Abstract
The massive use of fossil energy and the gradual rise of biomass energy has led to a rapid increase in the production of solid ashes such as coal fly ash, sewage sludge fly ash, municipal solid waste bottom ash, and fly ash, which has caused serious damage to the environment. The effective disposal and recycling of solid ash has become an important research focus area. However, the treatment strategies of solid ash vary with different sources and chemical properties. Understanding the chemical properties and determining the source of solid ash is key to ensuring its proper disposal and efficient recycling. In this chapter, data on solid ashes were collected through literature searches, and statistical and correlation analyses of the chemical properties of solid ashes were performed. K-means and agglomerative nesting clustering algorithms and the Gaussian mixture model were used to cluster the data in combination with two different fitting ways. Four evaluation indicators were used to measure the consistency of the clustering results with the real data. We show that solid ashes from different origins have various chemical properties. The k-means clustering algorithm that used all features during clustering had a better performance and was more suitable for detecting the origin of a solid ash. In addition, the differences in the chemical properties of solid ashes from different sources and the correlation between oxides provided a theoretical basis for cluster analysis to a certain extent.
Original language | English |
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Title of host publication | Managing Mining and Minerals Processing Wastes |
Subtitle of host publication | Concepts, Design, and Applications |
Editors | Chongchong Qi, Craig H. Benson |
Publisher | Elsevier |
Chapter | 11 |
Pages | 235-247 |
Number of pages | 13 |
ISBN (Electronic) | 9780323912839 |
ISBN (Print) | 9780323912846 |
DOIs | |
Publication status | Published - 2023 |