On the prediction of thermal runaway of coal piles of differing dimension by using a correlation between heat release and activation energy

Yulianto Sulistyo Nugroho, Andrew C. McIntosh, Bernard M. Gibbs

Research output: Contribution to journalConference articlepeer-review

20 Citations (Scopus)

Abstract

Greater use of international coal and low-sulfur/low-rank coals brings new challenges in monitoring the spontaneous combustion behavior of these coals during transport, in stockpiles, and in coal milling systems. Extensive experimental work has been carried out to measure the kinetic parameters of low-temperature oxidation of a number of coals for varying particle fractions. A substantial set of experimentally measured values of activation energy, Ea, and the product of the exothermicity and the pre-exponential factor, QA, have indicated a strong relationship, which is shared by coals of different ranks and of different particle size. This correlation for Ea and QA leads to a new approach for estimating the thermal runaway behavior of coal piles based on small-scale experiments. By use of Frank-Kamenetskii theory, the correlation curve fit of Ea versus QA can be used to estimate hazardous conditions at varying scales by small-scale oven heating tests measuring the heat release rate at low temperatures. The results suggest that the increasing size of the pile alters the particle size effect. For large coal piles, large particle size can increase the potential for spontaneous combustion. This new approach provides a more cost-effective assessment of the susceptibility of various types of coal to self-ignition.

Original languageEnglish
Pages (from-to)2321-2327
Number of pages7
JournalProceedings of the Combustion Institute
Volume28
Issue number2
DOIs
Publication statusPublished - 1 Jan 2000
Event30th International Symposium on Combustion - Chicago, IL, United States
Duration: 25 Jul 200430 Jul 2004

Fingerprint Dive into the research topics of 'On the prediction of thermal runaway of coal piles of differing dimension by using a correlation between heat release and activation energy'. Together they form a unique fingerprint.

Cite this