Abstract
Foam-filled tubes (FFTs) have been widely applied in impact protection due to their energy-absorbing properties. However, there are limited studies on the graded FFT, which has a wider range of engineering applications. Therefore this work proposes an experimental investigation of these structures. An additive manufacturing technique is used to produce uniform foam-filled tubes (UFFTs) and graded foam-filled tubes (GFFTs). The deformation mechanism of the interaction between tube and foam, and the gradient effect on the compressive response of FFTs are both revealed. Results show that due to the interaction, FFT has a higher compressive force compared with the sum of tube and foam under the same mass. Moreover, GFFT shows an increasing compressive strength rather than a plateau of UFFT. A predictive model including three parts (tube, foam, and their interaction) is established to predict the load-bearing capacity of GFFTs. Good agreement is achieved between experimental data and the predictive model.
Original language | English |
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Title of host publication | Machine Learning Aided Analysis, Design, and Additive Manufacturing of Functionally Graded Porous Composite Structures |
Publisher | Elsevier |
Pages | 411-430 |
Number of pages | 20 |
ISBN (Electronic) | 9780443154256 |
ISBN (Print) | 9780443154263 |
DOIs | |
State | Published - 1 Jan 2023 |
Keywords
- finite element analysis
- Foam-filled tube
- graded foam
- predictive model
- strain hardening