ABWiSE v1.0: toward an agent-based  approach to simulating wildfire spread

Abstract. Wildfires are a complex phenomenon emerging from interactions between air, heat, and vegetation, and while they are an important component of many ecosystems’ dynamics, they pose great danger to those ecosystems, as well as human life and property. Wildfire simulation models are an important research tool that help further our understanding of fire behaviour and can allow experimentation without recourse to live fires. Current fire simulation models fit into two general categories: empirical models and physical models. We present a new modelling approach that uses agent-based modelling to combine the complexity possible with physical models with the ease of computation of empirical models. Our model represents the fire front as a set of moving agents that respond to, and interact with, vegetation, wind, and terrain. We calibrate the model using two simulated fires and one real fire and validate the model against another real fire and the interim behaviour of the real calibration fire. Our model successfully replicates these fires, with a figure of merit on par with simulations by the Prometheus simulation model. Our model is a stepping-stone in using agent-based modelling for fire behaviour simulation, as we demonstrate the ability of agent-based modelling to replicate fire behaviour through emergence alone.

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ABWiSE v1.0: Toward and Agent-Based Approach to Simulating Wildfire Spread

10.5194/nhess-2021-179 ◽

2021 ◽

Author(s):

Jeffrey Katan ◽

Liliana Perez

Keyword(s):

Human Life ◽

Simulation Models ◽

Empirical Models ◽

Physical Models ◽

Fire Behaviour ◽

Agent Based ◽

Agent Based Modelling ◽

Fire Front ◽

Wildfire Simulation ◽

Behaviour Simulation

Abstract. Wildfires are a complex phenomenon emerging from interactions between air, heat, and vegetation, and while they are an important component of many ecosystems’ dynamics, they pose great danger to those ecosystems, and human life and property. Wildfire simulation models are an important research tool that help further our understanding of fire behaviour and can allow experimentation without recourse to live fires. Current fire simulation models fit into two general categories: empirical models and physical models. We present a new modelling approach that uses agent-based modelling to combine the complexity found in physical models with the ease of computation of empirical models. Our model represents the fire front as a set of moving agents that respond to, and interact with, vegetation, wind, and terrain. We calibrate the model using two simulated fires and one real fire, and validate the model against another real fire and the interim behaviour of the real calibration fire. Our model successfully replicates these fires, with a Figure of Merit on par with simulations by the Prometheus simulation model. Our model is a stepping-stone in using agent-based modelling for fire behaviour simulation, as we demonstrate the ability of agent-based modelling to replicate fire behaviour through emergence alone.

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Mantras of wildland fire behaviour modelling: facts or fallacies?

International Journal of Wildland Fire ◽

10.1071/wf17097 ◽

2017 ◽

Vol 26 (11) ◽

pp. 973 ◽

Cited By ~ 16

Author(s):

Miguel G. Cruz ◽

Martin E. Alexander ◽

Andrew L. Sullivan

Keyword(s):

Wildland Fire ◽

Original Data ◽

Fire Spread ◽

Empirical Models ◽

Physical Models ◽

Fire Behaviour ◽

Fire Science ◽

Current State ◽

Valid Data ◽

Insight Into

Generalised statements about the state of fire science are often used to provide a simplified context for new work. This paper explores the validity of five frequently repeated statements regarding empirical and physical models for predicting wildland fire behaviour. For empirical models, these include statements that they: (1) work well over the range of their original data; and (2) are not appropriate for and should not be applied to conditions outside the range of the original data. For physical models, common statements include that they: (3) provide insight into the mechanisms that drive wildland fire spread and other aspects of fire behaviour; (4) give a better understanding of how fuel treatments modify fire behaviour; and (5) can be used to derive simplified models to predict fire behaviour operationally. The first statement was judged to be true only under certain conditions, whereas the second was shown not to be necessarily correct if valid data and appropriate modelling forms are used. Statements three through five, although theoretically valid, were considered not to be true given the current state of knowledge regarding fundamental wildland fire processes.

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Physical modelling of forest fire spreading through heterogeneous fuel beds

International Journal of Wildland Fire ◽

10.1071/wf09006 ◽

2011 ◽

Vol 20 (5) ◽

pp. 625 ◽

Cited By ~ 11

Author(s):

Albert Simeoni ◽

Pierre Salinesi ◽

Frédéric Morandini

Keyword(s):

Field Experiments ◽

Heterogeneous Medium ◽

Reaction Diffusion ◽

Physical Modelling ◽

Fire Spread ◽

Physical Models ◽

Fire Intensity ◽

Fire Behaviour ◽

Fire Front ◽

Fire Spreading

Vegetation cover is a heterogeneous medium composed of different kinds of fuels and non-combustible parts. Some properties of real fires arise from this heterogeneity. Creating heterogeneous fuel areas may be useful both in land management and in firefighting by reducing fire intensity and fire rate of spread. The spreading of a fire through a heterogeneous medium was studied with a two-dimensional reaction–diffusion physical model of fire spread. Randomly distributed combustible and non-combustible square elements constituted the heterogeneous fuel. Two main characteristics of the fire were directly computed by the model: the size of the zone influenced by the heat transferred from the fire front and the ignition condition of vegetation. The model was able to provide rate of fire spread, temperature distribution and energy transfers. The influence on the fire properties of the ratio between the amount of combustible elements and the total amount of elements was studied. The results provided the same critical fire behaviour as described in both percolation theory and laboratory experiments but the results were quantitatively different because the neighbourhood computed by the model varied in time and space with the geometry of the fire front. The simulations also qualitatively reproduced fire behaviour for heterogeneous fuel layers as observed in field experiments. This study shows that physical models can be used to study fire spreading through heterogeneous fuels, and some potential applications are proposed about the use of heterogeneity as a complementary tool for fuel management and firefighting.

