Modeling method of concrete material at mesoscale with refined aggregate shapes based on image recognition
| Autor: | Zeren Jin, Zhiyi Yin, Xin Ruan, Zichao Pan, Yue Li |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Aggregate (composite)
Aspect ratio Computer simulation Computer science business.industry 0211 other engineering and technologies 020101 civil engineering 02 engineering and technology Building and Construction Surface finish 0201 civil engineering Distribution function Joint probability distribution 021105 building & construction Particle General Materials Science Computer vision Particle size Artificial intelligence business Civil and Structural Engineering |
| Zdroj: | Construction and Building Materials. 204:562-575 |
| ISSN: | 0950-0618 |
| DOI: | 10.1016/j.conbuildmat.2019.01.157 |
| Popis: | Numerical simulation of concrete materials has become widely accepted, and modeling the aggregate based on the actual material is critical. However, the particle shape control still needs to be improved. In this paper, a refined aggregate modeling method is proposed using statistical rules based on image recognition. The geometrical data of 4407 real particles are extracted from the specimen cross-sections, and the joint probability distributions of particle size and aspect ratio are investigated. The statistical rules are remarkable and stable. The recommended distribution functions for geometrical parameters are provided to guide the simulation. The aggregate model is refined to a three-level framework based on the particle size, aspect ratio, and surface texture, and a corresponding concrete modeling method is also proposed. To investigate the method effect, numerical experiments on 800 models are conducted. The results show that it is necessary to precisely control the particle aspect ratio for accurate simulation. |
| Databáze: | OpenAIRE |
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