University of Oulu

Vasić, M. V., Jantunen, H., Mijatović, N., Nelo, M., & Muñoz Velasco, P. (2023). Influence of coal ashes on fired clay brick quality: Random forest regression and artificial neural networks modeling. Journal of Cleaner Production, 407, 137153.

Influence of coal ashes on fired clay brick quality : random forest regression and artificial neural networks modeling

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Author: Vasić, Milica Vidak1; Jantunen, Heli2; Mijatović, Nevenka1;
Organizations: 1Institute for Testing of Materials IMS, Bulevar vojvode Mišića 43, 11000, Belgrade, Serbia
2University of Oulu, P.O. Box (PL) 4500, FI-90014, Oulu, Finland
3ESIT, Universidad Internacional de La Rioja, Avda. de la Paz 137, 26007, Logroño, Spain
4Facultad de Ingeniería, Universidad Autónoma de Chile, 5 Pte, 1760, Talca, Chile
Format: article
Version: accepted version
Access: embargoed
Persistent link:
Language: English
Published: Elsevier, 2023
Publish Date: 2025-04-11


Finding a solution to the problem of the large buildup of coal ashes is a vital necessity. Although the use of coal ashes in fired clay bricks has been thoroughly investigated, there is insufficient information on their industrial utilization and researchers do not agree on whether or not this addition improves the quality of the final products. Therefore, a database has gathered 20 years of research containing key factors related to the quality of the bricks (i.e., chemical composition, firing temperature, soaking time, open porosity, water absorption and compressive strength). Then, random forest regression and artificial neural networks (ANN) modeling were used to separately predict the parameters concerning the quality of the final products. The overall conclusions were that the compressive strengths were the highest when using fly ashes and that class F ashes were highly suitable to be used in the brick industry as a replacement material for brick clay. In addition, the ANN models showed higher coefficients of determination and an overall better fit to the experimental data. By changing the chemical makeup of the initial materials and their proportions, the particle size of the ashes, the firing temperature and soaking time, as well as the size of a product, the created models can be used to estimate the quality of the brick containing coal ash. That is crucial because the inconsistent chemical composition of ash is generally the main obstacle to its utilization. The local sensitivity analysis revealed the highest influence of the content of the alkali oxides in the initial clay on the fired clay bricks due to their fluxing effect. In the case of ash-clay bricks, the decisive factors were the type of furnace used, the ashes’ class, the Na₂O content in raw clay, and the K₂O introduced with the ash. The F class ashes containing about 2–3% of K₂O and <5% of CaO gave the highest compressive strength in bricks fired at 1000–1100 °C.

Additional analyzes were made for 50% pond ash and 50% clay bricks to test the best-suited model and fill in the knowledge gap. The results obtained in this study are important for supporting the decision in the selection of materials and process parameter values that will increase the quality of the ash-clay-fired bricks.

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Series: Journal of cleaner production
ISSN: 0959-6526
ISSN-E: 1879-1786
ISSN-L: 0959-6526
Volume: 407
Article number: 137153
DOI: 10.1016/j.jclepro.2023.137153
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
222 Other engineering and technologies
Funding: This research was funded by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia [Contract No. 451-03-47/2023-02/200012]. The authors also wish to thank the Chilean National Commission on Research and Development (CONICYT) [FONDECYT REGULAR grant number 1180414].
Copyright information: © 2023. This manuscript version is made available under the CC-BY-NC-ND 4.0 license