000003360 001__ 3360
000003360 005__ 20190219123706.0
000003360 037__ $$aTESIS-2009-065
000003360 041__ $$aeng
000003360 1001_ $$aPallarés Ranz, Javier
000003360 24500 $$aUnburned carbon in ash prediction in pulverized coal utility boilers. Analysis and assessment of operation strategies.
000003360 260__ $$aZaragoza$$bUniversidad de Zaragoza$$c2008
000003360 300__ $$a314
000003360 500__ $$aPresentado: 05 02 2008
000003360 502__ $$aTesis-Univ. Zaragoza$$bZaragoza, Universidad de Zaragoza$$c2008
000003360 506__ $$aby-nc-nd$$bCreative Commons$$c3.0$$uhttps://creativecommons.org/licenses/by-nc-nd/3.0/
000003360 520__ $$aThe predictive system developed in this Thesis has the same structure as the so-called combustion kinetics models, however, it obtains the fluid and thermal description through CFD simulations. To solve the handicap of the high computational cost needed to run a CFD simulation, a neural network system is used to reproduce the solutions given by the CFD code. Moreover, a neural network system permits to interpolate in the range of variation used during the training stage, and thus, a predictive system covering the whole operational range of the plant is obtained.
000003360 6531_ $$aUnburned carbon
000003360 6531_ $$aCoal combustion modelling
000003360 6531_ $$aCFD
000003360 6531_ $$aNeural networks
000003360 700__ $$aArauzo Pelet, Inmaculada$$edir.
000003360 7102_ $$aUniversidad de Zaragoza$$bIngeniería Mecánica
000003360 8560_ $$fzaguan@unizar.es
000003360 8564_ $$s4138248$$uhttps://zaguan.unizar.es/record/3360/files/TESIS-2009-065.pdf$$zTexto completo (eng)
000003360 909CO $$ooai:zaguan.unizar.es:3360
000003360 909co $$ptesis
000003360 909CO $$pdriver
000003360 9102_ $$a$$bIngeniería Mecánica
000003360 980__ $$aTESIS