifications related to the Froude number-based scaling principles, to streamline the measurements. The proposed low-budget (< $1000) device was built, calibrated with a set of the reference optical filters, and used in a series of full- (1:1) and reduced-scale (1:4) experiments with n-Heptane fires in a small compartment. The main limitation of this study is the assumption that there is similar soot production in full- and reduced-scale fires, which may not be true for many Froude-number scaling applications. Therefore, it must be investigated in a case-by-case basis. In our case, the results are promising. The measured obscuration in the reduced-scale had a 10% error versus averaged measurements in full-scale measurements. Moreover, there were well represented transient changes of the smoke layer optical density during the combustion and after the smoke layer settled.

Prototype Downscaling Algorithm for MODIS Satellite 1 km Daytime Active Fire Detections

This work presents development of an algorithm to reduce the spatial uncertainty of active fire locations within the 1 km MODerate resolution Imaging Spectroradiometer (MODIS Aqua and Terra) daytime detection footprint. The algorithm is developed using the finer 500 m reflective bands by leveraging on the increase in 2.13 μm shortwave infrared reflectance due to the burning components as compared to the non-burning neighborhood components. Active fire presence probability class for each of the 500 m pixels within the 1 km footprint is assigned by locally adaptive contextual tests against its surrounding neighborhood pixels. Accuracy is assessed using gas flares and wildfires in conjunction with available high-resolution imagery. Proof of concept results using MODIS observations over two sites show that under clear sky conditions, over 84% of the 500 m locations that had active fires were correctly assigned to high to medium probabilities, and correspondingly low to poor probabilities were assigned to locations with no visible flaming fronts. Factors limiting the algorithm performance include fire size/temperature distributions, cloud and smoke obscuration, sensor point spread functions, and geolocation errors. Despite these limitations, the resulting finer spatial scale of active fire detections will not only help first responders and managers to locate actively burning fire fronts more precisely but will also be useful for the fire science community.

Discovering worst fire scenarios in subway stations: A simulation approach

Abstract This paper develops a systematic hybrid approach that integrates Available Safe Egress Time (ASET), Required Safe Egress Time (RSET), numerical simulation, and Multi-Attribute Decision Analysis (MADA) to support fire safety risk assessment and to discover the worst fire scenarios for improving evacuation efficiency. Three factors, namely heat release rate, fire location, and occupants, are used to identify the most likely fire scenarios with a high-potential risk. The main classes of hazards yielded by fire, including heat (temperature), toxic gases (carbonic oxide), and smoke obscuration (visibility), are employed as untenability criteria for the estimation of ASET in the numerical simulation. A more comprehensive indicator, SITotal, is proposed to quantify the magnitude of the overall safety risk of a building fire, in order to fully consider the fire escape performance in different evacuation routes. One realistic subway station located at the Wuhan Metro System in China is utilized as a case to testify the applicability and feasibility of the proposed approach in this research. Result indicate that (i) among the identified four most likely fire scenarios, Scenario IV, where the fire is located at the exit of Sair I at the hall floor of the station with a heat release rate of 3 MW/m2, is identified to be the worst fire scenario with an associated lowest value of SITotal; (ii) the fire release rate plays a very significant role in the magnitude of the fire safety risk, as a 50% increase of the fire release rate can lead to a rough 36% decrease of SITotal; and (iii) exits should be regarded as super bottlenecks with significant importance during the fire escape process, and much more attention should be paid to those bottlenecks in the possible evacuation routes. The simulation models developed in this research are further validated by the observed results from the field test and experiment. This research contributes: (a) to the body of knowledge by providing an improved ASET/RSET approach that is capable of taking numerical factors (i.e., fire, building, and human features) into account to assess the safety risk of fire conditions in a three-dimensional environment; and (ii) to the state of practice by providing a more accurate data-driven solution for the perception and discovery of the worst fire scenarios.

Some relevant parameters for assessing fire hazards of combustible mine materials using laboratory scale experiments

When combustible materials ignite and burn, the potential for fire growth and flame spread represents an obvious hazard, but during these processes of ignition and flaming, other life hazards present themselves and should be included to ensure an effective overall analysis of the relevant fire hazards. In particular, the gases and smoke produced both during the smoldering stages of fires leading to ignition and during the advanced flaming stages of a developing fire serve to contaminate the surrounding atmosphere, potentially producing elevated levels of toxicity and high levels of smoke obscuration that render the environment untenable. In underground mines, these hazards may be exacerbated by the existing forced ventilation that can carry the gases and smoke to locations far-removed from the fire location. Clearly, materials that require high temperatures (above 1400 K) and that exhibit low mass loss during thermal decomposition, or that require high heat fluxes or heat transfer rates to ignite represent less of a hazard than materials that decompose at low temperatures or ignite at low levels of heat flux. In order to define and quantify some possible parameters that can be used to assess these hazards, small-scale laboratory experiments were conducted in a number of configurations to measure: 1) the toxic gases and smoke produced both during non-flaming and flaming combustion; 2) mass loss rates as a function of temperature to determine ease of thermal decomposition; and 3) mass loss rates and times to ignition as a function of incident heat flux. This paper describes the experiments that were conducted, their results, and the development of a set of parameters that could possibly be used to assess the overall fire hazard of combustible materials using small scale laboratory experiments.

