Evaluation of the Reliability of Thermogravimetric Indices for Predicting Coal Performance in Utility Systems

A thorough understanding of fuel behaviour is essential for designing and operating thermochemical systems. Thermogravimetric analysis (TGA) is among the most widely used fuel characterization methods, offering parameters like reactivity and ignition temperature, and enabling comprehensive fuel beha...

Full description

Saved in:
Bibliographic Details
Main Author: Krzysztof M. Czajka
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/18/13/3473
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A thorough understanding of fuel behaviour is essential for designing and operating thermochemical systems. Thermogravimetric analysis (TGA) is among the most widely used fuel characterization methods, offering parameters like reactivity and ignition temperature, and enabling comprehensive fuel behaviour assessment through combined indices. This study critically examines the applicability of TGA-based indices for predicting coal performance in industrial processes such as gasification and combustion, where devolatilization, ignition, and burnout stages are key. TGA-derived data are compared with results from established methods, including drop tube furnace (DTF), pulse ignition (PI), and entrained flow reactor (EFR) tests. Findings indicate that the Volatile Matter Release Index (<i>D</i><sub>2</sub>) effectively predicts DTF behaviour (R<sup>2</sup> = 0.938, max residuals: 4.1 pp), proving useful for fast devolatilization analysis. The Flammability Index (<i>C</i><sub>1</sub>) and Ignition Index (<i>C</i><sub>3</sub>) correlate well with PI results (R<sup>2</sup> = 0.927 and 0.931, max residuals: 53.3a °C), making them reliable ignition indicators. While TGA tools showed limited accuracy in burnout prediction, the proposed Modified Burnout Characteristic Index (<i>B</i><sub>1′</sub>) achieved reasonable performance (R<sup>2</sup> = 0.734, max residuals: 0.062%∙°C<sup>−1</sup>). Overall, selected TGA-based indices offer strong predictive potential for key thermochemical conversion stages.
ISSN:1996-1073