Application study on conditional generative adversarial network (cGAN) to generate ballast particles for discrete element method simulation
Understanding ballast particle morphology is important for evaluating the load-bearing capacity of ballasted track foundations using numerical simulations. Although several methods, such as digital imaging, laser scanning, and computed tomography scans, are widely used to capture ballast morphology,...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Case Studies in Construction Materials |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214509525007855 |
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