Alyssa Schwengel - Design Journal Entry - Module 7

• Design Decision 1 - Envelop Performance
• Design Variables
• Window-to-Wall Ratio: 0.2 - 0.8
• Overhang Depth: 0 - 10 ft
• Story Height: 9 - 15 ft
• Floor Area Depth: 15 - 45ft
• Evaluators
• Facade Cost
• Thermal Load
• Solar Penetration Ratio
• Overhang Structural Load
• Most Important Tradeoffs to Consider
• Higher WWR improves daylight but increases facade cost and thermal load
• Deeper overhangs reduce thermal load but add structural demand and reduce solar penetration for daylighting
• Taller story heights increase the glazing area and daylighting but increase both cost and thermal load
• Design Decision 2 - HVAC Zoning Strategy
• Design Variables
• Number of Zones per Floor: 2 - 16
• Perimeter Zone Depth: 3 - 6 ft
• Supply Air Volume in each zone (ACH): 4 -12
• Number of Floors per AHU: 1 - 4
• Evaluators
• Equipment Cost
• Total Duct Distribution Length
• Thermal Comfort
• Fan Energy
• Most Important Tradeoffs to Consider
• More thermal zones help to increase thermal comfort increase equipment cost
• Fewer zones reduce the cost but also reduce the thermal comfort
• Larger coverage for each AHU reduces the equipment cost but increases the fan energy
• Design Decision 3 - Tower Crane Selection
• Design Variables
• Crane Lifting Capacity: 4 - 16 tons
• Crane Boom Radius: 50 - 200 ft
• Number of Cranes on Site: 1- 3
• Rental Duration: 8 - 24 Weeks
• Evaluators
• Total Rental Cost
• Site Coverage Area
• Daily Lift Capacity
• Schedule Duration
• Most Important Tradeoffs to Consider
• Larger cranes that have longer booms improve site coverage and lift efficiency but increase the cost
• Adding more cranes greatly reduces the schedule but also greatly increases the rental cost while also introducing swing radius conflicts
• Shorter rental duration saves money but also creates a schedule risk if there are delays

For this design study, I decided to go with the envelope performance option where I study the impact of changing conditions on the building performance and cost. I chose this decision because it aligns most strongly with my own interests and because it was the option that would most make sense to visualize with Dynamo geometry which was a personal goal of mine for this module. Additionally, this study has four variables that are genuinely independent from each other that help to create real tension across the four evaluators which makes it suite for a Generative Design Optimization.

So, the objective of this study was to determine what combination of WWR, overhang depth, story height, and floor area depth would create the optimal solution that would minimize facade cost, thermal load, and overhang structural load while maximizing the solar penetration ratio on the southern facade to increase the daylighting potential of the building.

To do this I built a model in Dynamo that created a single-story cuboid geometry with a facade surface and overhang surface on the southern facade. I then utilized the following variables, constants, and evaluators.

Design Inputs:

• WWR: 0.2 - 0.8
• Overhang Depth: 0 - 10 ft
• Story Height: 9 - 15 ft
• Floor Area Depth: 15 - 45ft

Design Constants:

• Facade Width: 35 ft
• Floor Area Width: 35 ft
• Sill Height: 3 ft
• Solar Altitude Angle: 45 degrees (average sun angle throughout the year)
• Glazing Unit Cost: 28 $/sf
• Wall Unit Cost: 14 $/sf
• Overhang Unit Cost: 28 $/sf
• Solar Heat Gain Coefficient: 0.4
• Overhang Unit Weight: 15 lb/sf

Design Evaluators:

1. Facade Cost ($) - total material cost of the glazing, opaque wall, and overhang
1. Goal is to minimize the cost
2. Thermal Load - unshaded glazing area multiplied by the solar heat gain coefficient which represents the solar heat gain entering the space
1. Goal is to minimize the thermal load
3. Solar Penetration Ratio (%) - determines how far into the space there is direct light using the solar altitude angle and overhang depth
1. Goal is to maximize the solar penetration ratio to increase daylighting effects in the space
4. Overhang Structural Load - overhang depth squared multiplied by the facade width and unit weight of the overhang to help quantify the structural demand of the cantilever
1. Goal is to minimize the structural load to help reduce design complexity and cost

My Dynamo geometry can be seen in the following image:

Tradeoff 1: Facade Cost vs. Solar Penetration Ratio

This scatterplot shows the facade cost on the Y-Axis and the solar penetration ratio on the X-Axis, with the bubble size and color representing the thermal load. This graph shows that solutions with lower solar penetration ratios seem to be on the higher side of the cost. On the other hand, solutions with higher solar penetration ratios seem to be financially cheaper. There is also a strong correlation between solar penetration ratio thermal load which makes sense because both of these evaluators increase with more direct sun. However, it is important to remember that we do have two distinct goals for those two evaluators.

This scatterplot tells us that spending more on a restrictive facade does not necessarily guarantee our thermal load goals. Additionally, it tells us that we can achieve low cost even when having a high solar penetration ratio (more glass = expensive), most likely by reducing the overhang depth. The practical takeaway from this plot is to look for solutions that have lower facade cost but moderate solar penetration. This is because moderate solar penetration also corresponds to moderate thermal loads, which means this decision is about the balance of those two evaluators.

Tradeoff 2: Thermal Load vs. Overhang Structural Load

This scatterplot is more revealing for the study. It shows thermal load on the Y-Axis and overhang structural load on the X-Axis, with the bubble color and size representing the facade cost. This plot shows a strong negative correlation because solutions with near-zero overhang structural loads have very high thermal loads while solutions with high overhang structural loads have thermal loads that are close to zero. The color and size gradient help us to see that while the increase in structural load does increase the facade cost, it is not linear since the facade cost also depends on the amount of glazing which in turn also affects the thermal loads of the space.

The main struggle we see with this scatterplot is that as you increase the overhang depth, you reduce the thermal loads in the space. However, this also increases the overall facade cost which includes the cost of the overhang. To make my decision, I would consider the light green dots that go in a diagonal because this gives me the optimized overhang structural load and thermal load to have the lowest cost. I would do this because the facade cost does include some of the impacts of thermal load as well.

Finally, my Dynamo logic can be seen in the following image: