Scenario simulation of indoor post-earthquake fire rescue based on building information model and virtual reality

Advances in Engineering Software 143 (2020) 102792

Contents lists available at ScienceDirect

Advances in Engineering Software journal homepage: www.elsevier.com/locate/advengsoft

Research paper

Scenario simulation of indoor post-earthquake fire rescue based on building information model and virtual reality

T

Xinzheng Lua, , Zhebiao Yangb, Zhen Xuc, Chen Xiongd ⁎

a

Key Laboratory of Civil Engineering Safety and Durability of China Education Ministry, Department of Civil Engineering, Tsinghua University, Beijing, China Beijing Engineering Research Center of Steel and Concrete Composite Structures, Tsinghua University, Beijing, China c School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing, China d Guangdong Provincial Key Laboratory of Durability for Marine Civil Engineering, Shenzhen University, Shenzhen, China b

ARTICLE INFO

ABSTRACT

Keywords: Earthquake Fire rescue BIM Virtual reality Non-structural components

Post-earthquake fires occur frequently, and the seismic damage to non-structural components results in dangerous fire and evacuation environments. Both firefighters and trapped people will face serious threats to life during the rescue. Consequently, a simulation framework of an indoor post-earthquake fire rescue scenario based on building information model (BIM) and virtual reality (VR) is proposed herein. Information of structural and non-structural components is extracted from the BIM. Subsequently, the seismic damage of non-structural components is predicted according to the time-history results and fragility curves. Moreover, a smoke visualization method combining volume rendering and the particle system is also proposed. A case study of a 19-story hospital is conducted using the proposed method for establishing the fire rescue scenario. The results show that the established VR scenario has high realism and smooth interactivity, and the influence of smoke on the fire rescue is more significant than that of fallen debris.

1. Introduction Earthquakes can cause structural damage to buildings, and various non-structural components, such as sprinkler systems, suspended ceilings, and infilled walls, can also be damaged. The damage to structural and non-structural components will lead to a higher risk of postearthquake fire [1–3]. Furthermore, when the sprinkler system is damaged, its ability to suppress fire will be weakened dramatically. In addition, people may be trapped indoors due to injuries or moving difficulties, especially in some special types of buildings (e.g., hospitals, primary and secondary schools, or nursing homes). Damaged nonstructural components such as suspended ceilings and infilled walls will result in obstacles in the evacuation paths [4–6]. When firefighters enter the building to search for trapped people, in many cases, they are not familiar with the indoor environment. As the evacuation paths are covered by debris and the visibility is limited owing to smoke, both firefighters and trapped people might face serious risks. It is worth mentioning that a post-earthquake fire environment is more complex than that in conventional fires, and the experience of firefighters in this environment is quite limited. Therefore, it is necessary to establish a post-earthquake fire rescue scenario and provide realistic and reliable training for firefighters.

⁎

An effective method of fire training is to set up an environment with real fire [7,8]. However, such a training environment is costly, involves high risks, and cannot meet the fire training requirements of a large number of firefighters (there are 370,000 firefighters in China [9]). The development of virtual reality (VR) technology provides an effective solution for such training tasks, and has been successfully applied in the field of emergency training and education [10–13]. However, owing to the combination of various hazards, the influencing factors on postearthquake fires are very complex. Research on the construction of post-earthquake fire scenarios is very limited, and almost no system exists for post-earthquake fire rescue training. Therefore, the purpose of this study is to establish a post-earthquake fire VR scenario, to achieve a highly realistic post-earthquake fire environment and provide the necessary and reliable training system for evacuation and rescue. Although research on VR is abundant, there are few studies on postearthquake fire rescue VR scenarios. To establish a post-earthquake fire rescue VR scenario, the following two key problems need to be addressed: (1) The combination of multiple hazards. Post-earthquake fire rescue involves several combined hazards, including post-earthquake fire, seismic damage of non-structural components, and fallen debris.

Corresponding author. E-mail address: [email protected] (X. Lu).

https://doi.org/10.1016/j.advengsoft.2020.102792 Received 19 May 2019; Received in revised form 27 November 2019; Accepted 21 February 2020 0965-9978/ © 2020 Elsevier Ltd. All rights reserved.

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

pedestrian speed [11,31,32]. By analyzing the data on human behavior in a smoke diffused environment, some researchers have proposed a quantitative relationship between pedestrian speed and soot density [33,34]. Based on the aforementioned studies, the pedestrian speed in a VR scenario when considering the combined effect of the soot density and fallen debris will be simulated and analyzed. Problem (2) involves the construction of VR scenarios and the visualization of smoke. In terms of scenario construction, existing VR engines provide an efficient and convenient modeling platform. Unity, as a professional cross-platform game development and VR engine [35], has been widely used in the development of a VR fire environment [36–38]. Therefore, Unity is employed in this work. The construction of VR scenarios requires detailed building models. Although the VR scenarios are established in [32], the modeling of the beams, columns, and walls of the scenario relies highly on manual work, which is unsuitable for large-scale buildings with a complex indoor environment. To avoid the labor-intensive model generation, BIM, which is a three-dimensional model with details [39,40], is adopted to establish the VR scenario. Existing methods for smoke visualization include particle systems and volume rendering [7]. Particle systems can quickly model smoke and provide a certain degree of realism [41,42], but the smoke motion generated by a particle system does not match the actual diffusion process, especially in complex indoor spaces [31,43]. By contrast, volume rendering visualizes smoke by adjusting the opaqueness of each grid in the space. Many researchers have used volume rendering to demonstrate the spread of smoke based on FDS simulation results [11,32], which provides a realistic diffusion process. However, it should be noted that the volume rendering method will consume substantial computer resources. As volume and complexity of the building increase, the fluency of display and interactivity will be significantly reduced when the volume rendering method is adopted. Regarding the problems mentioned, a simulation framework for a post-earthquake fire rescue scenario is proposed in this study. BIM, VR, and the new-generation of seismic performance assessment methods are adopted to develop a highly realistic visualization of post-earthquake fire scenarios, in which seismic damage, fire spread, and fallen debris are taken into consideration. The combined effects of the earthquake, post-earthquake fires, and fallen debris can be analyzed through the proposed framework, and the characteristics of evacuation and rescue in a multi-hazard environment can also be studied. Moreover, both realism and performance can be balanced using the proposed smoke visualization method. Based on the Unity platform, the modeling and visualization of the post-earthquake fire scenario of a 19-story hospital building is accomplished, and the fire spread and personnel movement in different scenarios are analyzed. The methodology proposed herein can assist firefighters to conduct specialized drills and provide an effective technical support for fire rescue training.

