Development of a Permanent Deformation Model of Asphalt Mixtures for South Korean Pavement Design Guide

2009 ◽  
Vol 2095 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Anh Thang Le ◽  
Hyun Jong Lee ◽  
Hee Mun Park ◽  
Sang Yum Lee
Keyword(s):  
Permanent Deformation ◽  
Asphalt Mixtures ◽  
Pavement Design ◽  
Deformation Model ◽  
South Korean ◽  
Design Guide

Laboratory-based Unified Permanent Deformation Model for Hot-Mix Asphalt Mixtures

2007 ◽  
Vol 35 (3) ◽  
pp. 13153 ◽  
Author(s):  
M. R. Mitchell ◽  
R. E. Link ◽  
Elie Y. Hajj ◽  
Raj V. Siddharthan ◽  
Peter E. Sebaaly ◽  
...  
Keyword(s):  
Hot Mix Asphalt ◽  
Permanent Deformation ◽  
Asphalt Mixtures ◽  
Deformation Model

scholarly journals Local calibration of MEPDG for Superpave Pavements in Ontario : Enhance rutting calibration and preliminary study on IRI model

2021 ◽  
Author(s):  
Maryam Amir
Keyword(s):  
Permanent Deformation ◽  
Pavement Design ◽  
Local Calibration ◽  
Iri Model ◽  
International Roughness Index ◽  
Local Conditions ◽  
Calibration Methods ◽  
Roughness Index ◽  
Design Guide ◽  
Deformation Models

The AASHTO Mechanistic-Empirical Pavement Design Guide requires local calibration to account for local conditions, materials, and engineering practices. Previous local calibration studies in Ontario focused mainly on permanent deformation models for pavement rutting. The objectives of this study are twofold. First, to provide an enhanced calibration for the rutting models by using more vigilantly cross-verified input data and updated observed rutting data. Second, to perform a trial calibration for the international roughness index (IRI) model by considering three different calibration methods. Cracking models calibration, being performed by another colleague, has not yet been finalized; therefore, the IRI model calibration cannot be finalized in this study. Based upon 63 Superpave sections, the local calibration coefficients were found to be βAC = 1.7692, βT = 1.0, βN = 0.6262, βGB = 0.0968 and βSG = 0.2787 , which reduced the standard deviation of residuals to a value of 1 mm. The IRI calibration study found that the initial IRI value plays an important role in the calibration. Keywords: International Roughness Index (IRI) model; local calibration; Mechanistic-Empirical Pavement Design Guide (MEPDG); rutting model; Superpave.

scholarly journals Local calibration of MEPDG for Superpave Pavements in Ontario : Enhance rutting calibration and preliminary study on IRI model

2021 ◽  
Author(s):  
Maryam Amir
Keyword(s):  
Permanent Deformation ◽  
Pavement Design ◽  
Local Calibration ◽  
Iri Model ◽  
International Roughness Index ◽  
Local Conditions ◽  
Calibration Methods ◽  
Roughness Index ◽  
Design Guide ◽  
Deformation Models

The AASHTO Mechanistic-Empirical Pavement Design Guide requires local calibration to account for local conditions, materials, and engineering practices. Previous local calibration studies in Ontario focused mainly on permanent deformation models for pavement rutting. The objectives of this study are twofold. First, to provide an enhanced calibration for the rutting models by using more vigilantly cross-verified input data and updated observed rutting data. Second, to perform a trial calibration for the international roughness index (IRI) model by considering three different calibration methods. Cracking models calibration, being performed by another colleague, has not yet been finalized; therefore, the IRI model calibration cannot be finalized in this study. Based upon 63 Superpave sections, the local calibration coefficients were found to be βAC = 1.7692, βT = 1.0, βN = 0.6262, βGB = 0.0968 and βSG = 0.2787 , which reduced the standard deviation of residuals to a value of 1 mm. The IRI calibration study found that the initial IRI value plays an important role in the calibration. Keywords: International Roughness Index (IRI) model; local calibration; Mechanistic-Empirical Pavement Design Guide (MEPDG); rutting model; Superpave.

scholarly journals Effect of Different Rheological Models on the Distress Prediction of Composite Pavement

Materials ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 229
Author(s):  
Ki Hoon Moon ◽  
Augusto Cannone Falchetto ◽  
Hae Won Park ◽  
Di Wang
Keyword(s):  
Dynamic Modulus ◽  
Asphalt Mixtures ◽  
Pavement Design ◽  
Reflective Cracking ◽  
Rheological Models ◽  
Pavement Distress ◽  
Upper Limits ◽  
Distress Prediction ◽  
Design Guide ◽  
Cam Model

In this paper, three different rheological models including a newly developed formulation based on the current Christensen Anderson and Marateanu (CAM) model, named sigmoidal CAM model (SCM), are used to estimate the evolution of roughness, rutting, and reflective cracking in a typical composite pavement structure currently widely adopted in South Korea. Three different asphalt mixtures were prepared and dynamic modulus tests were performed. Then, the mechanistic-empirical pavement design guide (MEPDG) was used for predicting the progression of the pavement distress and to estimate the effect of the three different models on such phenomena. It is found that the three different mathematical models provide lower and upper limits for roughness, rutting, and reflective cracking. While the CAM model may not be entirely reliable due to its inability in fitting the data in the high-temperature domain, SCM might result in moderately more conservative pavement design.

Evaluating Dynamic Modulus for Indiana Mechanistic-Empirical Pavement Design Guide Practice

2019 ◽  
Vol 2673 (2) ◽  
pp. 346-357 ◽  
Author(s):  
Dario Batioja-Alvarez ◽  
Jusang Lee ◽  
Tommy Nantung
Keyword(s):  
Dynamic Modulus ◽  
Functional Performance ◽  
Aggregate Size ◽  
Asphalt Mixtures ◽  
Pavement Design ◽  
Maximum Aggregate Size ◽  
Pavement Distress ◽  
Design Guide ◽  
Pavement Structures ◽  
Level I

After the implementation of the Mechanistic-Empirical Pavement Design Guide (MEPDG) in Indiana, an overall evaluation of the stiffness characteristics of local AC mixtures and the ability of level III MEPDG predictive equations to estimate dynamic modulus (E*) with local mixtures was required. Therefore, the primary objectives of this study were to identify significant differences among Indiana asphalt mixtures, to evaluate the performance of commonly used E* predictive models, and to assess the influence of level III E* input on the pavement design life of typical pavement structures. It was found that Indiana mixtures do not show extensive variability among mixtures having the same nominal maximum aggregate size. When conducting a statistical analysis to group asphalt mixtures having similar characteristics, few mixtures were left out of the groups. In general, it was observed that mixtures having Ndes equal to 75, showed the lowest E* values along the entire frequency range. The Witczak 1-37A showed the most accurate and less biased E* predictions for Indiana mixtures. It showed the highest R2, and the least deviation from the measured E* values. However, predicted E* input values produced higher levels of pavement distress compared with measured E* values, indicating general overprediction. Besides, using level III (predictive) rather than level I (measured) E* input values can influence the pavement thickness design due to the functional performance (i.e., the International Roughness Index (IRI)). When a structural performance (i.e., bottom-up cracking) was taken into consideration, no influence of the E* input type on the design AC layer thickness was observed.

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