## Workflow (2 units)

**Step 1 - Generative Design Framework**

**Step 1 - Generative Design Framework**

**Design Decision 1: Material for building construction**

As society is progressing towards constructing net-zero buildings, there are often tensions between choosing sustainable materials and and building costs because of the typical high cost associated with sustainable materials. Hence it would be useful to be able to find the optimal building form that minimizes building costs related to sustainable materials.

*Objective:* Finding the optimal building form that minimizes project costs associated with choosing sustainable materials

*Model:*

- Design variables
- Height of Building
- Number of Floors in Building
- Angle of Twists in Building
- Shape of Building
- Constants:
- Average cost of sustainable material per square foot
- Embodied carbon per square foot
- Location of Building
- Emissions per square foot

*Evaluators: *

- Total Embodied Carbon
- Total Project Costs
- Total Emissions

*Tradeoffs to consider:*

- Total costs vs Total Embodied Carbon
- Total costs vs Total Emissions

**Design Decision 2: Green Roof Design**

This design decision looks at maximizing the size of a garden to maximize carbon offsets on a rooftop while ensuring that it is economically feasible.

*Objective: *Optimize the carbon offsets based on the size of a rooftop garden while being economically reasonable.

*Model: *

- Design variables:
- Surface Area of the Roof
- Shape of the Roof
- Height of the Building
- Layout of the Green Roof (placement)
- Constants:
- Location of roof
- Carbon Offsets per square foot area
- Climate
- Type of plants

*Evaluators: *

- Total Costs
- Water Usage
- Carbon Offsets

*Tradeoffs to consider:*

- Total Cost vs. Carbon Offsets
- Total Cost vs. Water Usage
- Carbon Offsets vs. Water Usage

**Design Decision 3: Optimizing the shape of a 2-part building**

Decide the optimal design of a 2-part building that uses two different geometries that could vary based on certain parameters (listed below).

*Objective: Minimizing the heat loss ratio (SV Ratio) of the 2-part building while maximizing the rentable floor area*

*Model: *

- Design variables:
- Building part Dimensions: height, width, length, radius etc.
- Distance/intersection between building parts → Building part 1 position (in the x and z axis)
- Constants:
- Building Shapes
- Building part 1 position

*Evaluators: *

- Floor Area
- Surface Area to Volume Ratio (SV Ratio)

*Tradeoffs to consider: *

- Maximize Floor Area for rent while minimizing heat loss from building by evaluating SV Ratio

__Step 2 - Generative Design Study__

I decided to go with design decision 3 - here is the more detailed design thinking framework after going further into detail.

*Objective: Minimizing the heat loss ratio (SV Ratio) of the 2-part building while maximizing the rentable floor area*

*Model: *

- Design variables:
- Building Part 2 Top Radius
- Building 2 placement (and intersection) in the x axis
- Constants:
- Building Part 1 height, width, length
- Building Shapes
- Building Part 2 Bottom Radius
- Building Part 2 height
- Building 2 placement (and intersection) in the z axis

*Evaluators: *

- Floor Area
- Surface Area to Volume Ratio (SV Ratio)

*Tradeoffs to consider: *

- Maximize Floor Area for rent while minimizing heat loss from building by evaluating SV Ratio

### Setup for the generative design study

The first step was to initialize certain parameters that were considered inputs to the generative design study. These parameters could either be variables or constants that we could set later in the next step. An interesting point to note was that the range of values for some of the inputs had to be physically feasible else the generative design study would not be able to work.

### Input Parameters

These are parameters that are required to create each part of the building. In this case, I am choosing a cuboid (Building part 1) and a cone (Building part 2). For Building part 1, potential variables could be its height, width and length, while for Building part 2, potential variables could include its position relative to the x and z axis (which affects the intersection of both building parts), its height and its top/bottom radius.

### Combining building parts

The next step is creating the building shapes and intersecting them together using the Solid By Union node. This allows the study of the combined building parts as a whole in the generative design study section later.

### Evaluators for analysis

As mentioned above, the 2 evaluators chosen for this generative study design will be the SV Ratio, as well as the floor area. Using the Solid Volume node, and Solid Area node, I was able to find the surface area and volume of the combined building and subsequently the SV Ratio.

To find the floor area, I needed to divide the combined building into various floors, by setting the floor height as 10 ft. This gave me the combined floor area as an evaluator.

### Evaluators as Output

Finally, to ensure a completed setup for the generative design study, I needed to set the evaluators as output variables so it could be used to filter results in the generative design study. Thus the output variables are the SV Ratio and Floor Area.

__Step 3 - Generative Design Study Results__

The top 10 most optimized permutations from the generative design study were obtained. It was interesting to note that the top 10 optimized permutations chose the maximum value of the Building part 2 top radius for all 10 results, while varying Building part 2’s position in the x axis, which determines the extent to which building part 2 intersects with building part 1.

We were able to understand the relationship between some of the input variables as well as the output variables. A notable relationship to highlight is how the SV Ratio varies with the position of building part 2 in the x axis. The greater the position X, the less there is intersection between both parts and it makes sense that there will be more overall surface area for the combined building. It is interesting to note that there are 2 kinks in this graph, where the first kink occurs between the ranges of 30-40 ft for building part 2 position X, and the second kink occurs when position X exceeds 40 ft. Since the tradeoff is between maximizing the floor area, while minimizing the SV Ratio to mitigate heat loss, the shaded circle shows the possible optimal building form where its floor area is much greater than the previous building form with a slightly smaller SV Ratio.

The graph below also affirms the selection of the optimal building form, where we see that the optimal point has a much greater floor area with a relatively smaller increase in SV Ratio.

This is the chosen optimal design that balances the minimization of SV Ratio as well as maximizes the floor area of the combined building: