**2 Units:**

**Overall Study Results:**

**Step 1 - Generative Design Framework**

**Step 1 - Generative Design Framework**

A very brief description of the design decisions from Step 1 following the Generative Design Framework.

**Design Decision 1: Reducing embodied carbon and column grid that allows for optimal views**- Design Variables
- Fly Ash in Concrete Columns
- Concrete Column x and y spacing
- Evaluators
- Embodied carbon
- View line of site from center of building to windows
- Most Important Tradeoffs to Consider
- Increased fly ash reduces concrete strength so more columns or larger columns will be needed which will obstruct views
**Design Decision 2: Optimal bridge construction**- Design Variables
- Number of trusses
- Area of trusses
- Evaluators
- Maximum deflection
- Material cost
- Most Important Tradeoffs to Consider
- Decreasing the maximum deflection will require more truss members and larger truss area which will increase material cost.
**Design Decision 3: Best views for sports stadium**- Design Variables
- Amount of seats
- Shape of the stadium
- Evaluators
- Views from the seats
- Revenue for ticket sales
- Most Important Tradeoffs to Consider
- To maximize the revenue from seats while having the best views. More seats could mean more revenue from seats but worse views on average.

__Step 2 - Generative Design Study__

I decided to move forward with Design Decision 2: Optimal Bridge Construction. The goal is to figure out optimal combinations of amount of truss members and truss area to minimize material cost and maximum deflection. An overall workflow of the dynamo script is seen at the top or bottom of this post.

**Overall Dynamo Script:**

**In-depth Breakdown of Dynamo Script:**

**Inputs:**

The changeable inputs are the inputs used for the generative design study. The other values are fixed for the purpose of this study but could be changed if a different generative design study was desired. The truss members go in a step of 2 to account for the addition on a full new V truss every time.

**Geometry:**

The above four groups of nodes create the geometry for the truss. A line and arc were created and then split into points that were used for the truss members. These point locations were formatted using a python node to get them into an order where a PolyCurve.ByPoints could create lines that could be used for the truss members. Finally, all of the geometry is translated to create the other side of the bridge.

**Analysis:**

The calculation for max deflection is mainly using a python node. The above script walks through the steps of how the maximum deflection was calculated. Some course assumptions were made through this calculation of deflection, but it is a good back of the envelope calculation.

The calculation for material cost is mostly done using a python node. The above script walks through the steps of how the material cost was calculated.

**Outputs:**

These are the outputs used for the generative design analysis.

__Step 3 - Generative Design Study Results__

For my generative design, I choose to minimize the material cost and minimize deflection. I chose to have the maximum deflection be 4 inches based off code compliance for a bridge.

The generative design results are shown below.

The results show that 14 and 16 truss members is the most common amount for the optimized result. Truss member areas very for most of the designs.

The scatterplot shows that there is an inverse relationship between material cost and max deflection. The size of the bubbles indicates the amount of truss members in the bridge and the color shows the truss area. Blue is a larger area and red is a smaller area. Using other factors that are outside the scope of this study (like construction time), one can decide if it is better to have larger truss areas and less trusses or smaller truss areas and more trusses. Overall, the engineer and owner can decide which combination of cost and deflection they are most comfortable with.

Finally, here is another image of my final dynamo script.