Fire Growth Model Research Articles

PostBP: A Python library to analyze outputs from wildfire growth models

Wildfire is an important natural disturbance agent in Canadian forests, but it has also caused significant economic damage nationwide. Spatial fire growth models have emerged as important tools for representing wildfire dynamics across diverse landscapes, enabling the mapping of key wildfire hazard metrics such as location-specific burn probabilities or likelihoods of fire ignition. While these summary metrics have gained popularity, they often fall short in capturing the directional spread of wildfires and their potential spread distances. The metrics depicting the directional spread of wildfire can be derived from raw outputs generated with fire growth models, such as the perimeters and ignition locations of individual fires, but extracting this information requires complex data processing. To address this data gap, we present PostBP, an open-source Python package designed for post-processing the raw outputs of fire growth models — the ignition locations and perimeters of individual fires simulated over multiple stochastic iterations — into a matrix of fire spread likelihoods between all pairs of forest patches in a landscape. The PostBP also generates several other summary outputs, such as the source-sink ratio and the fire spread rose diagram. We provide an overview of PostBP's capabilities and demonstrate its practical application to a forested landscape.•Wildfire growth models generate large amounts of outputs, which are hard to summarize for practical decision-making.•The PostBP package calculates the summary metrics characterizing the directional spread of wildfires.•The fire risk summaries generated with PostBP can support the assessments of wildfire risk and mitigation measures.

Evaluation of Available Safety Egress Time (ASET) in Performance-Based Design (PBD) Using CFAST

In South Korea, the need to link fire and evacuation simulations to compare the available safety egress time (ASET) and required safety egress time (RSET) in real time when implementing performance-based design in buildings is increasing. Accordingly, the Consolidated Model of Fire Growth and Smoke Transport (CFAST) has been discussed as an alternative to the fire dynamics simulator, which requires high computational costs, sufficient experience in fire dynamics numerical calculations, and various input parameters and faces limitations in integration with evacuation simulations. A method for establishing a reasonable computational domain to predict the activation times of smoke and heat detectors has been proposed. This study examined the validity of using CFAST to predict factors relevant to the ASET evaluation. The results showed that CFAST, which solved empirical correlations based on heat release rates, predicted high gas temperatures similarly. Moreover, the applicability of the visibility distance calculation method using smoke concentration outputs from CFAST was examined. The results suggest that despite the limitations of the zone model, CFAST can produce reasonable ASET results. These results are expected to enhance the usability of CFAST in terms of understanding general fire engineering technology and simple fire dynamics trends.

Comparison of Different Models to Simulate Forest Fire Spread: A Case Study

With the development of computer technology, forest fire spread simulation using computers has gradually developed. According to the existing research on forest fire spread, the models established in various countries have typical regional characteristics. A fire spread model established in a specific region is only suitable for the local area, and there is still a great deal of uncertainty as to whether or not the established model is suitable for fire spread simulation for the same fuel in other regions. Although many fire spread models have been established, the fuel characteristics applicable to each model, such as the fuel loading, fuel moisture content, combustibility, etc., are not similar. It is necessary to evaluate the applicability of different fuel characteristics to different fire spread models. We combined ground investigation, historical data collection, model improvements, and statistical analysis to establish a multi-model forest fire spread simulation method (FIRER) that shows the burning time, perimeter, burning area, overlap area, and spread rate of fire sites. This method is a large-scale, high-resolution fire growth model based on fire spread in eight directions on a regular 30 m grid. This method could use any one of four different physical models (McArthur, Rothermel, FBP, and Wang Zhengfei (China)) for fire behavior. This method has an option to represent fire breaks from roads, rivers, and fire suppression. We can evaluate which model is more suitable in a specific area. This method was tested on a single historical lightning fire in the Daxing’an Mountains. Different scenarios were tested and compared: using each of the four fire behavior models, with fire breaks on or off, and with a single or suspected double fire ignition location of the historical fire. The results show that the Rothermel model is the best model in the simulation of the Hanma lightning fire; the overlap area is 5694.4 hm2. Meanwhile, the real fire area in FIRER is 5800.9 hm2; both the Kappa and Sørensen values exceed 0.8, providing high accuracy in fire spread simulations. FIRER performs well in the automatic identification of fire break zones and multiple ignited points. Compared with FARSITE, FIRER performs well in predicting accuracy. Compared with BehavePlus, FIRER also has advantages in simulating large-scale fire spread. However, the complex data preparation stage of FIRER means that FIRER still has great room for improvement. This research provides a practical basis for the comparison of the practicability and applicability of various fire spread models and provides more effective practical tools and a scientific basis for decision-making and the management of fighting forest fires.

