Prediction of hot mix asphalt dynamic modulus using dimensional analysis

2012 ◽  
Vol 165 (1) ◽  
pp. 15-25 ◽  
Author(s):  
Ahmad Abu Abdo ◽  
Balasingam Muhunthan
Keyword(s):  
Dimensional Analysis ◽  
Dynamic Modulus ◽  
Hot Mix Asphalt

Laboratory Investigation of Pavement Backfilling Materials for Micro-Trenching in Cold Regions

2018 ◽  
Vol 2672 (12) ◽  
pp. 62-71
Author(s):  
Leila Hashemian ◽  
Vinicius Afonso Velasco Rios ◽  
Alireza Bayat
Keyword(s):  
Laboratory Investigation ◽  
Dynamic Modulus ◽  
Laboratory Tests ◽  
Hot Mix Asphalt ◽  
Cement Grout ◽  
Host Material ◽  
High Quality ◽  
Cold Temperatures ◽  
Asphalt Mixes ◽  
Freeze Thaw

This study investigated the performance of different materials in a micro-trench composite backfilling design. Laboratory tests were conducted to evaluate the effect of cold temperatures and freeze/thaw cycles on a cement grout and seven preparatory cold asphalt mixes. To compare the performance of cold mix asphalt and epoxy grout with hot mix asphalt as the host material, rutting tests and dynamic modulus tests at different loading frequencies and temperatures were conducted. Finally, laboratory scale micro-trench samples were prepared using different backfilling materials and were loaded using a wheel tracker after freeze/thaw conditioning. The results showed that cement grout could effectively be used to secure the conduit inside the trench. It was also concluded that using high-quality cold mix asphalt, a compatible material with hot mix asphalt, could improve micro-trench durability compared with epoxy grout.

scholarly journals Advanced approaches to hot-mix asphalt dynamic modulus prediction

2008 ◽  
Vol 35 (7) ◽  
pp. 699-707 ◽  
Author(s):  
Halil Ceylan ◽  
Kasthurirangan Gopalakrishnan ◽  
Sunghwan Kim
Keyword(s):  
Prediction Model ◽  
Dynamic Modulus ◽  
Prediction Models ◽  
Hot Mix Asphalt ◽  
Logical Structure ◽  
Ann Model ◽  
Model Predictions ◽  
Input Variables ◽  
Artificial Neural Network Ann ◽  
National Cooperative

The dynamic modulus (|E*|) is one of the primary hot-mix asphalt (HMA) material property inputs at all three hierarchical levels in the new Mechanistic–empirical pavement design guide (MEPDG). The existing |E*| prediction models were developed mainly from regression analysis of an |E*| database obtained from laboratory testing over many years and, in general, lack the necessary accuracy for making reliable predictions. This paper describes the development of a simplified HMA |E*| prediction model employing artificial neural network (ANN) methodology. The intelligent |E*| prediction models were developed using the latest comprehensive |E*| database that is available to researchers (from National Cooperative Highway Research Program Report 547) containing 7400 data points from 346 HMA mixtures. The ANN model predictions were compared with the Hirsch |E*| prediction model, which has a logical structure and a relatively simple prediction model in terms of the number of input parameters needed with respect to the existing |E*| models. The ANN-based |E*| predictions showed significantly higher accuracy compared with the Hirsch model predictions. The sensitivity of input variables to the ANN model predictions were also examined and discussed.

Effect of Long Term Oven Aging on Dynamic Modulus of Hot Mix Asphalt

2011 ◽  
Author(s):  
Dharamveer Singh ◽  
Musharraf Zaman ◽  
Sesh Commuri
Keyword(s):  
Dynamic Modulus ◽  
Hot Mix Asphalt

scholarly journals Measurement of Dynamic Modulus and Master Curve Modeling of Hot Mix Asphalt from Senegal (West Africa)

2015 ◽  
Vol 2 (1) ◽  
pp. 124 ◽  
Author(s):  
Mouhamed Lamine Chérif Aidara ◽  
Makhaly Ba ◽  
Alan Carter
Keyword(s):  
Dynamic Modulus ◽  
Master Curve ◽  
Hot Mix Asphalt ◽  
Complex Modulus ◽  
Test Results ◽  
Asphalt Mixes ◽  
Design Guide ◽  
Asphalt Mix ◽  
Sigmoidal Model ◽  
Curve Modeling

The main purpose of this paper is to model the master curve of dynamic modulus |E*| for Hot Mix Asphalt mix designed with aggregate from Senegal named basalt of Diack and quartzite of Bakel. The prediction model used is the Witczak model, used in the Mechanistic-Empirical Pavement Design Guide. A study has been conducted in the Laboratory of Pavements and Bituminous Materials. Six different HMA (BBSG 0/14 mm) were subjected to complex modulus test by tension-compression according to the European or Canadian procedure using the same range of temperatures and frequencies. For each mixture studied the uniqueness of modulus curves in the Cole-Cole or in Black diagrams have shown that the asphalt mixes are thermorheologically simple materials and the Canadian test process is suitable for determining the HMA complex modulus mix designed with the aggregates from Senegal. This implies their tender with the principle of time-temperature equivalence. The test results were used to model the master curves of HMA studied. A correlation with the results of dynamic modulus measured have shown an accuracy of R2 = 0,99 and p = 0,00 in STATISTICA software, which allows to conclude that the sigmoidal model has good modeling of the dynamic modulus.

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