These hazards affect each other. For example, the post-earthquake fire will spread more quickly owing to the damage of the sprinkler system, and the evacuation and rescue will be severely hindered by smoke and fallen debris. Therefore, to create a realistic postearthquake fire environment, it is necessary to conduct accurate and efficient simulations of various hazards and consider the combining effects among the different hazards. (2) VR scenario construction and smoke visualization. Establishing a post-earthquake fire rescue scenario requires a refined building model. Owing to the complexity of the indoor environment, the modeling workload is quite labor intensive. To meet the fire training requirements of firefighters in different types of buildings, a convenient and efficient VR scenario generation methodology needs to be proposed. In addition, smoke spread will affect evacuation and rescue behavior. Considering the variation in performance of different computers, smoke visualization needs to consider both the computer performance and the realism of visual effects. For problem (1), many studies have been performed on postearthquake fire and seismic damage of non-structural components. Different ignition models and fire spread models of post-earthquake fires have already been developed [14–17]. The computational fluid dynamics software Fire Dynamics Simulator (FDS), widely used in ordinary fires, can also be used for post-earthquake fire simulation [11,18–20]. However, the damage of the sprinkler system will affect the spread of a post-earthquake fire. Note that the components of the sprinkler system work together, and the damage of different water pipes and sprinkler drops will affect the overall fire extinguishing performance. Most studies have only focused on the seismic damage assessment of individual sprinkler components [21,22], and there has been very limited research on the overall performance of the sprinkler system [17]. Xu et al. [23] proposed a seismic damage assessment method based on a building information model (BIM) of the sprinkler system, which can efficiently and accurately determine its overall fire extinguishing performance. Therefore, this method is adopted herein for predicting the performance of the sprinkler system. A considerable amount of fallen debris will be produced during an earthquake, and most of the indoor fallen debris comes from suspended ceilings [5,6,24]. Many experiments on seismic damage to suspended ceiling have been conducted and fragility curves of suspended ceiling have been proposed [25–27]. These studies provide a basis for determining the damage of suspended ceilings and the corresponding fallen debris. Fire smoke will significantly reduce visibility. Existing research indicates that pedestrian speed decreases when soot density increases [17,28,29], and earthquake-induced fallen debris will also reduce pedestrian speed [30]. There is no research on the combined influence of these two factors on pedestrian speed. Furthermore, existing VR scenarios do not consider the influence of smoke and fallen debris on

Fig. 1. The proposed framework of post-earthquake fire rescue scenario simulation. 2

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

are required to construct the post-earthquake fire rescue scenario. The BIM contains key information, such as the geometric dimensions, structural parameters, and information of non-structural components and materials. The geometric dimensions can be used for establishing the indoor environment; the structural parameters can be used for seismic response calculation; and the material will affect the combustion performance of building components. The widely-used BIM software Revit [45] is adopted herein. The FBX file is exported from Revit to generate the geometric model needed for subsequent modeling. The structural model of the building can also be constructed using BIM to conduct the seismic response analysis [46,47]. The pre-processing software for FDS, PyroSim [48], is used to convert the data from BIM to FDS. Note that the seismic damage of the sprinkler system should be considered in the post-earthquake fire simulation, but PyroSim cannot handle such data. Consequently, Xu et al. [23] proposed a method based on Dynamo to obtain the required data of the sprinkler system. This method is adopted herein to establish the complete FDS model.

2. Framework As shown in Fig. 1, the proposed framework consists of five modules: (1) BIM; (2) Unity modeling; (3) Seismic damage assessment; (4) Post-earthquake fire simulation; (5) VR scenario construction. Module 1: BIM BIM is used to establish the geometric, structural, and FDS fire models. These three models form the basis of subsequent analyses and simulations. Specifically, the geometric model used by Unity can be established, according to the geometric information of the BIM [35,44]. The structural model can be established according to structural information, and it is employed to conduct further seismic response analysis. The FDS fire model can be established based on the building and sprinkler system information extracted from the BIM. Module 2: Unity modeling

3.2. Unity modeling

The construction of a post-earthquake fire VR scenario is implemented using Unity. The geometric model obtained in Module 1 cannot meet the requirements of high realism of the VR scenario. Therefore, it is necessary to employ both 3ds Max and Unity software to add texture, illumination, and the fallen debris of suspended ceilings (which is simulated in Module 3) to the geometric model.

The FBX file exported from BIM contains the geometric information of the building. However, some components (e.g., texture and illumination) are not included in the BIM. Because the 3ds Max software has outstanding model modification functions [49], it is adopted to construct a more realistic indoor environment. Specifically, the FBX file of the building obtained in Module 1 is imported into the 3ds Max software, and the professional editing tools provided by 3ds Max are used to add texture and illumination in the geometric model to enrich the details. The completed model will be exported to Unity to generate the VR scenario.

Module 3: Seismic damage assessment The earthquake will cause damage to various building components. Based on the structural model, the seismic response results (e.g., the time history results of displacement, velocity, and acceleration of each story) can be obtained through the nonlinear time-history analysis (THA). Non-structural components, such as suspended ceilings and sprinkler systems, will significantly affect the post-earthquake building fire rescue [2,23]. Therefore, based on the time history results and fragility curves, the seismic damage of these two types of non-structural components is calculated in this module, which provides the input data for the Unity modeling in Module 2 and post-earthquake fire simulation in Module 4.

