Dynamic Modulus Regression Models for Cold Recycled Asphalt Mixtures

Cold recycling is an advantageous technique from economic and environmental perspectives for asphalt pavement rehabilitation, interventions, and maintenance. This work covered the investigation of dynamic modulus (|E*|) test models and their effects on cold recycled asphalt mixture (CRAM) |E*| data...

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Bibliographic Details
Main Authors: João Meneses, Kamilla Vasconcelos, Kazuo Kuchiishi, Liedi Bernucci
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Infrastructures
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Online Access:https://www.mdpi.com/2412-3811/10/6/143
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Summary:Cold recycling is an advantageous technique from economic and environmental perspectives for asphalt pavement rehabilitation, interventions, and maintenance. This work covered the investigation of dynamic modulus (|E*|) test models and their effects on cold recycled asphalt mixture (CRAM) |E*| data fitting, considering different mixture parameters such as asphalt binder type and content, active filler type and content, aggregate gradation, reclaimed asphalt pavement content, and curing conditions. Multiple mixtures from a dynamic modulus test database were fitted using six different regression models and the results were analyzed by means of different residuals analysis. Finally, the effects of CRAM composition on |E*| data were graphically assessed. For the analyzed specimens, two models were found to be the most adequate for CRAM’s |E*| data regression. The analysis of CRAM composition showed a strong relation between the compaction method and the stiffness of CRAMs.
ISSN:2412-3811