| Autor: |
Yutai Su, Percy M. Iyela, Jiaqi Zhu, Xujiang Chao, Shaobo Kang, Xu Long |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Materials & Design, Vol 244, Iss , Pp 113159- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
0264-1275 |
| DOI: |
10.1016/j.matdes.2024.113159 |
| Popis: |
This paper presents an innovative numerical modeling framework capable of generating highly realistic 3D mesoscale multi-phase concrete models with unprecedented efficiency and accuracy. Addressing a significant wide range in aggregate volume fraction (0 to 80%) and featuring rapid model generation capabilities, our framework marks a breakthrough in reducing computational time—achieving simulations of 1 million elements within mere 30 s on readily available hardware. By analyzing randomly generated concrete samples across varying compositions, our algorithm can provide deep mesoscopic insights into their compressive properties, validated against a wide array of experimental results. Additionally, our comprehensive analytical model sheds light on the intricate roles of aggregate volume fraction and porosity, enhancing understanding of the meso-scale compressive behavior. We also make the source code available on GitHub, offering a valuable tool for the engineering and research community to optimize concrete material design and performance. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full Text from ScienceDirect