3.3. Seismic damage assessment In the post-earthquake fire rescue scenario, the impacts caused by the seismic damage of the sprinkler system and suspended ceilings are the most significant. The seismic damage of these two types of nonstructural components, along with their influences on post-earthquake fire and personnel movement, are discussed in this section. 3.3.1. Analysis of seismic damage of non-structural components The seismic responses of the building should first be obtained when conducting seismic damage assessment of building components. As the structural model has been established in Module 1, the nonlinear THA is conducted to obtain the seismic responses (e.g., the time history results of the displacement, velocity, and acceleration of each story). The fragility curves of non-structural components are provided in FEMA P-58 [25], and the probabilities of various damage states can be determined based on the time history results and fragility curves. The sprinkler system consists of sprinkler drops and water pipes, which have two damage states [25], namely DS1 and DS2. Different performances will be exhibited at different damage states. For example, pipes will suffer losses in their volume of flow at DS1 and a significant leakage at DS2. The method proposed by Xu et al. [23] is adopted herein to predict the influence of seismic damage on the fire extinguishing performance. Specifically, fragility curves (Fig. 2) are first employed to evaluate the seismic damage of each sprinkler component, and the overall seismic damage of the sprinkler system is determined through a tree data structure. The seismic damage assessment for the suspended ceiling is introduced as follows. According to FEMA P-58, the suspended ceiling (C3032) has three damage states, i.e., DS1, DS2, and DS3. A certain percentage of area will fall off at each damage state, as presented in Table 1. When the suspended ceiling is at DS3, it will fall completely. The suspended ceiling is an acceleration-sensitive component [25]. Therefore, the damage state and its probability can be determined by the corresponding fragility curve based on the peak floor accelerations

Module 4: Post-earthquake fire simulation The performance of the sprinkler system is affected by the damage states of sprinkler drops and water pipes, which have already been obtained in Module 3. According to the performance of the sprinkler system, the post-earthquake fire simulation model of the building is established. FDS software is employed to simulate the fire spread process and calculate the motion of smoke particles. Monitoring grids are set inside the building to output soot densities for fire analysis and visualization. Module 5: VR scenario construction The fire rescue VR scenario consists of three parts, namely, (1) fallen debris modeling, (2) smoke visualization, and (3) VR scenario construction. The building model established in Module 2 contains the geometry of the fallen debris, to which the collider property [35]. should be assigned to mimic real obstacles. The combination of volume rendering and particle system is employed to realize smoke visualization based on the soot density results. 3. Methodology 3.1. BIM Building information, seismic damage results, and fire spread data 3

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

Fig. 2. Fragility curves of sprinkler system.

story, Ps(DSi) represents the percentage of fallen area of the suspended ceiling at DSi, and Pj(DS = DSi) represents the probability that the suspended ceiling on the jth story is at DSi. After determining the total fallen area of the suspended ceiling, the model of fallen debris can be established in 3ds Max. The fallen debris is randomly distributed on the ground [50], and this area is equal to the results calculated by Eq. (4).

Table 1 Damage states of suspended ceilings.

Damage condition

DS1

DS2

DS3

5% of the area falls

30% of the area falls

All area falls

3.3.2. Influence of seismic damage of non-structural components on the fire scenario The influence of the seismic damage of non-structural components on the fire scenario includes two parts: (1) the influence of sprinkler system damage on fire spread, and (2) the influence of smoke and fallen debris on pedestrian speed. The sprinkler drop has two types of seismic damage states, namely complete loss of function and partial loss of function [25]. It should be noted that because the sprinkler system works as a whole, the damage of water pipes will eventually influence the spray flow of the connected sprinkler drops, which will affect the fire suppression effect of the sprinkler system. The influence of the sprinkler system damage on fire spread can be determined through the FDS simulation in Module 4. Both smoke and fallen debris will reduce pedestrian speed [30,33,34], and the combined effects are complex. Fridolf et al. [33] indicating that when the soot density is high, pedestrian speed can be quite slow. Therefore, in the present study, the upper limit of the pedestrian speed under different scenarios is first determined according to the soot density, and the impact of fallen debris on the pedestrian speed is further discussed.

Fig. 3. Fragility curves of suspended ceilings.

(PFAs) obtained from the nonlinear THA. Fig. 3 shows the fragility curves of the suspended ceiling provided by FEMA P-58. The probability of DS1, DS2, and DS3 can be calculated using Eqs. (1) to (3), where P(DS > DS1), P(DS > DS2), and P(DS > DS3) are obtained from the fragility curves based on the PFAs. (1)

P (DS = DS3) = P (DS > DS3)

P (DS = DS2 ) = P (DS > DS2)

P (DS > DS3)

(2)

P (DS = DS1) = P (DS > DS1)

P (DS > DS2)

(3)

3.4. Post-earthquake fire simulation Based on the FDS model established in Module 1, combined with the seismic damage of the sprinkler system obtained in Module 3, the performance of the sprinkler system in the fire analysis model is determined. The FDS software [51] can then be used to perform postearthquake fire simulations to calculate the movement of smoke particles. The fire spread process can be visualized through Smokeview, which is the post-processing software of FDS [52]. Because the interactivity of personnel is necessary in a fire rescue scenario, the visualization in Smokeview cannot meet the training requirements. Therefore, smoke results should be extracted from the FDS results. Specifically, smoke monitoring grids are set inside the building, with a size of 0.25 m × 0.25 m × 0.25 m. The FDS keyword “QUANTITY = 'DENSITY', SPEC_ID = 'SOOT'” [51] is utilized to monitor and output the soot densities of each grid, which provides the input data for establishing the fire VR scenario in Unity.

When calculating the seismic damage of the sprinkler system, the number of sprinkler drops at different damage states can be determined by multiplying the total number of drops by the probability [23]. Similarly, the fallen area of the suspended ceiling can be determined by multiplying the total area by the probability of the corresponding damage state. Because three seismic damage states exist, and the percentages are different, the total fallen area can be calculated as expressed in Eq. (4), 3

Sdebris, j = Stotal, j ×

[Ps (DSi ) × Pj (DS = DSi )] , j = 1, 2, 3, ...,n i=1

(4)

where Sdebris, j represents the fallen area of the suspended ceiling on the jth story, Stotal, j represents the total suspended ceiling area on the jth 4

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

3.5. VR scenario construction

effectively improved. The workload of modeling and controlling each grid is quite heavy, owing to the large number of grids during smoke rendering. However, as these grids are the same in size and mechanism, Prefabs provided by Unity can adapt well to this situation. Specifically, corresponding to the mesh size of the FDS grid, which is 0.25 m × 0.25 m × 0.25 m, a cube with the same size is also established in Unity, and then it is set as Prefabs. The above process is implemented using the C# script supported by Unity, where the steps are as follows:

The fire rescue VR scenario is established in Unity, in which smoke visualization is achieved by combining volume rendering and the particle system. When using the volume rendering method, FDS results are mapped to the soot densities of the grids. Therefore, a highly realistic visualization can be achieved. However, as a large quantity of soot density data needs to be read and updated during rendering, substantial system resources will be consumed. The particle system method is simple and efficient. It requires few system resources, which can ensure smooth interactivity. However, the soot densities of each grid using the particle system cannot coincide with the FDS results, resulting in a difference in visual effects. In the initial stage of the fire, the smoke diffusion path is complex owing to the indoor layout of the building, which makes it difficult to model using the particle system. For a building with a floor area of 1100 m2, after 5 min of fire ignition, the ignited room and the nearby corridor have already been filled with smoke [23]. This stage can be called “the smoke spread stage”. As visibility is quite poor in this period, smoke particle systems arranged inside the building can achieve visual effects similar to those in the volume rendering method. Therefore, to balance the characteristics of the indoor smoke spread and the requirements of computer performance, a smoke visualization method combining volume rendering and the particle system is proposed. That is, volume rendering is adopted in the initial stage of the fire and the particle system is adopted in the smoke spread stage. This combination can fully exploit the strengths of the two methods to ensure the visual effects and smooth interactivity for rescue training. The details are introduced as follows:

(1) Duplicate the cube Prefabs to fill the space that needs smoke rendering. (2) Read opaqueness data and assign them to every grid in the space. (3) Update the opaqueness of all grids at each time step to visualize the smoke spread in the building. The pseudo code is as follows: public class CubeController : MonoBehaviour { t ← number of time steps //Number of time steps noc ← number of cubes //Number of space grids create cube[noc] //Duplicate space grids for i ← 0 to noc-1 for j ← 0 to t-1 cubecolor[i, j] ← transparency[i, j] //Read opaqueness data and assign to array end for end for for j ← 0 to t-1 for i ← 0 to noc-1 cube[i].color ← cubecolor[i, j] //Assign opaqueness data to space grids end for end for }

3.5.1. Volume rendering Soot density data of the grids is required during volume rendering. Module 4 has already output the soot density Ds of the FDS grids, whose size is 0.25 m × 0.25 m × 0.25 m. For the space to be rendered, the maximum soot density Ds, max of all the grids should be first determined. Then, the opaqueness values α of each grid at each time step are calculated according to Eq. (5), which are adopted to perform smoke rendering [32] as shown in Fig. 4.

=

Ds Ds,max

3.5.2. Particle system The smoke particle system is contained in the Unity package. To mimic the process of smoke diffusion, the number and locations of the smoke particle systems should be set, whose parameters (e.g., duration, start speed, start size, emission, and shape) also need to be adjusted. As the room and corridor are filled with smoke in the smoke spread stage, it is only necessary to fill the corridor with the particle system to achieve a realistic visualization. It should be noted that the flame is also a type of particle system in Unity. The same method can be adopted to add the flame to the building, which effectively improves the realism of the scenario. Fig. 5 shows the smoke spread scenario in the initial stage of fire,

(5)

Smoke rendering in Unity requires real-time updating of the opaqueness values of all grids, which needs to control and update the property of each voxel. As a collection of game objects and components, Prefabs of Unity enables the game objects and resources to be reused [35]. Resource utilization and rendering efficiency can thus be

Fig. 4. Transformation from soot densities to opaqueness values. 5

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

Fig. 5. Smoke spread scenario.

which is implemented through volume rendering. The soot densities in the scenario correspond to the results of FDS. After the fire ignition, the smoke spreads from the ignited room to the corridor, and it first accumulates in the upper part of the floor. Then, the height of the smoke layer gradually moves downwards. It can be seen that volume rendering can achieve realistic visual effects in the initial stage of the fire. In the smoke spread stage, owing to the high soot density indoors, the visibility is extremely low. The diffusion scenarios of smoke using volume rendering and the particle system are shown in Fig. 6. At this moment, only the door on the left side and nearby fallen debris on the ground can be seen. The particle system can realize a smoke visualization scenario similar to that obtained with the volume rendering method. It should be noted that for the visualization of smoke in a 400 m3 space, the volume rendering method occupies nearly 1200 MB of memory, and the results of FDS need to be pre-processed before rendering, which occupies additional computer memory. Meanwhile, the particle system method only occupies 400 MB of memory and the modeling process is convenient. Therefore, the particle system method is adopted to realize smoke visualization in the smoke spread stage.

dormitory. The indoor environment of a hospital is more complicated compared with a dormitory. Therefore, the simulation of the scenario of an indoor post-earthquake fire in a hospital is more meaningful than that in a dormitory. Based on these demands, a 19-story hospital is chosen as the case study for a post-earthquake fire rescue. The building is a frame–shear wall structure with a total height of 81.6 m. The 3D BIM of the hospital is built in Revit, as shown in Fig. 7. There are 344 sprinkler drops on each floor, which are of 20 mm in diameter. Their designed volume of flow is 80 L/min, and the activated temperature is 68 ℃ [53]. According to the Chinese Code for Seismic Design of Buildings [54]. this region has an 8-degree seismic design intensity. The peak ground acceleration (PGA) is 200 cm/s2 for a design basis earthquake (DBE) with a return period of 475 years, and the PGA is 400 cm/ s2 for a maximum considered earthquake (MCE) with a return period of 2475 years. The widely used El-Centro ground motion record is selected as a typical ground motion input, whose PGA is scaled to 400 cm/s2. The seismic response of the building is obtained through nonlinear THA, and the peak accelerations of each floor are listed in Table 2. As the hospital is classified as Category B in the Chinese code “Standard for classification of seismic protection of building constructions” [55], it has superior structural performance. As a result, the hospital suffers slight structural damage under the given ground motion. The PFA varies from 2.62 to 5.53 m/s2. The maximum PFA, except the roof, occurs on the 10th story, which is of 4.80 m/s2. Fire is thus assumed to be ignited in a room on the 10th floor. The combustibles being ignited are mattresses undergoing polyurethane reactions [51]. According to the method proposed in Module 3, the seismic damage of the suspended ceilings and sprinkler system is calculated and as a result, 43% of the area of the suspended ceiling on the 10th floor falls off and six sprinkler

4. Case study 4.1. Case introduction Hospitals are densely populated and contain complex facilities, which results in a high risk of post-earthquake fire. Many patients in a hospital have mobility impairments; thus, they can become easily trapped indoors and cannot take refuge by themselves. Consequently, firefighters are often required to rescue them. The case in [23] is a

Fig. 6. Scenario comparison of two methods in the smoke spread stage. 6

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

Fig. 7. Schematic diagram of the hospital building.

(Fig. 8(b)). The fire data (e.g., temperature, soot density, and fractional effective dose (FED)) are monitored during the fire simulation. The FED is a commonly used measure of human incapacitation from combustion gases and is dimensionless [56,57]. When the FED reaches 100%, the person is considered to be incapacitated.

