Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2015-12-02T22:57:03Z No. of bitstreams: 1 YuriShalomDeFreitasBezerra_DISSERT.pdf: 1870636 bytes, checksum: fa87a782197886fe563d90143a5c4a3a (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2015-12-09T20:15:23Z (GMT) No. of bitstreams: 1 YuriShalomDeFreitasBezerra_DISSERT.pdf: 1870636 bytes, checksum: fa87a782197886fe563d90143a5c4a3a (MD5) / Made available in DSpace on 2015-12-09T20:15:23Z (GMT). No. of bitstreams: 1 YuriShalomDeFreitasBezerra_DISSERT.pdf: 1870636 bytes, checksum: fa87a782197886fe563d90143a5c4a3a (MD5) Previous issue date: 2014-08-30 / O m?todo de Monte Carlo ? preciso e, quando comparado com outras t?cnicas num?ricas, ? de relativamente f?cil implementa??o para a solu??o de problemas envolvendo geometrias complexas e espalhamento anisotr?pico da radia??o. Al?m disso, diferentemente do que ocorre para a maioria das t?cnicas num?ricas, cujo tempo necess?rio para a execu??o de simula??es tende a crescer exponencialmente ? medida que a complexidade do problema aumenta, no Monte Carlo, o aumento no tempo computacional tende a ser linear. Ainda assim, as solu??es em Monte Carlo s?o computacionalmente pesadas para a solu??o da maioria dos problemas de interesse. O modelo dos Pacotes de Energia Multiespectrais permite a redu??o dos tempos computacionais associados ?s solu??es atrav?s do m?todo de Monte Carlo. O modelo ? aqui analisado para aplica??es em meios constitu?dos por esp?cies n?o-participantes e vapor d??gua, que ? um importante emissor de radia??o formado na combust?o de hidrocarbonetos. Aspectos relacionados ? otimiza??o dos tempos computacionais s?o investigados e solu??es obtidas com o modelo s?o comparadas com solu??es linha-por-linha benchmark. / The Monte Carlo method is accurate and is relatively simple to implement for the solution of problems involving complex geometries and anisotropic scattering of radiation as compared with other numerical techniques. In addition, differently of what happens for most of numerical techniques, for which the associated simulations computational time tends to increase exponentially with the complexity of the problems, in the Monte Carlo the increase of the computational time tends to be linear. Nevertheless, the Monte Carlo solution is highly computer time consuming for most of the interest problems. The Multispectral Energy Bundle model allows the reduction of the computational time associated to the Monte Carlo solution. The referred model is here analyzed for applications in media constituted for nonparticipating species and water vapor, which is an important emitting species formed during the combustion of hydrocarbon fuels. Aspects related to computer time optimization are investigated the model solutions are compared with benchmark line-by-line solutions