Quantitative evaluation of the relationship between physical parameters and building demolition or adaptation outcomes

Building adaptation and re-use can contribute to a circular and sustainable built environment, as existing buildings are adapted and the need for new construction materials is reduced. The “adaptability” of buildings has been widely studied; however, few of these studies are quantitative. This paper uses Artificial Neural Networks (ANN) and Logistic Regression (LR) models to explore relationships between the physical features of buildings and their demolition or adaptation outcomes. Source data were taken from 59 buildings that were either demolished or adapted in the Netherlands. After the models were created and validated, a series of sensitivity studies were conducted to evaluate relationships between physical parameters and building outcomes. The physical parameter with the strongest relationship to adaptation outcomes was demountability (ease of removal) of building service elements. The quantitative results were then compared to results from an adjacent qualitative study. The relationships observed from the quantitative sensitivity studies align well with the qualitative observations.

The Enigma of BIM

This position paper outlines a number of key questions concerning BIM (Building Information Modelling), as well as the arguments and the historical background behind them. These include the incomplete theory of BIM, the reasons for the emergence of understanding BIM as a panacea for all ills in AECO (architecture, engineering, construction and operation of buildings), the relation between BIM promise and BIM performance, some of the key misconceptions and misunderstandings concerning BIM, and fundamental concerns about what is assumed to be the future of BIM. The paper concludes by suggesting four themes for further discussion and research into the nature and future of BIM and of AECO computerization in general: BIM theory, implementation, the view from practice and legislation / policies.