Modeling Vorticity-Driven Wildfire Behavior Using Near-Field Techniques

Sharples, Jason J.; Hilton, James

doi:10.3389/fmech.2019.00069

Cited by 13 publications

(11 citation statements)

References 21 publications

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“…Using the foregoing assumptions, Sharples and Hilton (2019) showed that the pyrogenic vertical vorticity due to a line source of ambient horizontal vorticity s xy can be written as:…”

Section: Near-field Modelling Of Vlsmentioning

confidence: 99%

“…where k is a constant based on factors including the vertical speed of the plume, the vortex strength, the nominal mid-flame height and ν (Sharples and Hilton, 2019). The function δ(x) is a Dirac delta function, the variable x is the nearest point on the line source to position x, φ is the distance from the fire perimeter andn is the outward normal of the fire perimeter.…”

Section: Near-field Modelling Of Vlsmentioning

confidence: 99%

“…Even more recently, Sharples and Hilton (2019) demonstrated how the inclusion of vorticity effects as part of a two-dimensional near-field modelling approach could be used to emulate the pattern of fire propagation associated with VLS. In particular, they showed that output from the two-dimensional model compared favourably with that obtained from a fully coupled fire-atmosphere model.…”

Section: Introductionmentioning

confidence: 99%

“…However, at present this modelling only captured the lateral spread associated with VLS and no attempt was made to model the spotting component that produces deep flaming. Therefore, in this paper we combine the model considered by Sharples and Hilton (2019) with a Lagrangian firebrand model to simulate the transport of firebrands and subsequent spot fire formation.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Incorporating firebrands and spot fires into vorticity-driven wildfire behaviour models

2019

El Sawah, S. (Ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation.

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Complex modes of fire behaviour resulting from local coupling between the fire and the atmosphere are a significant challenge for rapid operational wildfire spread simulations. While threedimensional fully coupled fire-atmosphere models are able to account for many types of fire behaviour, their computational demands are prohibitive in an operational context. Two-dimensional fire spread models have much lower computational overhead, but are generally not able to account for complex local coupling effects and cannot provide a three-dimensional flow structure suitable for modelling the transport of firebrands. In this paper we investigate extending two-dimensional fire spread simulations to model local coupling effects resulting from wind flow over a ridge that can result in a number of non-intuitive modes of fire behaviour. These include fire propagation opposite to the direction of the prevailing wind on the lee slope of ridges caused by re-circulation on the lee slope, called vorticity-driven lateral spread (VLS). Furthermore we develop extensions of these two-dimensional models to incorporate three-dimensional firebrand transport and show that enhanced downwind spot fire formation can result under certain VLS conditions. The spread of fires under VLS conditions is driven by vortices in the ground plane. A model for the production and effects of these vortices was incorporated into computational simulations using a vector potential formulation in similar manner to a scalar 'pyrogenic potential' model, detailed in earlier studies. Firebrands were incorporated using a Lagrangian scheme to model transport through the atmosphere and a sub-scale model for spot fire creation and growth. The firebrand transport took factors such as drag, gravity and buoyancy into account. As effect of plume buoyancy on firebrands under real-world conditions for this scenario is currently unknown, the plume buoyancy was parameterised using a exponential decay model. The sensitivity of the decay parameter in this model was then examined in relation to the resulting spot fire distribution and area burnt. All simulations were carried out using Spark, a wildfire prediction framework. The coupled VLS and firebrand transport simulations indicated that a higher value of decay parameter, representing a higher cooling rate of the plume, acted to enhance the lateral spread as firebrands were lofted for shorter times and were caught in the vortices at the edge of the lateral spread region. In contrast, a lower value of decay parameter, representing a lower cooling of the plume, resulted in widespread downwind spot fires and larger burnt areas. This appeared to be due to longer lofting times resulting in firebrands being transported further downwind and away from the vortices within the lateral spread region. The model appears, at least qualitatively, to match observed lateral spread and 'deep flaming' fire behaviour although many of the parameters in the model require further research and experimental calibration. Further development of the model ...

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“…Using the foregoing assumptions, Sharples and Hilton (2019) showed that the pyrogenic vertical vorticity due to a line source of ambient horizontal vorticity s xy can be written as:…”

Section: Near-field Modelling Of Vlsmentioning

confidence: 99%

Section: Near-field Modelling Of Vlsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Incorporating firebrands and spot fires into vorticity-driven wildfire behaviour models

2019

El Sawah, S. (Ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation.

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show abstract

“…The coupling between surface fire and wind on larger scales involves interactions between fire-generated convection and frontal motion (e.g., Hilton et al [17]), background and induced local vorticity, and the tilting of the surrounding horizontal vorticity field. Sharples and Hilton [18] isolated and described such an effect in their model of flow over a ridge, with the associated vorticity-induced lateral fire spread. In this mechanism, the vorticity of the background flow is lifted by the fire plume, tilted, and modifies the horizontal flow.…”

Section: Introductionmentioning

confidence: 99%

A Simple Model for Wildland Fire Vortex–Sink Interactions

Quaife

Speer

2021

Atmosphere

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A model is developed to explore fire–atmosphere interactions due to the convective sink and vorticity sources in a highly simplified and idealized form, in order to examine their effect on spread and the stability of various fire front geometries. The model is constructed in a cellular automata framework, is linear, and represents a background flow, convective sink, and vortices induced by the fire plume at every burning cell. We use standard techniques to solve the resulting Poisson equations with careful attention to the boundary conditions. A modified Bresenham algorithm is developed to represent convection. The three basic flow types—large-scale background flow, sink flow, and vortex circulation—interact in a complex fashion as the geometry of the fire evolves. Fire-generated vortex–sink interactions produce a range of fire behavior, including unsteady spread rate, lateral spreading, and dynamic fingering. In this simplified framework, pulsation is found associated with evolving fire-line width, a fire-front acceleration in junction fires, and the breakup of longer initial fire lines into multiple head fires. Fuel is very simply represented by a single burn time parameter. The model fuel is uniform yet patchiness occurs due to a dynamic interaction of diffusive and convective effects. The interplay of fire-induced wind and the geometry of the fire front depends also on the fuel burn time.

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Intelligent Architectures for Extreme Event Visualisation

Song,

Pagnucco,

et al. 2024

Arts, Research, Innovation and Society

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Realistic immersive visualisation can provide a valuable method for studying extreme events and enhancing our understanding of their complexity, underlying dynamics and human impacts. However, existing approaches are often limited by their lack of scalability and incapacity to adapt to diverse scenarios. In this chapter, we present a review of existing methodologies in intelligent visualisation of extreme events, focusing on physical modelling, learning-based simulation and graphic visualisation. We then suggest that various methodologies based on deep learning and, particularly, generative artificial intelligence (AI) can be incorporated into this domain to produce more effective outcomes. Using generative AI, extreme events can be simulated, combining past data with support for users to manipulate a range of environmental factors. This approach enables realistic simulation of diverse hypothetical scenarios. In parallel, generative AI methods can be developed for graphic visualisation components to enhance the efficiency of the system. The integration of generative AI with extreme event modelling presents an exciting opportunity for the research community to rapidly develop a deeper understanding of extreme events, as well as the corresponding preparedness, response and management strategies.

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Modeling Vorticity-Driven Wildfire Behavior Using Near-Field Techniques

Cited by 13 publications

References 21 publications

Incorporating firebrands and spot fires into vorticity-driven wildfire behaviour models

Incorporating firebrands and spot fires into vorticity-driven wildfire behaviour models

A Simple Model for Wildland Fire Vortex–Sink Interactions

Intelligent Architectures for Extreme Event Visualisation

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