For this Module, I furthered the work from Module 5 using the Twisting Simple Triangle Mass. The Dynamo script iterates through various Mid Rotation angles to determine an optimal form. The original building form is illustrated below with the given parameters developed in one of the iterations conducted in Module 5. Note that the floor-to-floor heights vary over the building’s height to improve the architectural appeal and maximize revenues from the lowermost and uppermost floors. The first story is 25’ tall, the next stories are 18’ tall, the middle stories are 15’ tall, and the top floors are 18’ tall.

This building form is to be optimized according to three metrics: Construction Cost, Expected Revenue, and User Wellbeing. Construction Cost is calculated using the Custom Node available to the CEE220C course; Expected Revenue and User Wellbeing are computed in Custom Nodes which I created.

To confirm the success of the Custom Node calculations, I made a test Dynamo script which reports the expected values and the values calculated in the Custom Nodes. In this script, the Mid Rotation and Mid Height values are kept constant for simplicity during debugging. Note that the “BuildingForm.MassFloors” Custom Node is also implemented with a few alterations to output the floor volume and external surface area of the selected mass. By comparing the “Watch” node values, it is evident that the Custom Nodes are correctly inputting, calculating, and outputting data.

The Custom Node titled “EstimateRevenueByFloorVolume” aims to compute the amount of revenue that the client will earn from renting out the space. The Node receives each mass floor volume and multiplies it by a revenue/volume dollar amount calculated by user inputs. The idea behind this evaluation metric, is that the building owner is able to charge more in rent per square foot based on the story height: the lower and upper stories have more rental value while the stories in the middle have less rental value. Because the level elevations were designed by the architect to optimize the floor-to-floor heights (reference the “Module 5 Summary” section), it is appropriate to use the mass floor volumes to capture this effect. The output value is the computed revenue value for the building’s lifespan.

The Custom Node titled “EstimateWellbeingByVisibility” quantifies the potential wellbeing of the users due to their views of the outdoors. Research demonstrates that ability to see outside improves the wellbeing of office employees. This metric computes a ratio of the exterior surface area of a mass (which represents the window area) to the floor area of a mass to illustrate the proximity of a typical building occupant to a window. The Node receives each mass floor surface area and divides it by the mass floor area. The output value is the ratio which quantifies the user wellbeing by external visibility.

Now that the Custom Nodes are confirmed to be computing correctly, I edited my Module 5 Dynamo script to implement the Nodes that I defined as well as the CEE220C Nodes. I updated my user inputs to call for the values required to calculate construction cost and building revenue. The other required values are determined from the updating mass geometry. The cost at lowest level and cost at highest level are given in the Module 6 assignment description. The values for calculating building revenue are selected from preliminary research on commercial real estate value in San Francisco. The user inputs are passed into a code block developed in Module 5 which creates the different mass geometries. The inputs are also passed into the “BuildingForm.EvaluationPairsOfInputs” CEE220C Custom Node which I updated to compute and produce the results needed for my analysis.

The following image captures the main changes I made to the “BuildingForm.EvaluationPairsOfInputs” Custom Node. I updated the required inputs and desired outputs; I defined the mass properties to report (rather than making that a user input which allows me to have control over what is being passed into my custom nodes); and I called my three custom nodes.

The Dynamo script runs various geometries through the analysis to produce the table below. I have post-processed the data to make the information clear. First, the floor area is assessed to determine which combinations meet the required floor area criteria (green) and which do not (red). The values which do not meet the floor area criteria are not considered reasonable products for this optimization. The reported Construction Cost, Estimated Revenue, and Estimated Wellbeing values for each combination are evaluated against each other. A green value represents a desirable outcome; a red value represents an undesirable outcome.

The values for Construction Cost, Estimated Revenue, and Estimated Wellbeing are then normalized to make their values equally comparable across category. The normalized values are then averaged, resulting in a score for each combination of rotation angle and height value. Note that this process of averaging assumes that the client equally prioritizes cost, revenue, and wellbeing. Weights could be assigned to each category if that is not the case. The largest score that meets the floor area requirement is selected as most optimal.

The resulting optimal building design is illustrated and described below.

Although the construction cost for this design is very high, the projected revenue much outweighs this negative. Similarly, the expected user wellbeing is lower for this design than some of the other potential building designs. This can be mitigated with other measures, like incorporating biophilic design, within the building.