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- For 2 or More Units: Create Two New Evaluator Nodes
- Metric 1: Construction Cost (USD)
- Input parameter 1: Top Height
- Input parameter 2: Top Rotation
First, I set the height of the tower top to increase from 672 ft to 744 ft, generating a sample every 12 ft. I also set the Top Rotation to switch between 20° and 30°. Then, I used List.CartesianProduct to combine the Top Height list and the Top Rotation list, and after flattening it with List.Flatten, I connected it to BuildingForm.EvaluateValueByFloorAreaForTwoInputs to generate the blocks one by one and evaluate the corresponding indicators.
I use a Code Block to define four key constants: 500 (ground-level unit cost), 1000 (top-level unit cost), 744 (the upper limit of Top Height in this case), and 12 (level-to-level height). Then, I use Compute Series of Values for Each Level to generate a unit cost list from 0 ft to 744 ft, increasing by 12 ft each time. Next, in Compute Value at Each Level, I multiply the mass floor area of each level by the corresponding unit price. Finally, I use Math.Sum to summarize and obtain the total construction cost of the entire tower.
The above screenshot illustrates the example node (Step 4A & 4B) for calculating construction cost. To add innovation and my own perspective, I first extract the Top Height and Gross Floor Area columns, then apply a more concise formula: Construction Cost = FloorArea * (500 +(TopHeight / 2 / 744) * 500). This expression averages the linear unit-cost curve—USD $500/SF at 0 ft rising to USD $1000/SF at 744 ft—thereby reducing node count and speeding execution. With my approach (Step 4C & 4D), the resulting construction cost is virtually identical to the value produced by the example node in Step 4A & 4B.
Therefore, I exported results to excel and got Top Height, Top Rotation, Gross Floor Area, Gross Surface Area, Gross Volume and Construction Cost (metric 1) as below table (results rounded to two decimal places):
- Metric 2: Surface to Floor Area Ratio
I use the Surface-to-Floor Area Ratio (Gross Surface Area / Gross Floor Area) to indicate how many square feet of façade are required for each square foot of floor area. A larger value means more envelope per usable area, leading to higher cladding cost and greater heat loss, whereas a smaller ratio indicates a more compact, economical form that meets the owner’s goal to minimize envelope area.
In Dynamo I first apply List.Transpose to convert the row-based list from Step 3B into a column-based list. Then two List.GetItemAtIndex nodes pull out the required columns: index 2 for Gross Floor Area and index 3 for Gross Surface Area. Finally, a Code Block computes ‘surfaceArea / floorArea’, producing the Surface to Floor Area Ratio for each case.
Therefore, I exported results to excel and got Top Height, Top Rotation, Gross Floor Area, Gross Surface Area, Gross Volume and Construction Cost (metric 1) and Surface to Floor Area Ratio (metric 2) as below table (results rounded to two decimal places):
- Your answers to the Points to Ponder questions for each stage of the assignment that you completed.
Do the new evaluation metrics that you’ve designed capture the meaningful differences between the building form alternatives?
Yes. Construction Cost directly reveals how variations in Top Height and Top Rotation affect overall expenditure, making it clear when minor geometric changes trigger major cost increases. Surface-to-Floor Area Ratio quantifies envelope efficiency, so towers of equal height but different massing exhibit distinct values. Together, Construction Cost and Surface-to-Floor Area Ratio identify cost-inefficient or façade-heavy designs far better than looking at Floor Area or Volume alone.
What other metrics would be useful to compute to help understand and make the case for which alternatives are truly better than others? I think we could also include a Directionality metric to evaluate façade orientation toward key viewpoints or landmarks. A simplified model could estimate Operational Carbon Avoided and Pollution Potential, quantifying each massing’s long-term carbon-reduction and emissions benefits. Using existing geometry, we can construct Surface-to-Volume Ratio and FloorArea-to-Volume Ratio to assess compactness. Finally, calculating Solar Insolation Potential would let us compare annual sunlight exposure across the schemes. Other helpful metrics include sun hour, daylight potential, wind, microclimate, noise, solar energy, and embodied carbon—all of which can be computed directly in Autodesk Forma to strengthen the case for which alternatives are truly superior.