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Impact of Pervious Concrete Porosity on Permeability by 3D Image Analysis

机译：通过3D图像分析透水混凝土孔隙率对渗透率的影响

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Pervious concrete is an effective solution to manage storm water runoff because of its ability to allow permeation of huge quantities of water. The objective of the present study is to define relationships between formulation parameters (like aggregate sizes and paste quantities) and final properties of pervious concrete (permeability, mechanical resistance, and porosity) through 3D images obtained by micro-tomography. Through an original experimental program, we attempt to determine the permeability of different pervious concretes directly from microstructural parameters extracted from 3D images. We exploit mathematical morphology tools, such as two-point correlation functions to access specific surface area, porosity value, and granulometric distribution of porosity. The permeability of pervious concrete is finally estimated by solving the Stokes equation on the 3D pore network numerically with finite elements. Permeability values obtained from 2D images and 3D acquisitions with water permeability measured in laboratory are then compared.
机译：渗透混凝土由于能够渗透大量水，因此是管理雨水径流的有效解决方案。本研究的目的是通过显微断层扫描获得的3D图像来定义配方参数（如骨料大小和浆糊量）与透水混凝土的最终性能（渗透性，机械强度和孔隙率）之间的关系。通过原始的实验程序，我们尝试直接从3D图像中提取的微观结构参数来确定不同透水混凝土的渗透率。我们利用数学形态学工具，例如两点相关函数来访问比表面积，孔隙率值和孔隙率的粒度分布。最终，通过用有限元对3D孔网络上的Stokes方程进行数值求解，来估算透水混凝土的渗透性。然后比较从2D图像和3D采集的渗透率值，以及在实验室中测量的水渗透率。

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