Abstract

Foundry sand (FS) is produced as a waste material by metal casting foundries. It is being utilized as an alternative to fine aggregates for developing sustainable concrete. In this paper, an artificial intelligence technique, i.e., gene expression programming (GEP) has been implemented to empirically formulate prediction models for split tensile strength (ST) of concrete containing FS. For this purpose, an extensive experimental database has been collated from the literature and split up into training, validation, and testing sets for modeling purposes. ST is modeled as a function of water-to-cement ratio, percentage of FS, and FS-to-cement content ratio. The reliability of the proposed expression is validated by conducting several statistical and parametric analyses. The modeling results depicted that the prediction model is robust and accurate with a high generalization capability. The availability of reliable formulation to predict strength properties can promote the utilization of foundry industry waste in the construction sector, promoting green construction and saving time and cost incurred during experimental testing.

Highlights

  • Introduction iationsConcrete is at the top of the list for most widely used material in construction and serves as the backbone of the modern construction industry

  • A widely dispersed database was collected from the literature

  • The model was validated by verifying various statistical benchmarks such as correlation coefficient, root mean square error, root squared error, mean absolute error, and relative root mean square error

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Summary

Introduction

Concrete is at the top of the list for most widely used material in construction and serves as the backbone of the modern construction industry It is a heterogeneous material containing cement, fine aggregate, coarse aggregate, water, and admixtures as five major constituents. The production of one ton of concrete releases up to 20% (by weight) of greenhouse gases into the atmosphere. This percentage can have a detrimental impact considering the global concrete production of approximately 30 billion tons. The application of green concrete is fast gaining attention.

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