Optimization of adobe clay bricks based on the raw material properties (mathematical analysis)
Abstract
This research studies the effects of composition and granulometry analysis of 139 heavy clays on the important characteristics of wet and adobe clay bricks. ANN models were obtained with high prediction accuracy in training cycles (r(2)): 0.580-0.907. Standard score analysis (SS) is performed to evaluate the optimal content of raw materials to gain adobe bricks. Optimal macro-oxides content was 53-66% SiO2, 4.6-7.5% Fe2O3, 12.5-18.2% Al2O3, 0.9-8.8% CaO, 1.2-3.6% MgO. The optimal quantity of alevrolite-sized particles varied between 46 and 65%, and clay-sized particles contents ranged from 20.4 to 40.6%.
Keywords:
Plasticity / Optimization / Drying sensitivity / Adobe clay brickSource:
Construction and Building Materials, 2020, 244Publisher:
- Elsevier Sci Ltd, Oxford
Funding / projects:
- Development and application of multifunctional materials using domestic raw materials in upgraded processing lines (RS-45008)
- Osmotic dehydration of food - energy and ecological aspects of sustainable production (RS-31055)
DOI: 10.1016/j.conbuildmat.2020.118342
ISSN: 0950-0618
WoS: 000527410200052
Scopus: 2-s2.0-85079191816
Collections
Institution/Community
Institut za ispitivanje materijalaTY - JOUR AU - Vasić, Milica AU - Pezo, Lato AU - Radojević, Zagorka PY - 2020 UR - http://rims.institutims.rs/handle/123456789/383 AB - This research studies the effects of composition and granulometry analysis of 139 heavy clays on the important characteristics of wet and adobe clay bricks. ANN models were obtained with high prediction accuracy in training cycles (r(2)): 0.580-0.907. Standard score analysis (SS) is performed to evaluate the optimal content of raw materials to gain adobe bricks. Optimal macro-oxides content was 53-66% SiO2, 4.6-7.5% Fe2O3, 12.5-18.2% Al2O3, 0.9-8.8% CaO, 1.2-3.6% MgO. The optimal quantity of alevrolite-sized particles varied between 46 and 65%, and clay-sized particles contents ranged from 20.4 to 40.6%. PB - Elsevier Sci Ltd, Oxford T2 - Construction and Building Materials T1 - Optimization of adobe clay bricks based on the raw material properties (mathematical analysis) VL - 244 DO - 10.1016/j.conbuildmat.2020.118342 ER -
@article{ author = "Vasić, Milica and Pezo, Lato and Radojević, Zagorka", year = "2020", abstract = "This research studies the effects of composition and granulometry analysis of 139 heavy clays on the important characteristics of wet and adobe clay bricks. ANN models were obtained with high prediction accuracy in training cycles (r(2)): 0.580-0.907. Standard score analysis (SS) is performed to evaluate the optimal content of raw materials to gain adobe bricks. Optimal macro-oxides content was 53-66% SiO2, 4.6-7.5% Fe2O3, 12.5-18.2% Al2O3, 0.9-8.8% CaO, 1.2-3.6% MgO. The optimal quantity of alevrolite-sized particles varied between 46 and 65%, and clay-sized particles contents ranged from 20.4 to 40.6%.", publisher = "Elsevier Sci Ltd, Oxford", journal = "Construction and Building Materials", title = "Optimization of adobe clay bricks based on the raw material properties (mathematical analysis)", volume = "244", doi = "10.1016/j.conbuildmat.2020.118342" }
Vasić, M., Pezo, L.,& Radojević, Z.. (2020). Optimization of adobe clay bricks based on the raw material properties (mathematical analysis). in Construction and Building Materials Elsevier Sci Ltd, Oxford., 244. https://doi.org/10.1016/j.conbuildmat.2020.118342
Vasić M, Pezo L, Radojević Z. Optimization of adobe clay bricks based on the raw material properties (mathematical analysis). in Construction and Building Materials. 2020;244. doi:10.1016/j.conbuildmat.2020.118342 .
Vasić, Milica, Pezo, Lato, Radojević, Zagorka, "Optimization of adobe clay bricks based on the raw material properties (mathematical analysis)" in Construction and Building Materials, 244 (2020), https://doi.org/10.1016/j.conbuildmat.2020.118342 . .