Image analysis for detecting aggregate gradation in asphalt mixture from planar images

Bruno, Loredana; Parla, Giuseppe; Celauro, Clara

doi:10.1016/j.conbuildmat.2011.08.007

Cited by 87 publications

(37 citation statements)

References 15 publications

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“…Similar to a laser scanner [26] or digital imaging processing [27,28], used respectively for texture characteristics and sample strain evaluation, spectroradiometrical laboratory measurements can be computed to analyze asphalt physical properties for remote sensing applications.…”

Section: Laboratory Datamentioning

confidence: 99%

“…It is only after aging and degradation processes, causing the loss of the bitumen component and the outcropping of aggregate, that the reflectance values slightly increase and the absorption peaks related to mineralogical characteristics of outcropping aggregate fragments appear. Therefore, asphalt color can be used to identify variations from quality requirements [21][22][23][24][25][26][27][28][29].…”

Section: Field Data Computationmentioning

confidence: 99%

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Integration of Field and Laboratory Spectral Data with Multi-Resolution Remote Sensed Imagery for Asphalt Surface Differentiation

et al. 2014

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Abstract:The ability to classify asphalt surfaces is an important goal for the selection of suitable non-variant targets as pseudo-invariant targets during the calibration/validation of remotely-sensed images. In addition, the possibility to recognize different types of asphalt surfaces on the images can help optimize road network management. This paper presents a multi-resolution study to improve asphalt surface differentiation using field spectroradiometric data, laboratory analysis and remote sensing imagery. Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) airborne data and multispectral images, such as Quickbird and Ikonos, were used. From scatter plots obtained by field data using λ = 460 and 740 nm, referring to MIVIS Bands 2 and 16 and Quickbird and Ikonos Bands 1 and 4, pixels corresponding to asphalt covering were identified, and the slope of their interpolation lines, assumed as asphalt lines, was calculated. These slopes, used as threshold values in the Spectral Angle Mapper (SAM) classifier, obtained an overall accuracy of 95% for Ikonos, 98% for Quickbird and 93% for MIVIS. Laboratory investigations confirm the existence of the asphalt line also for new asphalts, too.

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Section: Laboratory Datamentioning

confidence: 99%

Section: Field Data Computationmentioning

confidence: 99%

Integration of Field and Laboratory Spectral Data with Multi-Resolution Remote Sensed Imagery for Asphalt Surface Differentiation

et al. 2014

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“…It was found that two specimens (six sections) was sufficient to satisfactorily capture the actual gradation of coarse aggregate. Bruno et al estimated mixture gradation using the length of the minor axis of the ellipse that had the same normalized second central moments as the aggregate [6]. The average gradation curve obtained from 22 planar slices was compared with the laboratory gradation.…”

Section: Introductionmentioning

confidence: 99%

“…The solvent extraction method or the ignition oven method is often used to measure segregation. However, these laborious and time-consuming tests involve a specially-equipped laboratory, as well as the use of solvents hazardous to workers' health [6].…”

Section: Introductionmentioning

confidence: 99%

Three Dimensional Digital Sieving of Asphalt Mixture Based on X-ray Computed Tomography

Kutay

2017

Applied Sciences

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Abstract:In order to perform three-dimensional digital sieving based on X-ray computed tomography images, the definition of digital sieve size (DSS) was proposed, which was defined as the minimum length of the minimum bounding squares of all possible orthographic projections of an aggregate. The corresponding program was developed to reconstruct aggregate structure and to obtain DSS. Laboratory experiments consisting of epoxy-filled aggregate specimens were conducted to investigate the difference between mechanical sieve analysis and the digital sieving technique. It was suggested that concave surface of aggregate was the possible reason for the disparity between DSS and mechanical sieve size. A comparison between DSS and equivalent diameter was also performed. Moreover, the digital sieving technique was adopted to evaluate the gradation of stone mastic asphalt mixtures. The results showed that the closest proximity of the laboratory gradation curve was achieved by calibrated DSS, among gradation curves based on calibrated DSS, un-calibrated DSS and equivalent diameter.

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“…According to Bruno et al (2012), the mechanical properties of asphalt mixture strongly depends on the gradation of the aggregate that forms the mineral skeleton of the mixture and the presence of granular gaps improves mixture compatibility. Rutting is one of the major distresses of flexible pavement.…”

Section: Introductionmentioning

confidence: 99%

Effects of Mixture Aging on the Performance of Gap Graded Asphalt Mix Experimented on the Malaysian North-South Expressway

Hamzah¹,

Jamaluddin²,

Rosli³

et al. 2017

dtetr

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Gap Graded Asphalt (GGA) is a new type of asphalt mix developed by OPUS International. It has been successfully experimented on several trial sites along the Malaysian North South Expressway. GGA differs from ordinary dense asphalt by incorporating a high proportion of coarse aggregate, filler and bitumen. The high coarse aggregate structure helps to build a stable matrix enabling it to better resist permanent deformation. The main objective of this study is to investigate the effects of mixture aging on GGA mix properties and compare the mixture performance with porous asphalt (PA), and asphaltic concrete (AC). The performance tests conducted in this study includes indirect tensile strength (ITS), resilient modulus, abrasion loss, permeability, skid resistance and rutting. A One-Way ANOVA statistical analysis was used to analyze the results. From the results, aging duration has a statistically significant effect on the resilient modulus and skin temperature difference. GGA mixtures exhibit lower ITS and resilient modulus compared to PA and AC. However, GGA mix exhibits better resistance to rutting and being impermeable enables it to completely waterproof the pavement.

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Image analysis for detecting aggregate gradation in asphalt mixture from planar images

Cited by 87 publications

References 15 publications

Integration of Field and Laboratory Spectral Data with Multi-Resolution Remote Sensed Imagery for Asphalt Surface Differentiation

Integration of Field and Laboratory Spectral Data with Multi-Resolution Remote Sensed Imagery for Asphalt Surface Differentiation

Three Dimensional Digital Sieving of Asphalt Mixture Based on X-ray Computed Tomography

Effects of Mixture Aging on the Performance of Gap Graded Asphalt Mix Experimented on the Malaysian North-South Expressway

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