Architecture Engineers Award

Circular economy strategies in the construction sector increasingly emphasize the reuse of structural elements from obsolete buildings to reduce environmental impact and resource consumption. However, implementing these strategies is often constrained by limited information on building composition, particularly at the structural element level. Conventional estimation approaches are typically deterministic, subjective, or lack sufficient detail to support accurate material recovery planning. This study introduces a probabilistic modelling framework to improve the estimation of structural element dimensions and material quantities in residential timber buildings. Bayesian Network Framework for Structural Estimation The research proposes a probabilistic modelling approach based on Bayesian Networks (BNs) to estimate structural characteristics under uncertainty. Bayesian Networks provide a structured framework that represents relationships among variables through probabilistic dependenc...

The construction industry is increasingly required to adopt sustainable materials as buildings grow in scale, complexity, and environmental impact. Simultaneously, post-consumer clothing waste has become one of the fastest-growing solid waste streams worldwide. Due to its heterogeneous composition and low biodegradability, textile waste poses significant environmental challenges and is often underutilized in recycling systems. This study investigates the architectural potential of unsorted clothing waste as a scalable resource for developing multifunctional interior materials capable of providing both acoustic control and thermal insulation in building environments. Material Processing and Fabrication Method A simplified thermo-mechanical processing technique was developed to convert heterogeneous textile waste into fiber-based insulation panels. The process eliminates the need for chemical additives or prior sorting of materials, making it more feasible for large-scale waste recycl...