Abstract
The early architectural design involves the most salient decisions. However, because of the large amount of variance, the decision-making is highly arduous. This article presents a methodology to enable the most effective design variables to be selected within the most effective value range by presenting a method that allows the measurement of output uncertainty depending on the impact of design decisions on outputs. The methodology was tested with different building functions and climate regions using two-phase sensitivity analysis. The values of design variables were generated with quasi-random sampling. They were sorted with factor prioritization. Ineffective variables were eliminated with factor fixing. Advanced global sensitivity analyses were performed for the total effect. Factor mapping was applied with the output weighting. The results were presented with Parallel Coordinate Plot (PCP). The designers can make selections from alternatives with PCP. Finally, the study demonstrated how climate and building functions should be considered for building performance.
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More From: International Journal of Digital Innovation in the Built Environment
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