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An integrated evaluation of waste materials containing recycled asphalt fine aggregates using central composite design

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Abstract

This research examines the feasibility of using washed recycled fine aggregates (WRFA) as a substitute for natural virgin aggregates in concrete. The aim is to develop novel models, based on Response Surface Method (RSM) and Artificial Neural Network (ANN), for predicting compressive strength and optimizing the results in concrete pavement development. The Central Composite Design (CCD) approach is utilized to optimize the concrete's strength parameters, considering WRFA, Zirconia Silica Fume (ZSF), and Steel Slag (SS) content. The RSM model does not perform well for compressive strength and split tensile strength, prompting the development of an ANN model to enhance prediction accuracy. The optimal proportion of training, testing, and validation datasets is determined as 70%, 15%, and 15% respectively. The ANN model, evaluated using Coefficient of Determination (R2) and Mean Square Error (MSE), outperforms the RSM model with higher prediction accuracy and better model fit. The findings highlight the potential of WRFA in concrete mixes, offering the ability to achieve desired strength levels surpassing conventional concrete. This research underscores the viability of WRFA as a sustainable construction material, supporting the development of environmentally friendly concrete pavements.

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Data availability

Some or all data, models, or code generated or used during the study are available from the corresponding author by request.

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Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology, Jamshedpur, 831014, India

    M. K. Diptikanta Rout, Kumar Shubham & Abdhesh Kumar Sinha

  2. Department of Civil Engineering, National Institute of Technology, Durgapur, 713209, India

    Sabyasachi Biswas

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  1. M. K. Diptikanta Rout
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  2. Kumar Shubham
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  3. Sabyasachi Biswas
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  4. Abdhesh Kumar Sinha
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Contributions

MKDR: Writing, original drafting & Data Interpretation. KS: Model Development, Drafting & Data Curation. SB: Conceptualization, Methodology & Supervision. AKS: Editing, Methodology, & Supervision.

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Correspondence to M. K. Diptikanta Rout.

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Rout, M.K.D., Shubham, K., Biswas, S. et al. An integrated evaluation of waste materials containing recycled asphalt fine aggregates using central composite design. Asian J Civ Eng 25, 1007–1025 (2024). https://doi.org/10.1007/s42107-023-00828-6

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