Recycling combustion ash for sustainable cement production: A critical review with data mining and time series predictive models
Abstract Combustion is a complex process that produces energy as the goal and ashes as by products. The ash of coal, biomass and solid waste combustion can be used as pozzolans in blended cement due to the similarity of their physiochemical properties to conventional pozzolans (e.g. silica fume) This strategy effectively recycles pozzolanic active combustion ash and replaces a significant proportion of Portland cement, which potentially reduces the greenhouse gas (GHG) emissions from cement production. However, cement producers wishing to substitute pozzolanic active ash for conventional pozzolans lack information on the pozzolanic activity (PA) of ash from diverse combustible materials. A data mining model that can extract key information for predicting the PA of combustion ash is envisioned as a screening tool to assess the pozzolanic potential of candidate combustible materials prior to experimental work. Hence, the objectives of this chapter are, 1) to critically review the recent research progress in using various combustion ashes as pozzolans, including the mechanism of the pozzolanic reaction, sources of eligible materials, and methods of PA improvement, 2) to create a data mining artificial neural network (ANN) model for PA prediction built upon data reported in the scientific literature from 1998 to 2015, and 3) to describe the effect of cement curing period on PA, based on a time series model. The ANN and time series models developed in this study can accurately forecast the PA of combustion ashes during 3 90 d curing (R 2 0.8479 0.9914) We recommend these screening tools as rapid indicators of the pozzolanic potential of combustion ash prior to undertaking strength tests and other experimental testing.