A new design exploring framework based on sensitivity analysis and Gaussian process regression in the early design stage

Abstract

With building energy codes getting strict, quantitative analysis is necessary in the early design stage of high-energy-performance buildings. To fully explore the design space, a highly efficient method is necessary. In the research, a new design exploring framework was proposed. Parameters are screened and separated into groups based on the sensitivity analysis, to reduce the dimension of inputs. Gaussian process regression, able to deal with the uncertainty in inputs, was used to make metamodels to reduce the calculation cost and fully explore the design space. Dashboards were made to visualize the data interactively, to help designers make decisions and make communications smooth. This framework was demonstrated with a case study and showed its efficiency.