{"title":"BIM-based generative design approach for integral residential energy-efficient façades","authors":"Wei Ma , Xiangyu Wang","doi":"10.1016/j.enbuild.2024.115118","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div><div>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.</div></div>","PeriodicalId":11641,"journal":{"name":"Energy and Buildings","volume":"328 ","pages":"Article 115118"},"PeriodicalIF":6.6000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy and Buildings","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0378778824012349","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
An international journal devoted to investigations of energy use and efficiency in buildings
Energy and Buildings is an international journal publishing articles with explicit links to energy use in buildings. The aim is to present new research results, and new proven practice aimed at reducing the energy needs of a building and improving indoor environment quality.