Abstract
The growing rate of plastic waste generation is becoming a global concern due to the adverse impacts of plastics on the environment. Recycling and reusing plastic waste has been identified as a sustainable approach to mitigate the environmental concerns associated with landfilling of plastics. This study aims to evaluate the effect of the addition of waste polyethylene terephthalate (PET) on the thermal conductivity, resilient modulus, and strength properties of recycled concrete aggregate (RCA) as an alternative pavement construction material. A suite of laboratory tests including thermal conductivity, repeated load triaxial, unconfined compressive strength, and triaxial shear tests were undertaken to evaluate the effect of up to 10% waste PET on the performance of RCA as a pavement material. A relatively simple, yet robust, resilient modulus constitutive model was developed for RCA/PET blends using the multivariate adaptive regression spline (MARS) approach. The proposed model incorporated thermal conductivity, unconfined compressive strength, confining stress, and deviator stress for modeling the resilient modulus response of the RCA/PET blends. A unique feature of the developed model is the incorporation of thermal conductivity as model input. Several verification phases were conducted to validate the accuracy and reliability of the MARS model. The performance of the MARS model was compared with a neural network model to further evaluate the predictive capability of the developed model. The results indicated that the MARS model was an efficient and accurate tool in predicting the resilient modulus of recycled material blends. The experimental and numerical investigations aimed to provide novel insight into the thermal and mechanical properties of recycled materials to expand their usage in pavement and geotechnical applications.
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Ghorbani, B., Yaghoubi, E. & Arulrajah, A. Thermal and mechanical characteristics of recycled concrete aggregates mixed with plastic wastes: experimental investigation and mathematical modeling. Acta Geotech. 17, 3017–3032 (2022). https://doi.org/10.1007/s11440-021-01370-y
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DOI: https://doi.org/10.1007/s11440-021-01370-y