Fire Following Earthquake Modelling, Probabilistic Ignition Model For Building Stock (original) (raw)
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Urban Utility Ignition Model, A Probabilistic Approach For Modelling Fire Following Earthquake
This paper presents the methodology proposed for modelling ignitions caused by urban utility network following earthquakes. In this model ignition following earthquake is modelled probabilistically, being dependent on several parameters such as strong ground motions, volume of utility network, type of gas pipeline, type of power network and urban building density. In order to consider uncertainties associated with the parameters controlling urban utility ignitions, an analytical approach using logic tree and Monte Carlo simulation process is proposed here. A GIS-based computer program has been also designed and developed in this work which can estimate ignition probability for urban utility network following earthquakes. As a pilot study, the utility network for a city district in northern Tehran, the capital city of Iran is modelled in this work. Preliminary results for a scenario earthquake as well as probabilistic earthquake scenarios are shown in this paper.
Fire Safety Journal, 2012
Risk Monte Carlo simulation Urban fire spread model Urban evacuation model Fires following an inland earthquake a b s t r a c t An evaluation method for urban post-earthquake fire risk is presented. Urban fires and urban evacuations are highly dependent on uncertain factors, such as the number and locations of fire outbreaks, the wind velocity and direction, and the population distribution. To implement effective measures to ensure the safety of buildings and individuals in fires, a method to evaluate the effectiveness of the various safety measures that consider the influence of the uncertain factors is essential. Risk is introduced into the proposed method, in which the risk is defined as the probability that the ratio of burned-down buildings or fire fatalities in a district will exceed a threshold within a given time period after an earthquake. The risk is calculated by a combination of Monte Carlo simulation and physics-based fire-spread/evacuation simulation, in which uncertainty is considered in the following inputs: (1) the number and locations of fire outbreaks; (2) the firefighting at the initial stages; (3) the weather; (4) the earthquake-related structural damage to buildings; (5) the initial evacuee locations and (6) the obstruction of roads. In this paper, the risk of Kyoto City was evaluated for eight types of inland earthquake to demonstrate the use of the model. As a result, the effectiveness of countermeasures that improve the fire resistance of buildings could be quantified in terms of risk reduction. This result indicates that the method could be an effective tool for disaster prevention.
Sensitivity Analysis of Fire-Following Earthquake Models
2016
Fire-Following Earthquake (FFEQ) is a secondary disaster to earthquakes which can cause significant losses and, in some cases, may comprise a large portion of the total loss by developing into large conflagrations (e.g., 1906 San Francisco earthquake). In order to estimate fire losses, conditioned on the occurrence of an earthquake, a probabilistic conflagration model is required. Such a model predicts the burnt areas based on the three-phases of the FFEQ process: fire ignition, fire spread and fire suppression. The first phase, fire ignition, estimates the number of fires that can occur in the aftermath of an earthquake and is a function of the intensity and time of occurrence of the earthquake, the square footage of the buildings in the impacted region, and the mix of construction and occupancy classes. The second phase, fire spread, estimates the propagation of each of the initial fires within a building, to other buildings, and among city blocks. This process is in general a fun...
Journal of architecture,planning and environmental engineering, 2012
A risk-based evaluation method for countermeasures against seismic-induced fires was developed considering the influences of uncertain factors governing behaviors of urban fire and evacuation. A risk concept was introduced into the proposed method, where the risk was defined as the probability that the ratio of burnt down buildings or burn death people in an administrative unit exceeds a threshold within a given time period from the earthquake. The risk was calculated by a combination of Monte Carlo simulation and physics-based fire/evacuation simulation, where the following uncertain factors were considered to set fire scenarios: (1) ignition; (2) fire fighting at initial stage; (3) weather; (4) structural damage of a building; (5) initial location of an evacuee; and (6) passage obstruction of a road. In this paper, the risk of Kyoto city was evaluated by the assumption of eight kinds of inland earthquakes to validate the availability of the method. As a result, the effect of the measure which enhances fireproof performance of buildings could be quantified with the decrement of the risk.
This paper presents the proposed methodology and preliminary results for modelling intra-structure effective ignition following earthquakes. In this model the occurrence of intra-structure ignitions is correlated to several parameters such as seismic ground motions, buildings seismic vulnerability, building content characteristics, utility damage, building area, building occupancy and time of earthquake. During an earthquake, depending on building and contents characteristics, many simultaneous ignitions might occur but not all could turn into devastating fires. Fire following ignitions may turn into real fire where fire fighting efforts are interrupted. In this paper the effect of such interruptions due to damages to urban water network system induced by earthquake are modelled. In this paper probability of fire following ignitions is modelled using a probabilistic algorithm involving many factors and their uncertainties such as building characteristics as well as ground motion parameters. At the same time damage to urban water supply systems is estimated for each earthquake scenario using an analytical approach in order to estimates the water loss as well as restoration time period. The geographical and probabilistic distribution of ignition following earthquakes, once combined with probabilistic distribution of water loss distribution and restoration maps, provides probabilistic maps of effective ignitions following earthquakes. A GIS-based computer tool has been also developed in this study which consists of modules for analytical and probabilistic analyses as well as GIS functionality for spatial analyses and data visualization. As a pilot study, inventory of building and urban water network data for a residential district in northern Tehran are used in this paper to demonstrate the application and preliminary results for this study.
