Figure 1
The flowchart depicts the following sequence from left to right and top to bottom: A large dotted rectangular block titled “5 parametric models representing 28 building archetypes.” The text below the title reads, “Fixed parameters: Building dimensions, Floor layout, Number of storeys, Compactness ratio and typology, Function and occupancy, Roof type, Window to wall ratio and Dynamic parameters (retrofitting measures): Ventilation system, Infiltration level, Window insulation quality, Roof insulation quality, Façade insulation quality, Ground floor insulation quality. The text below these parameters reads, “Weather data (.e p w).”“ An arrow from this block is pointing to a second block titled “Parametric engine.” The text below the title reads, “Using Ladybug tools.” Below the text there are three distinct logos. From left to right, the first logo is a red ladybug with black spots. The second logo is a yellow and black striped bee. The third logo is a light blue hummingbird with outstretched wings. An arrow from this block is pointing to a third block titled “Dynamic simulation.” The text below the title reads, “Using OpenStudio and EnergyPlus.”Below the text are two distinct logos. On the left, there is a logo for “EnergyPlus,” which features a stylized red “e” with a blue “plus” sign and the word “EnergyPlus” in smaller text beneath it. On the right, there is a blue cube logo with “O S” inscribed in white on two of its visible faces, representing “OpenStudio.” An arrow from this block is pointing to a fourth block titled “Scenario analysis.” The text below the title reads, “Selection retrofitting packages for “Current,” “M T,” and “L T” scenarios.” Below this text, a parallel coordinates plot is depicted. The plot features multiple vertical axes, each representing a different variable, and numerous lines connecting points across these axes. An arrow from this block is pointing to a fifth block titled “Parametric model “aggregator”.” The text below the title reads, “Matching spatial data on building within the studied area with hourly profiles of the 28 archetypes to create aggregated thermal profiles.” Above this block, a sixth block is titled “G I S data extracted from studied urban area.” The text below the title reads, “Building blocks and attributes, Residual heat potential from cooling processes, Potential from open water, Open space (private and public), and Street network.” A logo below the text reads, “Q G I S.” An arrow from this block is also pointing to the fifth block. Arrows from the fifth and sixth blocks are pointing to the seventh block titled “Clustering model.” The text below this title reads, “Spatial integration of the networks using Urbano, Spiderweb, A asterisk search algorithm” and “Defining fitness objectives for simulation.” Below this text are two distinct graphic elements. On the left, there is a stylized black spider sitting on a spiderweb. Around the spider and web, several small, colorful, abstract square icons are scattered. On the right side, there is a metallic, rectangular toolbox with a handle on top. The word “LunchBox” is visible in a light grey font on the front of the toolbox. The text below these graphics reads, “Fitness objectives: (1) Minimise the overall length of the pipe network, (2) Minimise the number of isolated buildings, (3) Minimise the absolute imbalance, and (4) Minimise the number of clusters.” An arrow from this block is leading to a final block titled “Evolutionary solver.” The text below the title reads, “Computing scenarios considering the four fitness objectives; Selecting and extracting Pareto front solutions with the K-means clustering to get best-balanced results.” Below, there are four layouts arranged in a 2 by 2 grid, featuring a building block with highlighted sections. Each layout contains a diamond chart below it. At the top, “5 parametric models representing 28 building archetypes,” “Parametric engine,” “Dynamic simulation,” and “Scenario analysis” are combinedly labeled “Building retrofitting scenarios”; “G I S data extracted from studied urban area” and “Parametric model “aggregator”“ are labeled “Area definition context”; “Clustering model” and “Evolutionary solver” are labeled “Clustering scenarios.”Overview of the design workflow (Dang, 2024)