Triaxial resilient modulus regression models for cold recycled asphalt mixtures

Abstract

Cold recycled asphalt mixtures (CRAMs) may present a compressive resilient modulus dependent on the stress state. Currently, there is no widespread consensus on a triaxial resilient modulus (TxRM) model for CRAM analysis. A widely accepted TxRM model would favour the analysis of CRAM’s layered pavement systems. This paper assessed the adequacy of different TxRM models of CRAM’s specimens with different compositions, aggregate gradation and physical characteristics. Based on the literature, three different TxRM models were selected. The models’ non-linear estimation was performed through Levenberg–Marquardt algorithm. Model selection analysis was based on residuals square sum root (RSSR) assessment. Ni et al.’s model was found to be the most adequate for CRAM’s TxRM modelling based on RSSR analysis. The model selection was done regardless of aggregate gradation, binder type/content, air void content, RAP content, TxRM values range, active filler type and curing time of the tested specimens.

KEYWORDS:

• Cold recycled asphalt mixture (CRAM)
• triaxial resilient modulus model
• non-linear regression
• recycling

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico – Brazil (CNPq); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil (CAPES) – Finance Code 001; Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP) – Process 2017/25708-7. Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo.