Prediction of thermal insulation performance of concrete lining with multi-component solid waste aggregate under freeze–thaw action based on machine learning

Puntos clave

• Thermal insulation performance improves with specific waste aggregate compositions under freeze-thaw conditions.
• Machine learning models demonstrated over 85% accuracy in predicting insulation performance for different aggregate combinations.
• Assessment using machine learning on multiple datasets revealed significant insights into material properties and performance.
• Findings suggest machine learning can optimize the use of solid waste aggregates for enhanced thermal insulation in construction.