Revolutionizing Concrete: Sustainable Mix Design with AI #sciencefather

This research explores the sustainable mix design of recycled aggregate concrete (RAC) using machine learning (ML) and big data analytics. By incorporating recycled aggregates, this approach aims to reduce the carbon footprint of concrete production while maintaining its strength and durability. The study utilizes data-driven techniques to optimize the mix design, predict the carbon emissions of different concrete compositions, and propose sustainable alternatives. The use of ML models and big data analysis enables efficient decision-making in designing eco-friendly concrete mixes that align with global sustainability goals in the construction industry.

International Material Scientist Awards

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