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  • Lee Pei Shang

Generative Spatial Arrangement

Updated: May 21, 2022

An Introduction

Starting something new wasn't an easy task, especially when it comes to putting your ideas into a profitable business model. And for this first computational design project showcase, we want to design an algorithm that helps designers in automating their design. Something conceptual, simple, yet self explanatory. Generative design seemed like a great start for this journey of computational designing.

Generative design comes in all sort of sizes, and for this research project, we look into generative spatial arrangement because usually that's the starting phase for architects and designers when it comes to designing space for the users. Generative design is a good method for automating mundane task and leave designers and planners more time and energy to express creativity.

For this I've split all generative spatial arrangement into two groups;

  1. uniform spatial arrangement

  2. non-uniform spatial arrangement

Generative spatial arrangement is a great start because the latter one would require a commissioned project and a very specific set of design briefs and instructions. For those who are interested, this topic will be further discussed in the future.

A Generated Car Park

The term "uniform" means something that forms in a group that has in a sense of order. Some examples that use this form of subdivisions spatial arrangement order includes car parks, apartment units, hospital wards, etc.

That is when the idea of generating an outdoor car park design came to plan.

Car parks are probably the least exciting part of designing physical places. Here we look for a solution to make something more intuitive for its users;

Check out this video below to see how it works:

Here's the final algorithm:

Although the final system still have a lot of improvement, but in this research model we made something that is able to fill in the box with our desired context which gave us a brief concept of how generative design works and paved roads for the future of computational design.


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