Sustainability and extreme environmental adaptability have always been research hotspots in the field of building materials.
Geopolymer concrete (GPC) has become an ideal substitute material for traditional Portland cement concrete (OPC) due to its advantages of low carbon emissions and utilization of industrial by-products.
Especially in special scenarios such as industrial plants and high-temperature work areas, their high-temperature mechanical properties directly affect structural safety.
This article combines experimental testing and machine learning (ML) modeling to systematically explore the variation law of compressive strength of GPC under high temperature environment, providing key technical support for its engineering application.
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