Study on the key parameters of vehicle fires for the growth stage in road tunnels

AbstractAs the golden period for evacuation and rescue in road tunnel fires, the fire growth stage is indispensable for security. The key parameters of this stage must be clearly defined, including the maximum heat release rate (HRR), growth time, and growth coefficient. Based on the squared model, the correlations between the key parameters are investigated according to the existing fire tests of vehicle‐related materials and actual vehicles or mock‐ups. The maximum HRR and the growth coefficient of different types of vehicles are obtained. The results show that the maximum HRR is linearly related to the growth coefficient in the fire tests of vehicle‐related materials. And it is logarithmically related in the fire tests of actual vehicles or mock‐ups. The growth coefficient and growth time represent the possibility of a disaster. The larger the growth coefficient is or the shorter the growth time is, the greater the possibility is. The maximum HRR in a fire is 2 ~ 10 MW for a car, 10 ~ 50 MW for a bus, and 50 ~ 200 MW for a heavy goods vehicle. The growth coefficient in a fire is 0.003 ~ 0.013 kW/s2 for a car, 0.05 ~ 0.15 kW/s2 for a bus, and 0.2 ~ 0.3 kW/s2 for a heavy goods vehicle. The corresponding fire growth types are slow and medium, fast, fast, and ultra‐fast, respectively. This study is beneficial for the establishment of the fire growth model and the setting of emergency response time.

The Alberta Wildland Fuels Inventory Program (AWFIP): data description and reference tables

Key messageThis document describes a dataset obtained from a field sampling program conducted in Alberta, Canada. Field data were used to describe the structure and composition of forest stands, including several fuel loads (e.g., surface, understory, canopy fuels). The dataset can be downloaded from https://doi.org/10.17605/OSF.IO/FZ8E4 and metadata is available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/527efb49-43b4-43eb-88b2-70535ff99fc5We present a quality-checked and curated dataset obtained from a field sampling program conducted in the province of Alberta, Canada. Field data were used to describe the structure and composition of forest stands documented in 476 sampling events. Each sampling event record consists of 42 different variables, including several fuel loads (e.g., surface, understory, canopy fuels). The dataset has been created for operational and research applications including but not limited to fuel classification, estimation of fuel attributes from remote sensing technologies, fuel treatment planning, fire behavior prediction, and use in high resolution fire growth models.

Simulating Potential Impacts of Fuel Treatments on Fire Behavior and Evacuation Time of the 2018 Camp Fire in Northern California

Fuel break effectiveness in wildland-urban interface (WUI) is not well understood during downslope wind-driven fires even though various fuel treatments are conducted across the western United States. The aim of this paper is to examine the efficacy of WUI fuel breaks under the influence of strong winds and dry fuels, using the 2018 Camp Fire as a case study. The operational fire growth model Prometheus was used to show: (1) downstream impacts of 200 m and 400 m wide WUI fuel breaks on fire behavior and evacuation time gain; (2) how the downstream fire behavior was affected by the width and fuel conditions of the WUI fuel breaks; and (3) the impacts of background wind speeds on the efficacy of WUI fuel breaks. Our results indicate that WUI fuel breaks may slow wildfire spread rates by dispersing the primary advancing fire front into multiple fronts of lower intensity on the downstream edge of the fuel break. However, fuel break width mattered. We found that the lateral fire spread and burned area were reduced downstream of the 400 m wide WUI fuel break more effectively than the 200 m fuel break. Further sensitivity tests showed that wind speed at the time of ignition influenced fire behavior and efficacy of management interventions.

