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

Hao Hua, Ludger Hovestadt, Qian Wang

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Front. Archit. Res. ›› 2024, Vol. 13 ›› Issue (3) : 639-649. DOI: 10.1016/j.foar.2024.02.001
RESEARCH ARTICLE

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

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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.

Keywords

Flexible housing / High-rise apartment / Data driven / Computational design / Wall-frame structure

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Hao Hua, Ludger Hovestadt, Qian Wang. Flexible high-rise apartments with sparse wall-frame structure: A data-driven computational approach. Front. Archit. Res., 2024, 13(3): 639‒649 https://doi.org/10.1016/j.foar.2024.02.001

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2024 2024 The Author(s). Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.
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