Bench-Scale Test Facility for Evaluating the Performance of Thermal Imagers for Fire Service Applications.

A bench-scale facility was developed for the evaluation of thermal imaging cameras. Smoke obscuration conditions in the optical smoke cell were characterized by measuring laser light transmittance through the cell. Measurements showed that the laser transmittance along the axial direction of the optical smoke cell was relatively uniform in the upper and lower halves of the cell for various smoke obscuration conditions. The thermal sensitivity of thermal imagers was investigated using the Michelson Contrast (CM) as a performance metric for a bar target viewed through the smoke-filled cell for different background thermal conditions. The results of the study indicate that the optical smoke cell can be utilized as a well-controlled and effective bench-scale test apparatus to evaluate aspects of the performance of thermal imagers for fire service applications.

Poly(vinyl chloride) and its fire properties

SummaryThis work provides an up‐to‐date review of the fire properties of poly(vinyl chloride) (PVC) materials, both rigid (unplasticized) and flexible (plasticized). The fire properties addressed include ignitability, ease of extinction (oxygen index), flame spread (small scale and intermediate scale), heat release, smoke obscuration, smoke toxicity, hydrogen chloride emission and decay, and performance in real‐scale fires.This comprehensive review includes a wide selection of references and tables illustrating the properties of PVC materials in comparison with those of other polymeric materials, including, in many instances, wood materials. The work puts these fire properties in perspective, showing that the heat release rate (the key fire property) of rigid PVC (and that of properly flame‐retarded flexible PVC) are among the lower values found for combustible materials. This work also shows that the smoke toxicity and smoke obscuration resulting from burning PVC materials in real‐scale fires is in the same range as those of other materials.

ASSESSMENT OF THE UTILITY OF THE ADVANCED HIMAWARI IMAGER TO DETECT ACTIVE FIRE OVER AUSTRALIA

Wildfire detection and attribution is an issue of importance due to the socio-economic impact of fires in Australia. Early detection of fires allows emergency response agencies to make informed decisions in order to minimise loss of life and protect strategic resources in threatened areas. Until recently, the ability of land management authorities to accurately assess fire through satellite observations of Australia was limited to those made by polar orbiting satellites. The launch of the Japan Meteorological Agency (JMA) Himawari-8 satellite, with the 16-band Advanced Himawari Imager (AHI-8) onboard, in October 2014 presents a significant opportunity to improve the timeliness of satellite fire detection across Australia. The near real-time availability of images, at a ten minute frequency, may also provide contextual information (background temperature) leading to improvements in the assessment of fire characteristics. This paper investigates the application of the high frequency observation data supplied by this sensor for fire detection and attribution. As AHI-8 is a new sensor we have performed an analysis of the noise characteristics of the two spectral bands used for fire attribution across various land use types which occur in Australia. Using this information we have adapted existing algorithms, based upon least squares error minimisation and Kalman filtering, which utilise high frequency observations of surface temperature to detect and attribute fire. The fire detection and attribution information provided by these algorithms is then compared to existing satellite based fire products as well as in-situ information provided by land management agencies. These comparisons were made Australia-wide for an entire fire season - including many significant fire events (wildfires and prescribed burns). Preliminary detection results suggest that these methods for fire detection perform comparably to existing fire products and fire incident reporting from relevant fire authorities but with the advantage of being near-real time. Issues remain for detection due to cloud and smoke obscuration, along with validation of the attribution of fire characteristics using these algorithms.

