Step 1 - Generative Design Framework
Step 2 - Generative Design Study
Step 3 - Generative Design Study Results
This scatterplot below visualizes the relationship between Total Building Weight (lb) on the x-axis and Drift Ratio on the y-axis. The trend reveals a clear inverse correlation—as building weight increases (due to changes in the building geometry), the drift ratio decreases. This tradeoff highlights a challenge in structural design of balancing mass and drift demands. While lower drift ratios are desirable for structural performance and occupant comfort, achieving them by increasing total weight may not always be optimal. Heavier structures typically require more material, deeper foundations, and generate higher embodied carbon, which impacts sustainability goals. From this analysis, a designer may choose to target a moderate weight range where drift is controlled without excessively increasing structural mass. Since controlling drift is a key priority in structural engineering, this tradeoff analysis would likely be one of the most important factors informing the design decision.
A secondary tradeoff analysis as shown in the scatterplot below is with Perimeter Bay Beam Length (ft) on the x-axis and Framing Cost Efficiency ($/SF) on the y-axis The graph demonstrates a clear inverse relationship—longer bay beam lengths are associated with lower framing cost per square foot. This trend makes sense: as each bay becomes longer, fewer structural members are needed around the perimeter for the same overall floor area, reducing total framing material and associated costs. This tradeoff is central to optimizing structural layout for economy. From a cost perspective, maximizing beam spans can help lower framing costs per floor area, improving structural efficiency. However, longer spans may introduce structural performance challenges, such as increased deflection or vibration. Designers could use this insight to push toward maximizing bay length when the priority is framing cost reduction. But for high-performance or sensitive structures, they may need to balance this cost-saving strategy with additional checks for serviceability that come with longer structural spans. It is important to note that this tradeoff would not typically serve as the primary driver of structural design decisions, as other considerations—such as lateral system performance, load path continuity, and overall stability—tend to play a more critical role in governing the structural layout.
Another tradeoff analysis is illustrated in the scatterplot below, which maps Framing Cost Efficiency ($/SF) on the x-axis and Total Building Weight (lb) on the y-axis. The graph reveals a clear inverse relationship—as framing cost per square foot decreases, total building weight tends to increase. Lower framing cost per area often results from maximizing beam spans or reducing grid complexity, which in turn increases the overall surface area of floors and walls. This expanded surface footprint leads to more material usage, contributing to a higher total structural weight. In other words, while structural simplicity may reduce connection and framing costs, it can unintentionally raise the weight of the structure. From a design perspective, this tradeoff emphasizes the importance of balancing cost efficiency with structural mass. Designers can use this analysis to explore cost-effective options that don’t overly compromise on building weight. However, as with all tradeoffs, these findings should be considered alongside other evaluators—such as drift ratio and perimeter span feasibility—to ensure holistic structural performance.
