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Theoretical models to evaluate the effect of SiO2 and CaO contents on the long‑term compressive strength of cement mortar modified with cement kiln dust (CKD)

Abdalla Aso A., Salih Mohammed Ahmed

Archives of Civil and Mechanical Engineering

2022

Vol. 22, no. 3

art. no. e105

Cement kiln dust (CKD) is a fine powder similar to Portland cement in appearance and produced during grinding and burning of the raw material in the cement kiln. Large amounts of CKD have accumulated in the cement factories annually. It is necessary to re-use this waste material in the construction field instead of landfilling, causing environmental problems, such as the death of vegetation and groundwater pollution. One of the choices to re-use CKD is replacing Portland cement in cement-based mortar and reducing greenhouse gas emissions like carbon dioxide to the atmosphere. This study evaluated the effect of the main two components of CKD, such as SiO2 and CaO, on the long-term compressive strength of cement-based mortar up to 360 days of curing. For that purpose, 167 data of cement-based mortar samples modified with CKD were collected from literature and analyzed. Water-to-binder ratio (w/b) was ranged from 0.34 to 0.76, CKD content ranged from 0 to 50% (dry weight of cement), different CaO and SiO2 of CKD and cement are ranged from 17.64 to 25.45%, and 51.45 to 65.57%, respectively. Several soft computing models, such as multi-expression programming (MEP), artificial neural network (ANN), nonlinear regression (NLR), and full quadratic (FQ), were developed to predict the compressive strength of the cement mortar modified with CKD. Statistical assessment tools were also used to evaluate the proposed models. It was obtained from the modeling results that are increasing SiO2(%) increased the compressive strength of the mortar, and increasing CaO (%) decreased compressive strength for CKD content from 0 to 15% and increasing compressive strength for CKD content of 15-50%. According to the assessment criteria, the ANN model predicted compressive strength up to 360 days of curing better than other developed models with high R2 and a20-index and low RMSE, MAE, SI, and OBJ. The second-best model was the MEP model. Based on the sensitivity analysis, the curing time is the most influential parameter in compressive strength prediction of cement-based mortar modified with CKD.