- Tytuł:
- Prediction of asphalt creep compliance using artificial neural networks
- Autorzy:
-
Zofka, A.
Yut, I. - Powiązania:
- https://bibliotekanauki.pl/articles/230827.pdf
- Data publikacji:
- 2012
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
lepiszcze asfaltowe
mieszanka asfaltowa gorąca
sieć neuronowa sztuczna
belka zginana
reometr
podatność na pełzanie
badanie napięcia pośrednie
asphalt binder
hot mix asphalt
artificial neural network
bending beam
rheometer
creep compliance
indirect tension test - Opis:
- Creep compliance of the hot-mix asphalt (HMA) is a primary input of the current pavement thermal cracking prediction model used in the US. This paper discusses a process of training an Artificial Neural Network (ANN) to correlate the creep compliance values obtained from the Indirect Tension (IDT) with similar values obtained on small HMA beams from the Bending Beam Rheometer (BBR). In addition, ANNs are also trained to predict HMA creep compliance from the creep compliance of asphalt binder and vice versa using the BBR setup. All trained ANNs exhibited a very high correlation of 97 to 99 percent between predicted and measured values. The binder creep compliance functions built on the ANN-predicted discrete values also exhibited a good correlation when compared with the laboratory experiments. However, the simulation of trained ANNs on the independent dataset produced a significant deviation from the measured values which was most likely caused by the differences in material composition, such as aggregate type and gradation, presence of recycled additives, and binder type.
- Źródło:
-
Archives of Civil Engineering; 2012, 58, 2; 153-173
1230-2945 - Pojawia się w:
- Archives of Civil Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł