The current paper deals with the numerical prediction of the mechanical response of Asphalt Concretes (AC) for flexible pavements, using Artificial Neural Networks (ANN). The AC mixes considered in the study were consisted of diabase aggregates and two different types of bitumen; a conventional bituminous binder and a polymer modified one. The ACs were produced in the laboratory and in a production plant. The ACs mechanical behaviour was investigated in terms of Marshall Stability, Flow, Quotient and Stiffness Modulus. The ANN used had one hidden layer and 10 artificial neurons. The results have been extremely satisfactory, with correlation coefficients in the testing phase within the range 0.98798 – 0.91024, demonstrating the feasibility of ANN prediction models’ application. Furthermore, a closed form equation has been with input parameters the production process, the bitumen type and content, the filler/bitumen ratio and the volumetric properties of the mixes.

Asphalt concrete mechanical behavior prediction by artificial neural networks

Baldo N.;
2019

Abstract

The current paper deals with the numerical prediction of the mechanical response of Asphalt Concretes (AC) for flexible pavements, using Artificial Neural Networks (ANN). The AC mixes considered in the study were consisted of diabase aggregates and two different types of bitumen; a conventional bituminous binder and a polymer modified one. The ACs were produced in the laboratory and in a production plant. The ACs mechanical behaviour was investigated in terms of Marshall Stability, Flow, Quotient and Stiffness Modulus. The ANN used had one hidden layer and 10 artificial neurons. The results have been extremely satisfactory, with correlation coefficients in the testing phase within the range 0.98798 – 0.91024, demonstrating the feasibility of ANN prediction models’ application. Furthermore, a closed form equation has been with input parameters the production process, the bitumen type and content, the filler/bitumen ratio and the volumetric properties of the mixes.
9781351063265
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11390/1190948
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact