Mechanical, surface and environmental evaluation of stone mastic asphalt mixtures with advanced asphalt binders using waste materials

Fernandes, Sara R. M.; Silva, Hugo Manuel Ribeiro Dias da; Oliveira, Joel

doi:10.1080/14680629.2017.1387169

Cited by 30 publications

(26 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, the relative error of the monthly attenuation value GM (1, 1) prediction models of the PCI and PQI is also smaller than that of other asphalt pavement performance prediction models. sequence, Z (1) denotes the X (1) neighboring mean generation sequence, whereas X (0) (k) + aZ (1) (k) � b is considered a gray differential equation [18]. It is also known as the definition of the GM (1, 1) model.…”

Section: Research Significancementioning

confidence: 99%

“…en, the least-squares estimation parameter sequence of the gray differential equation X (0) (k) + aZ (1)…”

Section: Research Significancementioning

confidence: 99%

“…⟶ n − 1, the matrix witnesses a severe drift. Notably, the gray system studies small samples; however, in actual production and life, the value of Z (1) (k) varies significantly with actual production and life issues. If Z (1) (k) > 10 or above, the value of 4 n k�2 [Z (1)…”

Section: Research Significancementioning

confidence: 99%

“…In other words, the condition number of the matrix B T B is correspondingly larger, which, in turn, leads to the morbid matrix. When n − 2 < [ n k�2 Z (1)…”

Section: Research Significancementioning

confidence: 99%

“…Factors that affect pavement performance include traffic volume, structural strength, structural composition, material characteristics, and environmental factors. To that end, Fernandes conducted a study on a new asphalt mixture using waste materials and found that it can be used for road-paving works in order to improve the performance without compromising on human and environmental safety [1]. Correspondingly, Camargo and Bernucci carried out a study in order to characterize the field performance of Brazil's first pavement rehabilitation job using a field-blended rubber asphalt mixture and attempted to predict its future performance [2].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Monthly Attenuation Prediction for Asphalt Pavement Performance by Using GM (1, 1) Model

Tang

Xiao

2019

Advances in Civil Engineering

View full text Add to dashboard Cite

Due to the uncertainty and variability of various factors affecting the pavement performance, the change in pavement performance cannot be completely determined. In addition, this uncertainty is not accurately reflected by the pavement performance prediction model. In particular, the gray GM (1, 1) model is very suitable due to it is ability to better predict the existing situation of a domestic asphalt pavement along with the actual performance of a road surface of the “small sample, poor information” gray system. In this regard, the gray GM (1, 1) model is being increasingly used to forecast the performance of an asphalt pavement. When a gray GM (1, 1) model is used to predict the performance of an asphalt pavement, the condition number of the GM (1, 1) model matrix is too large, which, in turn, leads to the deviation of calculation and even wrong results in some cases. This study analyzed the reason for a large condition number of the GM (1, 1) model matrix. Combined with the numerical characteristics of the pavement condition index (PCI) and pavement quality index (PQI), this study focused on the annual, monthly, and daily attenuations of PCI and PQI to the condition number of the GM (1, 1) model matrix. Accordingly, we propose a method to forecast the performance of an asphalt pavement using the monthly attenuation of PCI and PQI. The PCI and PQI in Hunan Province in recent years have been predicted, and the findings reveal that the prediction GM (1, 1) model for the monthly attenuation of PCI and PQI not only effectively lowered the condition number of the matrix but also ensured that the relative error was small.

show abstract

Section: Research Significancementioning

confidence: 99%

“…en, the least-squares estimation parameter sequence of the gray differential equation X (0) (k) + aZ (1)…”

Section: Research Significancementioning

confidence: 99%

Section: Research Significancementioning

confidence: 99%

“…In other words, the condition number of the matrix B T B is correspondingly larger, which, in turn, leads to the morbid matrix. When n − 2 < [ n k�2 Z (1)…”

Section: Research Significancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations