The Speed of a Fire Front and Its Dependence on Wind-Speed

1993 ◽  
Vol 3 (4) ◽  
pp. 193 ◽  
Author(s):  
T Beer
Keyword(s):  
Wind Speed ◽  
Laboratory Tests ◽  
Field Data ◽  
Fire Spread ◽  
Measured Data ◽  
Rate Of Spread ◽  
Wind Rate ◽  
Fire Front ◽  
Analytical Formulae ◽  
Definition Of

The results of a number of laboratory tests of wind-driven fires indicate the existence of a characteristic wind speed, U'. The form of the fire spread (V) as a function of mid-flame wind speed (U) differs above and below this characteristic speed. The scatter in field data is so great that it is difficult to confirm this result for field data. However, expressions of the form: V/V0 -1 = α(U/U')0.5 U/U' < 1 and V/V0 -1 = α(U/U')3 U/U' > 1 with U' = 2.5 m s-1 perform in a similar manner to existing models. For many fuel types α = 15. A difficulty with existing fire spread models is the measurement and definition of V0, the no-wind rate of spread. It can hardly ever be measured in the field and has to be inferred from analytical formulae, or by extrapolating measured data. The value of a depends on the method used estimate V0.

Fine-Scale Fire Spread in Pine Straw

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 69
Author(s):  
Daryn Sagel ◽  
Kevin Speer ◽  
Scott Pokswinski ◽  
Bryan Quaife
Keyword(s):  
Fire Spread ◽  
Small Scale ◽  
Natural Setting ◽  
Fine Scale ◽  
Prescribed Burn ◽  
Fire Dynamics ◽  
Rate Of Spread ◽  
Scale Models ◽  
Fire Front ◽  
Visible Images

Most wildland and prescribed fire spread occurs through ground fuels, and the rate of spread (RoS) in such environments is often summarized with empirical models that assume uniform environmental conditions and produce a unique RoS. On the other hand, representing the effects of local, small-scale variations of fuel and wind experienced in the field is challenging and, for landscape-scale models, impractical. Moreover, the level of uncertainty associated with characterizing RoS and flame dynamics in the presence of turbulent flow demonstrates the need for further understanding of fire dynamics at small scales in realistic settings. This work describes adapted computer vision techniques used to form fine-scale measurements of the spatially and temporally varying RoS in a natural setting. These algorithms are applied to infrared and visible images of a small-scale prescribed burn of a quasi-homogeneous pine needle bed under stationary wind conditions. A large number of distinct fire front displacements are then used statistically to analyze the fire spread. We find that the fine-scale forward RoS is characterized by an exponential distribution, suggesting a model for fire spread as a random process at this scale.

Simulation study of grass fire using a physics-based model: striving towards numerical rigour and the effect of grass height on the rate of spread

2018 ◽  
Vol 27 (12) ◽  
pp. 800 ◽  
Author(s):  
K. A. M. Moinuddin ◽  
D. Sutherland ◽  
W. Mell
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Heat Release ◽  
Bulk Density ◽  
Simulation Study ◽  
Release Rate ◽  
Rate Of Spread ◽  
Fire Front ◽  
Physics Based Simulation ◽  
Mode A

Grid-independent rate of spread results from a physics-based simulation are presented. Previously, such a numerical benchmark has been elusive owing to computational restrictions. The grid-converged results are used to systematically construct correlations between the rate of spread (RoS) and both wind speed and grass height, separately. The RoS obtained from the physics-based model is found to be linear with wind speed in the parameter range considered. When wind speed is varied, the physics-based model predicts faster RoS than the Mk III and V (McArthur) models (Noble et al. 1980) but slower than the CSIRO model (Cheney et al. 1998). When the grass height is varied keeping the bulk density constant, the fire front changes from a boundary layer flame mode to plume flame mode as the grass height increases. Once the fires are in plume mode, a higher grass height results in a larger heat release rate of the fire but a slower RoS.

