Original Model Form:
Best Model Form:
Notes for Pre Thoughts and work:
Dynamo Graphs and Node Logic:
Excel Charts Based on Data:
Analysis and Final Thoughts:
For this module I wanted to attack the Optimization a little bit different and focus on metrics that were not so normal. My building form is very unique and after pushing through several iterations of work to find out that some rotational forms did not work the way I wanted them too took some time to get them right. My main focus for the metrics was to focus on people per level. The goal was to calculate how many people could fit comfortably on each level. I think the math ratio I used was 1 person per 15 square feet of space. I called this Peeps/Floor. The other two main focuses were a bit more challenging to figure out. A lot of math was required and the goal was to see how much Co2 was in the walls and floor. Co2 is bad and the higher the number the worse it is for the environment. This is important because when you calculate how much glass, or other materials are on the façade of a building for “green purposes” you want to see how those levels vary from one building to another. All of the graphs above and screenshots show my work to figure out what building shape and height is qualified to be the best. The results are explained below:
- The best rotation is minimal - 20 in each case, meaning the less the building rotates the better off the building is.
- The optimized height is at 100 feet high
- The higher the building the smaller the amount of people
- The more you rotate the floors the less amount of people can fit in one level
These all make sense when you think about how the building form was created. I started off with an arrow shaped triangle that lofted into a mid sized triangle into a regular triangle. When the tower is twisted the floors become irregular.
The conclusion through the data shows that the best option (listed in pic 2 above) is a tower with 100 feet high and no rotation or minimal rotation for my building design. This exercise was extremely helpful in determining and learning what an Optimized Report Looks like and how for future buildings this node script can help determine those buildings metrics as well in a quick manner.
I’m curious now if I applied these metrics to my skyscraper (Parametric Biosystems 2 classes ago) what the Optimized version of that tower would be considering it is in New York City. It appears for my project that the lower the building the better, but I am not convinced yet if that is true for all buildings because some need more height to deal with overpopulation and other constraints. The question I am left with now is; in the field how do teams prioritize constraints and goals over what is proposed to be the “optimized design”, and how do they build what is right, if it does not follow the “Optimized Design”?