ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at email@example.com.
- 3 Public
- Mechanical engineering
- 2 Machine Learning
- 1 Aerospace engineering
- 1 Biaxial Fatigue
- 1 Biaxial fatigue
- 1 Bridge Scour
- 1 Buckypaper
- 1 Carbon Fiber Composite
- 1 Crack growth
- 1 Damage Localization
- 1 Damage Prognosis
- 1 Material Characterization
- 1 Multifunctional
- 1 Overload
- 1 Prognostics
- 1 Self sensing
- 1 Structural Health Monitoring
- 1 System Health Management
- 1 Ultrasonic Guided Wave
Multiaxial mechanical fatigue of heterogeneous materials has been a significant cause of concern in the aerospace, civil and automobile industries for decades, limiting the service life of structural components while increasing time and costs associated with inspection and maintenance. Fiber reinforced composites and light-weight aluminum alloys are widely used in aerospace structures that require high specific strength and fatigue resistance. However, studying the fundamental crack growth behavior at the micro- and macroscale as a function of loading history is essential to accurately predict the residual fatigue life of components and achieve damage tolerant designs. The issue of mechanical fatigue can …
- Datta, Siddhant, Chattopadhyay, Aditi, Liu, Yongming, et al.
- Created Date
This dissertation presents the development of structural health monitoring and prognostic health management methodologies for complex structures and systems in the field of mechanical engineering. To overcome various challenges historically associated with complex structures and systems such as complicated sensing mechanisms, noisy information, and large-size datasets, a hybrid monitoring framework comprising of solid mechanics concepts and data mining technologies is developed. In such a framework, the solid mechanics simulations provide additional intuitions to data mining techniques reducing the dependence of accuracy on the training set, while the data mining approaches fuse and interpret information from the targeted system enabling the …
- Li, Guoyi, Chattopadhyay, Aditi, Mignolet, Marc, et al.
- Created Date
There is a concerted effort in developing robust systems health monitoring/management (SHM) technology as a means to reduce the life cycle costs, improve availability, extend life and minimize downtime of various platforms including aerospace and civil infrastructure. The implementation of a robust SHM system requires a collaborative effort in a variety of areas such as sensor development, damage detection and localization, physics based models, and prognosis models for residual useful life (RUL) estimation. Damage localization and prediction is further complicated by geometric, material, loading, and environmental variabilities. Therefore, it is essential to develop robust SHM methodologies by taking into account …
- Neerukatti, Rajesh Kumar, Chattopadhyay, Aditi, Jiang, Hanqing, et al.
- Created Date