Effects of thermal aging on degradation mechanism of flame retardant-filled ethylene-propylene-diene termonomer compounds

2014 ◽  
Vol 132 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
Changwoon Nah ◽  
Jaeho Oh ◽  
Bismark Mensah ◽  
Kwang-Un Jeong ◽  
Dae Up Ahn ◽  
...  
Keyword(s):  
Flame Retardant ◽  
Thermal Aging ◽  
Degradation Mechanism ◽  
Ethylene Propylene

Degradation of Mechanical and Dielectric Properties of Flame‐Retardant Ethylene Propylene Rubber by Thermal Aging

2020 ◽  
Vol 15 (4) ◽  
pp. 488-495 ◽  
Author(s):  
Hikaru Yamaguchi ◽  
Hiroyuki Ishii ◽  
Naoshi Hirai ◽  
Yoshimichi Ohki
Keyword(s):  
Dielectric Properties ◽  
Flame Retardant ◽  
Thermal Aging ◽  
Ethylene Propylene ◽  
Ethylene Propylene Rubber

scholarly journals Modeling the concentration of carbonyl of ethylene propylene diene monomer during the thermal aging using artificial neural network

2021 ◽  
Vol 03 (01) ◽  
pp. 45-52
Author(s):  
Hadjira Maouz ◽  
◽  
Asma Adda ◽  
Salah Hanini ◽  
◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Thermal Aging ◽  
Training Data ◽  
Ethylene Propylene Diene Monomer ◽  
Ann Model ◽  
Ethylene Propylene ◽  
Artificial Neural ◽  
Input Variables ◽  
Artificial Neural Network Ann

The concentration of carbonyl is one of the most important properties contributing to the detection of the thermal aging of polymer ethylene propylene diene monomer (EPDM). In this publication, an artificial neural network (ANN) model was developed to predict concentration of carbenyl during the thermal aging of EPDM using a database consisting of seven input variables. The best fitting training data was obtained with the architecture of (7 inputs neurons, 10 hidden neurons and 1 output neuron). A Levenberg Marquardt learning (LM) algorithm, hyperbolic tangent transfer function were used at the hidden and output layer respectively. The optimal ANN was obtained with a high correlation coefficient R= 0.995 and a very low root mean square error RMSE = 0.0148 mol/l during the generalization phase. The comparison between the experimental and calculated results show that the ANN model is able of predicted the concentration of carbonyl during the thermal aging of ethylene propylene diene monomer

Flame retardant and the degradation mechanism of high impact polystyrene/Fe-montmorillonite nanocomposites

2008 ◽  
Vol 15 (6) ◽  
pp. 453-458 ◽  
Author(s):  
Qinghong Kong ◽  
Ruibin Lv ◽  
Shijun Zhang
Keyword(s):  
Flame Retardant ◽  
Degradation Mechanism ◽  
High Impact ◽  
High Impact Polystyrene ◽  
Montmorillonite Nanocomposites
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