#hydrationheat

This study explores smart machine learning models to predict hydration heat in energy-efficient cement composites, improving thermal control, durability, and sustainability. Data-driven insights reduce cracking risk, optimize mix design, and support greener construction practices for next-generation infrastructure materials using advanced algorithms, validation metrics, and real-time performance evaluation in practical scenarios. 🌱🤖🏗️

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