Methodology for Modeling the Uncertainty of Material Properties in Asphalt Pavements

Caro, Silvia; Castillo, Daniel; Sánchez-Silva, Mauricio

doi:10.1061/(asce)mt.1943-5533.0000841

Cited by 23 publications

(9 citation statements)

References 11 publications

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“…Herein, the set of input values (i.e., μ, σ, L x , L y , n, and m) were determined by analyzing the distribution of the parameter of interest. Regarding f, an exponential correlation function is adopted based on the work of (Caro et al, 2014(Caro et al, , 2018. The horizontal and vertical correlation lengths (L x and L y ) determine how values are correlated within a spatial range in each direction; values within this range are expected to be highly correlated; within the range of a correlation length meaning that the likelihood of finding similar values increases.…”

Section: Rf Theorymentioning

confidence: 99%

Computational generation of multiphase asphalt nanostructures using random fields

Aljarrah

Karaki

Masad

et al. 2022

Computer aided Civil Eng

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This study presents a novel methodology to generate computational replicates of nanostructures of multiphase materials, such as asphalt binders, by integrating image analysis techniques with stochastic random field (RF) modeling. Image analysis techniques are used to identify and segment nanostructure images obtained by atomic force microscopy, while RF is used to model the spatial distribution of their material properties. The results of this process are images showing probable arrangements of nanostructures with stochastic material properties that replicate the experimentally obtained images. The computationally generated nanostructures are then used as inputs in a finite element model to evaluate the effect of heterogeneity on their mechanical response. The efficacy of the developed approach is demonstrated through simulations of asphalt binders' nanostructures, which reveal novel insights regarding their nanoscale mechanical behavior and response. The FE simulations provided the link between the distribution of nanoscale properties of asphalt binders and variations in their mechanical response. The application of this methodology expands the body of knowledge beyond the deterministic analysis of asphalt binders toward probabilistic analysis and uncertainty quantification that considers their heterogeneous, multiphase structures. Consequently, the methodology can be used to design multiphase materials, such as asphaltic blends, with tailored properties and enhanced performance.

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Section: Rf Theorymentioning

confidence: 99%

Computational generation of multiphase asphalt nanostructures using random fields

Aljarrah

Karaki

Masad

et al. 2022

Computer aided Civil Eng

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“…Finally, some recent works have studied the variability of material properties in field compacted HMA [9,10]. Although these analyses do not consider the complexities of the microstructure of HMA, which are effectively addressed in the present paper, they apply an efficient stochastic technique to incorporate inherent irregularities present at the top asphalt course to evaluate their effect on the response of asphalt pavement structures.…”

Section: Introductionmentioning

confidence: 98%

Studying the effect of microstructural properties on the mechanical degradation of asphalt mixtures

Castillo

Caro

Darabi

et al. 2015

Construction and Building Materials

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“…In terms of material variability, previously published studies have applied a variety of stochastic tools to assess its impact on the mechanical performance of asphalt materials (Lua and Sues 1996, Lea 2010, Caro et al 2013, Dilip and Sivakumar Babu 2014. In all cases, these works recognise that asphalt mixtures are heterogeneous materials (i.e.…”

Section: Introductionmentioning

confidence: 99%

Incorporating the heterogeneity of asphalt mixtures in flexible pavements subjected to moisture diffusion

Caro

Castillo

Masad

2015

International Journal of Pavement Engineering

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Moisture diffusion is one of the mechanisms by which water can reach the microstructure of asphalt mixtures and negatively affect their performance. In this work, a finite element model and computational simulations were used to study the response of asphalt pavement layers subjected to the coupled effects of moisture diffusion and mechanical loading. The model considered that the evolution of water-related diffusion processes in these materials is influenced by the microstructure of the mixture, particularly by the air void (AV) phase. Thus, a stochastic technique was used to incorporate the heterogeneity of the AV structure in compacted asphalt layers, which also permitted to account for the variability of the physical and mechanical properties that result from the heterogeneous void structure. The results demonstrate that moisture diffusion has a significant influence on the macromechanical response of asphalt pavement layers, especially during the initial months of service. In addition, the results clearly demonstrate that including the heterogeneity of material properties is valuable to quantify the uncertainty associated with these coupled processes.

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Methodology for Modeling the Uncertainty of Material Properties in Asphalt Pavements

Cited by 23 publications

References 11 publications

Computational generation of multiphase asphalt nanostructures using random fields

Computational generation of multiphase asphalt nanostructures using random fields

Studying the effect of microstructural properties on the mechanical degradation of asphalt mixtures

Incorporating the heterogeneity of asphalt mixtures in flexible pavements subjected to moisture diffusion

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