| About this Abstract |
| Meeting |
2024 ASC Technical Conference, US-Japan Joint Symposium, D30 Meeting
|
| Symposium
|
2024 ASC Technical Conference, US-Japan Joint Symposium, D30 Meeting
|
| Presentation Title |
Understanding the Loading Memory of Composites Using Ultrasonic Inspection |
| Author(s) |
Sourav Banerjee, Hossain Ahmed, Asef Ishraq Sadaf |
| On-Site Speaker (Planned) |
Sourav Banerjee |
| Abstract Scope |
Just like history is stored in the human brain as memory, composite materials also have an observable means to store the loading histories. We lack the fundamental understanding of microphysics, in part, because we lack the fundamental ability to characterize the material to differentiate the loading memory effect. To understand how the material memory could be interrogated, in this article a design of experiment is created where two different set of materials obtained from one composite article manufactured are subjected to different sequency of loading. Set one was first loaded under mechanical fatigue and then the same specimens were subjected to thermal fatigue. Set two was first subjected to thermal fatigue and then the samples were mechanically fatigued. It is traditionally known that both sets at the end of both the loading cycles must have the same material state. However, we hypothesize that the material state at the end of mechanical loading followed by thermal loading is different than thermal loading followed by mechanical loading. To prove the hypothesis chronological ultrasonic imaging and physics driven understanding of wave features is proposed followed by data driven understanding with machine learning and deep neural network. It was found that the material state was indeed different for two different set, which indicates that materials has the means to store the memory of loading information. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |