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dc.contributor.authorMampel Data, Jorge
dc.contributor.authorEgorova, Vera 
dc.contributor.authorPagnini, Gianni
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2025-04-25T11:06:31Z
dc.date.issued2024-11
dc.identifier.issn1007-5704
dc.identifier.otherPID2019-107685RB-I00es_ES
dc.identifier.otherPDC2022-133115-I00es_ES
dc.identifier.urihttps://hdl.handle.net/10902/36292
dc.description.abstractA discrete map for modelling wind-driven wildfire propagation is derived from a prototypical reaction–diffusion equation for the temperature field. We show that, for a constant fuel concentration at the fire-front, the heat transfer coefficient from fuel to surroundings and as well as an effective heat of reaction are two independent mechanisms that can cause the transition to chaos, when they may depend on temperature as a consequence of the fire-atmosphere coupling and of the fuel inhomogeneity, respectively. In particular, chaos can enter when the coefficient for the heat transfer from the fuel to the surrounding depends linearly on the temperature and when the effective heat of reaction depends quadratically. Moreover, when the fuel concentration field at the fire-front fluctuates because of fuel porosity, this embodies a third mechanism that may cause the transition to chaos even without any fire-atmosphere coupling or fuel inhomogeneity. Surprisingly, when the effective heat of reaction depends linearly on the temperature, the chaos generated by the non-constant fuel concentration is ceased. This suppression is not observed when the chaos is due to the fire-atmosphere coupling with constant fuel concentration. In all cases, the onset of chaos is related to the logistic map. Although our study is a proof-of-concept not yet checked against realistic test cases, our main results may be of some interest for fire scientists and firefighters. Thus, the application of this approach for setting an alternative method for real-time risk assessment is discussed in the conclusions.es_ES
dc.description.sponsorshipThis research is supported by the Basque Government, Spain through the BERC 2022–2025 program, by the Ministry of Science and Innovation, New Zealand: BCAM Severo Ochoa accreditation CEX2021-001142-S/MICIN/AEI/10.13039/501100011033 and the project PID2019-107685RB-I00/MCIN/AEI/ 10.13039/501100011033, and by the Spanish State Research Agency (AEI) through the project PDC2022-133115-I00 entitled “B_2 F_2: Be a Better digital Fire-Fighter” funded by MCIN/AEI/ 10.13039/501100011033 and by European Union “NextGenerationEU”/PRTR; by the European Regional Development Fund (ERDF) and the Department of Education of the regional government, the Junta of Castilla y León (Grant contract SA089P20).es_ES
dc.format.extent28 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rights© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 licensees_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceCommunications in Nonlinear Science and Numerical Simulation, 2024, 138, 108190es_ES
dc.subject.otherWildland firees_ES
dc.subject.otherTransition to chaoses_ES
dc.subject.otherChaotic mapes_ES
dc.subject.otherReal-time risk assessmentes_ES
dc.titlePredicting the arrival of the unpredictable: an approach for foreseeing the transition to chaos of wildfire propagationes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.cnsns.2024.108190es_ES
dc.rights.accessRightsembargoedAccesses_ES
dc.identifier.DOI10.1016/j.cnsns.2024.108190
dc.type.versionacceptedVersiones_ES
dc.embargo.lift2026-12-01
dc.date.embargoEndDate2026-12-01


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© 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 licenseExcepto si se señala otra cosa, la licencia del ítem se describe como © 2024. This manuscript version is made available under the CC-BY-NC-ND 4.0 license