Prediction of Specific Volume of Polypropylene at High Cooling Rates by Artificial Neural Networks

2021 ◽  
Vol 60 (40) ◽  
pp. 14434-14446
Author(s):  
Jian Wang ◽  
Christian Hopmann ◽  
Ben Liu ◽  
Yannik Lockner
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Specific Volume ◽  
Cooling Rates ◽  
Artificial Neural ◽  
High Cooling Rates

Predicting the effect of cooling rate on the mechanical properties of glass fiber–polypropylene composites using artificial neural networks

2018 ◽  
Vol 32 (9) ◽  
pp. 1268-1281 ◽  
Author(s):  
Mohammed S Kabbani ◽  
Hany A El Kadi
Keyword(s):  
Mechanical Properties ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Glass Fiber ◽  
Cooling Rate ◽  
Cooling Rates ◽  
Polypropylene Composites ◽  
Unidirectional Glass ◽  
Static Tensile ◽  
Artificial Neural

Properties of thermoplastic-based composites are affected by their processing conditions, and understanding their behavior under these different conditions is of most importance. The current study aims to predict the static tensile behavior of unidirectional glass fiber–polypropylene composite materials processed under different cooling rates using artificial neural networks (ANNs). Stress–strain relations for the material processed under various cooling rates were predicted using ANN. For all the cases investigated, the modulus of elasticity was predicted with a minimum accuracy of 97%, while the ultimate strain was predicted, in most cases, with a minimum accuracy of 90%. These predictions indicate that ANN can be successfully used to predict the mechanical properties of unidirectional composites manufactured under different cooling rates. This method allows users to predict the behavior of the material under cooling rate conditions for which no experimental data are available.

FUTURE OF ARTIFICIAL NEURAL NETWORKS IN SPACE EXPLORATION AND SPACE ENGINEERING

2018 ◽  
pp. 6-11
Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Space Exploration ◽  
Artificial Neural

Bankruptcy Prediction Models: A Bet on Artificial Neural Networks

2012 ◽  
Vol 3 (2) ◽  
pp. 48-50
Author(s):  
Ana Isabel Velasco Fernández ◽  
◽  
Ricardo José Rejas Muslera ◽  
Juan Padilla Fernández-Vega ◽  
María Isabel Cepeda González
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Artificial Neural
Sign in / Sign up

Export Citation Format

Share Document