Evaluation of textile effluent treatment plant sludge as supplementary cementitious material in concrete using experimental and machine learning approaches

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The growing demand for readymade garments is leading to the production of a large amount of textile effluent sludge (TES) from wastewater treatment plants, which is currently disposed of as backfill, causing land and groundwater contamination. This scenario has prompted researchers to explore the use of industrial waste, such as TES, as a supplementary cementitious material (SCM) to mitigate the carbon footprint of cement production. Therefore, this study aims to investigate the fresh, mechanical, non-destructive characteristics, and predictive modeling of mechanical strengths of TES-based concrete. Machine learning models, including random forest (RF) and artificial neural networks (ANN), were utilized to predict compressive and tensile strengths from various input variables. This study also evaluated the alkalinity, specific gravity, oxide content, and surface area of TES. The findings showed a pH of 9.4 and a CaO content of 33.3 %, indicating TES's potential as an SCM. The research further investigated the properties of concrete with 5–20 % cement-replaced TES, using a total binder content of 488.1 kg/m3 and a water-binder ratio of 0.32. The fresh state properties of the 5–15 % TES incorporated concrete produced normal density concrete, with a slump of 100 ± 20 mm, Kelly ball penetration of 45 ± 7 mm, a compaction factor of 0.92 ± 0.05, and a fresh density of 2464 ± 152 kg/m3. At 28 days, concrete with 15 % TES replacement showed a compressive strength of 25.6 MPa and a tensile strength of 2.88 MPa, achieving 76 % of the strength activity index and 72 % of the relative tensile strength. However, the 15 % TES concrete displayed a water permeability coefficient of 4.4 × 10−12 m/s and an electrical resistivity of 31.5 kΩ cm, compared to the control mix's 2.0 × 10−12 m/s and 37.7 kΩ cm. However, the hardened properties declined significantly after replacing 15 % of cement with TES. The mechanical properties were also estimated using ultra pulse velocity and rebound hammer tests, showing a coefficient of determination (R2) higher than 0.87. The RF model demonstrated superior performance with an R2 value of 0.8802 for compressive strength and 0.8518 for tensile strength, outperforming the ANN model's R2 values of 0.8126 and 0.695, respectively. Scanning electron microscopy confirmed the consistent development of hydration products in the TES-enhanced concrete samples.