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Walking Speed in Smoke: Representation in Life Safety Verifications
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... Xie et al. [5] indicated that the body mass index (BMI) has a significant effect on ascending evacuation speed and proposed an evacuation model to predict the best evacuation path in fire stairways. The effect of occupant characteristics on crawling speed in evacuations has been studied by Kady and Davis [6], who showed that the mean crawling speed is 0.77 m/s, significantly higher than other studies which propose a crawling speed of around 0.3 m/s [7,8]. This finding is vital in order to improve the reliability of evacuation models. ...
... He created a graphic relation between extinction coefficient and walking speed for irritant and non-irritant smoke. For example, for an extinction coefficient of 0.5, which corresponds to a visibility of approximately 6 m for irritant and 12 m for non-irritant smoke, the walking speed is 0.3 m/s and 1 m/s, respectively [7,8,11]. In addition, Fridolf et.al reveal that the crucial visibility limit is set to 3 m, and for values below that, speed decreases radically; they also provided a variation of unimpeded walking speed according to population characteristics [7]. ...
... For example, for an extinction coefficient of 0.5, which corresponds to a visibility of approximately 6 m for irritant and 12 m for non-irritant smoke, the walking speed is 0.3 m/s and 1 m/s, respectively [7,8,11]. In addition, Fridolf et.al reveal that the crucial visibility limit is set to 3 m, and for values below that, speed decreases radically; they also provided a variation of unimpeded walking speed according to population characteristics [7]. ...
In order to achieve a comprehensive study regarding evacuation efficiency in underground space, globally accepted regulations and standards include, among other parameters, the maximum unimpeded travel speed of occupants in case of emergency evacuation. Researchers attempt to investigate the variation of travel speed using different approaches. The aim of this paper is to study occupants’ travel speed during evacuation procedures in an underground space. Underground spaces have special requirements as they differentiate from a typical building regarding the absence of physical lighting, the fact that exit route paths are always ascending and the limited orientation awareness of their users. A total of 40 volunteers participated in a large-scale experiment that involved
the evacuation of the underground space in real time. Two distinct evacuation drills took place, the first one in a smoke-free environment and the second simulated fire conditions via the presence of dense artificial smoke. During each trial, the required evacuation time as well as the walking speed of each occupant were monitored, with the aid of digital cameras positioned in appropriate spots inside the underground space. The evacuation speed resulted from the experiments is compared to those of international regulations (e.g., NFPA 130) regarding horizontal travelling, as well as travelling on an upward staircase. The effect of the presence of smoke on evacuation speed is discussed. The
importance of direct and constant guidance to the occupants of an underground space is highlighted during evacuation in a smoked environment and its contribution to safety improvement. Finally, the effect of the egress route type of an underground space on occupants’ speed is discussed and how this may affect the decision making during the design of an underground infrastructure, in order to achieve a safe environment.
... where w m ax is the maximum gait speed, w 0 is the comfortable unimpeded speed, V is visibility, T is temperature, C CO is the percentage concentration of CO, and t exp is the time of exposure to smoke in minutes. For irritant gases, Purser (15) developed an equation illustrating the effect of fractional walking speed as a function of FIC, as shown in Equation 13. ...
... Sixthly, a further investigation on the weighting of each factor and the influence on the walking speed based on Equation 14 would be beneficial. Currently, the assumption is that the impact of visibility, temperature, CO, and irritant gases on walking speed is equal, as each factor has been separately studied by Cao et al. (4), Jin (10), Fridolf et al. (13), Fruin (14) and Purser (15). ...
