Flexible high-rise apartments with sparse wall-frame structure: A data-driven computational approach

Abstract

Flexible housing resolves the fundamental conflicts between the long-standing structure and the evolving demands. We propose a computational method of optimizing the structural layout of high-rise residential buildings. Chinese high-rise apartment buildings have widely employed shear wall-frame structure in which one big room or multiple small rooms could occupy the same span. Fitting multiple floor plans into a fixed sparse scheme of shear walls and columns is feasible. We developed a computational framework to seek flexible structural schemes. A building scheme consists of a circulation core, shear walls, columns, and boundaries. The computer program automatically adapts floor plans to any drawn or generated scheme. Based on a large dataset of apartment layouts, the number of apartments that fit into a building scheme statistically reflects the flexibility of the scheme. If many hypothetical plans can fit into a wallframe structure in computer simulation, this structure could probably support several generations of unknown plans. Such a data-driven computational method provides the possibility of creating a one-to-many mapping between permanent structure and evolving apartment plans.

Key words： Flexible housing; High-rise apartment; Data driven; Computational design; Wall-frame structure