Dissertation
Data-driven computational modeling of plasticity-induced damage effects
Doctor of Philosophy (Ph.D.), Drexel University
Jun 2022
DOI:
https://doi.org/10.17918/00001301
Abstract
Computational modeling of damage is an important tool in understanding and predicting failure in engineering applications. Current modeling and simulation techniques often struggle to identify two aspects of failure which are of interest, including the location of damage onset and the prediction of damage evolution. There are multiple factors which cause this deficiency and include material, geometrical and loading aspects, among others. In this context, the use of Non-Destructive Evaluation (NDE) data has the potential to provide damage information into computational workflows. Specifically, recent advancements in sensing methods and data processing techniques have made possible the acquisition of high temporal and spatial resolution data related to damage. This dissertation seeks, therefore, to leverage these advancements and demonstrate numerical workflows which are based on using NDE data into Finite Element Models (FEMs) to improve aspects of damage modeling. To demonstrate this approach, Acoustic Emission (AE) data is first used to define a damage parameter within a plasticity FEM, which is shown to succeed in inducing deformation localizations that agree with related experimental observations. In addition, Digital Image Correlation (DIC) deformation data is used to further refine such data-defined damage parameter and assist also in the modeling of the characteristics of deformation localizations in specified regions of the model. Finally, full field, surface DIC data is incorporated directly into a custom-built, three-dimensional, non-local FEM model to assist in the prediction of onset, characteristics and evolution of plasticity-induced damage, originating in deformation localization sites observed experimentally. Details on the ways that such data-driven computational modeling techniques could increase the fidelity of and the confidence in failure prediction models are discussed.
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Details
- Title
- Data-driven computational modeling of plasticity-induced damage effects
- Creators
- Sara Elizabeth Schlenker
- Contributors
- Antonios Kontsos (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xx, 164 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- College of Engineering (1970-2026); Mechanical Engineering (and Mechanics) (1970-2026); Drexel University
- Other Identifier
- 991018528111504721