432007 Development of Kinetic Models of Biomass Gasification

Thursday, November 12, 2015: 9:04 AM
250B (Salt Palace Convention Center)
Ruochen Wu, Chemical Engineering, Brigham Young University, Provo, UT

This investigation provides a comprehensive analysis of simplified kinetic model for biomass gasification, over a wide temperature range (1150-1350°Ϲ) in CO2, H2O and the combination of these two reactant gases. And the model simulates pyrolysis and gasification stages for a single biomass particle of three different types (poplar wood, corn stover and swichgrass) and different sizes. With the power-law model and non-linear least squares regression method, the kinetic model is optimized and the regressed kinetic parameters (pre-exponential factor and activation energy) are derived for both H2O and CO2. A = 0.0025 (g/m^2 s Pa) and E/R = 5179 K are the optimal parameters we obtain from these data, in order to predict the mass loss and the reaction rate. Model simulations follow great agreement with measured data.

Some publications investigated the influence of particle shape and size, including three main shapes, sphere, cylinderl and flat plate. Previous works reported that spherical particles react most rapidly, and flat particle react most slowly. The high ratio of surface-area-to-volume explains this observation. In order to better illustrate the influence of particle shape and size on the reaction rates, the spherical-equivalent-diameter is introduced in this investigation. This parameter is the diameter of a sphere derived with the same volume of any aspherical particles. The data shows that the normalized spherical-equivalent-diameter (d/d0) starts from 1 at the beginning of the reaction, and decreases to about 0.65 at the end of the reaction. Similar results are obtained for the other two biomass materials.

Ash effect is another important factor in the model. Based on the experimental data, a negative effect of the ash has been observed on the reaction rate. Some publications suggest that ash act as catalyst in gasification reactions, as a lot of researchers have observed this phenomena in their work. However, the experimental results indicate that the high-ash fuels react more slowly rather than more rapidly than the low ash fuels – the opposite of a catalytic effect. In conclusion, not all ash compositions are catalysts in the biomass gasification reactions. Even if the ash components have catalytic effects on the reactions, the effects of ash excluding available surface area has overwhelmed the catalytic effects on the reaction rates, as the reactions are kinetic limited in the experimental conditions. Thus, the net effect is a significant decrease rather than an increase in reactivity of biomass char, indicating that those catalytic effects could only be included by a compensating change in the ash exclusion model, if ash content is acting as catalyst in biomass gasification reaction.

More sophisticated models that dealing with surface adsorption, such as Ely-Reidel or Langmuir-Hinshelwood are compared in this investigation. From the observation, the simulated model fits the measured data without using the other terms in those complex expressions, which indicates that those terms are negligible compared to the dominant factors.

The uniform regressed parameters used in optimizing the global kinetic model works for most data in great correlation. And the regressed kinetic parameters explains why biomass gasification reaction proceeds more rapidly in H2O environment than in CO2 environment under otherwise similar conditions. 

The conclusions from the experimental data are as follow:

  1. Biomass raw materials in our experiments are mainly obtained from heartwood, corn stover and switchgrass, with an extensive range of both organic and inorganic components, nevertheless, no cardinal differences appear in the gasification parameters of char.
  2. Under the same reacting conditions except reactant gas components, char gasification indicates different reaction rate, without any exception, reactions proceeds more rapidly with H2O than with CO2.
  3. Over a broad range of temperature (1150°C-1350°C), and for different concentrations of CO2, H2O, and for the combination of CO2 and H2O, the first-order global model discussed in this study is accurate enough to optimize the kinetic rate data, which means the assumptions excellently satisfy the biomass gasification mechanisms.
  4. Some advanced models need to be developed for high concentration of H2O, however, that will increase the cost of optimization, and even none of the terms in those expressions can be precisely optimized. Thus, those added terms play minor roles in this model.
  5. Some publications suggest that CO and H2 are absorbed on particle surface. Howbeit, no statistically significant absorption is indicated, which affects the gasification reaction rates. Therefore, the diffusion of CO and H2 molecules are negligible in this model.
  6. The ash exclusion model indicates that although positive catalytic effects are reported in some publications, the negative effects has overwhelmed the catalytic effects. And the net effect is a significant decrease rather than an increase in reactivity of biomass char The pre-fixed experimental conditions determine that the reaction is kinetically limited, not diffusion limited, indicating that advanced and accurate surface-reaction-based model is not necessary.
  7. The changing of biomass particle shape and size influences the reaction rates in profound ways, which cannot be described with any simple model trend. Better assumption and treatment should be developed to fit the data in this stage. 

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