Date of Award

2024-05-01

Degree Name

Master of Science

Department

Mechanical Engineering

Advisor(s)

Tzu-Liang Tseng

Second Advisor

Yirong Lin

Abstract

The contribution of the research made is derived into two sections. The first topic discusses the prediction modeling of Foreign Object debris (FOd) impact on aircraft structures through the use of digital engineering. The program used in this project is Ansys Explicit Dynamics to evaluate the stress and strain caused by the initial conditions of flight trajectory and impact created from FOd found inside of aircraft structures. The prediction modeling consists of creating a repetition of simulations with different FOds to evaluate the damage created to subsystems of the wing bay such as the fuel system and internal structures. The FOds used for this analysis are washers, fasteners, & plastic caps. By defining the solutions from the explicit dynamic environment, it can be concluded that such foreign objects (FO) can or cannot cause failure to the aircraft. The development of these simulations would be exported to Unity to create a model for in-depth analysis of impact and location of FOd after flight trajectory. With this research, it would assist engineers in how to prevent a major accident from happening while an aircraft is operating. The second topic focuses on the optimization of scanning parameters of Non-Destructive Equipment (NDE) and the development of different intentional defects on manufactured curved carbon fiber composites. Composites are made of carbon fiber and epoxy resin with placement of washers and teflon pieces layer by layer through compression pressing and molded vacuum bagging. The technique used for NDE is ultrasonic testing and the transducer used was a phased array probe and the NDE equipment was an Omniscanner SX. The use of this technique allows us to scan the composite row by row to detect handmade defects on composites at different locations. The Omniscanner SX would allow us to obtain high resolution scans for present research. By having different scans, an AI model is created and trained to automatically detect such defects at different depths and location on composites.

Language

en

Provenance

Received from ProQuest

File Size

38 p.

File Format

application/pdf

Rights Holder

Luis Eduardo Rodriguez

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