INTEROPERABILITY-BASED OPTIMISATION OF ARCHITECTURAL DESIGN objectives simultaneously. Objective vectors, where none of the components can be improved without deterioration to at least one of the other components (Miettinen 1999). A Pareto optimal set usually has a lot of Pareto optimal solutions which could be nonconvex and nonconnected. It is the decision maker’s task to select the optimum value based on the decision matrix or decision plot.
Results for Kilkenny, regular schedule Results from study 2 for the building in Kilkenny, operating in regular schedule, are given in Table 6.8. Values of objective function (Total Energy Consumption) increases with the corresponding increase in the constraint value (Average Daylight Factor). Design variables for best design points are given in Figure 6.20 which shows relatively benign characteristics of Kilkenny climate, also been observed in study 1.
90
0.4
60
0.2
30
0.0
0
Building Azimuth (deg)
0.6
8%
120
7%
0.8
6%
150
5%
1.0
4%
180
3%
1.2
2%
Area (sqm)
Design variables for best design points, Kilkenny Regular schedule
Constraint - Average Daylight Factor Building Aspect Ratio East Window
North Window West Window
South Window Building Azimuth
Figure 6.20: Design variables for best design points for study 2, Kilkenny, regular schedule. Relatively larger value of south glazing fraction and corresponding area of glazing reinforces conventional wisdom of bioclimatic design in Marine climates such as Kilkenny. Relatively larger glazing fractions on east and west walls particularly at 8% ADF can be explained with Figure 6.21, where design variables are interpreted to corresponding glazing areas. As building aspect ratio became smaller, the corresponding areas for east and west glazing are considerably smaller than that of north and south. The dominance of south glazing over other cardinal sides is visible from the 138