Orientation
South · East · West
KTI · Parametric facade study
Facade performance for a modular office building.
A Grasshopper shoebox model and ClimateStudio simulations compare seven window designs, three orientations and several external-louvre settings.
648configurations
5input variables
3performance outputs
01 · Project setup
Building and simulation model.
The building is a modular office block of roughly 37 × 14 m. Repeated 3.7 × 5.4 m office modules sit on both sides of a central corridor, providing a consistent room geometry for the facade study.
The long facade faces south. Orientation, window layout and louvre geometry were varied while the room dimensions and internal setup remained fixed.
Each simulation row connects a specific set of design inputs to total load, cooling load and useful daylight illuminance at desk level.
02 · Parameters
Five variables define each run.
The depth-zero cases retain one canonical gaps and rotation setting to avoid repeating identical no-louvre simulations.
Louvre gaps
5 · 6 · 7
Rotation
−40° · −20° · 0° · 20° · 40°
Depth
0 · 20 · 40
Window design
Design 0 to design 6
03 · Results
Filter and compare the configurations.
Use the first row of controls to define a set. The second row creates a direct comparison. Select a point to load its exact facade image and input settings.
Total load vs. UDI at desk levelNavy: first selection · yellow: comparison · green: shared · red outline: ranked
648 configurationsPerformance by orientationShared range is green; differences retain each selection colour
Selected configuration
Select a point in the scatter plot.
Input settings and output values will appear here.
Total load—
Cooling load—
UDI at desk level—
04 · Reading the dataset
Energy and daylight do not produce one universal optimum.
The red-outlined configurations identify five options per orientation after applying a minimum UDI requirement of 55%. The ranking weights lower cooling load at 70% and higher UDI at 30%.
Keeping the graph limits fixed allows filtered groups to remain visually comparable with the full dataset.
The paired filters reveal how a single design decision changes the result while the remaining parameters stay fixed.