IRI Sensitivity to the Influence of Surface Distress on Flexible Pavements


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COATINGS, cilt.8, sa.8, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 8
  • Basım Tarihi: 2018
  • Doi Numarası: 10.3390/coatings8080271
  • Dergi Adı: COATINGS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: HMA, IRI, pavement distress, MARS approach, ADAPTIVE REGRESSION SPLINES, NEURAL-NETWORKS, FUZZY-LOGIC, ROUGHNESS, MODEL, PERFORMANCE, ROADS, MARS
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

Today, authorities responsible for the operation of highways aim to provide comfort to road users as well as safety while driving. While driving, the most important component that determines comfort for road users is the pavement. The relative effects of various surface distress types in bituminous, hot mixed asphalt pavements on the International Roughness Index (IRI) component-used to evaluate the present performance, and hence the comfort, of pavements-are determined in this study. The presence of only one type of surface distress is very difficult to achieve in practice, especially in regards to pavements where a high degree of deterioration is observed. The presence of different types of surface distress in road pavements, due to similar problems in very close positions and even in nested forms, makes it difficult to assess this issue. The relationships between surface distress and IRI have been modelled to overcome this challenge. To this end, the Multivariate Adaptive Regression Splines (MARS) modelling approach, which is very successful in investigating the relationships between a large number of independent variables and dependent variables, has been used. The sensitivities of the surface distress inputs are evaluated singularly by means of a model with 29 input variables calibrated using the pavement distress data collected in 3295 highway pavement sections. As a result of this analysis, the sensitivity of surface distress inputs collected, as an area, has been determined to have an effect on the increase in IRI. The results are interpreted with the help of figures and tables.