Table 2 PFAs of the hospital building. Story

PFA (m/ s2)

Story

PFA (m/ s2 )

Story

PFA (m/ s2)

Story

PFA (m/s2)

1 2 3 4 5

3.93 3.97 4.10 4.27 4.39

6 7 8 9 10

4.50 4.17 4.50 4.70 4.80

11 12 13 14 15

4.45 3.88 3.19 2.63 2.62

16 17 18 19

2.58 2.68 3.84 5.53

4.2. Results of post-earthquake fire simulation The smoke distributions under both the non-damage and damage scenarios are illustrated in Fig. 9, where deeper color indicates higher soot density. The smoke spread in these two scenarios is significantly different. When the sprinkler system is not damaged, the smoke propagation is effectively controlled. However, when the sprinkler system is damaged, the smoke has already occupied the ignited room and nearby corridor 500 s after fire ignition, and the soot density is much greater than that of the non-damage scenario. To analyze the effects of seismic damage quantitatively, the fire data of the key locations are compared in these two scenarios. The average fire data from the nine monitoring points are shown in Fig. 10. When no seismic damage occurs, the sprinkler system works normally. After approximately 150 s,

drops in the ignited room are completely damaged. The fire suppression ability of the sprinkler system is significantly weakened. The FDS simulation time is set to 500 s, and two fire scenarios are analyzed: the sprinkler system with seismic damage (namely “damage scenario”) and the sprinkler system without seismic damage (namely “non-damage scenario”). As shown in Fig. 8(a), the ignited room (labeled as L-1) is associated with fire initiation, whereas the lobby (labeled as L-2) and the staircase (labeled as L-3) are critical areas for evacuations. Therefore, they are selected as three key locations. Nine monitoring points are uniformly distributed in the ignited room

Fig. 8. Schematic diagram of the 10th floor. 7

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

Fig. 9. Comparison of smoke distribution between two scenarios.

the temperature in the room remains stable at 50 ℃. When the sprinkler system is damaged, the highest temperature of the ignited room reaches approximately 360 ℃. The maximum soot density (Fig. 10(b)) does not exceed 4 × 10−4 mg/m3 under the non-damage scenario, and it remains at 1 × 10−4 mg/m3, which is only 7.4% that of the damage scenario. Similarly, the maximum FED value in the room is 23-times that of the non-damage scenario (Fig. 10(c)). As the combustibles burn out, the temperature and soot density of the ignited room decrease significantly at approximately 400 s. It can be seen that the fire suppression ability of the sprinkler system is significantly weakened owing to the seismic damage, which has an extremely negative influence on

the movement of personnel. The combined effects of multiple hazards such as seismic damage of non-structural components and post-earthquake fire can be considered using the proposed method. At other key locations on the floor (Figs. 11–12), the soot densities and FED values in the damage scenario are obviously larger than those in the non-damage scenario. Because L-1 is located in the ignited room, whereas L-2 and L-3 are located in the corridor, and therefore the soot density and FED of L-1 are much higher than those of L-2 and L-3, which means the environment in the ignited room is more dangerous than that in the corridor. Given that the soot density and FED have great impacts on people's safety, the damage of the sprinkler system will cause more

Fig. 10. Quantitative comparisons between two scenarios in the ignited room. 8

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

Fig. 11. Quantitative comparisons between two scenarios at Location L-2.

Fig. 12. Quantitative comparisons between two scenarios at Location L-3.

serious casualties, which need to be considered in the fire rescue. 4.3. VR scenario The VR fire rescue scenario is established using the aforementioned methodology. The BIM is effectively utilized together with the texture and illumination added with 3ds Max. Consequently, the workload of the modeling is significantly reduced. The indoor scenario before the earthquake is shown in Fig. 13, in which the details of the building can be seen clearly, including walls, columns, doors, windows, and suspended ceilings. Fig. 14 shows the damage of the suspended ceilings and the fallen debris after the earthquake. According to the output of smoke results from the monitoring grids in FDS, the method proposed in Section 3.5 is adopted to visualize the smoke. In the smoke spread stage, trainees enter the room to conduct operations. The mouse and keyboard or other VR devices can be used to control actions and viewpoints. The post-earthquake fire scenario is shown in Fig. 15, where the viewpoints of the trainees are given in Fig. 16. It can be seen that there is some irregular fallen debris on the ground (Figs. 15(c)–(d)). Besides, the suspended ceiling of the building is damaged, and part of it is detached (Fig. 15(e)). In the environment filled with smoke, visibility is severely limited, which greatly hinders the actions of personnel. It should be noted that the VR scenario established herein has low requirements regarding device configuration. The scenario can be run and displayed smoothly on a desktop computer with an Intel Pentium G640 processor, 8 GB RAM, and NVIDIA GTX 750 graphics card. Such a platform is economic for promoting the training. To investigate the influence of the seismic damage to the nonstructural components on the rescue, it is assumed that some people are

Fig. 13. Indoor scenario before the earthquake.

9

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

Fig. 14. Damage of suspended ceilings and fallen debris after the earthquake.

trapped in Room A, and the firefighters start from the stairs to perform the rescue (Fig. 16). Three VR scenarios are established herein:

• Scenario 1: No fire, and the seismic damage of the sprinkler system and fallen debris are not considered; • Scenario 2: Fire exists, but the seismic damage of the sprinkler system and fallen debris are not considered; • Scenario 3: Fire exists, and the seismic damage of the sprinkler system and fallen debris are considered.

Due to the influence of smoke and fallen debris, the pedestrian speeds in these three rescue scenarios are different. Pedestrian speed in a smokeless environment is 4.60 m/s [34]. Smoke exists in Scenarios 2 and 3, and when people enter the fire rescue environment, the rescue route has already been filled with smoke. Based on the soot density, the visibilities of these two scenarios are calculated as 12.3 and 0.29 m, respectively [58,59]. In [33], the relationship between the pedestrian speed and smoke based on several experiments is proposed, which is adopted to calculate the pedestrian speed in Scenarios 2 and 3. The corresponding speeds are 3.73 and 0.42 m/s, respectively, which are set as the upper speed limits in these scenarios. It should be noted that, when the trainees control their movements in the VR scenario, the speed and route are influenced by smoke and fallen debris conjunctively. Smoke results in low visibility, which will reduce the speed and influence the route. Fallen debris will also collide with the trainee, thus influencing the speed and route. The rescue time depends on the speed and route of the trainee, which cannot be obtained directly based on the distance and speed taken from the references. To reduce the bias of the data, each scenario is implemented five times by the trainee. The average rescue time of these scenarios is shown in Fig. 17(a). In addition, people in the fire environment will face the threat of hazardous gases and heat radiation. When people are exposed to fire for more than a certain period of time, their lives will be in danger. The integrated hazards dose (IHDpath) proposed by Xu et al. [32] is selected as the indicator to calculate and compare the risk of the rescue route in these three scenarios (Fig. 17(b)). As Fig. 17 shows, in Scenario 1 the firefighter only needs 12 s to reach the room where the trapped person is located. In Scenario 2,

Fig. 15. Post-earthquake fire scenario.

