- For 2 or More Units: Create Two New Evaluator Nodes
- Images showing the node logic in your new evaluator nodes
- An Image/screenshot of your summary table (created in Word, Excel, Google Sheets, or any data table tool) showing the input values tested and the values computed for each of the reported parameters
- For 3 or More Units: Develop a Single-Objective Optimization Scheme
- Brief description:
Custom Node 1 - Total Cost, High-Cost Area Ratio, Cost Efficiency Index
The total cost was made based on function in which the cost per square foot increased as the height increased from 500 to 1000. Using these values as well as the areas of the floors I computed the high-cost area ratio which is the percent area exceeding the average price per area in Dubai. This is around 3100 AED or 850 USD on average. Ideally, a building would stay in between 0.2 and 0.3 or lower. The cost efficiency ratio is the total cost divided by the total floor area. The smaller this number the better.
Custom Node 2 - Surface Area to Volume Ratio, Surface Area to Floor Area Ratio, Facade Cost Index
The second custom node focuses on energy efficiency, passive design, and cladding efficiency. The surface area to volume ratio measures the energy efficiency of the building. A lower surface to volume area is typically better as there is less surface for heat transfer. The surface area to floor area ratio measures the efficiency of the envelope per usable space. Typically, lower values are better (more floor area and less surface area). The facade cost index measures the cost per SF of facade. Thus, for efficiency, lower numbers are better.
The first thing done was to filter the tested values in order for all of them to have a total gross floor area between 2500000 and 3000000 SF. Conditional formatting was then used to highlight the lowest numbers in each of the 6 metrics (for all of them lower = better) (Table 2). The max and min was then found from each of the filtered columns (see Table 3). These maximum and minimum values were then used to normalize the values in each column with numbers between 0 and 1 (1 - lowest number which is the best; 0 - highest number which is the worst). Each of the metrics were also assigned a weight (See Table 2). These were then lastly used together with the normalized columns to find a weighted sum for all filtered options. The options with the highest score were selected (These are options 1, 3, and 8 from the filtered list).
I would recommend option 1. The recommendation is based on the weight of each metric and considers the best options out of each test case. The recommendation is based on a weighted sum. (The recommendation will vary in dependence with each one’s interpretation of the weight of each metric).
- Your answers to the Points to Ponder questions for each stage of the assignment that you completed.
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?
I would say so. The metrics are pretty variable and show significant differences between each alternative. One important metric that I would consider (that I wanted to but unfortunately, I did not have enough time), is the solar potential as well as the amount of clean energy that can be generated from solar panels due to that.
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.
I think that the metrics are definitely not equal between each other in how important they are. Thus, weights should be used to capture that. Then, a formula should be developed that considers the weights and calculates the score of each option. The higher the score the better the option. The numbers in each column can be normalized to numbers between 0 and 1 for an easier interpretation of the results.
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 is the single evaluation?
The recommendation had the highest score in this calculation. It also has a pretty low total cost compared to other options and the lowest HCAR, meaning it has the lowest percentage of area that costs above the Dubai average (only 29.5% of the area is above the average). It also has a decently low Facade Cost Index. As a tradeoff, the Surface to Volume and Surface to Floor Area Ratios were considerably high (The Surface to Floor Ratio is the highest out of all the options). However, this had a lower impact due to the selected weights of each metric. I considered these ratios to be less important than the total cost or cost efficiency index.