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Prediction of resilient modulus model for wearing asphalt pavement layer
Author
Source
Issue
Vol. 9, Issue 4 (31 Oct. 2018), pp.65-87, 23 p.
Publisher
University of Kufa Faculty of Engineering
Publication Date
2018-10-31
Country of Publication
Iraq
No. of Pages
23
Main Subjects
Abstract EN
Resilient modulus for pavement layers is a key design parameter for pavement systems and permits for determination of how the pavement system will react to traffic loadings.
It can be defined shortly as elastic modulus of a material under repeated loads.
Several factors have effects on the elastic modulus of the layers of asphalt pavements.
The indirect repeated axial load test was carried out by using the pneumatic repeated load system (PRLS) at Transportation Laboratory at Baghdad University to test seventy two cylindrical specimens prepared by the gyratory device.
SPSS program was used to predict the resilient modulus model which contains many factors like asphalt content, asphalt viscosity, air voids, surface area, and temperature.
Multiple linear regression is used to build the model of resilient modulus because it is a function of more than independent variables.
F statistical significance value from the results of ANOVA table is smaller than 0.05 in the predicted model then the independent variables in the predicted model explain the variation in the resilient modulus variable.
The coefficient of determination (R2) is 0.886 for the predicted model which is referred to a very good relation obtained.
The predicted model shows that the modulus of resilience is highly affected by variation of temperature and moderately by viscosity of the asphalt whereas the stress level, types of filler, and the asphalt content have smaller effect on resilient modulus.
The predicted model shows that there is a positive relationship among the resilient modulus and the two variables viscosity and the surface area whereas the three variables temperature, asphalt content, and air voids have inverse relationship with resilient modulus.
Two asphalt types (40-50) and (60-70) from Dora refinery were used; the average value of resilient modulus corresponding to asphalt grade (40- 50) is almost 21.331% times the value for asphalt grade (60-70).
Three asphalt contents (optimum asphalt content, optimum asphalt content±0.5) were used; when the content of asphalt was increased from 4% to 4.5%, the average resilient modulus decreased by 2.923% whereas increasing the percent of asphalt content from 4.5 to 5 the average resilient modulus decreased by 1.737%.
Two types of mineral fillers (cement and limestone) were used, and when cement was used as mineral filler, the average resilient modulus increased by 4.422% rather than using limestone as filler in the asphalt mixture.
Three temperatures for test were used 10, 25, and 40 oC.
The results showed that when temperature was increased from 10 to 25 ◦C, the average resilient modulus decreases by 65.738%; whereas when the test temperature was increased from 25 to 40 oC, the average resilient moduli decreased by 97.715%.
The results also showed that the average resilient modulus increased by 9.69% when the stress level increased from 6.5 psi to 13 psi.
American Psychological Association (APA)
Hilal, Miami Muhammad. 2018. Prediction of resilient modulus model for wearing asphalt pavement layer. Kufa Journal of Engineering،Vol. 9, no. 4, pp.65-87.
https://search.emarefa.net/detail/BIM-901774
Modern Language Association (MLA)
Hilal, Miami Muhammad. Prediction of resilient modulus model for wearing asphalt pavement layer. Kufa Journal of Engineering Vol. 9, no. 4 (Oct. 2018), pp.65-87.
https://search.emarefa.net/detail/BIM-901774
American Medical Association (AMA)
Hilal, Miami Muhammad. Prediction of resilient modulus model for wearing asphalt pavement layer. Kufa Journal of Engineering. 2018. Vol. 9, no. 4, pp.65-87.
https://search.emarefa.net/detail/BIM-901774
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 85-87
Record ID
BIM-901774