ASSESSMENT OF THE UTILITY OF THE ADVANCED HIMAWARI IMAGER TO DETECT ACTIVE FIRE OVER AUSTRALIA

Abstract. Wildfire detection and attribution is an issue of importance due to the socio-economic impact of fires in Australia. Early detection of fires allows emergency response agencies to make informed decisions in order to minimise loss of life and protect strategic resources in threatened areas. Until recently, the ability of land management authorities to accurately assess fire through satellite observations of Australia was limited to those made by polar orbiting satellites. The launch of the Japan Meteorological Agency (JMA) Himawari-8 satellite, with the 16-band Advanced Himawari Imager (AHI-8) onboard, in October 2014 presents a significant opportunity to improve the timeliness of satellite fire detection across Australia. The near real-time availability of images, at a ten minute frequency, may also provide contextual information (background temperature) leading to improvements in the assessment of fire characteristics. This paper investigates the application of the high frequency observation data supplied by this sensor for fire detection and attribution. As AHI-8 is a new sensor we have performed an analysis of the noise characteristics of the two spectral bands used for fire attribution across various land use types which occur in Australia. Using this information we have adapted existing algorithms, based upon least squares error minimisation and Kalman filtering, which utilise high frequency observations of surface temperature to detect and attribute fire. The fire detection and attribution information provided by these algorithms is then compared to existing satellite based fire products as well as in-situ information provided by land management agencies. These comparisons were made Australia-wide for an entire fire season - including many significant fire events (wildfires and prescribed burns). Preliminary detection results suggest that these methods for fire detection perform comparably to existing fire products and fire incident reporting from relevant fire authorities but with the advantage of being near-real time. Issues remain for detection due to cloud and smoke obscuration, along with validation of the attribution of fire characteristics using these algorithms.

Combustion and Toxic Gas Production from Disposable Barbecues in Enclosures

The production of carbon monoxide from disposable barbecues in an enclosed room has been investigated. Hazard calculations have shown that lethal concentrations of CO and CO2 can be produced easily. Burning rates and the relative formation of CO and CO2 depend on the ambient oxygen concentration. Smoke does not correlate with CO concentration as it is mostly produced by the combustion of volatile hydrocarbons added to facilitate ignition. In a typical room, this results in smoke clearing before the maximum CO concentration is reached. Smoke obscuration is therefore a poor indicator of the danger posed by CO. This is an important observation for those discovering or attempting to resuscitate or rescue comatose victims. Dilution caused by ventilation is described numerically and has allowed total volumes of CO and CO2 produced to be estimated.

Exploring the Role of Feature Subset Combinations on Performance of Multisensor Fire Detection

Multisensor technology has been widely accepted as the next generation fire detection technology. The objective of this research is to explore influence of various feature subset combinations on multisensor fire detection performances. ANN models of BP, RBF, and PNN are selected as fire detection classifier. Four fire signatures, namely temperature, smoke obscuration, CO, and CO2 concentrations, are used to generate possible fire detection combinations. Fire detection performance of reliability and sensitivity are investigated of different combinations using parameters of wrong alarm rate and detected fire point respectively. RESULTS indicate that fire detection performance declines with increasing number of ANN in multisensor fire detection. Various combinations with the same ANN number can still produce dramatically different multisensor fire detection performance, and ANN models can overcome the disadvantage of various combinations to a large extent. Performance of PNN is highlighted of all the three selected ANN models by investigation results.

Uncertainty of Tenability Times in Multiroom Building Fires

Fire risk for building occupants is determined by the time required for safe egress and the time at which untenable conditions develop in building rooms or on the egress routes. In the present study, the CFAST zone model is applied to the simulation of fire development and smoke propagation in multiroom buildings, with the aim of studying the sensitivity of predicted tenability times and quantification of the uncertainties due to variability of the scenario parameters. The building geometries considered are (i) a single room with a door and a window, (ii) three rooms connected by a long corridor, and (iii) two-level configuration with two rooms on the lower floor connected by a vertical vent to a room on the upper floor. Sensitivity indices of the tenability times due to high temperature and smoke obscuration are analyzed. Distribution functions of the tenability times are presented and compared for different building rooms.

Evaluation of criteria for the detection of fires in underground conveyor belt haulageways

Large-scale experiments were conducted in an above-ground gallery to simulate typical fires that develop along conveyor belt transport systems within underground coal mines. In the experiments, electrical strip heaters, imbedded ∼5cm below the top surface of a large mass of coal rubble, were used to ignite the coal, producing an open flame. The flaming coal mass subsequently ignited 1.83-m-wide conveyor belts located approximately 0.30m above the coal surface. Gas samples were drawn through an averaging probe located approximately 20m downstream of the coal for continuous measurement of CO, CO2, and O2 as the fire progressed through the stages of smoldering coal, flaming coal, and flaming conveyor belt. Also located approximately 20m from the fire origin and approximately 0.5m below the roof of the gallery were two commercially available smoke detectors, a light obscuration meter, and a sampling probe for measurement of total mass concentration of smoke particles. Located upstream of the fire origin and also along the wall of the gallery at approximately 14m and 5m upstream were two video cameras capable of both smoke and flame detection. During the experiments, alarm times of the smoke detectors and video cameras were measured while the smoke obscuration and total smoke mass were continually measured.Twelve large-scale experiments were conducted using three different types of fire-resistant conveyor belts and four air velocities for each belt. The air velocities spanned the range from 1.0m/s to 6.9m/s. The results of these experiments are compared to previous large-scale results obtained using a smaller fire gallery and much narrower (1.07-m) conveyor belts to determine if the fire detection criteria previously developed [1] remained valid for the wider conveyor belts. Although some differences between these and the previous experiments did occur, the results, in general, compare very favorably. Differences are duly noted and their impact on fire detection discussed.