Comparing laboratory dynamic modulus values with long term pavement performance predictions
This study compares laboratory dynamic modulus value of Superpave mixes with the dynamic modulus obtained from Long Term Pavement Performance (LTPP) database. The comparison shows that the dynamic modulus from LTPP database, which were determined by using different types of artificial neural networ...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
Vilnius Gediminas Technical University
2014-12-01
|
Series: | Engineering Structures and Technologies |
Subjects: | |
Online Access: | https://journals.vgtu.lt/index.php/EST/article/view/3203 |
id |
doaj-9eadee7cc53449b3ae487ee5c76b45aa |
---|---|
record_format |
Article |
spelling |
doaj-9eadee7cc53449b3ae487ee5c76b45aa2021-07-02T05:04:38ZengVilnius Gediminas Technical UniversityEngineering Structures and Technologies2029-882X2029-88382014-12-016210.3846/2029882X.2014.972625Comparing laboratory dynamic modulus values with long term pavement performance predictionsA. S. M. Asifur Rahman0Rafiqul A. Tarefder1Department of Civil Engineering, University of New Mexico, MSC01 1070, Albuquerque, 87131-0001 New MexicoDepartment of Civil Engineering, University of New Mexico, MSC01 1070, Albuquerque, 87131-0001 New Mexico This study compares laboratory dynamic modulus value of Superpave mixes with the dynamic modulus obtained from Long Term Pavement Performance (LTPP) database. The comparison shows that the dynamic modulus from LTPP database, which were determined by using different types of artificial neural network (ANN) models, differs from the laboratory tested dynamic modulus. The dynamic modulus data of five LTPP test sections are considered. Mixes similar to those five sections were collected from the field and tested in the laboratory. Based on the findings of this study, it can be said that dynamic modulus from ANN models are less than the laboratory dynamic modulus for New Mexico Superpave mixes. Therefore, as an important design parameter, the use of dynamic modulus predicted from Neural Network models can result in outcomes different from those using laboratory dynamic modulus. https://journals.vgtu.lt/index.php/EST/article/view/3203asphalt concretedynamic modulusmastercurvelong term pavement performancehot-mix asphaltshift factor |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
A. S. M. Asifur Rahman Rafiqul A. Tarefder |
spellingShingle |
A. S. M. Asifur Rahman Rafiqul A. Tarefder Comparing laboratory dynamic modulus values with long term pavement performance predictions Engineering Structures and Technologies asphalt concrete dynamic modulus mastercurve long term pavement performance hot-mix asphalt shift factor |
author_facet |
A. S. M. Asifur Rahman Rafiqul A. Tarefder |
author_sort |
A. S. M. Asifur Rahman |
title |
Comparing laboratory dynamic modulus values with long term pavement performance predictions |
title_short |
Comparing laboratory dynamic modulus values with long term pavement performance predictions |
title_full |
Comparing laboratory dynamic modulus values with long term pavement performance predictions |
title_fullStr |
Comparing laboratory dynamic modulus values with long term pavement performance predictions |
title_full_unstemmed |
Comparing laboratory dynamic modulus values with long term pavement performance predictions |
title_sort |
comparing laboratory dynamic modulus values with long term pavement performance predictions |
publisher |
Vilnius Gediminas Technical University |
series |
Engineering Structures and Technologies |
issn |
2029-882X 2029-8838 |
publishDate |
2014-12-01 |
description |
This study compares laboratory dynamic modulus value of Superpave mixes with the dynamic modulus obtained from Long Term Pavement Performance (LTPP) database. The comparison shows that the dynamic modulus from LTPP database, which were determined by using different types of artificial neural network (ANN) models, differs from the laboratory tested dynamic modulus. The dynamic modulus data of five LTPP test sections are considered. Mixes similar to those five sections were collected from the field and tested in the laboratory. Based on the findings of this study, it can be said that dynamic modulus from ANN models are less than the laboratory dynamic modulus for New Mexico Superpave mixes. Therefore, as an important design parameter, the use of dynamic modulus predicted from Neural Network models can result in outcomes different from those using laboratory dynamic modulus.
|
topic |
asphalt concrete dynamic modulus mastercurve long term pavement performance hot-mix asphalt shift factor |
url |
https://journals.vgtu.lt/index.php/EST/article/view/3203 |
work_keys_str_mv |
AT asmasifurrahman comparinglaboratorydynamicmodulusvalueswithlongtermpavementperformancepredictions AT rafiqulatarefder comparinglaboratorydynamicmodulusvalueswithlongtermpavementperformancepredictions |
_version_ |
1721339126427418624 |