A Contribution to Urban Mining Potential Through a Probability-of-conformity-based Indicator for Optimizing Reuse of Cut Concrete Slabs

Reusing concrete slab elements offers a promising urban mining strategy to reduce the environmental footprint of constructions. Cast-in-place concrete slabs represent a particularly large resource, yet their reuse is complicated by uncertainties regarding geometry, load-bearing capacity, serviceability, and fire resistance. To capture these uncertainties, this paper introduces the Urban Mining Potential (UMP) as a novel environmental indicator quantifying the expected CO₂ savings from reusing urban mining slabs compared to conventional construction. The UMP is defined by combining process-related efforts with probabilities of conformity (PoCs), which reflect the likelihood that urban mining slabs meet technical requirements of new structures. A recursive optimization algorithm is developed to solve the two-dimensional knapsack problem of cutting monolithic slabs into urban mining slabs, efficiently identifying cutting patterns that maximize the UMP. Sensitivity analyses assess the influence of the PoCs and material testing. Results from four case studies show that incorporating PoCs increases the UMP by at least 30% (5th percentile), while material testing of concrete cover significantly improves outcomes; in contrast, testing of compressive strength and reinforcement yield strength has only minor effects. The proposed methodology provides a probabilistic, optimization-based framework to maximize environmental benefits of concrete slab reuse, advancing urban mining as a viable business model for CO₂ reduction, resource efficiency, and waste minimization.