Step 1 - Generative Design Framework
Step 2 - Generative Design Study
For my generative model, I will manipulate the design variables of base width, building height, and top rotation to see their impacts on the outputs on:
- Operational Energy Cost, which is a function of the glazed area on building walls. This value was minimized.
- Volumetric Rent, which is a function of rentable building volume. This value was maximized.
- Directness of Views, which considers the additional rent you can charge for the amenity of a good view of a landmark. This value was maximized.
I also had constant values that set the amount of energy cost per unit area of glazing, rent per unit volume, and a base length.
Step 3 - Generative Design Study Results
In the above scatter plot, the x-axis is energy cost, the y-axis is volumetric rent and the size of the data point is the magnitude of directness of view. The scatter plot shows a direct relationship between increase in energy costs and increase in volumetric rent, which makes sense as a building with a larger base width or a greater height would see increases in both of these outputs. The directness of view output was a less direct relationship. There is a cluster of instances with higher directness of views value at the bottom left of the graph. These represent shorter, smaller, and lower surface area buildings that have a more direct view of the landmark as a summation of all building surfaces. These buildings are not as likely to be built because they are smaller developments that don’t maximize the usefulness of the site.
For my design decision, I would look for something that meets my minimum volumetric rent or floor area for the development and then see which of these options minimizes energy cost and maximizes view. Anything to the left of the trend line is also more attractive to me.
Dynamo Study Graph