Laboratory fire spread analysis using visual and infrared images

2006 ◽  
Vol 15 (2) ◽  
pp. 179 ◽  
Author(s):  
J. Ramiro Martínez-de Dios ◽  
Jorge C. André ◽  
João C. Gonçalves ◽  
Begoña Ch. Arrue ◽  
Aníbal Ollero ◽  
...  
Keyword(s):  
Graphical Model ◽  
Fire Spread ◽  
Rate Of Spread ◽  
Virtual View ◽  
Fire Front ◽  
Computer Based ◽  
Front Shape ◽  
Processing Techniques ◽  
Spread Analysis ◽  
Base Width

This paper presents an experimental method using computer-based image processing techniques of visual and infrared movies of a propagating fire front, taken from one or more cameras, to supply the time evolutions of the fire front shape and position, flame inclination angle, height, and base width. As secondary outputs, it also provides the fire front rate of spread and a 3D graphical model of the fire front that can be rendered from any virtual view. The method is automatic and non-intrusive, has space–time resolution close to continuum and can be run in real-time or deferred modes. It is demonstrated in simple laboratory experiments in beds of pine needles set upon an inclinable burn table, with point and linear ignitions, but can be extended to open field situations.

A cellular automata model to link surface fires to firebrand lift-off and dispersal

2013 ◽  
Vol 22 (4) ◽  
pp. 428 ◽  
Author(s):  
Holly A. Perryman ◽  
Christopher J. Dugaw ◽  
J. Morgan Varner ◽  
Diane L. Johnson
Keyword(s):  
Wind Speed ◽  
Wildland Fire ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Fuel Loading ◽  
Cellular Automata Model ◽  
Rate Of Spread ◽  
Lift Off ◽  
Fuel Moisture Content ◽  
Spot Fires

In spite of considerable effort to predict wildland fire behaviour, the effects of firebrand lift-off, the ignition of resulting spot fires and their effects on fire spread, remain poorly understood. We developed a cellular automata model integrating key mathematical models governing current fire spread models with a recently developed model that estimates firebrand landing patterns. Using our model we simulated a wildfire in an idealised Pinus ponderosa ecosystem. Varying values of wind speed, surface fuel loading, surface fuel moisture content and canopy base height, we investigated two scenarios: (i) the probability of a spot fire igniting beyond fuelbreaks of various widths and (ii) how spot fires directly affect the overall surface fire’s rate of spread. Results were averages across 2500 stochastic simulations. In both scenarios, canopy base height and surface fuel loading had a greater influence than wind speed and surface fuel moisture content. The expected rate of spread with spot fires occurring approached a constant value over time, which ranged between 6 and 931% higher than the predicted surface fire rate of spread. Incorporation of the role of spot fires in wildland fire spread should be an important thrust of future decision-support technologies.

Estimating error in wind speed measurements for experimental fires

2001 ◽  
Vol 31 (3) ◽  
pp. 401-409 ◽  
Author(s):  
A L Sullivan ◽  
I K Knight
Keyword(s):  
Wind Speed ◽  
Small Scale ◽  
Confidence Limits ◽  
Single Measure ◽  
Rate Of Spread ◽  
Scale Size ◽  
Fire Front ◽  
Scalar Measure ◽  
Eucalypt Forests ◽  
Measured Wind Speed

Most experimental fires, by nature, are small scale ([Formula: see text]100 m), and rate of spread measurements are taken over periods of several minutes. The aim of empirical fire modellers is to ascribe a single measure of rate of forward spread over a period to a single scalar measure of wind. The actual wind affecting the fire is unmeasurable; its value must be estimated from remote anemometry. Observation and consideration of the spatial and temporal statistics of the wind has allowed confidence limits to be placed upon the accuracy with which the measured wind reflects the wind acting on the fire front. Experimental data to verify these estimates was gathered during Project Vesta, a study into high-intensity fires in dry eucalypt forests. An equation that quantifies the accuracy of the estimate of wind affecting the fire front is given. The accuracy increases with time scale, size of the fire front, and density of anemometry. When applied to a measured wind speed taken some distance from the fire, it gives a useful estimate of the likely variation of the corresponding wind at the fire front.

