The original structure can be seen on the left and the optimized can be seen on the right.
The bulk of the code remained the same as last week’s module, however I added a third input parameter to vary, so now the variables are building height, rotation, and mid height. The mid height parameter was added as an input so that I could see the impact of different mass distributions up the height of the structure. The two evaluation metrics I measured were the max interstory drift ratio and the maximum seismic base shear. These are two parameters that are used in seismic engineering and can serve as estimates for potential nonstructural and structural damage, respectively.
In the custom node I made for last week’s project (BuildingFormAnalysis) I added another custom node which can be seen below (Sa_and_IDR_Estimates). Since both of these evaluation metrics use similar inputs for their calculations, I grouped both evaluation metrics into a single custom node.
The main calculations done in this node use a python code block (here it was renamed to “Modal Analysis”) and it runs a python script that analyses the structure based on the mass distribution and a uniform stiffness.
This script outputs the interstory drifts and some other building parameters that are used in a later python script to evaluate other aspects of the building. These parameters are fed into the next python code block (seen below). This node outputs the seismic base shear coefficient.
While the interstory drifts are a good indication of the nonstructural damage the building could face in a seismic event while the seismic base shear coefficient can be a good indication of the structural damage it could incur (I’m just pretending that wind doesn’t exist because it would definitely govern the design for a building this tall). After both the interstory drifts and seismic coefficients are calculated, they are input into a weighting function. I decided that both the structural (seismic coefficient) and nonstructural (interstory drift) terms were equally important as they can both cause significant damage in their own regards, so I added a 0.5 coefficient to each and added them together (the interstory drift parameter was multiplied by 10 in the python script so that it would be on a comparable order of magnitude to the seismic coefficient, so multiplying by 0.5 roughly equalizes the metrics).
The data for all scenarios was then exported to Excel and conditional formatting was added to rank the results.
This table shows that there are several buildings that act fairly well compared to the rest, with the best scoring structure resulting from the 580’ building with a rotation of 90 degrees and a mid height of 200’.
Overall BuildingFormAnalysis custom Node:
Overall Script:
