Advanced machine learning techniques for classification of recycled aggregates

This topic will focus on the application of advanced machine learning methods for the classification and characterization of recycled aggregates (RA) used in sustainable concrete production. The research will explore integrating machine learning models with sensor technologies, such as hyperspectral imaging, to improve the sorting of construction and demolition waste. Additionally, the study will involve micromechanical modeling of interfacial transition zones in recycled aggregate concrete and large-scale laboratory testing to assess the mechanical properties and durability of concrete made with RAs. This project aims to contribute to more efficient recycling practices and sustainable materials in the construction industry.