Study of air void topology of asphalt with focus on air void constrictions – a review and research approach

Schuck, Barbara; Teutsch, Tim; Alber, Stefan; Ressel, Wolfram; Steeb, Holger; Ruf, Matthias

doi:10.1080/14680629.2021.1907215

Cited by 14 publications

(2 citation statements)

References 37 publications

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“…The other pore space can be classified as isolated since they are not directly connected to the connected pores. Determining the total volume of the connected pore space can be measured in a lab with the right equipment, however information about the exact geometry of the connected pore space is required in order to study the infiltratingor permeable-behavior of the PA. A popular and non-destructive method to get highly-resolved pore space details involves taking hundreds of 2D images of a PA sample using a computertomography (CT) scanner and then performing a set of image processing techniques on these 2D images to construct a 3D digital representation of the sample (Schuck et al 2021). This same workflow of imaging, processing, and 3D reconstruction of a so-called digital twin has also been applied to many other areas of application, such as pervious concrete (Jagadeesh et al, 2022), geomaterials (Quinteros & Carraro, 2023), and even green roofs (De-Ville et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…And yet, even though we have found several studies that are based on self-generated code, we find a lack of reproducibility in the research community when it comes to image segmentation applied on PA samples and algorithms used to extract the effective pore space. For example, Schuck et al, 2021 andJagadeesh et al, 2022 documented very clearly their image processing steps, however leave the reader without any code that could be applied to their work. We understand that it is not always the objective of a researcher to openly publish their developed programs and codes, however we see the benefit that code-sharing can have in the research community.…”

Section: Introductionmentioning

confidence: 99%

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Development of a MATLAB-based code for quantification of effective void space in porous pavement

Allen,

Dongmo-Engeland,

Al-Batat

2023

Linköping Electronic Conference Proceedings

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Porous pavement is a well-documented, low-impact stormwater management technique. When it comes to design of the top layer, the amount of void space (porosity) is often of interest as it influences both infiltration and strength of the pavement. Laboratory equipment can be used to measure the porosity of core samples, but when more detail is required, other equipment or methods must be used. One such method is to scan the entire sample using a computer tomography (CT) machine and then perform some image processing techniques on the scanned data to reconstruct the sample digitally. While the workflow of scanning and processing to produce the 3D digital twin of porous pavement is not new and can be in fact done by open-source or commercial software, there are still some parts of the process that deserve a deeper investigation, for example binarization and segmentation algorithms applied to the solid-and-void space and void space, respectively. This is difficult to do with commercial software which operates like a black-box, and there needs to be more open-source codes that are user-friendly, extendable, and competitive to what commercial software can do. This work presents a MATLAB-based code that allows for a deeper investigation of how one can accurately and efficiently quantify the effective (or connected) void space of a porous pavement sample from a 3D digital model. We demonstrate the effect of dataset coarsening, which can be used to reduce the computational intensity of the algorithm while preserving accuracy. The code is publicly available online to allow for reproducible research and the possibility of extensions for increased functionality and complexity.

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