Simulation of Mass Fire-Spread in Urban Densely Built Areas Based on Irregular Coarse Cellular Automata

Abstract

Mass fire-spread is a potential threat to some densely built urban areas by its devastating destructions. Especially in case of a large earthquake when multiple fires break out simultaneously, fire-spread hazard is likely to overwhelm fire-fighting capabilities and enlarge damage area. To explore fire-spread behavior and assess its damages, a simulation model of fire-spread in densely built urban areas is developed. Cellular Automata (CA) is a Bottom-up dynamics model that can reproduce a complicated phenomenon by setting up simple rules in a cell space. However, the traditional grid-based cells of CA are not suitable for modeling building-to-building fire-spread behavior. Therefore, an irregular coarse CA schema is proposed in this paper. Two sub-processes are involved urban mass fire-spread, i.e. (I) fire-developing in a single building and (II) fire-spread among buildings. When a fire is developing in a single building, the building will experience 5 fire stages along time, which become the states of cell. While fire spreads among buildings, there are 2 spread patterns: (I) short-range direct flame contact, radiation and convection spread and (II) long-range firebrand spotting spread. In relation to the 2 spread patterns, 2 sets of neighborhoods and rules of CA are formulated respectively. To verify the newly developed model, 100 times of individual random simulations for a real site fire-spread in Kobe City after Hanshin Earthquake (1995, Japan) are performed using an integrated GIS-CA-fire tool developed in the paper. Comparing the simulation results with the local observations, the general feature of fire-spread is found similar, and it is proved that the newly developed model is reliable to simulate urban fire-spread. Furthermore, based on the simulated results, a loss assessment model is formulated to calculate economic and life losses after fire-spread.

Spatial Analysis of Fires in Vilnius City in 2010–2012

“…(Sternlieb, Burchell 1973;Bertrand, Lawrence 1976;Karter et al 1977Karter et al , 1978USFA 2004USFA , 2009). 21st century brought more studies in Europe (Corcoran et al 2007a(Corcoran et al , 2007bšpatenkova, Stein 2010), Asia (Urban Research Institute 2004;Nisanci 2010;Zhao 2011;Lu et al 2013), Australia Chhetri et al 2009;Sufianto, Green 2012). A number of them applied spatial and temporal analysis and resulted in prognostic maps Wu 2007;Rohde et al 2010;Zhao 2011) and mathematical models (Wu, Ren 2009;Ceyhan et al 2013;Zhang 2013).…”

A Hybrid Fire Warning Model Based on Cellular Automata

“…After the spread rate of forest fire is calculated, we use a continuous extended polygon to simulate the dynamic process of fire spread based on Huygens principle [4]. First, starting from the coordinates of the fire site, we calculate the speed of forest fire spread in eight directions (north, northeast, east, southeast, south, southwest, west, and northwest) based on the empirical formula.…”

Fire spread simulation using GIS: Aiming at urban natural gas pipeline

“…In 2006, Zhao et al simplified the model for spread inside buildings (Zhao et al, 2006;Zhao, 2010) and divided the entire fire simulation process into in-building spread and building-to-building spread. Cousins et al (2002) and Ohgai et al (2007) developed a cellular automata urban fire spread model based on a 3 Â 3 grid; Zhao et al (2011) improved this model by modifying its form and increasing the cell size to develop an urban fire spread model based on coarse cellular automata. In 2008, Lee et al compared and summarized existing urban post-earthquake fire spread models in terms of aspects such as the model algorithm, model parameter, result analysis, and model presentation (Lee and Davidson, 2008).…”

“…This study visualizes the analysis of fire impacts and simulation of fire spread by employing powerful GIS spatial analysis and image display technologies (Zhao, 2011). The pre-warning system can not only serve as an important reference for related decision-making departments in formulating contingency plans but also assist in related planning management departments in conducting prevention, control, publicity, and education regarding areas with potential safety hazards before any accident happens; furthermore, it can contribute toward the secondary planning and reconstruction of a city so as to nip any potential risks in the bud (Han and Weng, 2010).…”