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%.
TY - 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 . .
