Eric Innocenti

Modelling and simulation of ecological propagation processes: application to fire spread

An important class of ecological problems concerns propagation processes. In ecological modelling, these phenomena generally occur on large scales and are generally difficult to simulate efficiently because of the number of entities. Studies of this kind of phenomena lack genericity and reusability because they are often presented from the point of view of a single domain expert. Simulations made by domain experts seem to lack genericity for computer science specialists and simulations developed by computer science specialists seem not to grasp the terminology and problems of the domain experts. We propose here a general object-oriented framework for modelling and simulation of propagation processes. Object-oriented techniques help in developing generic and reusable models. From modelling to simulation, the Unified Modelling Language (UML) provides a common means of communication between computer science specialists and domain experts. The Model Driven Architecture (MDA) is used to improve object-oriented methodology. Simulation optimisations are defined for discrete time models of propagation. The approach is applied to the modelling and simulation of fire spread. Starting from wasteland fire problems, specification levels are used to gradually specify a fire spread simulator. Each level of the study is specified in UML and thus can be reused in another wasteland fire problem.

Specification of Discrete Event Models for Fire Spreading

The fire-spreading phenomenon is highly complex, and existing mathematical models of fire are so complex themselves that any possibility of analytical solution is precluded. Instead, there has been some success when studying fire spread by means of simulation. However, precise and reliable mathematical models are still under development. They require extensive computing resources, being adequate to run in batch mode but making it difficult to meet real-time deadlines. As fire scientists need to learn about the problem domain through experimentation, simulation software needs to be easily modified. The authors used different discrete event modeling techniques to deal with these problems. They have qualitatively compared the Discrete Event System Specification (DEVS) and Cell-DEVS simulation results against controlled laboratory experiments, which allowed them to validate both simulation models of fire spread. They were able to show how these techniques can improve the definition of fire models.

Cell-DEVS quantization techniques in a fire spreading application

We present the use of the CD++ tool to model and simulate forest fire-spread. A semi-physical fire spread model is implemented using the Cell-DEVS formalism. The use of Cell-DEVS enables proving the correctness of the simulation engines and permits to model the problem even by a non-computer science specialist. The high level language of CD++ reduces the algorithmic complexity for the modeler while allowing complex cellular timing behaviors. Different Cell-DEVS quantization techniques are used and developed to decrease execution time. The study is realized regarding time improvement and trades-off between model evolution, simulation time and incurred error. Finally, based on experimentations, interesting perspectives are defined to develop new quantization techniques.

A software framework for fine grain parallelization of cellular models with OpenMP: Application to fire spread

We are dealing here with the parallelization of fire spreading simulations following detailed physical experiments. The proposal presented in this paper has been tested and evaluated in collaboration with physicists to meet their requirements in terms of both performance and precision. For this purpose, an object-oriented framework using two abstraction levels has been developed. A first level considers the simulation as a global phenomenon which evolves in space and time. A local level describes the phenomena occurring on elementary parts of the domain. In order to develop an extensible and modular architecture, the cellular automata paradigm, the DEVS discrete event system formalism and design patterns have been used. Simulation treatments are limited to a set of active elements to improve execution times. A new kind of model, called Active-DEVS is then specified. The model is computed with a fine grain parallelization very efficient for present day multi-core processors which are elementary units of modern computing clusters and computing grids. In this paper, the parallelization with Open MultiProcessing (OpenMP) standard directives on Symmetric MultiProcessing (SMP) architectures is discussed and the efficiency of the retained solution is studied.

DYNAMIC STRUCTURE CELLULAR AUTOMATA IN A FIRE SPREADING APPLICATION

Studying complex propagation phenomena is usually performed through cellular simulation models. Usually cellular models are specific cellular automata developed by non-computer specialists. We attempt to present here a mathematical specification of a new kind of CA. The latter allows to soundly specify cellular models using a discrete time base, avoiding basic CA limitations (infinite lattice, neighborhood and rules uniformity of the cells, closure of the system to external events, static structure, etc.). Object-oriented techniques and discrete event simulation are used to achieve this goal. The approach is validated through a fire spreading application.

