Progressive Failure Modeling of Composite Materials Leveraging Multiscale Non-destructive Evaluation Data

Progressive Failure Modeling of Composite Materials Leveraging Multiscale Non-destructive Evaluation Data
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ISBN-13 : OCLC:1336500874
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Book Synopsis Progressive Failure Modeling of Composite Materials Leveraging Multiscale Non-destructive Evaluation Data by : Mohammadreza Bahadori

Download or read book Progressive Failure Modeling of Composite Materials Leveraging Multiscale Non-destructive Evaluation Data written by Mohammadreza Bahadori and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The reliable use of fiber reinforced composites (FRCs) in engineering applications depends, among other factors, on the quality of predictions related to their evolving damage state, which further affect design, operation and maintenance conditions. In this context, although a wealth of mechanical behavior, characterization, and failure data and information are available, it is still challenging to understand and predict the failure process in such materials. The main reasons for this deficiency are two. First, the failure processes in FRCs are fairly complex and highly variable given the available manufacturing, processing and usage parameters, which result in unique challenges when monitoring and simulating their performance. Second, despite the several modeling approaches developed using e.g. the Finite Element Analysis (FEA) method, it remains challenging to extend the use of such models across time and lengths scales. This dissertation targets the development of a data-driven modeling approach that is based on a key difference with respect to the previously reported methods on composite damage modeling. Specifically, instead of merely using a number of inputs for material and failure properties based on literature or some experiments, the presented approach targets to create computational workflows that enable the use of nondestructive evaluation data, collected at several scales to generate progressive failure inputs to FEA models, which are first calibrated for their predictions at the material scale and then use similar data to tune aspects of damage initiation and evolution at the structural scale. To demonstrate this approach, a particular class of FRCs is used and a number of analytical and numerical tools are developed or adapted to achieve this type of data-driven FEA modeling. The overall research output, demonstrates that such computational workflows are now possible to provide insights into progressive failure analysis of composite materials, which could impact all phases of design, manufacturing and use of them in applications.


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