Step 1 - Generative Design Framework
A very brief description of the design decisions from Step 1 following the Generative Design Framework.
- Design Decision 1: Structural Optimization of a truss with respect to self-weight while satisfying the deflection criteria
- Design Variables
- Number of bays in a truss
- Height of truss
- Cross-truss members at top, bottom, middle, vertical and diagonal
- Evaluators
- Weight of the truss
- Most Important Tradeoffs to Consider
- The goal of this optimization is to find the lightest steel truss by satisfying the constraint on the maximum displacement due to applied loads, however with extremely slender members buckling needs to be accounted for as well.
- Design Decision 2: Create tower form that has minimal cost, maximizing volume and level of compactness (measured by gross-to-skin ratio parameter)
- Design Variables
- Tower height
- Bottom profile radius
- Evaluators
- Tower volume
- GrossArea-to-skin ratio (skin is the cumulative sum of perimeters of all floors)
- Material cost
- Most Important Tradeoffs to Consider
- While we want to minimize the cost of materials and have a compact building, we also need to keep in mind that the the tower should have satisfy prescribed floor area requirements and height requirements.
- Design Decision 3: Aircraft wing optimization
- Design Variables
- Shape of the wing/ geometry variables
- Evaluators
- Drag Coefficient
- Most Important Tradeoffs to Consider
- While we want a sleek design for the aircraft wing we need to ensure that while optimizing the air resistance (drag coefficient) to enable forward motion we also need to ensure that the there lift coefficient generated is limited to a constraint (high lift coefficient will make the aircraft move very fast).
Step 2 - Generative Design Study
Step 3 - Generative Design Study Results
Shown above are the parallel coordinates graph and the scatter plot from the generative design study. The tradeoff that I made was based on the scatter plot results. The plot is made between Material Cost and Gross Volume, with the size of the bubble representing the value of the of the grossarea-to-skin ratio. Since I wanted to minimize cost and maximize gross volume I went midway towards both these goals, i.e. approximately at about $6553582 and gross volume of 878627.1 cubic ft. At the same time, I wanted to have a reasonable grossarea-to-skin ratio in order to maintain a reasonably good level of compactness of the tower floors. This reasonably large value (13.349) is represented by the dark blue color on the plot.
I also generated a scatter plot with the gross-to-skin ratios on the Y-axis and Material Cost on the X-Axis and the size of the bubbles representing Gross Volume. Again, the same choice proved to be the most ideal case as I achieved a reasonably high value of gross-to-skin ratio while maintaining a a not-so-high Material Cost and reasonable Gross Volume.
Shown below is the choice I made considering the above tradeoff:
Shown below is the overall Dynamo graph:
