Stage 1: Create Two New Evaluator Custom Nodes
For the two new custom nodes, I chose to look at the initial construction cost of the building and the cost of offsetting the cumulative solar insolation of the building. From a high level, I chose to look at this project from an purely economical standpoint. In Stage 1, I aimed to find the cost of these evaluation metrics, and ultimately compare the cost of each building layout in Stage 2.
First, I used my Module 5 Dynamo File to organize my nodes, such that all the user parameters could be modified on the left. In the middle, I placed my custom node, complete with all the inputs needed to run the internal solar insolation cost node and construction code node. Finally, I added modules that allowed the custom node output numbers to be linked accordingly to the user parameters, and subsequently exported neatly to an Excel file.
Inside my custom node, I used three custom nodes from the class files that allowed for the calculation of the total construction cost and total solar insolation offset cost. Using the output of the BuildingForm.MassFloors node, I could use the total square footage at each elevation of the building element to calculate the construction cost of the building, which varied from $500 / SQ on ground level to $1000 / SQ at 750 ft elevation.
The nodes BuildingForm.SelectNonGroundSurfaces and BuildingForm.SolarAnalysis were used for calculating the total insolation offset cost. The user would specify a percentage of the total solar insolation that they would like to offset, which represents the cost of AC, as well as a cost per kWh, which could then be translated into a total cost per total surface area of the building. The weather and time study were chosen to be Dubai, UAE, and the summertime, as this is when the sun would be the harshest.
From a quick online search, the average cost of electricity last year was approximately $0.16/kWh. Since Revit outputs energy in terms of BHU, the cumulative insolation value had to be converted into kWh. Thus, the total cost of offsetting the solar insolation during one summer cycle was estimated to be (% offset) * (cumulative insolation value) * ( $ / kWh) / (3412 kWh / BHU).
The Top Height and the Middle Width of the custom tower made in Module 5, as shown below, were chosen to be varied. The results for each custom metric are presented below in a table.
Point to Ponder: Do the new evaluation metrics that you’ve designed capture the meaningful differences between the building form alternatives?
Yes, the new evaluation metrics that I’ve designed does capture the differences between the building form alternative. Understandably, there is never going to be a perfect set of metrics that completely captures all the advantages and disadvantages of a building layout. However, looking from a specific viewpoint or frame, one can determine what is most important to a structure. In this case, the initial construction cost and yearly offset cost can be compared to the owner’s desired building height and gross floor area. Concrete values can be compared against each other instead of vague insights.
What other metrics would be useful to compute to help understand and make the case for which alternatives are truly better than others?
Other metrics that could be useful to help understand what alternatives are better than others could be how much the building obstructs the view from other existing buildings, the strength of the building required for its desired length and height, and the potential solar energy that could be harvested from the building’s position and dimensions. Ultimately, each of these metrics dig deeper into the cost of the building, how the building interacts with its environment and inhabitants, and how much the building can contribute to the community. The metrics listed above are concrete and able to be roughly computed. Other metrics that may be useful to the owner, such as public perception and public happiness gained from the building, is harder to measure and distill into a single calculable value.
Stage 2: Develop a Single-Objective Optimization Scheme
My single objective optimization scheme is based off of my economic frame in Stage 1. In Stage 1, I focused primarily on the negatives, or the costs of this building - in particular, its one-time construction cost and its yearly insolation offset cost (representing the cost of AC / HVAC equipment). To measure the benefits of changing each parameter, a simple calculation was added to determine the average yearly rent collected from the building. If this building were to have spaces that were roughly 500 SQ in size, and the rent for each 500 SQ space was approximately $2000 / month, then one could calculate a rough estimate of the yearly gross profit received from rent. Of course, this equation does not account for building spaces that are uninhabitable, including hallways, stairways, elevators, and HVAC storage rooms.
Additionally, factors that are measured per year, such as the insolation offset cost and the rent profit, could be multiplied by an estimated building life span - for instance, 60 years. Thus, by subtracting the initial construction cost from the yearly profit, one could determine the net profit gained from this building.
Thus, from our economic standpoint, it makes sense to have a high building with a larger middle width. As the building gets larger, while the surface area grows larger (and thus the cooling / air conditioning expenses grow), the gross floor area grows at a larger pace. Thus, under this metric, the largest building possible, with a top height of 700 ft and a middle width of 370 ft, is recommended. If this initial construction cost cannot be covered, then the following two largest buildings should be considered. Ultimately, the larger the building, the larger the net profit becomes from the rent - this is the best choice, as the building produces the highest revenue for the owner.
Point to Ponder: What overall strategy do you feel best captures the relationship between the evaluation metrics?
Ultimately, I believe that an economic standpoint best captures the relationship between the evaluation metrics. In reality, if resources were more abundant, more ambitious projects could be achieved and thought of. However, building resources are scarce, and thus each building should be carefully considered as to not waste its initial investment, or in other words, its construction. Hence, gross square footage could be thought of as a source of income through rent, and solar insolation can either be thought of as a cost from the use of AC units, or a profit from the use of solar panels. Ultimately, one should be realistic and thoughtful when it comes to benefiting the community and furthering its local economy.
What propelled the recommended alternative to the top of the list? Are there important nuances or tradeoffs that got lost in the single evaluation?
The largest building rose to the top of the recommended list due to two facts. First, the rent collection obtained from having a larger square footage outweighed the cost of offsetting the solar insolation. Moreover, as the building got larger, its gross volume and floor area grew at a larger pace than the gross surface area. If the gross surface area grew at a faster pace than the floor area, then we would see an eventual decline in the net profit of the building. From this viewpoint, this building is the best because it achieves the largest payout for the owner. However, this single evaluation system does not consider human factors at all - for instance, while sunlight is seen as a negative here, how much sunlight each floor receives could be viewed as a positive to a tenant, and therefore increase the value of the real estate within the building. Additionally, public perception of the building can not be easily measured within this initial study - especially in terms of dollar value.