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Prediction of the combustion process in fluidized bed based on physical–chemical properties of biomass particles and their hydrodynamic behaviors

handle: 11449/113561
Abstract The utilization of biomass in fluidized bed reactors is due to alternatives created by the carbon credit market and to environmental concerns. This fact calls for an accurate determination of physical–chemical properties and hydrodynamic studies on biomass-inert binary mixtures. In bubbling fluidized bed combustion processes, the inert material mass is approximately 95% of the total mass of the bed material, and an effective mixture between biomass and inert particles is desired to improve the efficiency of the process. In this study, binary mixtures, composed of biomass and sand as an inert material, were used. Thermal and physical–chemical properties of five biomass samples (sugarcane bagasse, pine sawdust, coffee husk, Tucuma seed, and rice husk) were experimentally evaluated. The morphology of the samples was determined by SEM, and the thermal properties were found by thermogravimetric analysis (TG) and differential thermal analysis (DTA). The hydrodynamic study was carried out in a fluidized bed at room temperature and local atmospheric pressure, in which the minimum fluidization velocity and voidage of the biomass-inert binary mixture were evaluated. The arrangement of the physical–chemical characteristics of biomass and the hydrodynamics of the binary mixture are equally important for predictions of the biomass behavior in fluidized bed combustors.
- University of São Paulo Brazil
- Sao Paulo State University Brazil
- State University of Campinas Brazil
- Universidade de São Paulo Brazil
Fluidized bed, 660, Thermal analyses, Hydrodynamics, Biomass
Fluidized bed, 660, Thermal analyses, Hydrodynamics, Biomass
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).30 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