Cell2Fire: A Cell-Based Forest Fire Growth Model to Support Strategic Landscape Management Planning

Cell2Fire is a new cell-based wildland fire growth simulator designed to integrate data-driven landscape management planning models. The fire environment is modeled by partitioning the landscape into cells characterized by fuel, weather, moisture content, and topographic attributes. The model can use existing fire spread models such as the Canadian Forest Fire Behavior Prediction System to model fire growth. Cell2Fire is structured to facilitate its use for predicting the growth of individual fires or by embedding it in landscape management simulation models. Decision-making models such as fuel treatment/harvesting plans can be easily integrated and evaluated. It incorporates a series of out-of-the-box planning heuristics that provide benchmarks for comparison. We illustrate their use by applying and evaluating a series of harvesting plans for forest landscapes in Canada. We validated Cell2Fire by using it to predict the growth of both real and hypothetical fires, comparing our predictions with the fire scars produced by a validated fire growth simulator (Prometheus). Cell2Fire is implemented as an open-source project that exploits parallelism to efficiently support the modeling of fire growth across large spatial and temporal scales. Our experiments indicate that Cell2Fire is able to efficiently simulate wildfires (up to 30x faster) under different conditions with similar accuracy as state-of-the-art simulators (above 90% of accuracy). We demonstrate its effectiveness as part of a harvest planning optimization framework, identifying relevant metrics to capture and actions to mitigate the impact of wildfire uncertainty.

Experimental Study on the Spread Characteristics of Initial Fires According to Corridor Types

During an accidental fire in buildings, the corridor becomes the path for flame and smoke to spread, exposing the occupants to danger. Therefore, this study conducted real-scale fire experiments using corridors of size 2.4(L) × 10(W) × 2.4(H) m an “L-type” corridor for one-way evacuation and a “T-type” corridor for two-way evacuation to analyze the characteristics of fire according to the shape of corridors. The real-scale fire experiments were conducted in a fire room (2.4(L) × 3.6(W) × 2.4(H) m) with a single opening (2.0(W) × 1.8(H) m). The combustibles used inside the fire room were wood cribs, with a heat release rate of 651.4 kW, in the L-type corridor and chairs, with a heat release rate of 95.7 kW, in the T-type corridor. The temperature inside the corridor was measured during the real-scale fire experiments, and the average maximum measured temperature was 432.1 °C in the L-type corridor and 103.5 °C in the T-type corridor. The experimental results and the ventilation characteristics according to the corridor types were applied to BFD curves to show the process of designing fire growth models according to corridor types.

PDE solution to UAV/UGV trajectory planning problem by spatio-temporal estimation during wildfires

Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) have been used in research and development community due to their strong potential in high-risk missions. One of the most important civilian implementations of UAV/UGV cooperative path planning is delivering medical or emergency supplies during disasters such as wildfires, the focus of this paper. However, wildfires themselves pose risk to the UAVs/UGVs and their paths should be planned to avert the risk as well as complete the mission. In this paper, wildfire growth is simulated using a coupled Partial Differential Equation (PDE) model, widely used in literature for modeling wildfires, in a grid environment with added process and measurement noise. Using principles of Proper Orthogonal Decomposition (POD), and with an appropriate choice of decomposition modes, a low-dimensional equivalent fire growth model is obtained for the deployment of the space–time Kalman Filtering (KF) paradigm for estimation of wildfires using simulated data. The KF paradigm is then used to estimate and predict the propagation of wildfire based on local data obtained from a camera mounted on the UAV. This information is then used to obtain a safe path for the UGV that needs to travel from an initial location to the final position while the UAV’s path is planned to gather information on wildfire. Path planning of both UAV and UGV is carried out using a PDE based method that allows incorporation of threats due to wildfire and other obstacles in the form of risk function. The results from numerical simulation are presented to validate the proposed estimation and path planning methods.

