Solid ashes investigation for its efficient recycling: chemical properties and clustering analysis

Mengting Wu, Chongchong Qi, Xiangjian Dong, Qiusong Chen

Research output: Chapter in Book/Conference paperChapterpeer-review

1 Citation (Scopus)

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 languageEnglish
Title of host publicationManaging Mining and Minerals Processing Wastes
Subtitle of host publicationConcepts, Design, and Applications
EditorsChongchong Qi, Craig H. Benson
PublisherElsevier
Chapter11
Pages235-247
Number of pages13
ISBN (Electronic)9780323912839
ISBN (Print)9780323912846
DOIs
Publication statusPublished - 2023

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