Empirical modelling of surface fire behaviour in maritime pine stands

2009 ◽  
Vol 18 (6) ◽  
pp. 698 ◽  
Author(s):  
Paulo M. Fernandes ◽  
Hermínio S. Botelho ◽  
Francisco C. Rego ◽  
Carlos Loureiro
Keyword(s):  
Wind Speed ◽  
Moisture Content ◽  
Fire Spread ◽  
Fire Intensity ◽  
Fuel Moisture ◽  
Fire Behaviour ◽  
Spread Rate ◽  
Surface Fire ◽  
Rate Of Spread ◽  
Fuel Moisture Content

An experimental burning program took place in maritime pine (Pinus pinaster Ait.) stands in Portugal to increase the understanding of surface fire behaviour under mild weather. The spread rate and flame geometry of the forward and backward sections of a line-ignited fire front were measured in 94 plots 10–15 m wide. Measured head fire rate of spread, flame length and Byram’s fire intensity varied respectively in the intervals of 0.3–13.9 m min–1, 0.1–4.2 m and 30–3527 kW m–1. Fire behaviour was modelled through an empirical approach. Rate of forward fire spread was described as a function of surface wind speed, terrain slope, moisture content of fine dead surface fuel, and fuel height, while back fire spread rate was correlated with fuel moisture content and cover of understorey vegetation. Flame dimensions were related to Byram’s fire intensity but relationships with rate of spread and fine dead surface fuel load and moisture are preferred, particularly for the head fire. The equations are expected to be more reliable when wind speed and slope are less than 8 km h–1 and 15°, and when fuel moisture content is higher than 12%. The results offer a quantitative basis for prescribed fire management.

Exploring fire response to high wind speeds: fire rate of spread, energy release and flame residence time from fires burned in pine needle beds under winds up to 27 ms−1

2020 ◽  
Vol 29 (1) ◽  
pp. 81
Author(s):  
Bret Butler ◽  
Steve Quarles ◽  
Christine Standohar-Alfano ◽  
Murray Morrison ◽  
Daniel Jimenez ◽  
...  
Keyword(s):  
Wind Speed ◽  
Energy Release ◽  
Residence Time ◽  
Wildland Fire ◽  
Ground Level ◽  
Fire Spread ◽  
Convective Heating ◽  
Atmospheric Conditions ◽  
Wind Speeds ◽  
Rate Of Spread

The relationship between wildland fire spread rate and wind has been a topic of study for over a century, but few laboratory studies report measurements in controlled winds exceeding 5ms−1. In this study, measurements of fire rate of spread, flame residence time and energy release are reported for fires burning under controlled atmospheric conditions in shallow beds of pine needles subject to winds ranging from 0 to 27ms−1 (measured 5m above ground level). The data suggested that under constant flow conditions when winds are less than 10ms−1, fire rate of spread increases linearly at a rate of ~3% of the wind speed, which generally agrees with other laboratory-based models. When wind speed exceeds 10ms−1, the fire rate of spread response to wind remains linear but with a much stronger dependence, spreading at a rate of ~13% of the wind speed. Radiative and convective heating correlated directly to wind speed, with radiant heating increasing approximately three-fold as much as convective heating over the range of winds explored. The data suggested that residence time is inversely related to wind speed and appeared to approach a lower limit of ~20s as wind exceeded 15ms−1. Average flame residence time over the range of wind speeds was nominally 26s.

scholarly journals Georeferencing Oblique Aerial Wildfire Photographs: An Untapped Source of Fire Behaviour Data

