Abstract
Closed-cell Al foam is widely utilized in high-temperature environments due to its high strength-to-weight ratio and considerable energy absorption capability. However, the mechanical properties depend on temperature and mesostructure. In this paper, the compressive responses of Al foams at temperatures ranging from 25 ℃ to 600 ℃ are investigated by experimental tests and two types of high-fidelity finite element simulations, including the X-ray computed tomography (CT) reconstructed model and Voronoi model. A deep learning approach is employed to remove tiny pores of CT slices, simplifying geometry features and improving the computational efficiency of the CT reconstructed model. A novel improved Voronoi model with high accuracy is proposed, considering the nonuniform distribution of cell wall thickness in actual closed-cell Al foams. A temperature-depend macro constitutive model is established and validated through the experimental and numerical results. This work reveals the influence mechanism of temperature and mesostructure on the mechanical responses of Al foams, and exhibits significant potential for the application of Al foams in high temperature environment.
| Original language | English |
|---|---|
| Article number | 109344 |
| Journal | International Journal of Mechanical Sciences |
| Volume | 275 |
| DOIs | |
| Publication status | Published - 1 Aug 2024 |
Keywords
- Closed-cell aluminum foam
- Deep learning approach
- Improved Voronoi model
- Mechanical performance
- Temperature effect
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