Simulation Emergency Fire Evacuation Model for Nuclear Power Plant

Simulation of egress is vital for minimizing losses during fire disasters, however accurate simulations are scarce and real-life data is hard to come by. In this paper, a Proposed Wireless Fire Evacuation Model (PWFEM) is proposed to simulate fire evacuation process in a short time to minimize evacuee’s exposure to the harmful radiation and fire hazards. The PWFEM simulation realistic by supposing fire scenario at cabined contains electrical cables inside a standard Main Control Room (MCR) in a Nuclear Power Plant (NPP) building. In addition, a new Hybrid Safest Shortest Exit (HSSE) is developed which consists of three stages: safest route based on rules-based technique, evacuees location based on the DV-hop technique [1] and shortest route that depends on Dijkstra technique. The PWFEM Simulations are appreciated to yield a realistic fire scenario by using a telecommunications TCP/IP network in form of server and client sides that help in transfer data inside internal networks in the NPP building. On the server-side, suppose that Consolidated Model of Fire Growth and Smoke Transport (CFAST) fire modeling is applied to simulate the fire scenario in MCR through CFAST model to generate fire products as output data in excel sheets and sends them to the client-side. The client-side then runs HSSE to produce the tree map for safest and shortest routes to help the evacuee for safe exit from his/her location. HSSE can be implemented on evacuee’s watches. From the results, it is concluded that PWFEM can simulate the fire scenario inside MCR, furthermore it is validated that HSEE can be used as an efficient emergency fire evacuation technique that can produce safest and shortest exit route for evacuee in any location inside NPP in very small time. In addition, PWFEM can be used for simulating fire evacuation inside any high-risk buildings and can appreciate yielding any realistic fire scenario with many types of fire sources in different places inside buildings.

Initial growth of fires in eucalypt litter, from ignition to steady-state rate of spread: laboratory studies

As part of an investigation of wildfire growth and acceleration, the initial growth of incipient fires burning in uniform dry eucalypt forest (Eucalyptus rossii, E. macrorhyncha) litter fuel of 1.2 kg m−2 was studied in a combustion wind tunnel with a fuel bed width of 1.5 m. Fifty-eight fires of three ignition patterns (point, 400-mm line and 800-mm line) were carried out at two air speeds (1.25 and 2.0 m s−1) and two dead fuel moisture content (FMC) groups for each air speed (≤7.5% and >7.5% oven-dry weight for the low air speed and ≤5% and >5% for the high air speed). The fraction of steady-state rate of spread reached as a function of time was determined and fitted to two theoretical fire growth models from the literature. The best model suggests the times for a point ignition fire to reach steady-state spread rate were ~38 and 50 min under the higher FMC for 2.0 m s−1 and 1.25 m s−1 air speeds, respectively, and ~25 min under the lower FMC for 2.0 m s−1. Future work will extend these results to field-scale fire behaviour, which will help improve operational response to wildfire outbreaks and planning of ignition patterns for prescribed burning.

Effect of weather forecast errors on fire growth model projections

Fire management agencies use fire behaviour simulation tools to predict the potential spread of a fire in both risk planning and operationally during wildfires. These models are generally based on underlying empirical or quasi-empirical relations and rarely are uncertainties considered. Little attention has been given to the quality of the input data used during operational fire predictions. We examined the extent to which error in weather forecasts can affect fire simulation results. The study was conducted using data representing the State of Victoria in south-eastern Australia, including grassland and forest conditions. Two fire simulator software packages were used to compare fire growth under observed and forecast weather. We found that error in the weather forecast data significantly altered the predicted size and location of fires. Large errors in wind speed and temperature resulted in an overprediction of fire size, whereas large errors in wind direction resulted in an increased spatial error in the fire’s location. As the fire weather intensified, fire predictions using forecast weather under predicted fire size, potentially resulting in greater risks to the community. These results highlight the importance of on-ground intelligence during wildfires and the use of ensembles to improve operational fire predictions.

