Prediction and Optimization of Heavy Clay Products Quality
Само за регистроване кориснике
2014
Поглавље у монографији (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
The effects of chemical composition, firing temperature (800-1100 °C), and several shape formats of laboratory brick samples on the final product quality were investigated. Prediction of the final laboratory products parameters was evaluated by second order polynomial regression models (SOPs) and artificial neural networks (ANNs), and aft erwards compared to experimental results. SOPs showed high r2 values (0.897-0.913 for compressive strength models, 0.942-0.962 for water absorption, 0.928 for firing shrinkage, 0.988-0.991 for water loss during firing, and 0.941 for volume mass of cubes models). An ANN model, coupled with sensitivity analysis, was obtained with high prediction accuracy: 0.866-0.939 for compressive strength models, 0.954-0.974 for water absorption, 0.882 for firing shrinkage, 0.982-0.988 for water loss during firing, and 0.920 for volume mass of cubes models. The optimal samples' chemical composition and firing temperature were chosen depending on a final usage of the ...raw material in heavy clay brick industry.
Кључне речи:
prediction / optimization / heavy clay productsИзвор:
Advanced Materials for Agriculture, Food and Environmental Safety, 2014, 87-120Издавач:
- Wiley Blackwell
Финансирање / пројекти:
- Осмотска дехидратација хране - енергетски и еколошки аспекти одрживе производње (RS-MESTD-Technological Development (TD or TR)-31055)
DOI: 10.1002/9781118773857.ch4
ISBN: 978-86-915627-2-4
Scopus: 2-s2.0-84927678659
Институција/група
Институт техничких наука САНУ / Institute of Technical Sciences of SASATY - CHAP AU - Arsenović, Milica AU - Pezo, Lato AU - Mančić, Lidija AU - Radojević, Zagorka PY - 2014 UR - https://dais.sanu.ac.rs/123456789/15206 AB - The effects of chemical composition, firing temperature (800-1100 °C), and several shape formats of laboratory brick samples on the final product quality were investigated. Prediction of the final laboratory products parameters was evaluated by second order polynomial regression models (SOPs) and artificial neural networks (ANNs), and aft erwards compared to experimental results. SOPs showed high r2 values (0.897-0.913 for compressive strength models, 0.942-0.962 for water absorption, 0.928 for firing shrinkage, 0.988-0.991 for water loss during firing, and 0.941 for volume mass of cubes models). An ANN model, coupled with sensitivity analysis, was obtained with high prediction accuracy: 0.866-0.939 for compressive strength models, 0.954-0.974 for water absorption, 0.882 for firing shrinkage, 0.982-0.988 for water loss during firing, and 0.920 for volume mass of cubes models. The optimal samples' chemical composition and firing temperature were chosen depending on a final usage of the raw material in heavy clay brick industry. PB - Wiley Blackwell T2 - Advanced Materials for Agriculture, Food and Environmental Safety T1 - Prediction and Optimization of Heavy Clay Products Quality SP - 87 EP - 120 DO - 10.1002/9781118773857.ch4 UR - https://hdl.handle.net/21.15107/rcub_dais_15206 ER -
@inbook{ author = "Arsenović, Milica and Pezo, Lato and Mančić, Lidija and Radojević, Zagorka", year = "2014", abstract = "The effects of chemical composition, firing temperature (800-1100 °C), and several shape formats of laboratory brick samples on the final product quality were investigated. Prediction of the final laboratory products parameters was evaluated by second order polynomial regression models (SOPs) and artificial neural networks (ANNs), and aft erwards compared to experimental results. SOPs showed high r2 values (0.897-0.913 for compressive strength models, 0.942-0.962 for water absorption, 0.928 for firing shrinkage, 0.988-0.991 for water loss during firing, and 0.941 for volume mass of cubes models). An ANN model, coupled with sensitivity analysis, was obtained with high prediction accuracy: 0.866-0.939 for compressive strength models, 0.954-0.974 for water absorption, 0.882 for firing shrinkage, 0.982-0.988 for water loss during firing, and 0.920 for volume mass of cubes models. The optimal samples' chemical composition and firing temperature were chosen depending on a final usage of the raw material in heavy clay brick industry.", publisher = "Wiley Blackwell", journal = "Advanced Materials for Agriculture, Food and Environmental Safety", booktitle = "Prediction and Optimization of Heavy Clay Products Quality", pages = "87-120", doi = "10.1002/9781118773857.ch4", url = "https://hdl.handle.net/21.15107/rcub_dais_15206" }
Arsenović, M., Pezo, L., Mančić, L.,& Radojević, Z.. (2014). Prediction and Optimization of Heavy Clay Products Quality. in Advanced Materials for Agriculture, Food and Environmental Safety Wiley Blackwell., 87-120. https://doi.org/10.1002/9781118773857.ch4 https://hdl.handle.net/21.15107/rcub_dais_15206
Arsenović M, Pezo L, Mančić L, Radojević Z. Prediction and Optimization of Heavy Clay Products Quality. in Advanced Materials for Agriculture, Food and Environmental Safety. 2014;:87-120. doi:10.1002/9781118773857.ch4 https://hdl.handle.net/21.15107/rcub_dais_15206 .
Arsenović, Milica, Pezo, Lato, Mančić, Lidija, Radojević, Zagorka, "Prediction and Optimization of Heavy Clay Products Quality" in Advanced Materials for Agriculture, Food and Environmental Safety (2014):87-120, https://doi.org/10.1002/9781118773857.ch4 ., https://hdl.handle.net/21.15107/rcub_dais_15206 .