Abstract
Coconut shell (CS) aggregates are naturally porous, allowing them to absorb up to 20–24%. However, treating the CS may decrease its porosity, potentially leading to a reduced penetrability of chloride ions in the resulting concrete. Six treatments were administered to the CS to explore this possibility, and the resulting concrete made from the treated CS was assessed for chloride ion penetrability. The treatments included sago flour (SF), slaked lime (SL), acetic acid (AA), ferrous sulfate (FS), polyvinyl alcohol (PVA), and corn flour (CF). The study used a salt ponding test to investigate the chloride ion penetrability of concrete made with treated CS as coarse aggregate in comparison with untreated CS aggregate used in concrete. The findings indicate that the treatments applied to the CS enhance its potential use as a coarse aggregate in concrete production for reducing chloride ion penetration. In this research endeavor, an artificial neural network (ANN) model was utilized to anticipate the compressive strength of untreated and treated coconut shell concrete. The findings yielded by the ANN model demonstrated remarkable precision, as evidenced by an R2 value of no less than 0.99, in projecting the compressive strength of the two concrete types.
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The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
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T. Thilagashanthi: Investigation, Data curation, Formal analysis, Software, Writing – original draft. K. Gunasekaran: Conceptualization, Methodology, Supervision, Writing – review & editing. K.S. Satyanarayanan: Conceptualization, Supervision, Validation, Visualization.
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Thilagashanthi, T., Gunasekaran, K. & Satyanarayanan, K.S. Assessment of chloride ion penetrability and compressive strength prediction in concrete with treated coconut shell aggregates using experimental and ANN approaches. Asian J Civ Eng 24, 3641–3652 (2023). https://doi.org/10.1007/s42107-023-00740-z
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DOI: https://doi.org/10.1007/s42107-023-00740-z