Abby Cripps

Link to Design Journal
Journal Entry For
Module 6 - Evaluate Your Alternatives
Created By
Abby Cripps
Property
Related to 120C/220C Students - Spring 2022 (1) (Related to Design Journal Entries | Winter 2022 (Linked Student))

2 Units

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I used the same tower (One WTC) as the previous module. For the two new metrics I choose, I decided to look at it from a structural perspective and a real estate perspective. I found the unscaled base shear of the structure and the first modal mass participation factor. I also found the internal rate of return (IRR) for the project.

Workflow:

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The above shows the overall workflow of my dynamo environment. I first select my Revit mass form and define my inputs for the custom nodes. The custom nodes calculate the gross floor area, gross surface area, gross volume, unscaled base shear, first modal mass participation factor, and IRR. The data is then formatted to be imported in excel. Color is also applied to the Revit mass for fun.

Custom Node 1 (Base Shear):

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The custom node is made into 6 different groups. The main groups are the mass floor area group and the python script.

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The python script takes the mass of the floors and the story stiffness as inputs. The mass and stiffness matrices are created. Then the eigenvalues are found and used to find the modal participation factors and base shear. The base shear is not scaled which makes it not usable for design but allows the engineer to know how different building shapes affect the base shear. Also, the first modal mass participation ratio is not often used in design explicitly but allows for the engineer to see how different building shapes will affect the needs of the structural design.

Custom Node 2 (Internal Rate of Return):

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This custom node is split into 8 groups. The node also uses the same mass floor group as the base shear node. The main groups were the construction value, construction time, NOI, and a python script to solve for the IRR.

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These nodes take the floor areas and convert them into construction costs for the building, construction length, and expected income post construction.

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A python script was used to calculate the cashflows from the project based on construction costs, construction time, and selling price. Using these metrics an IRR could be calculated. This is a very important project metric because without an acceptable IRR the developer will never build the project.

Excel:

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A python script was used to format the date into a list that could be exported to excel. Then the list was exported to excel using the above nodes.

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The final excel data is above. The higher tower top ratio has larger base shear and less first modal mass participation indicating a more involved structural design would be needed and the IRR is better for a lower tower top ratio which shows that is a more profitable project.