10

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

upper limit. Scenarios 4 and 5 are also implemented five times by the trainee. The total rescue time from the starting point to Room A is recorded. The comparison of Scenarios 3–5 is presented in Table 3. The average speeds in Scenarios 3–5 are 0.38, 2.91 and 0.42 m/s, respectively. Compared with Scenario 1 (i.e., no fire or seismic damage), the average speed in Scenario 4, v4r, is reduced by 1.69 m/s owing to a collision with fallen debris. The average speed in Scenario 5, v5r, is reduced by 4.18 m/s owing to the low visibility caused by smoke. However, when considering the combined effect (i.e., Scenario 3), the average speed, v3r, is reduced by 4.22 m/s. This is not simply equal to the sum of v4r and v5r, where the effects of the two hazards are considered separately. When the initial pedestrian speed is fast (i.e., 4.60 m/s), the speed of the trainee is susceptible to fallen debris (i.e., Scenario 4), which will be reduced by 37%. By contrary, as the pedestrian speed in an environment with dense smoke is already slow (i.e., 0.42 m/s), the trainee will walk more carefully, and thus the influence of fallen debris on the trainee is small. It is therefore necessary to establish a post-earthquake fire scenario in which the combined effect of smoke and fallen debris is considered. 4.4. Discussion

Fig. 16. Schematic diagram of rescue path.

Through an establishment of the post-earthquake fire scenario, the feasibility of the framework proposed herein is demonstrated, and the case studied is a representative one. Specifically, for the input ground motion, the El-Centro 1940 ground motion is adopted because it is widely-used as a benchmark input for a structural response analysis. For the building, a typical hospital is selected, which has a typical ward layout used in Chinese hospitals. In addition, for the key buildings located within the area of a certain fire brigade, fire VR scenarios under different ground motions can be established based on the framework proposed herein. Firefighters can experience numerous different postearthquake fire scenarios, and targeted training can be conducted. Their understanding of smoke diffusion and fallen debris distribution can be improved, and their rescue experience in a post-earthquake fire environment can increase, which does not need to come at the cost of human life. Because the presented case is a representative one, useful references can be acquired based on the analyses and comparisons. Figs. 10–12 show the temperature, soot densities, and FED values at different locations under both non-damage and damage scenarios. The rescue time and risk of the rescue route under the three scenarios are illustrated in Fig. 17. References regarding the equipment configuration of firefighters as well as the seismic design of the building can thus be provided. Different respiratory protection equipment is required in different fire environments. In addition to the necessary firefighting clothing, firefighters should also be equipped with suitable fire protection equipment. In Scenario 2, the basic protective equipment is sufficient

although fire exists, the fire is effectively controlled because the sprinkler system is undamaged. The firefighter only requires 16 s to reach the room, which is close to the time required in Scenario 1. By contrast, in Scenario 3, owing to the damage of the sprinkler system, the fire cannot be suppressed, and the smoke is diffused throughout the floor. The firefighter requires 144 s to reach the room, which is 9-times that required in Scenario 2. In terms of the risk of the rescue route, IHDpath of Scenarios 1, 2, and 3 is 0, 0.011, and 0.361, respectively. Similarly, IHDpath of Scenario 3 is 33-times that of Scenario 2. Through the comparison, it can be seen that the soot density has a significant influence on the rescue time and risk. Therefore, the damage of the sprinkler system and its impact on human behavior must be considered in post-earthquake fire rescue scenarios. To clarify the combined effect of smoke and fallen debris, two more scenarios are established, which are recorded as Scenarios 4 and 5. In Scenario 4, only the distribution of fallen debris is the same as that in Scenario 3, and no smoke is present. In Scenario 5, only the smoke is the same as that in Scenario 3, and no fallen debris exists. The upper speed limit in both Scenario 3 and Scenario 5 is 0.42 m/s, which is determined based on the smoke and visibility. Because there is no smoke in Scenario 4, the upper speed limit is set as 4.60 m/s, which is equal to the pedestrian speed in a smokeless environment. The keyboard and mouse are used to control the movement in the VR scenario. Fallen debris will collide with the trainee. Therefore, the movement of the trainee will be hindered, and the average speed will be slower than the

Fig. 17. Comparison of different rescue scenarios. 11

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

Table 3 Comparison of scenarios considering the influence of smoke and fallen debris. Scenario

Conditions

Average rescue time (s)

Average speed (m/s)

Speed reduction (m/s)

3 4 5

Both smoke and fallen debris exist Only fallen debris exists Only smoke exists

144 19 130

0.38 2.91 0.42

4.22 1.69 4.18

for the firefighters. However, in Scenario 3, professional equipment should be prepared. Specifically, according to the Chinese code "Allocation standard for personal protective equipment of firefighters” [60], the respiratory protection equipment includes a firefighter gas mask and a self-contained positive pressure air breathing apparatus. In Scenario 2, the fire inside the building is not serious. Firefighters only need to wear gas masks to perform a rescue. In Scenario 3, the fire in the building is serious with limited visibility. Therefore, the firefighters need to be equipped with an air breathing apparatus and other professional equipment (e.g., firefighter flashlights and equipment protecting the firefighters from a fall). The weight and price of different types of equipment also differ. For example, a firefighter gas mask weighs only 1 kg and costs 400 RMB (approximately 57 US dollars), whereas a self-contained positive pressure air breathing apparatus weighs approximately 15 kg and costs 4000 RMB (approximately 570 US dollars). Based on a reliable simulation and analysis, it has been deemed important to be equipped with the most suitable equipment when in a fire environment, which not only can improve the rescue efficiency of the firefighters, it can also protect their safety. In addition, the analysis described herein also indicates that properly designed seismic building measures are necessary. When no seismic damage occurs to the sprinkler system, the soot density and FED can be effectively controlled. This indicates that, if the seismic response of the building is reduced and the seismic performance of the sprinkler system is improved, a post-earthquake fire can be effectively controlled, and the risk of firefighters can be reduced. For key buildings such as hospitals, seismic isolation measures can be adopted. Seismic bracings of the sprinkler system can also be applied to improve the performance of the sprinkler system during an earthquake. A seismic protection of the sprinkler system should be strictly required during the fire protection approval process, which is one of the most effective ways to improve the fire resistance of buildings under the current fire services system.

