Modeling Response of Physical, Mechanical, and Durability Properties of Recycled Aggregate Concrete at Varying Replacement Ratios

Barisua E. N; B.G Jephter

doi:10.56201/ijemt.vol.12.no2.2026.pg434.451

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Modeling Response of Physical, Mechanical, and Durability Properties of Recycled Aggregate Concrete at Varying Replacement Ratios

Barisua E. N, B.G Jephter

Abstract

This research aimed to explore the physical, mechanical, and durability properties of concrete made from recycled aggregates at different replacement levels, while also creating a framework based on data to encourage its broader use and sustainable implementation. Descriptive statistics indicated that the mechanical properties of concrete with recycled aggregates typically followed a normal distribution, featuring an average compressive strength of 35.39 MPa, a tensile split strength of 3.30 MPa, and a flexural strength of 4.14 MPa, reflecting a moderately high structural performance aligning with standard concrete metrics. Correlation assessments indicated a strong inverse relationship between the water-cement ratio and strength characteristics, a moderate positive correlation between the age of curing and strength enhancement, and weak negative relationships between the content of recycled aggregates and mechanical performance, confirming that an up to 50% substitution can sustain adequate structural integrity. A four-layer feedforward Artificial Neural Network comprising two hidden layers, each with 32 neurons, utilizing ReLU activation and Adam optimization to analyze the nonlinear interactions among various mix parameters while simultaneously predicting compressive, tensile, and flexural strengths. The ANN model successfully represented the intricate behavior of recycled aggregate concrete and facilitated multi-objective optimization, resulting in balanced mixed designs that promote sustainability without considerable loss in performance. Additional comparative regression analysis indicated that polynomial models are more effective than linear models in capturing nonlinear relationships in strength, especially between compressive strength and tensile strength. In conclusion, the results indicate that data-driven modeling delivers both forecasting accuracy and prescribed capabilities, supporting the performance-oriented and sustainable design of recycled aggrega

Keywords

Recycledaggregateconcrete; Sustainableconcrete & production

References

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Modeling Response of Physical, Mechanical, and Durability Properties of Recycled Aggregate Concrete at Varying Replacement Ratios

Abstract

Keywords

References

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