Non-classical computing: feasible versus infeasible

Physics sets certain limits on what is and is not computable. These limits are very far from having been reached by current technologies. Whilst proposals for hypercomputation are almost certainly infeasible, there are a number of non classical approaches that do hold considerable promise. There are a range of possible architectures that could be implemented on silicon that are distinctly different from the von Neumann model. Beyond this, quantum simulators, which are the quantum equivalent of analogue computers, may be constructable in the near future

A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the International Journal of Wildland Fir

Discrete event front tracking simulator of a physical fire spread model

International audienceSimulation of moving interfaces, like a fire front usually requires the resolution of a large scale and detailed domain. Such computing involves the use of supercomputers to process the large amount of data and calculations. This limitation is mainly due to the fact that large scale of space and time is usually split into nodes, cells or matrices, and the solving methods often require small time steps. This paper presents a novel method that enables the simulation of large scale/high resolution systems by focusing on the interface. Unlike the conventional explicit and implicit integration schemes, it is based on the discrete-event approach, which describes time advance in terms of increments of physical quantities rather than discrete time stepping. Space as well is not split into discrete nodes or cells, but we use polygons with real coordinates. The system is described by the behaviour of its interface, and evolves by computing collision events of this interface in the simulation. As this simulation technique is suited for a class of models that can explicitly provide rate of spread for a given configuration, we developed a specific radiation based propagation model of physical wildland fire. Simulations of a real large scale fire performed with an implementation of our method provide very interesting results in less than 30 seconds with a 3 metres resolution with current personal computers

Alteração da paisagem e comportamento do fogo na freguesia de França, Bragança

Este trabalho, através do uso de métodos e ferramentas no campo da Ecologia da Paisagem, da Detecção Remota e Sistemas de Informação Geográfica, mostra que as alterações que ocorreram numa paisagem de montanha do Nordeste de Portugal entre 1958 e 2005, favorecem a ocorrência de incêndios de maior dimensão e severidade. As alterações na composição e estrutura paisagem na freguesia de França, uma área de 5373 ha do Parque Natural de Montesinho, no Concelho e Distrito de Bragança, foram avaliadas com base na elaboração de cartas de cobertura/uso do solo para os anos de (1958, 1968, 1978, 1993 e 2005), fotointerpretação de ortofotomapas, também, elaborados a partir de fotografias aéreas da área de estudo. A estrutura da paisagem para cada uma dessas datas foi descrita, através de métricas espaciais calculadas, para analisar a diferentes níveis de classes de uso do solo a paisagem. Estudou-se o comportamento do fogo em termos de abundância, configuração e tipo e características (densidade e continuidade) dos combustíveis. Para isso utilizamos o software FARSITE 4 Finney, (1998), com que simulámos, para todas as datas, a propagação do fogo ao nível da paisagem baseado nos combustíveis, em características do terreno (pendor e orientação das vertentes) e em parâmetros meteorológicos (temperatura, humidade do ar e velocidade e orientação do vento). Com este estudo, pretendeu-se mostrar as alterações estruturais, de funcionamento e dinâmica da paisagem, da freguesia de França e as implicações no comportamento do fogo relativamente ao padrão e severidade (velocidade e intensidade) de propagação dos incêndios, ao longo dos últimos 50 anos. Este trabalho será mais um contributo para a problemática dos incêndios florestais com vista à sua prevenção, evidenciando as suas consequências e permitindo a tomada de decisões antecipadas na gestão e conservação dos ecossistemas

Sistema adaptativo para la predicción de incendios forestales basado en estrategias estadístico-evolutivas

Es proposa mètodes per a millorar la qualitat de predicció d'Incendis forestals per mitjà de combinació d'estratègies basades en guia de dades. Els simuladors de foc són implementacions de models físics i matemàtics que són abstraccions de la realitat i per a funcionar necessiten paràmetres difícils de mesurar i/o amb un comportament dinàmic en el temps. Utilitzant Còmput d'Altes Prestacions apliquem algorismes evolutius reduint l'espai de cerca dels valors que posteriorment s'integren en un conjunt de possibilitats. Els resultats presenten adaptació al canvi de condicions de l'incendi que serveix de base per a generar una aplicación de temps real.Se propone métodos para mejorar la calidad de predicción de Incendios forestales por medio de combinación de estrategias basadas en guía de datos. Los simuladores de fuego son implementaciones de modelos físicos y matemáticos que son abstracciones de la realidad y para funcionar necesitan parámetros difíciles de medir y/o con un comportamiento dinámico en el tiempo. Utilizando Cómputo de Altas Prestaciones aplicamos algoritmo evolutivo reduciendo el espacio de búsqueda de los valores que posteriormente se integra en un conjunto de posibilidades. Los resultados presentan adaptación al cambio de condiciones del incendio que sienta base para generar una aplicación tiempo real

Cellular automata simulations of field scale flaming and smouldering wildfires in peatlands

In peatland wildfires, flaming vegetation can initiate a smouldering fire by igniting the peat underneath, thus, creating a positive feedback to climate change by releasing the carbon that cannot be reabsorbed by the ecosystem. Currently, there are very few models of peatland wildfires at the field-scale, hindering the development of effective mitigation strategies. This lack of models is mainly caused by the complexity of the phenomena, which involves 3-D spread and km-scale domains, and the very large computational resources required. This thesis aims to understand field-scale peatland wildfires, considering flaming and smouldering, via cellular automata, discrete models that use simple rules. Five multidimensional models were developed: two laboratory-scale models for smouldering, BARA and BARAPPY, and three field-scale models for flaming and smouldering, KAPAS, KAPAS II, and SUBALI. The models were validated against laboratory experiments and field data. BARA accurately simulates smouldering of peat with realistic moisture distributions and predicts the formation of unburned patches. BARAPPY brings physics into BARA and predicts the depth of burn profile, but needs 240 times more computational resources. KAPAS showed that the smouldering burnt area decreases exponentially with higher peat moisture content. KAPAS II integrates daily temporal variation of moisture content, and revealed that the omission of this temporal variation significantly underestimates the smouldering burnt area in the long term. SUBALI, the ultimate model of the thesis, integrates KAPAS II with BARA and considers the ground water table to predict the carbon emission of peatland wildfires. Applying SUBALI to Indonesia, it predicts that in El Niño years, 0.40 Gt-C in 2015 (literature said 0.23 to 0.51 Gt-C) and 0.16 Gt-C in 2019 were released, and 75% of the emission is from smouldering. This thesis provides knowledge and models to understand the spread of flaming and smouldering wildfires in peatlands, which can contribute to efforts to minimise the negative impacts of peatland wildfires on people and the environment, through faster-than-real-time simulations, to find the optimum firefighting strategy and to assess the vulnerability of peatland in the event of wildfires.Open Acces

Modelling Wildfire Dynamics via Interacting Automata

Abstract. The modelling of wildland fire spread across a heterogeneous landscape is significant because fire dynamics are sensitive to local spatial characteristics. The development of accurate fire models and simulations is important due to the economical and social losses wildland fire can cause and the resulting need to better understand, predict, and contain fire spread. We present a methodology for encoding the spread of wildland fire in a set of interacting automata. The Circal formalism is used to explicitly describe the transmission of fire as an interaction between discrete cells of landscape. We demonstrate the potential for the methodology to accurately model spatial dynamics by giving results of our implementation of a fire spread model that includes a heterogenous environment. Keywords: modelling wildfire spread, cellular automata, Circal. CR Classification: F.1.1 Models of Computation and I.6.5 Modeling Methodologies. 1 Modelling fire sprea