6533b82cfe1ef96bd128f5a5

RESEARCH PRODUCT

An ANN model to correlate roughness and structural performance in asphalt pavements

Gaetano BosurgiTien Fang FwaGiuseppe Sollazzo

subject

Artificial Neural NetworkEngineering0211 other engineering and technologies020101 civil engineering02 engineering and technologySurface finishcomputer.software_genreCivil engineering0201 civil engineeringDeflection (engineering)021105 building & constructionLinear regressionSettore ICAR/04 - Strade Ferrovie Ed AeroportiAsphalt pavementGeneral Materials ScienceCivil and Structural EngineeringArtificial neural networkLTPPbusiness.industryBuilding and ConstructionStructural performanceAsphaltMaterials Science (all)Data miningRoughnebusinesscomputerArtificial Neural Network; Asphalt pavements; LTPP; Roughness; Structural performance; Civil and Structural Engineering; Building and Construction; Materials Science (all)

description

Abstract In this paper, using a large database from the Long Term Pavement Performance program, the authors developed an Artificial Neural Network (ANN) to estimate the structural performance of asphalt pavements from roughness data. Considering advantages of modern high-performance survey devices in the acquisition of road pavement functional parameters, it would be of practical significance if the structural state of a pavement could be estimated from its functional conditions. To differentiate various road section conditions, several significant input parameters, related to traffic, weather, and structural aspects, have been included in the analysis. The results are very interesting and prove that the ANN represents an adequate model to evidence this relation. The papers shows the effectiveness of the adoption of a large database for the analysis of the correlation. ANN provides also better results in comparison with Linear Regression. Further, the authors trained three different ANNs to analyse the effects of modified datasets and different variables. The numerical outcomes confirm that, by using this approach, it is possible to correlate with good accuracy roughness and structural performance, allowing road agencies to actually reduce the deflection test frequency, since they are generally more costly, time consuming, and disruptive to traffic than functional surveys.

yearjournalcountryeditionlanguage
2017-03-01Construction and Building Materials
https://doi.org/10.1016/j.conbuildmat.2016.12.186