Hybrid computational model to assist in the location of victims buried in the tragedy of Brumadinho
DOI:
https://doi.org/10.24221/jeap.6.3.2021.4103.183-193Resumo
The rupture of dams in Brazil has caused great concern due to the environmental disaster and the loss of lives. The use of algorithms and computational models to assist search teams in locating victims when buried by tailings is essential but scarce. Those that exist are mainly slow, as they involve high computational costs. In this sense, in the context of the Brumadinho tragedy in 2019, this study aimed to develop a hybrid computational model to assist the search teams in locating victims buried by the tailings. The methodology for designing this model was based on regression techniques, machine learning, and physicomathematical algorithms. Firstly, the study resulted in a physicomathematical model based on integral and vector calculus and concepts of fluid mechanics, which provided results to assist in locating bodies buried by the tailings. More recently, based on data provided by the physicomathematical algorithm, two hybrid models have been developed. One uses statistical regression, and the other uses support vector regression, a type of machine learning. It is expected that a more accurate model can be used in other possible situations of disruption in future studies. Also, it is possible to apply the model developed in situations involving computational fluid dynamics in general.Downloads
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Copyright (c) 2021 RAFAEL FERNANDES PINHEIRO, Harold Ivan Angulo Bustos, Bruno Bestle Turrin, Francisco Marcos da Costa Monteiro, Diego Colón, Mirelly Ferreira Silveira, Dário José Aloise, Alysson Mendes de Oliveira
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