Empirical Quantification and Prediction of Building Component Lifespans with Graph Neural Networks
Extending the service life of existing buildings and their components is essential for slowing resource loops in circular construction. While overall building lifespans are relatively well understood, the actual service lives of individual components remain underexplored due to limited empirical data. This study addresses this gap by analyzing and modeling building component lifespans using real-w