Optimization of cell spaces simulation for the modeling of fire spreading

This paper presents a simulation performance improvement of the application of the Multicomponent Discrete Time System Specification (MultiDTSS) formalism to a fire spread. Multicomponent choice is explained through both multicomponent systems and networks of systems critical study for cell space modeling and simulation. A new function has been appended to the MultiDTSS formalism to achieve the Active MultiDTSS formalism extension. This function allows reducing the calculation domain of diffusion problems to active cells thus reducing execution time. The two formalisms have been implemented and are compared with a qualitative and quantitative analysis.

Methods for special applications: Cell-DEVS quantization techniques in a fire spreading application

We present the use of the CD++ tool to model and simulate forest fire-spread. A semi-physical fire spread model is implemented using the Cell-DEVS formalism. The use of Cell-DEVS enables proving the correctness of the simulation engines and permits to model the problem even by a non-computer science specialist. The high level language of CD++ reduces the algorithmic complexity for the modeler while allowing complex cellular timing behaviors. Different Cell-DEVS quantization techniques are used and developed to decrease execution time. The study is realized regarding time improvement and trades-off between model evolution, simulation time and incurred error. Finally, based on experimentations, interesting perspectives are defined to develop new quantization techniques.

Active-DEVS: a computational model for the simulation of forest fire propagation

This paper deals with the design of an efficient object model for propagation phenomena. It is applied to the phenomenological model developed at the University of Corsica, within the context of simulation of vegetation fires. The objective is to simulate large-scale fire propagation, and on the longer term to develop a decision aid tool to guide forest firemen and managers. Based on both cellular automata and discrete event specification (DEVS) formalisms, a new kind of model, called active-DEVS, is specified. Modeling methods based on enhanced cellular automata facilitate both spatial dynamic expression of propagation phenomena, and parallel architectures exploitation. However, such environments usually lack the ability to integrate easy component modifications. The DEVS formalism makes it possible to exploit the cellular models efficiently whatever their dimensions, and to reduce simulation times considerably. A simulation framework is developed to implement and compare active-DEVS model and classical discrete time system specification (DTSS) models. This framework relies on designs patterns, and thus keeps a modular, elegant and adaptable design.

Discrete-event modelling of fire spreading

We deal here with the application of discrete-event System Specification (DEVS) formalism to implement a semi-physical fire spread model. Currently, models from physics finely representing forest fires are not efficient and still under development. If current softwares are devoted to the simulation of simple models of fire spread, nowadays there is no environment allowing us to model and simulate complex physical models of fire spread. Simulation models of such a type of models require being easily designed, modified and efficient in terms of execution time. DEVS formalism can be used to deal with these problems. This formalism enables the association of object-oriented hierarchical modelling with discrete-event techniques. Object-oriented hierarchical programming facilitates construction, maintenance and reusability of the simulation model. Discrete-events reduce the calculation domain to the active cells of the propagation domain (the heated ones).

A new way to use fuzzy inference systems in activity-based cellular modeling simulations

Over the last few years, both the study and the design of IT implementations of Cellular Automata Models (CAM) have gained a renewed interest. The success of these models in the Theory of Modelling and Simulation (TMS) relies on the structural phenomenon of emergence which makes it possible to run realistic simulations, despite lacking a modeling process for real systems. Cellular Automata Models (CAMs)do not describe real systems with complex equations, they allow the complexity of real systems to emerge from simple interactions described locally from their cellular elements. In order to optimize simulations whatever the spatial dimension considered, the concept of activity is used. In this work, we introduce disturbances in propagation rules and we improve simulation rendering. We express a doubt in the expression of the cells activity, i.e. we express the activity rule by means of an Fuzzy Inference System (FIS). We present a new way to use Fuzzy Inference System (FIS), in an activity-based cellular modeling approach for fire spreading simulations.