A Simplified Method for Establishing Safe Available Evacuation Time Based on a Descending Smoke Layer

Keeping the smoke layer at a safe height is one of the most important tenability criteria in assessment of evacuation from buildings. The basis of this approach is an accurate approximation of the fire and smoke plume, which is formed above the fire source. The major variables affecting smoke filling are the fire growth rate and enclosure geometry, i.e. the floor area and height. This paper deals with the implementation of a new method for establishing safe available evacuation time based on the fundamental principles of smoke generation and flow into the national fire safety design standards in the Czech and Slovak Republic. Some of these calculation methods have also been included in fire safety engineering ISO standards. The devised method is based on the t-squared fire growth model and correlations for smoke production and air entrainment into the rising plume of smoke. Subsequently, the proposed method is validated against a wide range of benchmark scenarios in the two-zone fire model CFAST. The paper compares the differences, comments on their causes and evaluates the applicability of the new method in both countries. The proposed method is not only compatible with the national fire safety design standards, but also allows for a more precise assessment of life safety without the need for overly complicated calculations.

Front Shape Similarity Measure for Shape-Oriented Sensitivity Analysis and Data Assimilation for Eikonal Equation

We present a shape-oriented data assimilation strategy suitable for front-tracking problems through the example of wildfire. The concept of “front” is used to model, at regional scales, the burning area delimitation that moves, undergoes shape and topological changes under heterogeneous orography, biomass fuel and micrometeorology. The simulation-observation discrepancies are represented using a front shape similarity measure deriving from image processing and based on the Chan-Vese contour fitting functional. We show that consistent corrections of the front location and uncertain physical parameters can be obtained using this measure applied on a level-set fire growth model solving for an eikonal equation. This study involves a Luenberger observer for state estimation, including a topological gradient term to track multiple fronts, and of a reduced-order Kalman filter for joint parameter estimation. We also highlight the need – prior to parameter estimation – for sensitivity analysis based on the same discrepancy measure, and for instance using polynomial chaos metamodels, to ensure a meaningful inverse solution is achieved. The performance of the shape-oriented data assimilation strategy is assessed on a synthetic configuration subject to uncertainties in front initial position, near-surface wind magnitude and direction. The use of a robust front shape similarity measure paves the way toward the direct assimilation of infrared images and is a valuable asset in the perspective of data-driven wildfire modeling.

Large-scale fire suppression modeling of corrugated cardboard boxes on wood pallets in rack-storage configurations

In this study, the fire growth and suppression models in FireFOAM were validated for rack-storage commodities consisting of two solid fuels, namely corrugated cardboard boxes and hardwood pallets, which are referred to as Class 2 commodity. Validation experiments included two fire-growth and two fire-suppression configurations with different rack-storage array heights (3 and 5 tiers). In the suppression study, standard-response upright ceiling sprinklers (K-factor of 160lpm/bar1/2) were used. The time-resolved chemical heat release rates obtained from the experiments were used to validate the fire growth model. The observed sprinkler activations and fire-spread patterns were used to validate the suppression model. This study identified that lateral flame spread is primarily enabled by flames impinging on the commodity's bottom surfaces. This study also showed that obstructions, such as wood pallets, can significantly impede convective and radiative heat transfer to the underside of the commodity, reducing the lateral flame spread rate. Fire-suppression modeling revealed that both surface water transport and lateral flame spread rates are important when predicting fire-suppression behavior. Therefore, as the rack-storage array height increases, so does the water transport time, which results in the fire becoming more difficult to control. Likewise, as the lateral spread rate increases, e.g., as occurs in the absence of wood pallets, fire-suppression also becomes more difficult.

