Abstract
In thermoplastic composite joints with a circular ultrasonic spot weld, the damage growth is located at the interface between the joined components. This means that any damage in these joints is invisible from the outside. This experimental study compares three different in-situ methods to measure the damage growth indirectly. The motivation lies in the potential benefits of using multi-spot welded joints for increased damage tolerance and the need to prove the damage arresting and damage progression behaviour for certification. The current study focused on measuring the damage in single-spot welded Single Lap Shear (SLS) joints during fatigue test with the global specimen compliance, the local out-of-plane displacement and the local strain on the surface. Digital Image Correlation (DIC) measurements were used to obtain the local quantities. The results showed that the local quantities are better suited to obtain detailed information on the damage state. The local surface strain showed more distinct features that facilitate the recognition of damage locations. The benefits and challenges of all methods are discussed as well as the difference in the level of detail, generalization and the prior knowledge necessary to obtain the damage state.
Original language | English |
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Article number | 100152 |
Journal | Journal of Advanced Joining Processes |
Volume | 8 |
DOIs | |
Publication status | Published - 2023 |
Keywords
- Damage growth
- Digital image correlation (DIC)
- Thermoplastic composites
- Ultrasonic spot welding
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Dive into the research topics of 'To measure is to know: Evaluating indirect measurement techniques for observing the damage tolerance behaviour of spot welded thermoplastic composites'. Together they form a unique fingerprint.Datasets
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Data underlying the publication: Measuring fatigue damage growth of spot welded thermoplastic composites using Digital Image Correlation.
Rans, C. D. (Creator), Giovani Pereira Castro, S. (Creator), Fernandez Villegas, I. (Creator) & Smeets, E. T. B. (Creator), TU Delft - 4TU.ResearchData, 31 Dec 2022
DOI: 10.4121/21667796
Dataset/Software: Dataset