Planning Regulations and Modelled Constraints in BIM

Abstract

Planning regulations determine a substantial part of buildings, but their constraints are usually not included in the setup of a BIM model or used explicitly for design guidance, but only tested in compliance checks once a model has been made. This is symptomatic of wider tendencies and ingrained biases that emphasize tacit knowledge and assume that information in a project starts from scratch—an assumption that runs contrary to predesign information ordering practices, as well as to the findings of creativity studies. In terms of process control, it negates important possibilities for feedforward. The paper proposes that BIM and design computerization, in general, should avoid the generate-and-test view of design, the view of design knowledge as tacit, and the adherence to analogue workflows, but develop, instead, approaches and workflows that keep information explicit and utilize it to frame design problems. To demonstrate this, we describe an exercise in which the expectation that the geometric representation of planning regulations returns permissible building envelopes was tested on the basis of a large number of cases produced by students who each collected planning regulations for a particular plot of land in the Netherlands and modelled their constraints in BIM, using a workflow that can be accommodated within the scope of predesign information gathering in any project. The results confirm that, for a large part of Dutch housing, the representation of planning regulations in BIM returns the permissible building envelope, and, so, forms a clear frame for subsequent design actions. They also suggest that including such information in the setup of a model is constructive and feasible, even for novices, and produces a bandwidth view of project information that integrates pre-existing information in a BIM workflow through feedforward. By extension, they also indicate a potential for a closer relation between analysis and synthesis in BIM, characterized by transparency and simultaneity, as well as the thorough understanding of problem constraints required for both efficiency and creativity.