2 Units: Create Two New Evaluator Nodes
The building analysis custom node above creates the flower profile building and originally only outputs volume, surface area, and floor area. Two new nodes (shown in purple above) were added to the building to conduct a cost and solar analysis. Screenshots of the dynamo logic used is shown below. See details of building parameters and design in the Module 6 design journal entry. There is another dynamo file that imports inputs and exports outputs from the building analysis custom node into a CSV file.
Evaluator Node 1:
For the first custom node, three outputs were produced, although only two were used in the alternatives evaluation. The cost and profit metrics are based on the floor areas and their corresponding heights. The construction cost equation comes from the assignment brief, while the value equation is based on the research shown below. To estimate the value per square foot at different heights, I used the floor-based scaling relationship from the Forbes article graph and applied it to a base value taken from the average price per square foot in Business Bay, where the project site is located. This allowed the estimated value to increase by floor height while still being tied to the local market context. Profit was measured as a percentage between cost and profit.
https://www.engelvoelkers.com/ae/en/resources/average-price-per-square-foot-in-dubai
Evaluator Node 2:
For the second custom node, the solar insolation potential of the building was measured using the solar analysis node from the dynamo solar analysis add-in. The weather information was taken from the site with the sun setting being a full year of 2023. The surfaces evaluated were all non-ground surfaces. The total solar potential was divided by the surface area to get solar efficiency. Some unit conversions were made since the revit file is imperial but solar potential is often given in kWh/m^2.
Summary Table:
Point to Ponder:
Do the new evaluation metrics that you’ve designed capture the meaningful differences between the building form alternatives?
I think the two metrics I chose are meaningful metrics to evaluate buildings because profit of the utmost importance to owners and solar potential is important to building energy and thermal systems. What other metrics would be useful to compute to help understand and make the case for which alternatives are truly better than others?
I think some other useful metrics would be carbon emissions of constructing the building and the amount of time needed for construction.
3 Units: Develop a Single-Objective Optimization Scheme
Single-Objective Optimization Scheme: Done in Excel
- Floor Area Score = IF within required range, give full credit; if below or above, reduce based on closeness to the range: =IF(AND(CellValue>=2500000,CellValue<=3000000),1,IF(CellValue<2500000,CellValue/2500000,3000000/CellValue))
- Profit Score = higher profit is better: =(CellValue-MIN(ProfitRange))/(MAX(ProfitRange)-MIN(ProfitRange))
- Solar Efficiency Score = higher solar efficiency is better: =(CellValue-MIN(SolarEfficiencyRange))/(MAX(SolarEfficiencyRange)-MIN(SolarEfficiencyRange))
- Solar Potential Score = higher cumulative solar potential is better: =(CellValue-MIN(SolarPotentialRange))/(MAX(SolarPotentialRange)-MIN(SolarPotentialRange))
- Cost Score = lower construction cost is better: =(MAX(CostRange)-CellValue)/(MAX(CostRange)-MIN(CostRange))
- Surface Area Score = lower envelope surface area is better: =(MAX(SurfaceAreaRange)-CellValue)/(MAX(SurfaceAreaRange)-MIN(SurfaceAreaRange))
- Overall Single-Objective Score = weighted combined score: =0.25*FloorAreaScore+0.25*ProfitScore+0.10*SolarEfficiencyScore+0.20*SolarPotentialScore+0.10*CostScore+0.10*SurfaceAreaScore
- Rank = rank alternatives from highest overall score to lowest: =RANK.EQ(CellValue,OverallScoreRange,0)
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.
My overall strategy is to assign each metric a normalized score and combine the scores using a weighted sum to create one overall evaluation value. Each metric for each alternative is scaled from 0 to 1 based on its performance relative to the other alternatives, with 1 representing the best performance and 0 representing the worst. For floor area, alternatives receive a score of 1 if they fall within the desired range, and the score decreases based on how far they are from that range. For metrics where higher values are better, such as profit and solar potential, the normalized score increases with the metric value. For metrics where lower values are better, such as construction cost and surface area, the scoring equation is reversed so that lower values receive higher scores.
The weights were assigned based on a combination of the assignment goals, what I felt was most important to the developer, and how closely some metrics relate to each other. I used smaller weights for some related metrics to prevent one category from overpowering the overall evaluation.
Summary Table:
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? The top three alternatives are highlighted in yellow. The highest-ranked option was the alternative with a 0.75 top scale and 300 ft middle height. This alternative rose to the top because it had the best overall balance across the weighted metrics. It met the desired floor area range, had a very high profit score, and performed well in solar efficiency. Even though it did not have the lowest surface area, lowest cost, or highest total solar potential, it performed consistently well in the categories that were weighted most heavily.
One tradeoff that gets simplified in the single-objective score is the relationship between surface area and solar potential. A larger surface area can provide more opportunity for solar gain, but it can also increase envelope cost and may not always improve solar efficiency if the added surfaces are poorly oriented. Similarly, profit and cost are related. A larger building may increase potential value, but it also increases construction cost. Because the final score combines everything into one number, it may hide some of these individual tradeoffs even though I tried to include it in the weights.