realism and computer performance can be balanced. (4) The methodology proposed herein provides a scientific basis for the establishment of a highly realistic post-earthquake fire scenario. As a result, an immersive interactive fire training VR environment can be accomplished. This study is expected to provide a useful reference and technical support for fire rescue training. CRediT authorship contribution statement Xinzheng Lu: Conceptualization, Writing - review & editing. Zhebiao Yang: Methodology, Software, Writing - original draft. Zhen Xu: Methodology, Validation. Chen Xiong: Visualization, Investigation. Declaration of Competing Interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, ―Scenario simulation of indoor post-earthquake fire rescue based on building information model and virtual reality. Acknowledgments The authors would like to acknowledge the financial supports of the National Key R&D Program(No. 2018YFC1504401) and the National Natural Science Foundation of China (No. U1709212, No. 51978049). References [1] Todd DR, Carino NJ, Chung RM, et al. 1994 Northridge earthquake: performance of structures, lifelines and fire protection systems. gaithersburg: National Institute of Standards and Technology (NIST). 1994. [2] Sekizawa A, Ebihara M, Notake H. Development of seismic-induced fire risk assessment method for a building. Proc Seventh Int Symp 2003:309–20. [3] Mousavi S, Bagchi A, Kodur VKR. Review of post-earthquake fire hazard to building structures. Can J Civ Eng 2008;35(7):689–98. [4] Fierro EA, Miranda E, Perry CL, et al. Behavior of nonstructural components in recent earthquakes. Proceedings of the 2011 Architectural Engineering National Conference. 2011. p. 369–77. Oakland, CA. [5] Miranda E, Mosqueda G, Retamales R, et al. Performance of nonstructural components during the 27 February 2010 Chile earthquake. Earthq Spectra 2012;28(S1):453–71. [6] Jacques CC, McIntosh J, Giovinazzi S, et al. Resilience of the canterbury hospital system to the 2011 christchurch earthquake. Earthquake Spectra 2014;30(1):533–54. [7] Williams-Bell FM, Kapralos B, Hogue A, et al. Using serious games and virtual simulation for training in the fire service: a review. Fire Technol 2015;51(3):553–84. [8] Yang XJ, Yi X, Peng Z, et al. Preliminary discussion of real fire fire-fighting train system. Fire Science and Technology 2015;34(9):1233–6. in Chinese. [9] Fire Department of MPS (FDMPS). China fire yearbook. Kunming: Yunnan People's Publishing House; 2018. 2018. in Chinese. [10] Lee EJ, El-Tawil S. FEMvrml: an interactive virtual environment for visualization of finite element simulation results. Adv Eng Softw 2008;39(9):737–42. [11] Cha M, Han S, Lee J, et al. A virtual reality based fire training simulator integrated with fire dynamics data. Fire Saf J 2012;50:12–24. [12] Manca D, Brambilla S, Colombo S. Bridging between virtual reality and accident simulation for training of process-industry operators. Adv Eng Softw 2013;55:1–9. [13] Xu Z, Wei W, Jin W, et al. Virtual drill for indoor fire evacuations considering occupant physical collisions. Autom Constr 2020;109:102999. [14] Lee S, Davidson R, Ohnishi N, et al. Fire following earthquake—reviewing the stateof-the-art of modeling. Earthq Spectra 2008;24(4):933–67. [15] Himoto K, Mukaibo K, Akimoto Y, et al. A physics-based model for post-earthquake

5. Conclusions In this work, a framework for VR scenario modeling of post-earthquake indoor fires is proposed. The seismic damage of sprinkler systems and suspended ceilings is calculated, and the visualization of smoke spread is achieved. Taking a hospital building as an example, the VR environment of a post-earthquake fire is established, and the spread of indoor fire and rescue of personnel in different scenarios are analyzed. The following conclusions are drawn: (1) The generation of a BIM-powered model is clearly convenient for establishing the VR scenario, structural analysis model, and fire analysis model. The combined impacts of earthquake and fire to the rescue scenario can be clearly considered. (2) The rescue environment will be worsened because of the seismic damage of the sprinkler system and fallen debris. Compared with the scenario where the sprinkler system has no seismic damage, the time required for rescue will increase by nearly 800%, and the IHDpath will increase by 3200% in the damage scenario. Therefore, the seismic damage of non-structural components and its impact on the movement of personnel must be considered in the modeling of post-earthquake fire rescue environments. (3) The smoke visualization method combining volume rendering and the particle system can achieve realistic visual effects, and both the 12

Advances in Engineering Software 143 (2020) 102792

X. Lu, et al.

[16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38]