Fire ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 81
Author(s):  
Henry Hart ◽  
Daniel D. B. Perrakis ◽  
Stephen W. Taylor ◽  
Christopher Bone ◽  
Claudio Bozzini
Keyword(s):  
Fire Behavior ◽  
Fire Spread ◽  
Behavior Prediction ◽  
Empirical Relationships ◽  
Rate Of Spread ◽  
Front Position ◽  
Fire Front ◽  
Initial Work ◽  
The Mean ◽  
Behaviour Data

In this study, we investigate a novel application of the photogrammetric monoplotting technique for assessing wildfires. We demonstrate the use of the software program WSL Monoplotting Tool (MPT) to georeference operational oblique aerial wildfire photographs taken during airtanker response in the early stages of fire growth. We located the position of the fire front in georeferenced pairs of photos from five fires taken 31–118 min apart, and calculated the head fire spread distance and head fire rate of spread (HROS). Our example photos were taken 0.7 to 4.7 km from fire fronts, with camera angles of incidence from −19 to −50° to image centre. Using high quality images with detailed landscape features, it is possible to identify fire front positions with high precision; in our example data, the mean 3D error was 0.533 m and the maximum 3D error for individual fire runs was less than 3 m. This resulted in a maximum HROS error due to monoplotting of only ~0.5%. We then compared HROS estimates with predictions from the Canadian Fire Behavior Prediction System, with differences mainly attributed to model error or uncertainty in weather and fuel inputs. This method can be used to obtain observations to validate fire spread models or create new empirical relationships where databases of such wildfire photos exist. Our initial work suggests that monophotogrammetry can provide reproducible estimates of fire front position, spread distance and rate of spread with high accuracy, and could potentially be used to characterize other fire features such as flame and smoke plume dimensions and spotting.

Prediction of Fire Spread in Grasslands

1998 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
NP Cheney ◽  
JS Gould ◽  
WR Catchpole
Keyword(s):  
Wind Speed ◽  
Linear Relationship ◽  
Power Function ◽  
Fire Spread ◽  
Fuel Moisture ◽  
Critical Wind Speed ◽  
Rate Of Spread ◽  
The Relationship ◽  
Potential Rate

This pager describes a model to predict fire spread in grasslands from wind speed at 10 m, dead fuel moisture, and degree of grass curing in three defined pasture types, The model was developed from spread measurements of experimental fins that were adjusted to their potential rate of spread at wide fronts. Extrapolations of the model were compared with spread data from 20 major wildfires in Australia. This model uses different functions to describe the relationship between rate of spread and wind speed above and below a critical wind speed of 5 km h-1. A linear relationship is used below 5 km h-1; above 5 km h-1 rate of spread is described by a power function of wind speed with an exponent of less than 1.

A dimensionless correlation for the spread of wind-driven fires

1988 ◽  
Vol 18 (4) ◽  
pp. 391-397 ◽  
Author(s):  
Ralph M. Nelson Jr. ◽  
Carl W. Adkins
Keyword(s):  
Wind Speed ◽  
Residence Time ◽  
Fire Spread ◽  
Simple Expression ◽  
Small Scale ◽  
Strongly Correlated ◽  
Spread Rate ◽  
Ambient Wind ◽  
Rate Of Spread ◽  
Several Variables

Data for the behavior of 59 experimental wind-driven fires were extracted from the literature for use in determining a correlation among several variables known to influence the rate of forest fire spread. Also included in the correlation were unpublished data from six field fires. This information consisted of behavior measurements on small-scale burns of artificial fuels in the laboratory and measurements on field fires in diverse fuels such as grass and logging slash. Fire intensities ranged from about 40 to 4600 kW/m. Dimensional analysis was used to derive three variables governing the fire spread process. These variables, rearranged into a dimensionless rate of spread and a dimensionless wind speed, are strongly correlated and lead to a simple expression for fire spread rate in terms of fuel consumption, ambient wind speed, and flame residence time.

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