BIM-based generative design approach for integral residential energy-efficient façades

Abstract

Residential buildings significantly impact global energy consumption. Appropriate residential façade designs can considerably reduce energy consumption in maintaining indoor comfort. Current research on residential energy-efficient façade design primarily focuses on single-objective studies and exploring parameter boundaries of isolated façade elements, neglecting holistic perspectives. It results in a research deficiency in multi-objective optimisation and integral design approaches. This study presents an innovative AI-aided methodology integrating Building Information Modelling (BIM) and Generative Design (GD) to automate multi-objective optimisation and energy-efficient compliance assurance in Australian residential façade design. Through the developed BIM-based GD program, well-founded and compliant integral energy-efficient façade designs can be generated and modelled automatically and efficiently.

A practical case study on a self-contained dwelling using the developed program validates the feasibility and effectiveness of the proposed approach. The program can successfully generate multiple façade designs within a significantly short time, only taking an average of 2–3 s per design. The generated façade designs are verified energy efficient, reducing around 6.7 % in heating loads and 3.5 % in cooling loads compared to a reference building. These results demonstrate that the proposed approach enables the efficient generation of residential integral façade designs while ensuring the designs’ energy efficiency. This study’s contributions include advancing multi-objective optimisation, streamlining compliance processes, and demonstrating a practical method for AI-aided integral façade design. The paper also discusses limitations and future directions. The findings and methodologies provide valuable insights for advancing AI-aided energy-efficient building design.