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Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites
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| Zeitschriftentitel: | Polymer Composites |
|---|---|
| Personen und Körperschaften: | , , |
| In: | Polymer Composites, 30, 2009, 11, S. 1701-1708 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Wiley
|
| Schlagwörter: |
| author_facet |
Al‐Haik, M.S. Hussaini, M.Y. Rogan, C.S. Al‐Haik, M.S. Hussaini, M.Y. Rogan, C.S. |
|---|---|
| author |
Al‐Haik, M.S. Hussaini, M.Y. Rogan, C.S. |
| spellingShingle |
Al‐Haik, M.S. Hussaini, M.Y. Rogan, C.S. Polymer Composites Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites Materials Chemistry Polymers and Plastics General Chemistry Ceramics and Composites |
| author_sort |
al‐haik, m.s. |
| spelling |
Al‐Haik, M.S. Hussaini, M.Y. Rogan, C.S. 0272-8397 1548-0569 Wiley Materials Chemistry Polymers and Plastics General Chemistry Ceramics and Composites http://dx.doi.org/10.1002/pc.20745 <jats:title>Abstract</jats:title><jats:p>The viscoplastic behavior of a carbon fiber/polymer matrix composite is investigated via different modeling schemes. The first model is phenomenological in nature based on the overstress‐viscoplasticity. The second model utilizes neural networks paradigms. Genetic algorithm‐based strategies are used to prune the proposed neural network. Several optimization algorithms are implemented for training the network. In comparison, the neurocomputational model is found to outperform the phenomenological model. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers</jats:p> Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites Polymer Composites |
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10.1002/pc.20745 |
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Polymer Composites |
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| title |
Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_unstemmed |
Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_full |
Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_fullStr |
Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_full_unstemmed |
Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_short |
Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_sort |
artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| topic |
Materials Chemistry Polymers and Plastics General Chemistry Ceramics and Composites |
| url |
http://dx.doi.org/10.1002/pc.20745 |
| publishDate |
2009 |
| physical |
1701-1708 |
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<jats:title>Abstract</jats:title><jats:p>The viscoplastic behavior of a carbon fiber/polymer matrix composite is investigated via different modeling schemes. The first model is phenomenological in nature based on the overstress‐viscoplasticity. The second model utilizes neural networks paradigms. Genetic algorithm‐based strategies are used to prune the proposed neural network. Several optimization algorithms are implemented for training the network. In comparison, the neurocomputational model is found to outperform the phenomenological model. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers</jats:p> |
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| author | Al‐Haik, M.S., Hussaini, M.Y., Rogan, C.S. |
| author_facet | Al‐Haik, M.S., Hussaini, M.Y., Rogan, C.S., Al‐Haik, M.S., Hussaini, M.Y., Rogan, C.S. |
| author_sort | al‐haik, m.s. |
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| container_title | Polymer Composites |
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| description | <jats:title>Abstract</jats:title><jats:p>The viscoplastic behavior of a carbon fiber/polymer matrix composite is investigated via different modeling schemes. The first model is phenomenological in nature based on the overstress‐viscoplasticity. The second model utilizes neural networks paradigms. Genetic algorithm‐based strategies are used to prune the proposed neural network. Several optimization algorithms are implemented for training the network. In comparison, the neurocomputational model is found to outperform the phenomenological model. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers</jats:p> |
| doi_str_mv | 10.1002/pc.20745 |
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| finc_class_facet | Chemie und Pharmazie, Technik |
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| format_dezi4 | Article |
| format_dezwi2 | Article, E-Article |
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| id | ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTAwMi9wYy4yMDc0NQ |
| imprint | Wiley, 2009 |
| imprint_str_mv | Wiley, 2009 |
| institution | DE-D275, DE-Bn3, DE-Brt1, DE-D161, DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229 |
| issn | 0272-8397, 1548-0569 |
| issn_str_mv | 0272-8397, 1548-0569 |
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| physical | 1701-1708 |
| publishDate | 2009 |
| publishDateSort | 2009 |
| publisher | Wiley |
| record_format | ai |
| recordtype | ai |
| series | Polymer Composites |
| source_id | 49 |
| spelling | Al‐Haik, M.S. Hussaini, M.Y. Rogan, C.S. 0272-8397 1548-0569 Wiley Materials Chemistry Polymers and Plastics General Chemistry Ceramics and Composites http://dx.doi.org/10.1002/pc.20745 <jats:title>Abstract</jats:title><jats:p>The viscoplastic behavior of a carbon fiber/polymer matrix composite is investigated via different modeling schemes. The first model is phenomenological in nature based on the overstress‐viscoplasticity. The second model utilizes neural networks paradigms. Genetic algorithm‐based strategies are used to prune the proposed neural network. Several optimization algorithms are implemented for training the network. In comparison, the neurocomputational model is found to outperform the phenomenological model. POLYM. COMPOS., 2009. © 2008 Society of Plastics Engineers</jats:p> Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites Polymer Composites |
| spellingShingle | Al‐Haik, M.S., Hussaini, M.Y., Rogan, C.S., Polymer Composites, Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites, Materials Chemistry, Polymers and Plastics, General Chemistry, Ceramics and Composites |
| title | Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_full | Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_fullStr | Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_full_unstemmed | Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_short | Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_sort | artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| title_unstemmed | Artificial intelligence techniques in simulation of viscoplasticity of polymeric composites |
| topic | Materials Chemistry, Polymers and Plastics, General Chemistry, Ceramics and Composites |
| url | http://dx.doi.org/10.1002/pc.20745 |