(199b) A Numerical Study On Bio-Oil Gasification Using A Multicomponent Approach | AIChE

(199b) A Numerical Study On Bio-Oil Gasification Using A Multicomponent Approach

Authors 

Zhang, L. - Presenter, Iowa State University
Kong, S. C. - Presenter, Iowa State University


A Numerical Study on Bio-Oil Gasification Using A Multicomponent Approach

Bio-oil,
also called pyrolysis oil, is a complex biorenewable fuel produced from fast
pyrolysis of biomass. Since bio-oil is carbon dioxide neutral, it can be an
ideal replacement for petroleum fuel to be used in many kinds of combustion devices.
It can also be gasified to produce synthesis gas, which in turn can be used for
power generation or synthesized to produce liquid fuels. The objective of this
study is to investigate the gasification/vaporization characteristics of
bio-oil drops under gasfier and combustor conditions. In this study, numerical methods
considering the actual composition of bio-oil are mainly used in the simulation
of gasification/vaporization processes. Literature using experimental
approaches such as Gas Chromatography/Mass Spectrometer has shown that bio-oil components
can be categorized into several groups, including carbohydrates, furans,
phenols, guaiacols, syringols, water, etc. By analyzing the composition of
bio-oil produced from different sources, a group of ten dominant components are
identified from the above groups. Using group contribution methods, the
critical and physical properties of these dominant components are estimated. Simplifying
bio-oil as a mixture of these dominant components, a multi-component drop
vaporization model using a discrete component approach is developed in the
simulation of gasification/vaporization. Using the vaporization model, the
vaporization histories of single bio-oil drops with different initial
compositions, which are the mass fractions of the components determined by the
feedstock and pyrolysis process, are calculated. In addition, the dynamics of
bio-oil spray is also studied numerically, and the distributions of the vapors
of various bio-oil components in the reactor are also predicted.