Please enter the following info in the fields above:
- Your Name (just type your name, then click Create to add yourself to the list)
- Paste the link to your BIM 360 folder in the BIM 360 Link field.
Image of My Model
Paste images or screenshots of your original building form and the recommended building form based on your evaluation and analysis
Image of Your Results
Paste images or screenshots of the Summary Tables (created in Word, Excel, Google Sheets, or some other data table tool) showing the input values tested and the values computed for each of the reported parameters.
Description
Enter a brief description outlining:
- your comparison/ranking rationale or approach
- an explanation of why you consider the recommended building form to be the “best” choice
For this assignment, I wanted to keep my comparisons simple by using the mass floor logic outlined in the examples. I mainly used two parameters, namely the floor area and surface area of each mass floor. I edited the mass floor node from the example to also output the external surface area of each mass floor, which would give the facade areas for all floors except the roof, where it would give the roof area. For the floor area, I applied it to two different custom nodes, one that would calculate the construction cost and one that would calculate the annual revenue from renting space within the building. For the construction cost node, I used the example node and modified the equation governing the floor-by-floor variation in cost to reflect a parabolic increase from the ground to the highest floor. I allowed options to input the "maximum height allowed/considered" which in this case would be 750, such that if the building was shorter than 750ft, the cost at the highest floor would not be the maximum cost possible. For the rent node, a similar logic was used, but again using a slightly more complicated equation for evaluating the rentable area, with inputs for controlling the percentage of area per floor that would be available for rent. The price of annual rent per sf was based on typical values for commercial buildings in San Francisco. For the surface area, to keep things simple, I wanted to consider how much earnings could be made from leasing portions of the facade to clients for attachment of billboards or for electronic screens/projections for advertisements. To make this evaluation more interesting, I set a minimum and maximum height for the advertisement-friendly surface area. This way, even if buildings exceeded the advertising height, they would be unable to gain more advertising utility, while shorter buildings would have the ability to advertise on their roof as well. Again, users would be able to control what percentage of the exterior surface area of the building per floor would be usable for advertising, as well as the cutoff point for maximum height of advertising, with the minimum being set to the "Tower Mid Height" since that portion is non-vertical. These three nodes were combined with the modified mass floor node into the evaluation node for single input from module 5. The results were then exported to Excel, where they were compared to see which option would break even most quickly with the construction costs via revenue from rent and advertising. Surprisingly, despite the significant increase in construction costs, the tallest structure, at 750 ft, broke even the fastest, most likely due to the fact that rent per sf was set to increase parabolically with height, becoming 4 times the rent at the ground floor at 750 ft. However, due to the expectations that the total sf in the building was to be between 1.2 and 1.5 million square feet, the option of 625ft ended up being chosen because it had the fastest break even time for structures that fell within those limits.