Margaret Gereghty

Process

For this analysis, I evaluated my custom building form developed in Module 5 to better understand its economic and environmental performance. Rather than modifying only a single parameter, I decided to vary both the building height and the amount of twist in order to explore a broader solution space and better understand how the two parameters interact with one another.

To conduct this study, I created two custom performance metrics. Metric #1 focused on economic feasibility by estimating the amount of time required for the building to break even based on construction costs and rental income. Metric #2 built upon the solar analysis workflow developed in class with Glen and evaluated how evenly sunlight was distributed across the building envelope by comparing the maximum and minimum average solar insolation values on the façade surfaces.

The overall node logic used to automate the parameter changes and execute the analysis is shown below.

Metric #1: Cost of Construction + Cost of Rent (Time to Breakeven)

The first metric analyzed the relationship between construction cost and potential rental income in order to estimate the amount of time required for each design iteration to break even financially.

For this study, construction cost was assumed to increase linearly with building height, ranging from approximately $500/sf at the base condition to $1,000/sf at 750 feet tall. A similar assumption was made for rental income, with rent increasing from roughly $50/sf/year at the base condition to $75/sf/year at 750 feet due to the increased value typically associated with taller buildings and improved views.

Using these assumptions, each parametrically generated building variation was evaluated to determine its estimated breakeven time. While simplified, this metric provided insight into how geometric decisions such as increased height and twisting could influence economic feasibility.

Metric #2: Solar Analysis

The second metric focused on environmental performance through solar analysis. Building upon the workflow developed in class, I evaluated all non-ground-facing surfaces of the building envelope to measure average solar exposure.

To better understand how building geometry impacts sunlight distribution, I compared the ratio between the maximum and minimum average solar insolation values across the analyzed surfaces. This ratio helped quantify how evenly sunlight was distributed on the façade.

The analysis did not account for shadows from surrounding buildings, since the primary goal was to isolate the effect of the building’s own geometry on solar performance. As the amount of twist increased, the geometry created more self-shading conditions, resulting in larger differences between highly exposed and heavily shaded surfaces.

Results

The results of the analysis are summarized in the table below, with green-highlighted entries representing options that met the gross square footage requirements established in the project criteria.

Several overall trends emerged from the study:

• As the amount of twist increased, the ratio between maximum and minimum solar insolation values also increased. This indicates that twisting the building creates greater variation in solar exposure due to self-shading effects and uneven façade orientation.
• The estimated time to breakeven remained relatively consistent across most design options. This occurred because the assumed linear increase in rental income nearly balanced the linear increase in construction cost.
• In general, taller buildings still showed slightly longer breakeven periods because construction costs increased more rapidly at larger scales.
• Additional experiments using alternative rent assumptions produced more variation in breakeven time, suggesting that economic performance is highly sensitive to market assumptions.

Points to ponder:

1. Do the new evaluation metrics that you’ve designed capture the meaningful differences between the building form alternatives?

Yes. The economic metric helped compare financial feasibility between the design options, while the solar metric showed how increasing twist creates greater variation in sunlight exposure due to self-shading. Together, the metrics provided a clearer understanding of how geometry affects performance.

2. What other metrics would be useful to compute to help understand and make the case for which alternatives are truly better than others?

Additional useful metrics could include energy use, structural efficiency/complexity, daylighting performance, and usable floor area efficiency. These would provide a more complete understanding of sustainability, constructability, and occupant experience.