{"id":779,"date":"2020-07-14T19:57:55","date_gmt":"2020-07-14T18:57:55","guid":{"rendered":"https:\/\/cimafoundation.org\/2020\/07\/16\/propagator-how-to-simulate-fire-dynamics\/"},"modified":"2022-09-29T08:24:45","modified_gmt":"2022-09-29T08:24:45","slug":"propagator-how-to-simulate-fire-dynamics","status":"publish","type":"post","link":"https:\/\/www.cimafoundation.org\/en\/news\/propagator-how-to-simulate-fire-dynamics\/","title":{"rendered":"PROPAGATOR, how to simulate fire dynamics"},"content":{"rendered":"\n

An article recently published in the journal <\/em>Fire describes the characteristics and the latest implementations of the model developed by CIMA Research Foundation researchers for risk assessment and forest fire management<\/em><\/h4>\n\n\n\n

Predicting the possible dynamics that a wildfire can\nassume once it has started, even if it is affected by uncertainty, is extremely\nuseful to in advance address the operations that can be carried out to prevent\nthe fire from impacting potentially exposed people. From this point of view,\nmathematical models are extremely helpful. PROPAGATOR<\/a>\nis a model developed by CIMA Research Foundation researchers that offers, in\nprobabilistic terms, indications on how a fire can evolve under certain\nconditions and in a certain area. Employed for years in various research\nactivities and operational tests, a recent\narticle<\/a> published in the journal Fire<\/em> describes its\ncharacteristics and most recent implementations in detail.<\/p>\n\n\n\n

The probabilistic calculation for wildfire simulation<\/h4>\n\n\n\n

How does a fire evolve? There is no unambiguous answer.\nThere are many parameters to take into account, hence, fires are all different.\nThe humidity of the air and the soil have their own weight, as do the wind,\nwhich can push the fire one way or another at different speeds. The slope is\nalso a parameter that influences the speed and the prevailing direction of\npropagation. Moreover, the type of vegetation present, which can be more or\nless flammable depending on the species and on its phenological state (i.e. the\nlife cycle stage it is in: is the vegetation full of leaves and rich in water\nor dry and bare?). <\/p>\n\n\n\n

Notwithstanding these limitations, estimations of fire\nbehavior, based on the values of these parameters in a given area and at a\ngiven time, provide an important support for civil protection activities<\/strong>,\nto evaluate if and when a fire can approach infrastructures, houses or areas\nwith an important frequency of tourists, but also for the management and\ncontainment<\/strong> of the spread of the flame front. <\/p>\n\n\n\n

The PROPAGATOR model does exactly that: \u201cIt is a fire\nsimulator that, starting from a fire ignition, probabilistically determines how\nthe fire can move based on specific parameters, which are provided by the user\nor taken from monitoring stations or other models. For example, data on\nvegetation humidity are provided by RISICO<\/a>,\nanother model developed by CIMA Research Foundation, which allows for the integration\nof information on air humidity and other meteorological parameters on dried\nfine plant materials present on the ground\u201d, explains Andrea Trucchia,\nresearcher in the Wildfire\nRisk Management and Forest Conservation Department<\/a> of CIMA research\nFoundation and primary author of the study. \u201cBeing a probabilistic model<\/strong>,\nPROPAGATOR is in a way “less precise” than other mathematical models.\nIn fact, it returns an average probability, but it works quickly, providing\ninformation on potential risks on a small scale and on the single fire event in\na short time.\u201d<\/p>\n\n\n\n