A Framework of Decision Support System from BIM to Digital Twin Aiming Zero Energy Buildings

Mehmet Akif Aydin*, Gul Koclar Oral

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In buildings that have a large share of the world’s total energy consumption, reducing carbon emissions and zero energy building targets have become increasingly important in recent years. The most important problems in providing energy efficiency in building design are the difficulty in integrating energy efficient design tools into the design processes and the need for extra labor and time. Rapidly developing technology and digitalization processes create new advantages in zero energy building targets. However, there is not enough information about how to integrate these new technologies into zero energy design and operation processes. Therefore, in this study, the zero-energy building target is discussed in the context of BIM, generative design and digital twin, which are important technological thresholds for the building sector. The concept of zero-energy building and literature examined, zero-energy building parameters and strategies are determined, the concept of BIM and its use in zero energy buildings are discussed. In addition, the integration of generative design into BIM and energy efficient design is studied. In the last stage, the potential and usage areas of building digital twin technologies were investigated and their integration into zero energy building and BIM processes was enquired. As a result, through the information obtained from research, a decision support system framework consisting of four steps, based on the use and integration of current technologies that can contribute to zero energy building design and operation processes towards the aim of zero energy building, developed and presented.

Original languageEnglish
Title of host publicationProceedings of 6th International Conference on Civil Engineering and Architecture, Vol. 1 - Proceedings of ICCEA 2023
EditorsThomas Kang, Youngjin Lee
PublisherSpringer Science and Business Media Deutschland GmbH
Pages16-25
Number of pages10
ISBN (Print)9789819753109
DOIs
Publication statusPublished - 2024
Event6th International Conference on Civil Engineering and Architecture, ICCEA 2023 - Bali Island, Indonesia
Duration: 16 Dec 202318 Dec 2023

Publication series

NameLecture Notes in Civil Engineering
Volume530 LNCE
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565

Conference

Conference6th International Conference on Civil Engineering and Architecture, ICCEA 2023
Country/TerritoryIndonesia
CityBali Island
Period16/12/2318/12/23

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Keywords

  • Building Information Modelling (BIM)
  • Decision Support System
  • Digital Twin
  • Generative Design
  • Zero Energy Buildings

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