Using the GMDH and ANFIS methods for predicting the crack resistance of fibre reinforced high RAP asphalt mixtures
In this paper, the effectiveness of the group method of data handling (GMDH) and the adaptive neuro-fuzzy inference system (ANFIS) methods in modelling the fracture parameters of asphalt mixtures were studied. For this aim, the models were investigated on the fracture energy and J-integral results of hot mix asphalt in terms of temperature, reclaimed asphalt pavement (RAP) content and fibre content. It was found that the fibres have an outstanding effect on the fracture behaviour of asphalt mixtures especially at intermediate and high temperatures and can be considered as an alternative to enhance the fracture resistance of recycled asphalt mixtures. The fracture data of asphalt mixtures can be successfully modelled by the ANFIS method with a high level of correlation. The GMDH was unable to model the J-integral results, however, it had a fair correlation with the results of fracture energy.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/14680629
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Supplemental Notes:
- © 2020 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
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Authors:
- Ziari, Hassan
- Amini, Amir
- Moniri, Ali
- Habibpour, Mahdi
- Publication Date: 2021-10
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 2248-2266
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Serial:
- Road Materials and Pavement Design
- Volume: 22
- Issue Number: 10
- Publisher: Taylor & Francis
- ISSN: 1468-0629
- EISSN: 2164-7402
- Serial URL: http://www.tandfonline.com/loi/trmp20
Subject/Index Terms
- TRT Terms: Algorithms; Asphalt mixtures; Fiber reinforced materials; Fracture tests; Neural networks; Pavement cracking; Reclaimed asphalt pavements
- Subject Areas: Highways; Materials; Pavements;
Filing Info
- Accession Number: 01788505
- Record Type: Publication
- Files: TRIS
- Created Date: Nov 17 2021 2:28PM