Neural Networks in Composite Materials

Artificial neural networks (ANN) can provide new insight into the study of composite materials and can normally be combined with other artificial intelligence tools such as expert system, genetic algorithm, and fuzzy logic. Because research on this field is very new, there is only a limited amount of published literature on the subject.
Compiling information from diverse sources, Composite Materials Technology: Neural Network Applications fills the void in knowledge of these important networks, covering composite mechanics, materials characterization, product design, and other important aspects of polymer matrix composites.

This book examines artificial neural networks (ANNs) and their applications in various fields.

Fatigue has long been recognized as a mechanism that can provoke catastrophic material failure in structural applications and researchers are now turning to the development of prediction tools in order to reduce the cost of determining design criteria for any new material. Fatigue of Fiber-reinforced Composites explains these highly scientific subjects in a simple yet thorough way.

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Fatigue has long been recognized as a mechanism that can provoke catastrophic material failure in structural applications and researchers are now turning to the development of prediction tools in order to reduce the cost of determining design criteria for any new material. Fatigue of Fiber-reinforced Composites explains these highly scientific subjects in a simple yet thorough way.