Porosity And Permeability Evaluation Of Pervious Concrete Using 3D X-Ray Computed Tomography A. Jagadeesh and G. P. Ong National University of Singapore Y. M. Su National Kaohsiung University of Science and Technology

Introduction Porous pavements are used on highways & streets to minimize storm-water run-off, wet weather accidents & tire/road noise Increase in intrinsic permeability, wet pavement skid resistance & acoustic absorption coefficients 80% reduction in wet-weather accidents [Association of Japan Highway, 1996] Tire/road noise reduction of 3 to 5 dB [Berengier et al., 1997]

Pervious Concrete Special class of hydraulic cement concrete proportioned with sufficient interconnected voids that result in highly-permeable material [ACI, 2010] Isolated voids is minimal due to use of uniform single-size coarse aggregates in mixture Increased use as functional performance layers necessitates understanding of pore network properties and their relationships

X-Ray Computed Tomography in Pavement Research: Literature Review Limited studies in literature: Fluid flow simulation model for hot-mix asphalt using X-ray CT scan and Lattice Boltzmann method [Kutay et al., 2007] Permeability tensor coefficients for asphalt using fluid flow micro-simulation [Masad et al., 2007] Pore network parameters such as porosity, tortuosity & pore size determination [Coleri et al., 2012; Kuang et al., 2015, Biligiri, 2017] Digital image processing thresholds [Masad et al., 1999; Abera et al., 2017] High-resolution industrial X-ray CT is capable of producing detailed 3D imagery of Asphalt cores (Source: University of Texas at Austin)

Research Motivation & Objectives Examine the use of medical-grade 3D X-ray computed tomography (CT) to determine effective porosity & permeability of pervious concrete Examine performance of different segmentation threshold algorithms used in practice and research Medical-grade vs. Industrial-grade micro-CT [du Plessis et al., 2016] ↑ X-ray voltages with industrial CT systems ⇒ ↑ penetrating power ⇒ ↑ image quality for dense objects ↓ cost and ↓scan time for medical-grade X-ray CT Medical CT scans produce useful data in significantly reduced times especially for large no. of samples and moderate resolution Ability to scan larger objects than typical microCT systems ↓ data set sizes ⇒ faster analysis with ↓ computing power

Pervious Concrete Mixture Nominal Maximum Aggregate Size (NMAS) Materials Two pervious concrete mixtures (P1 & P2) were produced in laboratory: ASTM Type I cement as binding agent Superplasticizer of 0.5% by weight of cement added to improve pervious concrete workability Pervious Concrete Mixture Nominal Maximum Aggregate Size (NMAS) P1 9.5 mm P2 12.5 mm Note: Specific gravity and percent absorption of aggregates are 2.64 and 1.35% respectively

X-Ray CT Scan Somatom Emotion 16-channel X-Ray CT scanner with 110kV energy was used in this study A total of 300 section images of pixel size 1024 x 1024 were obtained at the interval of 0.7mm. Voxel size of about 300 mm (cf. 150 mm for micro-CT) [Chandraparra & Biligiri, 2018] Sample size of 150 mm diameter and 250 mm thickness scanned (cf. ~100 mm thickness for micro-CT) [Chandraparra & Biligiri, 2018] Somatom Emotion from Siemens with sample 2D slice raw image of pervious concrete sample for P1 (left) and P2 (right)

Thresholding Algorithms Thresholding of air voids based on grey-scale intensities was performed Otsu bi-level and tri-level algorithm [Otsu 1979]: Volumetric-based global minima algorithm [Zelelew & Papagiannakis, 2011]: Intraclass variance for material 1 Intraclass variance for material 2 Grey-scale histogram Experimental air void content Computed air void content given threshold value Reconstructed 3D model (right) from original CT 3D model before thresholding (left)

Threshold for Pervious Mixture P1 Threshold for Pervious Mixture P2 Thresholding Results Air-void thresholds for the three algorithms for this study: Algorithm Threshold for Pervious Mixture P1 Threshold for Pervious Mixture P2 Otsu bi-level 1678 1792 Otsu tri-level 1471 1168 Volumetric 1647 1694 (a) Original image (b) Otsu’s bi-level (c) Otsu’s tri-level (d) Volumetric method

Constant Head Permeability Test Permeability of pervious concrete samples was measured using the Association of Japan Highway (1996) standards Permeability coefficient kT: Percentage of inter-connected air voids or effective porosity: Height of specimen Volume of outflow water Constant head Cross sectional area Time taken Actual setup of constant head permeameter

Permeability Simulation Model Fluid behavior in porous media can be modelled using the Navier Stokes equations & k-ε turbulence equations. Standard properties of water at 25°C are adopted in this study. Performed for P1 and P2 reconstructed volumes for the three algorithms (Otsu bi-level, Otsu tri-level & volumetric) Continuity equation: Momentum equation with k-e turbulence: Sample simulation of fluid flow over pore network within pervious concrete specimen

Discharge Characteristics Experiments show that ↑NMAS ⇒ ↑ dimensional geometry of pore network ⇒ ↑ vertical & horizontal permeability of pervious concrete k-values: Otsu bi-level method > Volumetric method >> Otsu tri-level method Error in k values: Volumetric method (17% to 28%) < Otsu bi-level method (22% to 56%) < Otsu tri-level method (45% to 56%)

Discharge Characteristics Permeability anisotropy ratio: ratio of kv to kh values Tortuosity: ratio of actual length of fluid flow to shortest distance from top to bottom of sample ↑ in air void threshold ⇒ opening of new interconnected air void channels ⇒ ↓ in tortuosity value ⇒ ↑ in permeability values Similar findings to literature [Chandrappa & Biligiri 2017]

Discharge Characteristics Velocity streamlines obtained from the simulation model Reduced velocities were observed in the smaller pore channels and higher velocities at the larger pore channels. Pressure losses in porous domain observed due to inertial effects and geometric features of pore network Velocity streamlines of pervious concrete sample (obtained from permeability simulations)

Volumetric Characteristics ↑ in interconnected voids + ↓ in isolated voids ⇒ ↑ in permeability values NMAS has a significant effect on permeability despite having the same porosity due to varied pore network structure Error in effective porosity values: Volumetric method (<1%) < Otsu bi-level method (~5%) < Otsu tri-level method (25% to 35%)

Conclusion Volumetric segmentation algorithm is considered to be predicting the permeability and effective porosity more closely to the experimental results compared to the Otsu’s bi-level and tri-level algorithms Aggregate size and tortuosity have a significant influence on the permeability, despite having the same effective porosity. Overall, it is expected that the present research will help to understand the pore network characteristics of pervious concrete using non-destructive evaluation and digital image processing.

University Town, National University of Singapore