Issue |
E3S Web Conf.
Volume 237, 2021
3rd International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2020)
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|
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Article Number | 03007 | |
Number of page(s) | 8 | |
Section | Architecture Science and Civil Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202123703007 | |
Published online | 09 February 2021 |
Study on compatibility optimization of resin-based permeable pavement bricks
1
Key Laboratory of Advanced Civil Engineering Materials of Ministry of Education, Tongji University, Shanghai, China
2
CCCC (Shanghai) Harbor Engineering Design and Research Institute Co., Ltd, Shanghai, China
* Corresponding author: xiong.zhang@vip.sina.com
The permeable pavement plays an important role in mitigating urban flooding. In order to explore the relationship between materials and properties to better guide the practical production of resin-based permeable bricks, 10 kinds of representative aggregate samples with obvious different characteristics were selected for preparation. In this study, Image Pro Plus was used to binarize the acquired image pictures of the aggregate so as to obtain particle group characteristic parameters. The properties and porosity of the brick were measured in order to describe the influence of the material. The results are as follows. The relative standard deviation of aggregate and the amount of cementing material are negatively related to the compressive strength of permeable bricks, but positively related to water permeability and filtration performance. The roundness and roughness of the aggregate are the opposite. Furthermore, the porosity of the permeable brick is the essential reason for this phenomenon, that is, as the porosity increase, the compressive strength decrease, but the water permeability and the filtration performance become better. In the end, an optimization method for the compatibility of resin-based pavement permeable bricks was proposed through reflecting all factors in a two-bit flat grayscale image which can be applied in performance prediction and guidance of material selection.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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