Complex Network Theory Criterion to Distribute Fuel Breaks for the Hazard Control of Fire Spread in Forests (Articolo in rivista)

Type
Label
  • Complex Network Theory Criterion to Distribute Fuel Breaks for the Hazard Control of Fire Spread in Forests (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Alternative label
  • Ioannis N. Evaggelidis , Constantinos I. Siettos, Paola Russo, and Lucia Russo (2014)
    Complex Network Theory Criterion to Distribute Fuel Breaks for the Hazard Control of Fire Spread in Forests
    in AIP conference proceedings
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Ioannis N. Evaggelidis , Constantinos I. Siettos, Paola Russo, and Lucia Russo (literal)
Pagina inizio
  • 300 (literal)
Pagina fine
  • 303 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 1648 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 4 (literal)
Note
  • Scopus (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • School of Applied Mathematics and Physical Sciences, National Technical University of Athens, Greece Department of Chemical Engineering Materials Environment, Sapienza University of Rome, Rome, Italy Combustion Research Institute , Consiglio Nazionale delle Ricerche, Naples, Italy (literal)
Titolo
  • Complex Network Theory Criterion to Distribute Fuel Breaks for the Hazard Control of Fire Spread in Forests (literal)
Abstract
  • We propose a computational methodology based on complex network theory for distributing fuel breaks to reduce the spread rate and size of wildland fires. The development of fire spread is modeled via a lattice network on the basis of a cellular automata model. We illustrate the proposed approach through a simplistic example which considers a square lattice with periodic boundary conditions with a single type of vegetation and varying density. Simulation results over an ensemble of lattice realizations show that the methodology outperforms significantly the benchmark tactic of random distribution of fuel breaks. (literal)
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