Chemometric Approach for Mechanical Properties Prediction during the Electromagnetic Casting Process
2015
Преузимање 🢃
Аутори
Patarić, AleksandraGulisija, Zvonko
Jordović, Branka
Pezo, Lato
Mihailović, Marija
Stefanović, Milentije
Чланак у часопису (Објављена верзија)
Метаподаци
Приказ свих података о документуАпстракт
In this study the mechanical properties (reduction of area, S-0, tensile strength, R-m, yield strength, R-p, and elongation, A) of EN AW 7075 aluminum alloy obtained by electromagnetic casting were investigated at different operating parameters: frequency (V), field strength (T) and current intensity (I). The predictive mathematical models using Response Surface Methodology, with second order polynomial (SOP) regression models, and Artificial Neural Network model (ANN), were afterwards compared to obtained experimental results. Analysis of variance and post-hoc Tukey's HSD test at 95% confidence limit ("honestly significant differences") have been utilised to show significant differences between various samples. SOP models showed good prediction capabilities, with high coefficients of determination (r(2)), 0.531-0.977, while ANN model performed even better prediction accuracy: 0.800-0.992. The optimal samples were chosen depending on mechanical properties of the product (S-0 = 50.49mm(...2), R-m = 405.75Nmm(-2), R-p = 302.49Nmm(-2), A = 6.86%), using optimal operating parameters (V = 30 Hz, I = 250 A, T = 18 x 10(-3) At).
Кључне речи:
prediction / neural network modeling / mechanical properties / casting / aluminum alloyИзвор:
Materials Transactions, 2015, 56, 6, 835-839Финансирање / пројекти:
- Развој технолошких поступака ливења под утицајем електромагнетног поља и технологија пластичне прераде у топлом стању четворокомпонентних легура Al-Zn за специјалне намене (RS-MESTD-Technological Development (TD or TR)-34002)
- Осмотска дехидратација хране - енергетски и еколошки аспекти одрживе производње (RS-MESTD-Technological Development (TD or TR)-31055)
DOI: 10.2320/matertrans.M2015058
ISSN: 1345-9678
WoS: 000357692200012
Scopus: 2-s2.0-84929897648
Институција/група
Institut za opštu i fizičku hemijuTY - JOUR AU - Patarić, Aleksandra AU - Gulisija, Zvonko AU - Jordović, Branka AU - Pezo, Lato AU - Mihailović, Marija AU - Stefanović, Milentije PY - 2015 UR - https://riofh.iofh.bg.ac.rs/handle/123456789/415 AB - In this study the mechanical properties (reduction of area, S-0, tensile strength, R-m, yield strength, R-p, and elongation, A) of EN AW 7075 aluminum alloy obtained by electromagnetic casting were investigated at different operating parameters: frequency (V), field strength (T) and current intensity (I). The predictive mathematical models using Response Surface Methodology, with second order polynomial (SOP) regression models, and Artificial Neural Network model (ANN), were afterwards compared to obtained experimental results. Analysis of variance and post-hoc Tukey's HSD test at 95% confidence limit ("honestly significant differences") have been utilised to show significant differences between various samples. SOP models showed good prediction capabilities, with high coefficients of determination (r(2)), 0.531-0.977, while ANN model performed even better prediction accuracy: 0.800-0.992. The optimal samples were chosen depending on mechanical properties of the product (S-0 = 50.49mm(2), R-m = 405.75Nmm(-2), R-p = 302.49Nmm(-2), A = 6.86%), using optimal operating parameters (V = 30 Hz, I = 250 A, T = 18 x 10(-3) At). T2 - Materials Transactions T1 - Chemometric Approach for Mechanical Properties Prediction during the Electromagnetic Casting Process EP - 839 IS - 6 SP - 835 VL - 56 DO - 10.2320/matertrans.M2015058 UR - conv_325 ER -
@article{ author = "Patarić, Aleksandra and Gulisija, Zvonko and Jordović, Branka and Pezo, Lato and Mihailović, Marija and Stefanović, Milentije", year = "2015", abstract = "In this study the mechanical properties (reduction of area, S-0, tensile strength, R-m, yield strength, R-p, and elongation, A) of EN AW 7075 aluminum alloy obtained by electromagnetic casting were investigated at different operating parameters: frequency (V), field strength (T) and current intensity (I). The predictive mathematical models using Response Surface Methodology, with second order polynomial (SOP) regression models, and Artificial Neural Network model (ANN), were afterwards compared to obtained experimental results. Analysis of variance and post-hoc Tukey's HSD test at 95% confidence limit ("honestly significant differences") have been utilised to show significant differences between various samples. SOP models showed good prediction capabilities, with high coefficients of determination (r(2)), 0.531-0.977, while ANN model performed even better prediction accuracy: 0.800-0.992. The optimal samples were chosen depending on mechanical properties of the product (S-0 = 50.49mm(2), R-m = 405.75Nmm(-2), R-p = 302.49Nmm(-2), A = 6.86%), using optimal operating parameters (V = 30 Hz, I = 250 A, T = 18 x 10(-3) At).", journal = "Materials Transactions", title = "Chemometric Approach for Mechanical Properties Prediction during the Electromagnetic Casting Process", pages = "839-835", number = "6", volume = "56", doi = "10.2320/matertrans.M2015058", url = "conv_325" }
Patarić, A., Gulisija, Z., Jordović, B., Pezo, L., Mihailović, M.,& Stefanović, M.. (2015). Chemometric Approach for Mechanical Properties Prediction during the Electromagnetic Casting Process. in Materials Transactions, 56(6), 835-839. https://doi.org/10.2320/matertrans.M2015058 conv_325
Patarić A, Gulisija Z, Jordović B, Pezo L, Mihailović M, Stefanović M. Chemometric Approach for Mechanical Properties Prediction during the Electromagnetic Casting Process. in Materials Transactions. 2015;56(6):835-839. doi:10.2320/matertrans.M2015058 conv_325 .
Patarić, Aleksandra, Gulisija, Zvonko, Jordović, Branka, Pezo, Lato, Mihailović, Marija, Stefanović, Milentije, "Chemometric Approach for Mechanical Properties Prediction during the Electromagnetic Casting Process" in Materials Transactions, 56, no. 6 (2015):835-839, https://doi.org/10.2320/matertrans.M2015058 ., conv_325 .