Post-earthquake fires: risk assessment and precautions
2024
Earthquakes have great damage potential and importance in risk management and structural engineering, causing fires in buildings such as residences and commercial spaces. Post-earthquake fires (PEF) are secondary disasters that can cause material and moral destruction and loss of life. Similar to natural disasters, they show the time of occurrence and possible scenarios in places. This study aims to analyse and examine what precautions can be taken to prevent or minimize PEF through risk assessment. In this study, a literature review was conducted with the tracking method, focusing on examples from the world where the fires that occur as a secondary effect of the earthquake can cause devastating damages and significant disasters, and inferences are made by classifying the data obtained. Many factors, such as gas leaks due to earthquakes, cracks in pipelines, and short circuits in electrical installations, can cause fires. In addition, flammable liquid or combustible gas emissions and fire protection disturbances create significant fire hazards after earthquakes. In this paper, in which the causes and consequences of fires are analysed, risks, the evaluation process depending on the risks, the precautions that can be taken according to the situations that the risks will cause, and the models developed are emphasized. The research is a reference study with the expectation that there will be an increase in the number of studies examining experimental and physical PEF models.
This report describes an approach for modeling the number of ignitions (fires) following an earthquake. The modeling is not meant to be exact, but to provide a context for assessing the likelihood of various fire scenarios. The first component of the approach is a statistical model to predict the number of ignitions for a new earthquake event. This model is based on data for ignitions following earthquakes from 1906 to 1989 in Alaska and California. These U.S. fire data are taken from reports by fire departments on the fires they responded to immediately after the earthquakes and for several days thereafter. These data are for fires in the general built environment, including residential, commercial and industrial structures. The data contain estimates for the mean peak ground acceleration (PGA) for each earthquake, an estimate of the built area affected in million square feet (MMSF) for each earthquake, and the number of ignitions within the estimated affected area (IGNS). The statistical model uses negative binomial regression to estimate the expected number of ignitions as a function of the explanatory variables, PGA and MMSF. The associated upper confidence and prediction limits are derived from the statistical model using only spreadsheet technology. The upper prediction limit is used to determine a conservative estimate of the probability of a specified number of ignitions following a future earthquake event. The results from the spreadsheet technology are compared to more exact results based on numerical integration. The spreadsheet probability estimates are shown to be conservative.
Earthquake Spectra
This paper presents the development of a stochastic model for time series prediction of the number of post-earthquake fire ignitions in buildings for use in post-earthquake fire risk assessment. Here, two-kinds of Poisson regression models with an explanatory variable of JMA instrumental seismic intensity were applied to 126 ignitions affected by ground motion, which were extracted from the ignition record for the 2011 Tohoku Earthquake: (1) a time-dependent occurrence model for the ignitions from electricity-related sources, which is coupled with a statistical model for electrical supply rate after the earthquake, and (2) a time-independent occurrence model for the ignitions from gas-related sources, oil-related sources, and others. In order to verify the models, time series prediction of the number of ignitions in the 2011 Tohoku Earthquake was conducted by using Monte Carlo simulation. From the calculated results, we concluded that the models could reasonably explain the occurren...
RELIABILITY RISK ASSESSMENT IN HIGH RISE BUILDINGS IN CASE OF FIRE
The practice of structural fire safety engineering remains to be case-specific and the estimation of fire resistance of structures is mostly deterministic. Many researchers in structural fire engineering utilize the performance- based design method but these studies do not include the inherent uncertainties in both the demand and capacity. This paper investigates the structural fire reliability of tall buildings based on the framework used for earthquake hazard by the Pacific Earthquake Engineering Research (PEER) and Eurocode. The financial district of Istanbul in Turkey is taken as a case study for this research. Parameters such as building type and height, structural system, number of floors, floor area, number of elevators and stairs, the use of fire suppression systems, evacuation routes are provided by the municipalities in order to develop a probabilistic methodology to estimate the fire safety of these structures. The analysis is conducted by estimating the intensity or the hazard curve as described by PEER framework. The hazard domain includes random variables such as the fire load, the opening factor, the fire duration and the maximum fire temperature. The findings of this research will provide essential information on the fire safety risk of each tall building in a densely populated financial district. It will allow the municipalities and fire brigades to have a probabilistic risk assessment of these structures and develop evacuation and human rescue plans accordingly in case of a fire hazard. Further, this research will provide useful data to insurance companies to estimate fire hazard insurance premiums.