Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks

A Master of Science Thesis in Mechatronics Submitted by Mohamed Al Assadi Entitled, "Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks," September 2009. Available are both Soft and Hard Copies of the Thesis.

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Al Assadi, Mohamed (author)
التنسيق: doctoralThesis
منشور في: 2009
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/132
الوسوم: إضافة وسم
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author Al Assadi, Mohamed
author_facet Al Assadi, Mohamed
author_role author
dc.contributor.none.fl_str_mv El Kadi, Hany
Deiab, Ibrahim
dc.creator.none.fl_str_mv Al Assadi, Mohamed
dc.date.none.fl_str_mv 2009-09
2011-03-10T12:43:42Z
2011-03-10T12:43:42Z
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.identifier.none.fl_str_mv 35.232-2009.05
http://hdl.handle.net/11073/132
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Materials
Fatigue
Testing
Neural networks (Computer science)
Fibrous composites
Materials
dc.title.none.fl_str_mv Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science Thesis in Mechatronics Submitted by Mohamed Al Assadi Entitled, "Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks," September 2009. Available are both Soft and Hard Copies of the Thesis.
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network_acronym_str aus
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oai_identifier_str oai:repository.aus.edu:11073/132
publishDate 2009
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spelling Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural NetworksAl Assadi, MohamedMaterialsFatigueTestingNeural networks (Computer science)Fibrous compositesMaterialsA Master of Science Thesis in Mechatronics Submitted by Mohamed Al Assadi Entitled, "Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks," September 2009. Available are both Soft and Hard Copies of the Thesis.Artificial Neural Networks (ANN) have recently been used in modeling the mechanical behavior of fiberreinforced composite materials. ANN have also been successfully used in predicting the fatigue behavior of a certain material under loading conditions other than those used for training. The use of ANN in predicting fatigue failure in composites would be of great value if one could predict the failure of materials other than those used for training the network. This would allow developers of new materials to estimate in advance the fatigue properties of their material. In this work, experimental fatigue data obtained for certain fiber-reinforced composite materials is used to predict the cyclic behavior of a composite made of another material. The effect of the various mechanical properties on the training of the network is evaluated to obtain the most suitable combination of properties resulting in the best fatigue life prediction. The resilient back-propagation with 10 to 20 neurons depending on the input parameters resulted in accurate prediction when compared to experimental ones. An introduction to the use of Polynomial classifiers (PC) to predict the fatigue behavior is also presented. Using a first order PC with additional higher order terms gave good results when compared to experimental ones.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR)El Kadi, HanyDeiab, Ibrahim2011-03-10T12:43:42Z2011-03-10T12:43:42Z2009-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdfapplication/pdf35.232-2009.05http://hdl.handle.net/11073/132en_USoai:repository.aus.edu:11073/1322025-06-26T12:20:59Z
spellingShingle Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
Al Assadi, Mohamed
Materials
Fatigue
Testing
Neural networks (Computer science)
Fibrous composites
Materials
status_str publishedVersion
title Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
title_full Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
title_fullStr Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
title_full_unstemmed Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
title_short Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
title_sort Predicting the Fatigue Failure of Fiber Reinforced Composite Materials Using Artificial Neural Networks
topic Materials
Fatigue
Testing
Neural networks (Computer science)
Fibrous composites
Materials
url http://hdl.handle.net/11073/132