Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Mechanical and Aerospace Engineering

Committee Chair

Nathan Weiland.


Pyrolysis of biomass can produce several useful, renewable products: biochar for soil amendment and long-term carbon sequestration; tars for chemicals and biofuels; and syngas as an energy and biofuel production feedstock. The ability to predict the relative yields of gas, tar and char from the pyrolysis process of various biomasses will enable optimization of pyrolysis process for specific yield ratios. Component based kinetic and 1-D pyrolysis models are developed wherein the woody biomass is characterized by the mass percentage of its three primary components: cellulose, hemicellulose and lignin. Using dual stage mechanisms for primary component pyrolysis and tar cracking reactions, a kinetic model was built to simulate the pyrolysis of the biomass surrogate. The kinetic model was validated against published experimental data for experiments where thermal gradients and fluid flow could be neglected. This kinetic model was incorporated as a source term into a particle model which accounts for fluid flow through porous media. The particle model was validated against published and in-house experimental data for various biomass types. The kinetic model accurately predicts the yields of char, tar, and syngas as well as gas species concentrations to a lower degree of accuracy for biomass pyrolysis where particle sizes are small enough that the reaction is kinetically limited and sweep gas flows keep tar cracking to a minimum. The particle model predicts char, tar and syngas yields accurately provided sweep gas flow is high enough to minimize extra-particle tar cracking and heating rates are slow enough to keep the maximum temperature difference between the inside and outside of the particle less than 10°C. A criterion was developed to determine this maximum temperature difference. The particle model is able to predict gas species trends but fails to predict absolute values. These models can be incorporated into full multi-scale simulations of pyrolysis reactors, with the goal of optimizing various process variables for increasing specific product yields.