Glazing vs Shading Optimization (the one I chose to test):
Design Variables: Building height, building width, roof overhang depth, glazing-to-wall ratio
Evaluators: Glazing area, shading effectiveness, total material cost
Tradeoffs:
More glazing + more overhang = better shading, better views and daylighting, higher material cost (could lead to lower energy use cost)
More glazing + less overhang = better views and daylighting, worse shading, lower material costs (could lead to higher energy use cost)
Less glazing = worse views and daylighting better shading, lower material cost, (could lead to lower energy use cost)
Structural Grid Optimization:
Design Variables: Column spacing, slab thickness
Evaluators: Structural material cost, floor deflection, usable open space
Tradeoffs:
Wider spacing + smaller slab thickness = more usable space, more layout flexibility, higher material cost, higher deflection
Tighter spacing + larger slab thickness = less deflection, higher material cost, less usable space
Wider spacing + larger slab thickness = more usable space, less floor-to-ceiling height, more layout flexibility, higher material cost, less deflection
Tighter spacing + smaller slab thickness = less deflection, higher material cost, less usable space, less floor-to-ceiling Height
Glazing Performance Optimization:
Design Variables: Solar Heat Gain Coefficient (SHGC), Visible Transmittance (VT), glazing-to-wall ratio
Evaluators: Thermal performance, daylighting, glazing material cost
Tradeoffs:
High VT + low SHGC + high glazing-to-wall ratio = more daylight, moderate solar gain, higher cost
Low VT + low SHGC + low glazing-to-wall ratio = less daylight, less solar gain, lower cost
High VT + high SHGC + high glazing-to-wall ratio = more daylight, more solar gain, moderate cost
‣
Step 2 - Generative Design Study
Glazing vs Shading Optimization (the one I chose to test):
Design Variables:
Building height: Affects the vertical extent of glazing and shading
Building width: Impacts facade surface area and potential window placement
Roof overhang depth: Controls shading on upper-level glazing
Glazing-to-wall ratio: Amount of the facade that is transparent versus opaque
Evaluators:
Glazing area: values affects daylighting and solar heat gain
Shading effectiveness: how well roof overhangs shade the glazing systems
Total material cost: Includes wall, glazing, and shading system costs, changes based on glazing quantity and overhang depth
Tradeoffs:
Higher glazing-to-wall ratio improves daylighting and views, but raises the material cost due to more glass and supporting systems, and reduces passive shading unless mitigated by larger roof overhangs.
Deeper overhangs offset solar heat gain, improving comfort and energy performance, but also add cost and potentially impact aesthetics or structural considerations.
High glazing and shallow overhangs maximizes transparency and daylight but can raise material cost somewhat and lead to high solar heat gain.
Low glazing with deep overhangs minimizes solar gain and construction cost but compromises daylight and view quality.
‣
Step 3 - Generative Design Study Results
Results:
Results with Filters:
Explanation:
This scatterplot maps glazing area on the x-axis and shading effectiveness on the y-axis, with total material cost shown through the size and color of each point (larger and darker points represent the more expensive options). I originally chose the light blue dot at the top as the most optimal result because it has the highest shading effectiveness and one of the highest glazing values, meaning it is a front runner in terms of both passive shading and access to daylight, which are my main priorities.
Because of how high it was performing in shading effectiveness and glazing area, I assumed this option would be one of the most expensive. However, when I applied filters to highlight only the top-performing options, (shading effectiveness over 100 and glazing area over 100,000) I realized that the dot I picked also has the lowest material cost of the remaining 3.
The scatterplot was useful in helping me visualize how each design choice impacted multiple outputs at once, and it made the tradeoffs very clear. It also confirmed that the design I first identified as a top contender based on performance also ended up being the best choice for cost reduction. If I were a designer filtering through design options to pick based on this graph, I would use the filter and specifically look for options with good glazing area and solid shading effectiveness at a reasonable material cost. I’d probably prioritize designs that lean toward better shading (to reduce long-term energy use) but still offer enough transparency to keep the interior bright and connected to the outside. The goal wouldn’t be to max out one evaluator but to find a balanced configuration that can perform well across all three metrics.