An Implementation of the Rothermel Fire Spread Model in the R Programming Language

This note describes an implementation of the Rothermel fire spread model in the R programming language. The main function, ros(), computes the forward rate of spread at the head of a surface fire according to Rothermel fire behavior model. Additional functions are described to illustrate the potential use and expansions of the package. The function rosunc() carries out uncertainty analysis of fire behavior, that has the ability of generating information-rich, probabilistic predictions, and can be coupled to spatially-explicit fire growth models using an ensemble forecasting technique. The function bestFM() estimates the fit of Standard Fuel Models to observed fire rate of spread, based on absolute bias and root mean square error. Advantages of the R implementation of Rothermel model include: open-source coding, cross-platform availability, high computational efficiency, and linking to other R packages to perform complex analyses on Rothermel fire predictions.

Dionysus: a stochastic fire growth scenario generator

AbstractThe Prometheus Fire Growth Model is a deterministic wildfire simulator. Given weather, topographical and fuel information, the simulated fire front is plotted at equally spaced times. Unpredictability of fire behavior makes deterministic predictions inaccurate. By statistically modeling the data to which the model equations are fit, it is possible to obtain a distribution of fire front predictions. If the weather forecast is reliable, repeated stochastic simulation is not required, so probability contours require no more computing time than what is required for a single deterministic contour. Copyright © 2013 John Wiley & Sons, Ltd.

Experimental Investigation of a Motorcycle Burning Scenario

The statistical figures of Government showed, by the end of 2006, there were 13,579,885 motorcycles registered in Taiwan. Most of people in Taiwan are used to parking the motorcycles around buildings and the motorcycles are made of multifarious plastic materials (such as ABS, PP, PC, PU, PMMA, PA, etc.). Therefore, there were heavy casualties and property losses when motorcycle fires occurred. For research concerning motorcycles' combustion characteristics, the data is obtained via Cone Calorimeter, video recording, and other apparatuses. According to the experiment results, a full-scale motorcycle combustion, for which the fire growth model is α t2, the maximum heat release rate is about 1.106 MW, the fire decline model is a - b x ln (t + c), the average of flame height is 3.5 m, and the maximum temperature is 870.9°C.

A Semi-Markov Fire Growth Model

This paper aims to describe an alternative fire growth model that allows prediction of fire development, including time to flashover. The unpredictable nature of real fire development is incorporated into the model through use of probability distributions which can be defined using appropriate fire test data, when available. By assuming that the fire goes through five different stages starting from ignition and progressing to flashover, the total time to flashover may also be estimated. The model considers potential variability in the times at which the fire will undergo transitions between the various stages of development, using a state transition method called the semi-Markov process model. Different fire data may be incorporated into the model by defining appropriate statistical distributions for the transition descriptors, making the model flexible enough for use in a variety of applications important to both product design engineers and fire safety regulators.

A comprehensive model for simulating the interaction of water with solid surfaces in fire suppression environments

A novel framework for sprinkler-based fire suppression modeling has been developed that includes detailed interaction of water with solid surfaces. This model builds on the fire growth model (FireFOAM) previously developed at FM Global. The fundamental film-transport equations for mass continuity, momentum, and energy have been formulated and implemented in an open-source CFD code (OpenFOAM®) and subsequently coupled with FireFOAM. Water transport, as would occur in a fire suppression environment, is tracked along solid surfaces. Interaction of the water with the solid surfaces in the form of cooling and pre-wetting is represented. Coupling between the film-transport model and the gas-phase and condensed-phase regions has been specified through interfacial transport models. Model validation for vaporization and conjugate heat transfer is shown for a surrogate fire environment. Radiation heat transfer is applied to a vertical panel with water flowing down the surface. Heat fluxes range from 5 to 33kW/m2 and water flow rates range from 2 to 52g/m/s.