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Agent Based Modelling of Smart Structures

Modeling and Simulation Techniques in Structural Engineering - Advances in Civil and Industrial Engineering ◽

10.4018/978-1-5225-0588-4.ch002 ◽

2017 ◽

pp. 38-60

Author(s):

Andreea Ion ◽

Monica Patrascu

Keyword(s):

Large Scale ◽

Smart Structures ◽

Simulation Models ◽

Urban Environments ◽

Ease Of Use ◽

Agent Based ◽

Agent Based Modelling ◽

Automation Systems ◽

The Social ◽

Wide Range

Smart structures are complex systems situated in even more complex and large scale urban environments. This chapter opens the field of agent based modelling and simulation (ABMS) to civil engineers. ABMS offers a wide range of tools for implementing simulation models of systems with high degrees of interconnectivity and a large number of component subsystems. The ease of use for specialized engineers and the capabilities of integration with existent technologies and infrastructures, make agent based models a very attractive way to incorporate the social system in the design process of buildings. Moreover, ABMS allows for the testing and validation of structure wide control and automation systems. This chapter presents past and current efforts of using agent based modelling for smart structures, as well as the main challenges brought by this new interdisciplinary research domain.

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Physically motivated empirical models for the spread and intensity of grass fires

International Journal of Wildland Fire ◽

10.1071/wf06037 ◽

2008 ◽

Vol 17 (5) ◽

pp. 595 ◽

Cited By ~ 28

Author(s):

Steven I. Higgins ◽

William J. Bond ◽

Winston S. W. Trollope ◽

Richard J. Williams

Keyword(s):

Statistical Models ◽

Empirical Models ◽

Physical Models ◽

Training Data ◽

Fire Intensity ◽

Model Parameters ◽

Independent Data ◽

Fire Behaviour ◽

Rate Of Spread ◽

Better Than

We develop empirical models for the rate of spread and intensity of fires in grass fuels. The models are based on a well-known physical analogy for the rate of spread of a fire through a continuous fuelbed. Unlike other models based on this analogy, we do not attempt to directly estimate the model parameters. Rather, we use data on the rate of spread to indirectly estimate parameters that describe aggregate properties of the fire behaviour. The resulting models require information on the moisture content of the fuel and wind speed to predict the rate of spread of fires. To predict fire intensity, the models additionally use information on the heat yield of the fuel and the amount of fuel consumed. We evaluate the models by using them to predict the intensity of independent fires and by comparing them with linear and additive regression models. The additive model provides the best description of the training data but predicts independent data poorly and with high bias. Overall, the empirical models describe the data better than the linear model, and predict independent data with lower bias. Hence our physically motivated empirical models perform better than statistical models and are easier to parameterise than parameter-rich physical models. We conclude that our physically motivated empirical models provide an alternative to statistical models and parameter-rich physical models of fire behaviour.

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The Self-Enforcing Agreement in Cooperative Teams: An Agent-Based Modelling Approach

SSRN Electronic Journal ◽

10.2139/ssrn.2621606 ◽

2013 ◽

Author(s):

Hang Xiong ◽

Diane Payne ◽

Stephen Kinsella

Keyword(s):

The Self ◽

Agent Based ◽

Agent Based Modelling ◽

Modelling Approach

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Metamorphic Validation for Agent-based Simulation Models

2016 Summer Computer Simulation Conference (SCSC 2016) ◽

10.22360/summersim.2016.scsc.041 ◽

2016 ◽

Keyword(s):

Simulation Models ◽

Agent Based Simulation ◽

Agent Based

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Process Modeling and Simulation of Tableting—An Agent-Based Simulation Methodology for Direct Compression

Pharmaceutics ◽

10.3390/pharmaceutics13070996 ◽

2021 ◽

Vol 13 (7) ◽

pp. 996

Author(s):

Niels Lasse Martin ◽

Ann Kathrin Schomberg ◽

Jan Henrik Finke ◽

Tim Gyung-min Abraham ◽

Arno Kwade ◽

...

Keyword(s):

Raw Materials ◽

Pilot Scale ◽

Physical Models ◽

Agent Based Simulation ◽

Validation Data ◽

Agent Based ◽

Industrial Processing ◽

Digital Twins ◽

Product And Process ◽

The Impact

In pharmaceutical manufacturing, the utmost aim is reliably producing high quality products. Simulation approaches allow virtual experiments of processes in the planning phase and the implementation of digital twins in operation. The industrial processing of active pharmaceutical ingredients (APIs) into tablets requires the combination of discrete and continuous sub-processes with complex interdependencies regarding the material structures and characteristics. The API and excipients are mixed, granulated if required, and subsequently tableted. Thereby, the structure as well as the properties of the intermediate and final product are influenced by the raw materials, the parametrized processes and environmental conditions, which are subject to certain fluctuations. In this study, for the first time, an agent-based simulation model is presented, which enables the prediction, tracking, and tracing of resulting structures and properties of the intermediates of an industrial tableting process. Therefore, the methodology for the identification and development of product and process agents in an agent-based simulation is shown. Implemented physical models describe the impact of process parameters on material structures. The tablet production with a pilot scale rotary press is experimentally characterized to provide calibration and validation data. Finally, the simulation results, predicting the final structures, are compared to the experimental data.

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