AI in the Design Process

 - Iuliia Osintseva, Martin Bielik, Sven Schneider, Reinhard König

New digital algorithms support architects by partially automating the generation and analysis of design variants in multi-storey residential building construction.

AI in the Design Process
The algorithm selects the variants (left) from the variant pool (right). Centre (green): Settings for generating building typologies. © Bauhaus-Universität Weimar mit Rehub

Among the requirements that buildings must fulfil are not only energy and cost efficiency, user comfort and convenience but also urban development rules concerning aspects such as building setbacks, urban density, building lines and visual relationships. Keeping all these complex interdependencies in mind when seeking a high-quality, architecturally creative solution has always presented architects with a design challenge, which they can now overcome with the support of new digital tools: AI algorithms that automatically create and analyse design variants. They enable, for example, knowledge of geometric and semantic contexts and interpretation of building parameters to be brought together using spatial analysis. A team from the Bauhaus University Weimar working with project partners Rehub and DecodingSpaces has developed algorithms of this type based on Rhino Grasshopper. The result is a generation and evaluation system for the design of residential buildings. The algorithms perform the time-consuming parts of the design process and partially automate creative solution finding.

Variants efficiently created

The generation system is based on a hierarchical approach in which the design is created in steps - beginning with the building volume then the division into apartments and their individual floor plans. To define the building volume, the system looks at common residential building typologies such as perimeter block, row and free-standing. Next follow further steps such as the creation of set-backs, building subdivision or the introduction of additional blocks in an inner courtyard. The resulting volumes are divided into apartments considering common circulation typologies such as landings, halls and access balconies. Then the software looks at how many and what sizes of apartments are possible based on the desired housing mix, arriving iteratively at a feasible geometric division. The final step generates a suitable floor layout for every apartment. Using a database of existing floor plans, the AI-trained algorithms create new variants adjusted to the desired room sizes, geometry of the external walls, positions of entrances and other constraints.

Automated analysis

The evaluation of residential buildings considers aspects such as the density of development, energy requirement or questions of user convenience and comfort. The digital tools enable the required performance indices to be quickly calculated. The results of the analyses are arrived at objectively and not distorted by cognitive bias or individual opinion. Solar analyses calculate, for example, lightness levels in each room of a building and whether they have sufficient daylight and direct solar radiation. Visibility analyses quantify how well specific spaces or objects can be seen and recognised. The results supply information, for example, on how easily users find their way around complex buildings, the level of privacy of individual rooms and the quality of the view out. Accessibility analyses assess the movement patterns of building users. Which rooms have potential as communication zones or private withdrawal space can be derived from the results.

Design space exploration

The automatic generation and analysis of design variants opens new possibilities for compromise solutions arising out of opposing requirements. The researchers use interactive visualisation methods for design space exploration. The design space comprises all the created variants and the indices arising from the analyses. A parallel coordinate system displays the design variants with several Y-axes. Each axis represents an evaluation criterion such as density, solar energy admitted or cost. The designer then selects a range of values for a criterion, for example high solar gain, and the system shows all the variants with this characteristic. Applying similar limits to the values for different criteria allows the designer to identify which variants satisfy the most requirements. Correlations between analysis criteria become transparent, and it can be seen whether the design requirements can be fulfilled and the extent to which the various design strategies have been useful. Interested designers can download the software free from the DecodingSpaces web platform.


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