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Image of My Model
Design Iteration with Radiance Gradient Plot
Image of Your Results
Output Table with Input parameters and output metrics (best 3 highlighted in blue)
Optimization Scheme Table (best 3 highlighted in blue)
To complete this module, the Ladybug DirectSunHours and IncidentRadiation nodes were utilized as the two new metrics as well as a cost function similar to that in the examples. The additional metrics utilized the Ladybug create Sunpath and SkyMatrix nodes to calculate sunlight interacting with the building form. A San Francisco .epw file was imported to GH to simulate the weather and sun pattern in downtown SF. The grid spacing for both the DirectSunHours and IncidentRadiation was set to 25 but can be further refined used a number slider in the GH graph. The building height was kept at a constant 750 feet.
Once the sun pattern was created in the modeling environment, additional Brep solids were defined to act as surrounding buildings to inhibit views and direct sunlight to the building, much the same a building downtown would be surrounded by.
The loop structure was modified to loop through combinations of two parameters: middle and top scale factors. Previously, the middle scale factor and the middle rotation were tested but the results lacked diversity. By changing to top and middle scaling, the results diversified to cover a wider range of output metrics.
Once the outputs metrics were extracted to Excel, the optimization "scheme" was performed. First, the Direct Sun hours and the Radiation were divided by the cost to get a unit value per dollar. This procedure was performed because it is assumed that the clients want to maximize both the sun hours and the radiation for the tenants of the building. Next a simple check was performed on the square footage of each design to meet criteria 1,200,000<SF<1,500,000. This ruled out multiple samples (shaded in red in table above). Next, the design values per dollar were normalized by dividing by the maximum value. This was mostly done to display numbers on a scale 0-1 instead of e-10. They are simply easier to work with and visualize. Lastly, the two design metrics sun hours/$ and radiation kWh/$ where added together for each building and the largest value of a passable design was considered the optimal. Once again, the two normalized values are unitless metrics per dollar that wan to be maximized to get the "most bang for your buck."
It is assumed that the tenants would want the most sunlight hours/radiation gain and the lowest cost for the square footage available in the building, thus the normalized metrics were maximized. Sunlight is preferred to artificial lighting and radiation keeps the building warm (potentially using thermal mass as a heating source instead of artificial heaters). Using the limited list of input parameters the optimal was a middle scale factor of 0.5 and top scale factor of 1.1, creating an hourglass figure.