In the discipline of fire engineering, computational simulation tools are used to evaluate the available safe egress time (ASET) and required safe egress time (RSET) of a building fire. ASET and RSET are often analyzed separately, using computational fluid dynamics (CFD) and crowd dynamics, respectively. Although there are advantages to coupling the ASET and RSET analysis to quantify tenability conditions and reevaluate evacuation time within a building, the coupling process is computationally complex, requiring multiple steps. The coupling setup can be time-consuming, particularly when the results are limited to the modeled scenario. In addition, the procedure is not uniform throughout the industry. This paper presents the successful one-way coupling of CFD and crowd dynamics modeling through a new simplified methodology that captures the impact of fractional effective dose (FED) and reduced visibility from smoke on the individual evacuee’s movement and the human interaction. The simulation tools used were Fire Dynamics Simulator (FDS) and Oasys MassMotion for crowd dynamics. The coupling was carried out with the help of the software development kit of Oasys MassMotion in two different example geometries: an open-plan room and a floor with six rooms and a corridor. The results presented in this paper show that, when comparing an uncoupled and a coupled simulation, the effects of the smoke lead to different crowd density profiles, particularly closer to the exit, which elongates the overall evacuation time. This coupling method can be applied to any geometry because of its flexible and modular framework.
... Responders will then reduce their speed and modify their route accordingly. [30] provides a walking speed function as a function of visibility. This is referred to as absolute walking speed in the paper, but we will treat it as a factor that slows the speed of each occupant. ...
... Thus, an increased risk is observed for the fire case 2. We note that the visibility data are later used to assess each evacuee's speed factor in the evacuation simulation model, in which the agent movement and chosen evacuation routes will be determined based on the fire effect. In this study, the evacuee speed is computed from Equation (14) following an analysis from Fridolf et al. [52], where vis denotes the visibility data obtained from the visibility measurement device. ...
Emergency events in the industrial sector have been increasingly reported during the past decade. However, studies that focus on emergency evacuation to improve industrial safety are still scarce. Existing evacuation-related studies also lack a perspective of fire assembly point’s analysis. In this research, location of assembly points is analyzed using the multi-criteria decision analysis (MCDA) technique based on the integrated information entropy weight (IEW) and techniques for order preference by similarity to ideal solution (TOPSIS) to support the fire evacuation plan. Next, we propose a novel simulation model that integrates fire dynamics simulation coupled with agent-based evacuation simulation to evaluate the impact of smoke and visibility from fire on evacuee behavior. Factors related to agent and building characteristics are examined for fire perception of evacuees, evacuees with physical disabilities, escape door width, fire location, and occupancy density. Then, the proposed model is applied to a case study of a home appliance factory in Chachoengsao, Thailand. Finally, results for the total evacuation time and the number of remaining occupants are statistically examined to suggest proper evacuation planning.
... (1) [42] summarized data on the speed of pedestrians walking in smoke based on 10 different empirical formulas and provided a representation of walking. e relationship between the speed and visibility functions, the visibility impact coefficient and visibility are as follows: ...
Traditional methods are using FDS and Pathfinder for numerical simulation of fire evacuation and do not consider the impact of fire products on pedestrians, which will lead to erroneous evacuation results. In order to explore the impact of fire products on pedestrian evacuation when a fire occurs in a building, the pedestrian evacuation risk assessment results are closer to the actual situation. By establishing a full-scale model based on the pedestrian evacuation speed coefficient, a numerical simulation of the evacuation of pedestrians under the influence of fire products is carried out, and the influence of spray intensity and smoke exhaust rate on pedestrian evacuation is analysed at the same time. The results show that, compared with traditional methods, the fire evacuation model based on the evacuation speed coefficient can better reflect the evacuation effect of the real fire scene. At the same time, adding spray and smoke exhaust devices can give pedestrians more time to escape.
Bu çalışmada hastane binalarında yangın anında kullanıcıların tahliyesi ve dumandan etkilenme oranlarının simülasyon destekli olarak incelenmesi için HAD tabanlı yangın simülasyonu Fire Dynamic Simulator (FDS) ile birlikte tahliye simülasyonu kullanılarak, yatay tahliye, asistanlı tahliye gibi hastane binalarına özel tahliye olanaklarının irdelenmesi hedeflenmiştir. Yangın simülasyonunda ilgili yönetmelik ve standartlarda belirtilen yangın yükleri baz alınarak hesaplamalar yapılmıştır. Hastane binalarında bulunacak yaşam destek ünitesine bağlı, medikal gazlara muhtaç, hareket kabiliyetleri sınırlı vb. hastaların yangın anında tahliyesi ve dumandan etkilenme oranları incelenmiştir. Örnek bir hastane mimarisi üzerinden tahliye olanaklarının yeterliliği araştırılmıştır. Yapılacak tahliye simülasyonunda hastane ortamında bulunabilecek çeşitli hareket kabiliyetlerine sahip bina kullanıcılarının durumları göz önünde bulundurulmuştur. Bu bağlamda tahliye simülasyonu programında kullanıcı grupları oluşturularak gerçek duruma en yakın veriler elde edilmesi hedeflenmiştir. Yangın simülasyonu yazılımında hazırlanacak örnek yangın durumu tahliye simülasyonu yazılımına aktarılacak ve bu programda mimari üzerinde yerleştirilmiş olan bina kullanıcılarının tahliye süreleri, dumana maruz kalma düzeyleri, maruz kalınan sıcaklık değerleri ve yangın emisyonu olan toksik gazlara maruziyet dereceleri irdelenmiştir.
