Coal Pyrolysis Distribution

Abstract

Coal pyrolysis is a complex process involving a large number of chemical reactions. The most accurate and up to date approach to modeling coal pyrolysis is to adopt the Distributed Activation Energy Model (DAEM) in which the reactions are assumed to consist of a set of irreversible first-order reactions that have different activation energies and a constant frequency factor. The differences in the activation energies have usually been represented by a Gaussian distribution. This thesis firstly compares the Simple First Order Reaction Model (SFOR) with the Distributed Activation Energy Model (DAEM), to explore why the DAEM may be a more appropriate approach to modeling coal pyrolysis. The second part of the thesis uses the inverse problem approach together with the smoothing function (iterative method) to provide an improved estimate of the underlying distribution in the wide distribution case of the DAEM. The present method significantly minimizes the error due to differencing and smoothes the chopped off parts on the underlying distribution curve.