TY - JOUR
T1 - Predicting the strength of polymer-modified thin-layer asphalt with fuzzy logic
AU - Zehtabchi, Ali
AU - Hashemi, Seyed Amir Hossein
AU - Asadi, Somayeh
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/4/30
Y1 - 2018/4/30
N2 - Soft computing methods can be used with acceptable accuracy in predicting the strength of asphalt mixture. Moreover, estimating the compressive strength of asphalt mixture with 5% mean error by fuzzy logic shows the potential of this approach to predict its strength. More specifically, when the asphalt mix contains additives such as different types of polymers, accurate prediction of its compressive strength becomes more difficult. In most of the developed countries, polymer-modified thin-layer asphalt has long been used to increase the strength, lifespan, and properties of asphalt mixture. In the present study, the fuzzy logic model was developed to predict the compressive strength of the asphalt specimens in different scenarios including changing optimum bitumen percentage, adding granular polymer-modified bitumen, and using different percentages of fractured particles. Then the results were compared with laboratory measurements to determine the accuracy of the fuzzy logic model.
AB - Soft computing methods can be used with acceptable accuracy in predicting the strength of asphalt mixture. Moreover, estimating the compressive strength of asphalt mixture with 5% mean error by fuzzy logic shows the potential of this approach to predict its strength. More specifically, when the asphalt mix contains additives such as different types of polymers, accurate prediction of its compressive strength becomes more difficult. In most of the developed countries, polymer-modified thin-layer asphalt has long been used to increase the strength, lifespan, and properties of asphalt mixture. In the present study, the fuzzy logic model was developed to predict the compressive strength of the asphalt specimens in different scenarios including changing optimum bitumen percentage, adding granular polymer-modified bitumen, and using different percentages of fractured particles. Then the results were compared with laboratory measurements to determine the accuracy of the fuzzy logic model.
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U2 - 10.1016/j.conbuildmat.2018.02.002
DO - 10.1016/j.conbuildmat.2018.02.002
M3 - Article
AN - SCOPUS:85043388510
SN - 0950-0618
VL - 169
SP - 826
EP - 834
JO - Construction and Building Materials
JF - Construction and Building Materials
ER -