Modeling of the viscoelastic properties of thermoset vinyl ester nanocomposite using artificial neural network
| Autor: | Moh'd Sami Ashhab, Mohammad A. Omari, Ahmad Almagableh, Igor Sevostianov, Ahmad Bani Yaseen |
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| Rok vydání: | 2020 |
| Předmět: |
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Nanocomposite Materials science Artificial neural network Mechanical Engineering General Engineering Vinyl ester Thermosetting polymer 02 engineering and technology 021001 nanoscience & nanotechnology Viscoelasticity 020303 mechanical engineering & transports 0203 mechanical engineering Mechanics of Materials General Materials Science Graphite Composite material 0210 nano-technology |
| Zdroj: | International Journal of Engineering Science. 150:103242 |
| ISSN: | 0020-7225 |
| Popis: | In the present work, we use artificial neural network (ANN) approach to develop a tool for prediction of the effective viscoelastic properties - storage and loss moduli - of vinyl ester reinforced with graphite nanoplatelets. Explicit results are obtained in terms of the constituents’ volume fractions, temperature, and loading frequency. The experimental data for ANN training and testing ware obtained using a Dynamic Mechanical Analyzer (DMA) and contains 153 data sets; the training and testing sets consisted of randomly selected 131 and 22 sets, respectively. The good accuracy of the model demonstrates that ANN is efficient for predicting viscoelastic properties in terms of three independent parameters. |
| Databáze: | OpenAIRE |
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