[39] Cerovsek T. A review and outlook for a ‘Building Information Model’(BIM): a multistandpoint framework for technological development. Advanced Engineering Informatics 2011;25(2):224–44. [40] Ding L, Zhou Y, Akinci B. Building information modeling (BIM) application framework: the process of expanding from 3D to computable nD. Autom Constr 2014;46:82–93. [41] Ren AZ, Chen C, Luo Y. Simulation of emergency evacuation in virtual reality. Tsinghua Sci. Technol. 2008;13(5):674–80. [42] Sun QY, Wan WG, Yu XQ. The simulation of building escape system based on Unity3d. IEEE 2016;2016:156–60. [43] Cao LJ, Lin J, Li N. A virtual reality based study of indoor fire evacuation after active or passive spatial exploration. Comput Human Behav 2019;90:37–45. [44] Ardolino A, Arnaud R, Berinstein P, et al. Geometry and models: 3D format conversion (FBX, COLLADA). Game Development Tool Essentials. Berkeley: Apress; 2014. [45] Autodesk. revit: built for BIM. http://www.autodesk.com/products/revit-family/ overview, 2019. [46] Hu ZZ, Zhang JP. BIM-and 4D-based integrated solution of analysis and management for conflicts and structural safety problems during construction: 2. development and site trials. Autom Constr 2011;20(2):167–80. [47] Barazzetti L, Banfi F, Brumana R, et al. Cloud-to-BIM-to-FEM: structural simulation with accurate historic BIM from laser scans. Simul Modelling Pract Theory 2015;57:71–87. [48] Thunderhead engineering. Pyrosim, http://www.thunderheadeng.com/pyrosim/, 2019. [49] Murdock KL. autodesk 3ds max 2013 bible. John Wiley & Sons; 2012. [50] Cimellaro GP, Ozzello F, Vallero A, et al. Simulating earthquake evacuation using human behavior models. Earthq Eng Struct Dyn 2017;46(6):985–1002. [51] McGrattan K, Hostikka S, McDermott R, et al. Fire dynamics simulator user's guide (6th edition). Gaithersburg: National Institute of Standards and Technology. 2013. [52] Forney GP. Smokeview (Version 5)-A tool for visualizing fire dynamics simulation data, volume I: user's guide. gaithersburg. National Institute of Standards and Technology; 2017. [53] Ministry of public security of the people's republic of china (MPS). code for design of sprinkler systems (GB 50084-2017). Beijing: China Planning Press; 2017. in Chinese. [54] Ministry of housing and urban-rural development of the people's republic of China (MOHURD). code for seismic design of buildings (GB50011-2010). Beijing: China Architecture & Building Press; 2010. in Chinese. [55] Ministry of housing and urban-rural development of the people's republic of China (MOHURD). standard for classification of seismic protection of building constructions, GB 50223-2008. Beijing: China Architecture & Building Press; 2008. in Chinese. [56] Purser DA. SFPE handbook of fire protection engineering, chapter toxicity assessment of combustion products. 3rd edition Massachusetts: National Fire Protection Association, Quincy; 2002. [57] McGrattan K, Hostikka S, McDermott R, et al. Fire dynamics simulator technical reference guide, volume 2: verification. 6th edition Gaithersburg: National Institute of Standards and Technology; 2013. [58] Jin T. Studies on human behavior and tenability in fire smoke. Fire Safety Science 1997;5:3–21. [59] Mulholland GW, Croarkin C. Specific extinction coefficient of flame generated smoke. Fire and Mater 2000;24(5):227–30. [60] Ministry of public security of the people's republic of China (MPS). allocation standard for personal protective equipment of firefighters (GA 621-2013). Beijing: Standards Press of China; 2013. in Chinese.

fire spread considering damage to building components caused by seismic motion and heating by fire. Earthq Spectra 2013;29(3):793–816. Anderson D, Davidson R A, Himoto K, et al. Statistical modeling of fire occurrence using data from the Tōhoku. Jpn Earthq Tsunami 2016;36(2):378–95. Risk Analysis. Meacham BJ. Post-earthquake fire performance of buildings: summary of a largescale experiment and conceptual framework for integrated performance-based seismic and fire design. Fire Technol 2016;52(4):1133–57. Hu LH, Fong NK, Yang LZ, et al. Modeling fire-induced smoke spread and carbon monoxide transportation in a long channel: fire dynamics simulator comparisons with measured data. J. Hazard. Mater. 2007;140(1–2):293–8. Zalok E, Hadjisophocleous GV. Assessment of the use of fire dynamics simulator in performance-based design. Fire Technol 2011;47(4):1081–100. Šulc S, Šmilauer V, Patzák B, et al. Linked simulation for fire-exposed elements using cfd and thermo-mechanical models. Adv Eng Softw 2019;131:12–22. Soroushian S, Zaghi AE, Maragakis EM, et al. Seismic fragility study of displacement demand on fire sprinkler piping systems. J Earthq Eng 2014;18(7):1129–50. Jenkins C, Soroushian S, Rahmanishamsi E, et al. Experimental fragility analysis of pressurized fire sprinkler piping systems. J Earthq Eng 2017;21(1):62–86. Xu Z, Zhang ZC, Lu XZ, et al. Post-earthquake fire simulation considering overall seismic damage of sprinkler systems based on BIM and FEMA P-58. Autom Constr 2018;90:9–22. Wang Y. Lessons learned from the “5.12” Wenchuan earthquake: evaluation of earthquake performance objectives and the importance of seismic conceptual design principles. Earthq Eng Eng Vib 2008;7(3):255–62. Federal Emergency Management Agency (FEMA). Seismic performance assessment of buildings volume 1–methodology, technical report FEMA-P58, FEMA, Washington DC, 2012. Soroushian S, Rahmanishamsi E, Ryu KP, et al. Experimental fragility analysis of suspension ceiling systems. Earthq Spectra 2016;32(2):881–908. Soroushian S, Rahmanishamsi E, Jenkins C, et al. Fragility analysis of suspended ceiling systems in a full-scale experiment. J Struct Eng 2019;145(4):04019005. Wright M.S., Cook G.K., Webber G.M.B. The effects of smoke on people's walking speeds using overhead lighting and wayguidance provision. Proceedings of the 2nd international symposium on humanbehaviourin fire. MIT, Boston. 2001: 275–284. Yamada T, Akizuki Y. Visibility and human behavior in fire smoke. SFPE handbook of fire protection engineering. 2016:2181–206. Lu XZ, Yang ZB, Cimellaro GP, et al. Pedestrian evacuation simulation under the scenario with earthquake-induced falling debris. Saf Sci 2019;114:61–71. Smith SP, Trenholme D. Rapid prototyping a virtual fire drill environment using computer game technology. Fire Saf J 2009;44(4):559–69. Xu Z, Lu XZ, Guan H, et al. A virtual reality based fire training simulator with smoke hazard assessment capacity. Adv Eng Softw 2014;68:1–8. Fridolf K, Andrée K, Nilsson D, et al. The impact of smoke on walking speed. Fire Mater 2014;38(7):744–59. Seike M, Kawabata N, Hasegawa M. Experiments of evacuation speed in smokefilled tunnel. Tunn Undergr Sp Technol 2016;53:61–7. Unity Technologies. Unity 5.x entry to the master. Beijing: China Railway Press; 2016. in Chinese. Wang B, Li H, Rezgui Y, et al. BIM based virtual environment for fire emergency evacuation. The Sci World J 2014:1–22. Andrée K, Nilsson D, Eriksson J. Evacuation experiments in a virtual reality high‐rise building: exit choice and waiting time for evacuation elevators. Fire Mater 2016;40(4):554–67. Diez HV, García S, Mujika A, et al. Virtual training of fire wardens through immersive 3D environments. Proceedings of the 21st International Conference on Web3D Technology. California: Anaheim; 2016. p. 43–50.

13