Volume 5, Issue 2 (2021)
IQBQ 2021, 5(2): 105-116 |
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Mehralizadeh A, derakhshanfard F, GhaziTabatabaei Z. Investigation of influence of the Styrene Butadiene Styrene on the properties of the Expandable Poly Styrene and simulation of its laboratory data via Artificial Neural Networks. IQBQ 2021; 5 (2) :105-116
URL: http://arcpe.modares.ac.ir/article-38-48533-en.html
URL: http://arcpe.modares.ac.ir/article-38-48533-en.html
1- Islamic Azad University of Ahar - Department of Chemical Engineering
2- Islamic Azad University of Ahar - Department of Chemical Engineering ,f.dfard@gmail.com
3- Islamic Azad University of Ahar - Department of Chemistry
2- Islamic Azad University of Ahar - Department of Chemical Engineering ,
3- Islamic Azad University of Ahar - Department of Chemistry
Abstract: (2088 Views)
Research subject: Expandable Poly Styrene (EPS) has many applications. This polymer prepared by the radical polymerization. This material has many uses in packaging and insulation industries Some of the properties of this polymer like low mechanical strength caused its applications to be limited. By adding some materials, these properties can be improved. Styrene Butadiene Styrene (SBS) is from the materials that which by adding it to the EPS it can improve its quality.
Research approach: In this research, EPS having different percentages of SBS (0, 0.01, 0.02, 0.03) in different conversion percentages (0.6, 0.63, 0.66, 0.69) has been prepared. Different tests like Impact Test, Modular Melt Flow test, Vicat Softening Temperature test, Tensile at Break test, K-value test, Rochwell Hardness test and Elongation at Break test are done on the prepared polymer. Laboratory gained data has been simulated by Multi-Layer Perceptron (MLP) method of artificial neural networks (ANN) and the simulated data covers the laboratory data perfectly.
Main Results: Investigating the tests show that in constant percentages of SBS in EPS with increase in conversion percentage of EPS, the numerical amount of the tests increases except MFI test (low MFI number means better quality). Increase in SBS percentage in the EPS, increases the properties of polymer. In addition, the results of simulation show that the laboratory data covers the the simulated data perfectly. The data obtained from the results of this reasearch can be used for predicting the data for the points which has not been tested. Adding SBS in different weight percentages of poly styrene in different conversion percentages in order to increase the properties of poly styrene has been used for the first time in this research and the laboratory data results in points which has not been tested has been acquired by applications of ANN.
Research approach: In this research, EPS having different percentages of SBS (0, 0.01, 0.02, 0.03) in different conversion percentages (0.6, 0.63, 0.66, 0.69) has been prepared. Different tests like Impact Test, Modular Melt Flow test, Vicat Softening Temperature test, Tensile at Break test, K-value test, Rochwell Hardness test and Elongation at Break test are done on the prepared polymer. Laboratory gained data has been simulated by Multi-Layer Perceptron (MLP) method of artificial neural networks (ANN) and the simulated data covers the laboratory data perfectly.
Main Results: Investigating the tests show that in constant percentages of SBS in EPS with increase in conversion percentage of EPS, the numerical amount of the tests increases except MFI test (low MFI number means better quality). Increase in SBS percentage in the EPS, increases the properties of polymer. In addition, the results of simulation show that the laboratory data covers the the simulated data perfectly. The data obtained from the results of this reasearch can be used for predicting the data for the points which has not been tested. Adding SBS in different weight percentages of poly styrene in different conversion percentages in order to increase the properties of poly styrene has been used for the first time in this research and the laboratory data results in points which has not been tested has been acquired by applications of ANN.
Keywords: Expandable Poly Styrene, Styrene Butadiene Styrene, Mechanical Strength, Polymerization, Artificial Neural Networks
Article Type: Original Research |
Subject:
Polymerization Enginireeng
Received: 2020/12/21 | Accepted: 2021/06/3 | Published: 2021/09/22
Received: 2020/12/21 | Accepted: 2021/06/3 | Published: 2021/09/22
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