Stage 1: Create Two New Evaluator Custom Nodes
I used Dynamo to create 2 new custom nodes that evaluate various aspects of my Revit building mass (I chose to use the pre-made rectangular building mass from the class Google shared drive).
The first custom node I created is called “EmbodiedCarbonofFacade” and it uses the gross surface area (GSA) of the building envelope to calculate the embodied carbon of the facade. The facade system I propose is a curtain wall (glass) facade, that would be on all sides of the building (this helps provide simplification). This facade system was chosen because it is commonly used for tall buildings in Dubai, such as those near our project site (e.g. the Burj Khalifa), as it maximizes natural light and exterior views. Figure 1 below shows the node logic in my new evaluator custom node. It takes the GSA (in sq. ft) of the building as an input, converts it to m^2, then multiplies it by 205 kgCO2e / 1 m^2 of curtain wall. This number is the global warming potential (GWP) of a sample curtain wall product, obtained from its environmental product declaration (EPD). All resources I consulted for this module (including the EPD) are linked in my Excel spreadsheet, which is located in my Module 6 folder in the Autodesk Construction Cloud.
The second custom node I made is called “SolarCapacity” and it estimates the amount of solar energy that could be generated with rooftop photovoltaic (PV) panels on the building. The function’s input is the area of the rooftop, which is calculated by multiplying the “building top width” and the “building top depth” parameters from the Revit building mass. After obtaining this area, it is multiplied by 0.5 to reflect the area of the roof that could actually be used for PV panels (there may be other equipment on the roof, such as HVAC systems, that may limit space for PVs). Next, this usable rooftop area (in sq. ft) is divided by 19.5 sf, a typical area for a PV panel. After rounding, this gives us an estimate of the maximum amount of PV panels that can be placed on the roof. Finally, the number of PV panels is multiplied by 4 kWh/day * 310 days to determine how much solar energy can be generated by the system in a year. I am assuming one panel can generate 4 kWh a day for 310 days a year, since Dubai receives over 300 days of direct sunlight annually. This high solar irradiance helps create ideal conditions to set up a rooftop PV system. Although it was not specified in the design brief that the owners prioritize sustainability, perhaps my metrics can persuade them to integrate renewable energy systems to help offset their embodied carbon emissions from construction. The complete node logic for my custom node, “SolarCapacity”, can be found in figures 2 and 3 below.
The final custom node I created provides an additional interesting metric. It is called “CarbonPaybackPeriod” and uses the results of the previous two custom nodes to estimate the number of years it would take for the solar energy generated from the rooftop PV system to offset the embodied carbon of the curtain wall facade. This metric may not be particularly useful, as it does not account for the embodied carbon of the entire building but the reason I created it is because I thought it would help put the facade embodied carbon value into context, as the number of years it would take to offset the carbon may be easier for the owners to understand. This would also help to emphasize the importance of considering alternative facade materials / materials to be used in construction in general. Choosing more sustainable building materials (e.g. mass timber) can drastically reduce the embodied carbon of the building and also increase the value of the building (e.g. make it more attractive for environmentally-minded tenants), boosting long-term profits. Figure 4 below shows the node logic of my “CarbonPaybackPeriod” custom node.
After making sure that my custom nodes work for a single instance, I evaluated a range of twist angles and top widths of the building to see the resulting GFAs, GSAs, gross volumes, embodied carbon values, solar capacities, and carbon payback periods. The results are located in table 1 below.
💡 Point to Ponder: “Do the new evaluation metrics that you’ve designed capture the meaningful differences between the building form alternatives? What other metrics would be useful to compute to help understand and make the case for which alternatives are truly better than others?”
Yes, the new evaluation metrics I designed help capture the meaningful differences between the building form alternatives, such as the gross surface area and embodied carbon of the facade (which increases with GSA). If I had additional time, other metrics I would compute to assess better alternatives include:
- ☀️ Solar insolation potential - the amount of solar radiation on a surface. This would affect the cooling load, and thus, operating costs of the building.
- 🌊 Directness of wall surfaces/windows to the sun or to water views - to help determine the quality of the view and help inform occupant experience
- 🌬️ Wind Analysis (using Autodesk Forma) - analyze occupant window comfort, wind effects on the building (important for structural and MEP considerations), etc.
- ⛅ Sun Hours (using Forma) - Assess the hours of sunlight the building receives in a day/year (building could be partially shaded by surrounding structures). This is important for MEP and rooftop solar considerations.
Stage 2: Develop a Single-Objective Optimization Scheme
💡 Point to Ponder: “What overall strategy do you feel best captures the relationship between the evaluation metrics? Clearly articulating your design strategy is the key aspect of this task. Before you dive into implementing your scheme, briefly describe your thinking and strategy in a paragraph that outlines your thinking and approach.”
For my optimization scheme, I chose to incorporate three building metrics that I thought were the most important: area efficiency, embodied carbon, and construction cost. Since it was stated in the design brief that the owner would like to reduce the construction cost, this metric has the most weight, of 50%, in my scheme. Area efficiency (higher is better) has a weight of 30%, and the embodied carbon of the facade (want to minimize) has a weight of 20%. As the gross surface area increases, the embodied carbon of the facade rises, along with the cost. The construction cost does not increase or decrease with the twist angle though. It is the highest at a twist angle of 60-70 degrees, and lowest at 120 degrees.
Although the owner did not specifically list any sustainability goals in the project brief, I am hoping I can help convince them to incorporate some. After exporting results from Dynamo to my Excel, for each of the three metrics I listed above, I normalized the values using the formula: (x - min) / range, where x is each individual value. For the reverse-normalized values (for metrics we are trying to minimize), I subtracted the normalized value from 1. Then, I multiplied each value by the metric’s respective weighting percentage, and obtained the weights. Finally, I summed the 3 weights for each run to get the final weighted score for each run. Table 2 below contains the results of implementing my optimization scheme as well as the final weighted scores.
According to this weighting system, run #12 with a twist angle of 120 degrees and a top width of 650 ft is the best recommended design alternative because it had the highest final weighted score. This is likely because the large angle in the building helps reduce the volume and floor area in the floors affected by the twist angle. In second place was run #1, with a twist angle of 10 degrees and a top width of 100 ft. The small top width helped to reduce the construction cost. In third place was run #11, with a twist angle of 110 degrees and a top width of 600 ft. It has characteristics similar to run #12, but a slightly smaller angle. The “worst” designs were runs #6 and #7, which had the lowest final weighted score. They were costly and had large top widths but small twist angles.
The one design that I would consider to be the “best” would be run #12. It had the highest final weighted score and is visually interesting because of the large twist angle. It also has a lower embodied carbon value compared to many of the other alternatives.
💡 Point to Ponder: “What propelled the recommended alternative to the top of the list? Explain your reasoning -- include a brief analysis of why this alternative rose to the top of the list and why you consider it to be the best option. Are there important nuances or tradeoffs that got lost in the single evaluation?”
Run #12 was the recommended alternative because it had a lower cost, embodied carbon, and area efficiency than many of the other alternatives. As explained previously, the large twist angle helped to reduce the gross surface area and gross volume of the building, which helped reduce the cost and material usage. However, the single evaluation scheme cannot account for many other factors that are crucial in real-world projects. For example, one important nuance that got lost in the single evaluation is the effect of the twist angle on the ease of structural design and construction. We did not assess the effect of the twist angle and top width on the structural design/feasibility, which are crucial for a building project. It might be extremely difficult (or maybe even impossible) to building a tower with a twist angle of 120 degrees.