Please use this identifier to cite or link to this item:
Title: Relationship between abrasion, fragmentation and thermal weathering resistance of aggregates: Regression and artificial neural network analyses
Authors: Gökalp, İslam
Kaya, Orhan
Uz, Volkan Emre
Keywords: Abrasion
Artificial neural network
Thermal weathering
Publisher: Springer
Abstract: For being used in pavement construction, properties of aggregates must satisfy the minimum requirements specified by highway agencies or institutions. The properties of the aggregates are determined by many tests lasting anywhere between a couple of hours to a few weeks depending on the type of the test. If good correlations can be established between the tests taking longer time and the ones taking comparably shorter time, there might be no need to conduct these longer time-taking tests for the sake of time. The aim of this study is to investigate the relationships between abrasion, fragmentation, and thermal weathering resistances of different aggregate types. To accomplish this aim, aggregates with different origins (natural and slags) were tested and correlative analyses utilizing regression analysis and artificial neural network (ANN) models were performed to establish relationships between the results of these test methods. It was found that good correlations can be established especially with ANN models and significant amount of time and effort can be saved with these developed models. © 2023, The Author(s), under exclusive licence to Chinese Society of Pavement Engineering.
Description: Article; Early Access
ISSN: 1996-6814
Appears in Collections:Civil Engineering / İnşaat Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
  Until 2026-01-01
2.58 MBAdobe PDFView/Open    Request a copy
Show full item record

CORE Recommender

Page view(s)

checked on May 20, 2024

Google ScholarTM



Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.