One of the challenges in the case of fire in tunnels is how to limit the propagation of smoke efficiently. Solid curtains which are released from the tunnel ceiling at the time of fire can prevent the smoke from further spread in the tunnel. The main issue with the traditional straight shape curtains is that there is no guarantee for providing a complete safe environment as enough visibility, temperature, and smoke concentration for the people at the region where the smoke is trapped behind the curtain. This paper introduces an idea to make a modification of the straight curtain shape to be L-shape and to use it at a location close to the smoke extraction vent. Results showed that in the case of straight curtain, part of the smoke moves downward after hitting the curtain and then diffuses at low elevations. On the other hand, the L-shape curtain redirects the smoke stream moving downward about 90° before being captured by the smoke extraction vent. The L-shape curtain increased the visibility and provided lower temperatures and smoke concentration compared with the straight curtain shape. Moreover, L-shape curtain created better interaction with the vent resulting in higher smoke flow extraction rate.
In order to increase the knowledge on human behavior in smoke, an evacuation experiment was performed in a road tunnel in Stockholm in July, 2014. The experiment included 66 participants, who individually were instructed to evacuate a smoke-filled tunnel. The experiment focused on measuring the participants’ walking speed in smoke-filled, as well as smoke-free parts of the tunnel. In addition, exit choice was studied. In this paper, the experiment is described, and novel data on walking speed in smoke is presented, including coupled data on unobstructed walking speed. In addition, a short presentation of the results related to way-finding and exit choice is included. It is clear that although this paper expands the current knowledge on walking speed in smoke, future research is necessary in order to conclude how to represent an individual’s walking speed in smoke. Recommendations on a way forward are suggested, and included is a review of the now currently available data-sets, as well as a suggestion for a future evacuation experiment.
The visibility of signs in smoldering smoke of filter-paper was reported in the previous issue by the author. In this paper, the visibility of signs in various smoke such as generated from wooden and various plastic building materials is studied. The relation between the visibility and the smoke density at the obscuration threshold of the sign in smoldering smoke (white) or in flaming smoke (black) are shown in Fig. 1 and Fig. 2. The product of the visibility (V) and the smoke density (σ) at the obscuration threshold is almost constant in the case of either white smoke or black one. Relative scattered luminous flux due to smoke, which influences the visibility of sign, is measured (see Fig. 3). There is no difference between the scattered luminous flux due to smoldering smoke of Japanese cedar and that of various plastics. However, the scattered luminous flux due to flaming smoke varies with the kind of building materials or the quantity of supplied air for burning. Assuming that the value of k for smoldering smoke (white) is 1.0, the values of k for flaming smoke is obtained from the experimental results to be about 0.3∼1.0 as shown in Table 1 and Table 2. The sizes of smoke particles, which influence strongly the scattered luminous flux, are measured by taking microscopic photographes (see Fig. 4). The particles of various smoldering smoke are sphere of about 1 μ as shown in Photo. 1, Photo. 2, and Fig. 5, while those of flaming smoke are consists of non-sphere particles of about 1∼20 μ, and some sphere particles which are considered smoldering smoke particles. Also, an experiment is carried out to take microscopic photographes on suspended smoke particles (see Photo. 4 and Photo. 5). The threshold contrast (δc) of a back-lighted sign varies depending on the visibility, the illuminance in corridor and the properties of smoke, but it is presumed to be δc = 0.01∼0.02 under the conditions of the visibility of 5∼15 m and usual corridor-illumination lights (see Fig. 8). The value of L in white smoke is given by the mean illuminance (Mean illuminance from all direction multiplied by 1/π) without smoke. However, L in black smoke requires tremendous calculation because it depends on the smoke density and the properties of smoke. By assuming that the illumination is given by point light source, and reflection from wall surface can be neglected, L in black smoke will be given approximately by Eq. (4). © 1971, Japan Association for Fire Science and Engineering. All rights reserved.
This chapter is an updated version of the previous chapter �Evacuation Timing� that appeared in thefourth edition of the SFPE Handbook. This new version of the chapter represents a significant change to previous versions, moving from a narrative description of important case studies that include data to a tabular representation of a broader range of data-sets. It is hoped that this approach provides a useful reference resource for readers © Society of Fire Protection Engineers 2016. All rights reserved.
Among tunnel fire safety strategies, evacuation speed in smoke, which is the basic evacuation performance characteristic, is one of the most important factors when assessing safety. An evacuation experiment in a full-scale tunnel filled with smoke has been done in order to clarify the relation between extinction coefficient up to Cs = 1.0 m−1, which includes Cs = 0.4 m−1 as a Japanese road tunnel fire prevention standard, and evacuation speed. The maximum, minimum and mean values of normal walking speeds are almost constant regardless of the extinction coefficient. As for the emergency evacuation speeds, the maximum speed is largely influenced by extinction coefficient, decreasing rapidly from 3.55 m/s at Cs = 0.30 m−1 to 2.53 m/s at Cs = 0.75 m−1 while the minimum and mean speeds are almost constant with a slight decrease as Cs increases. The maximum evacuation speed trends in the present experiments and those in Frantzich and Nillson (2003, 2004) and Fridolf et al. (2013), lie on the same decreasing logarithmic curve as a function of extinction coefficient.
The aims of this chapter are to provide methods for the assessment of life safety hazards in fires and an understanding of the effects of smoke, heat, and toxic fire effluents on occupants of buildings and other enclosures. Detailed discussions of the physiology and derivation of expressions suitable for a range of applications are presented in the main sections of the chapter. The assessment of toxic products from materials and the findings from studies of the toxicity of fire effluents in humans and animals from fire incident investigations, large and bench-scale fire tests and animal exposures is presented in Chapter 62 (Purser). To aid the reader wishing to apply the methods to engineering hazard calculations, a summary of all the principal calculation expressions required for ASET design calculations, is presented in Appendix 2.6A with an example of an application in Table 2.6. 22 and associated explanations. Full descriptions of the derivation of the different expressions, with more detail variations for specific applications, and further examples are presented in the later sections of this chapter. The summary section expressions are fully cross-referenced to the main text.
We conducted travel speed measurements to clarify the effect of visibility on evacuee’s performance. As visual ability is dependent on the individual, members of the two age groups (30 youths and 30 seniors) were subjected to a visual acuity test prior to the travel experiment. In our research, we define subject’s visual acuity as recognizable threshold of form perception using Landolt Ring. Visual acuity is a person’s ability to see distinctly the details of an object. We set eight levels of floor illuminance, complete or incomplete adaptation conditions and luminous conditions with or without smoke. Since the travel speed of the younger group was faster than that of the older group, regardless of illuminance level or smoke density, the difference in travel speed can be predicted by visual acuity. In this report, we constructed a calculation model to predict travel speed as functions of the luminous environment (incorporating illuminance level, adaptation condition, and smoke density) and evacuee’s visual acuity. This model helps us predict performance of evacuees under fire, smoke or blackout conditions.
An experimental study was conducted in order to clarify a degree of human emotional instability under smoke condition. Mental arithmetic and walking speed were adopted as indices of the emotional instability, and furthermore an annoyance of smoke and heat was investigated by questionnaire. The emotional instability caused by physiological factors, such as smoke irritation, is found to be important as well as a psychological unrest under high irritant smoke. Such fire smoke affects the thinking power and walking speed. Especially the heat from smoke is found to reduce the thinking power in the range between 2,030 kcal/m² h and 1,370 kcal/m² h.