Optimising energy performance of an Eco-Home using Building Information Modelling (BIM)

Chai, Chang Saar; Abidin, Nur IzieAdiana; Khoso, Ali Raza; Luenhui, Ling; Yaoli, Xiong; Gui, Hun Chuen

doi:10.1007/s41062-022-00747-6

Cited by 14 publications

(12 citation statements)

References 17 publications

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“…Evaluate the availability of using BIM big data in Building Digital Twins for building energy efficiency [24].…”

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

“…After energy simulation by GBS, they found that using the developed framework can reduce service life costs and energy consumption for the studied case building by 24-58%. Wang and Guo [24] evaluated the availability of using BIM big data in Building Digital Twins for building energy efficiency. They developed a simulating experiment and used some approaches including DL, DFA and BPNN, etc.…”

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

“…In addition, some researchers also stated that BIM could effectively assist the designers and stakeholders in identifying the key parameters which could affect building energy consumption and make sustainable design in the early phase of construction design for green buildings [15,16,20]. Motalebi and Rashidi [22] and Wang and Guo [24] even made some improvements to BIM with other technologies for building energy performance. They integrated LCA theory and Digital twins technology into BIM, respectively, to improve the ability to assess the environmental impact and the interaction capacity of BIM, and the results showed that BIM performed well in both pieces of research.…”

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

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Using Regression Model to Develop Green Building Energy Simulation by BIM Tools

et al. 2022

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Energy consumption in the building sector poses a huge burden in terms of global energy and pollution. Recent advancements in building information modelling and simulating building energy performance (BEP) have provided opportunities for energy optimization. The use of building information modelling (BIM) also has increased significantly in the last decade based on the requirement to accommodate and manage data in buildings. By using the data, some building information modelling tools have developed the function of energy analysis. This paper aims to identify design parameters critical to BEP to assist architects in the initial stages of building design and to investigate their relationship. The outcomes of the prototype model’s energy simulations were then used to construct multilinear regression models. For the rest of the independent building design variables, linear regression models are used to analyse the relationship between it and energy consumption. It was concluded that, in the same building conditions, diamond-shaped buildings have the highest energy consumption, while triangle-shaped buildings showed the most efficient energy performance through energy simulations for seven fundamental prototype building models based on Autodesk Kits, Green Building Studio (GBS) with a Doe-2 engine. In addition, the developed regression models are validated to within 10% error via a case study of the ABS building. At the end of this paper, recommendations are provided on energy optimisation for the initial stages of building design. The parametric analysis of design variables in this study contributed to the total energy consumption at the early phases of design and recommendations on energy optimization.

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“…Evaluate the availability of using BIM big data in Building Digital Twins for building energy efficiency [24].…”

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

Section: Aim Methods Findings and Limitationsmentioning

confidence: 99%

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Using Regression Model to Develop Green Building Energy Simulation by BIM Tools

et al. 2022

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“…In the same way, the distinction has been made with several identifications of the scope of the decision support the approach should provide. Moreover, several study projects based in this field have the objective of supporting the generation of design alternatives via knowledge-based inference algorithms [30]. Furthermore, in opposition to this forward-reasoning strategy, the Smart (DMF) has the objective of evaluating design alternatives already generated via a human development team (Figure 1).…”

Section: The Decision-making Issuesmentioning

confidence: 99%

Assessment of a Decision-Making Model for Monitoring the Success of a Project for Smart Buildings

2023

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Objective: To express the usage of intelligent concepts in the architectural building construction field that are primarily concerned with reducing building energy use. Improved energy-saving methods and the use of environmentally friendly design principles are essential in this field. This type of managerial decision-making is necessary for the success of these types of projects. Methods: monitoring the performance of intelligent buildings use the cost variance (CV) and schedule variation as standard metrics to track the progress of a project based on the save energy concept. Also, this research conducted a comparative study on Building Information Modelling (BIM) and (MCDM) decision-making limitations as presented in the article. Analysis: the conventional technique, on the other hand, is unable to offer data on variance from typical performance levels. The main point based on Delphi results of construction cost variables has been observed 19 effective factors. Finding and Novelty: The RII observed that the most effective aspects of an intelligent building are the number of floors in the building, the kind of structural design, and the size of the shadow cast on the surface of the building. The Multi-Criteria Decision Maker (MCDM) observed significant differences in planned value (PV) and actual value (AC) results. In addition, as a result of the current approach, it is possible to track project costs and timelines more precisely. Doi: 10.28991/CEJ-2023-09-01-010 Full Text: PDF

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“…Digital has multiple roles in facilitating a sustainable built environment, for instance, catalysing enhanced health and the prosperity of humans and the environment and establishing mutually beneficial interactions that self-replicate to generate inclusive resilience (Jenkin & Zari, 2009;Changsaar et al, 2022). To ensure the viability and acceptance of technological advancements in the construction industry, they must respect and have a profound regard for local settings, whether cultural, economic, or ecological, for development to be appropriately tailored to local culture, ecosystems, and economic situations and ensure development that meets the needs of the present without compromising the ability of future generations to meet their own needs.…”

Section: Sustainable Development and Built Environmentmentioning

confidence: 99%

Evaluation of Digital’s Role in Sustainable Built Environment

Wayne¹,

Chai²,

Wong³

et al. 2023

JST

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The construction industry has been evolving, embracing the delicate balance between the Fourth Industry Revolution and sustainable construction to create a sustainable and resilient built environment. Integrating digital tools and technologies in a renowned conventional construction industry is challenging, mainly due to the complex interaction between heterogeneous but heuristic construction processes, building systems, and workflows in achieving a common goal. This study took the initiative to review digital tool adoption and its role in the sustainable built environment by examining the impact of digital adoption in a sustainable built environment in terms of societal and industry impacts. A quantitative analysis is conducted, collecting 63 industry practitioners analysed through regression analysis. The result reveals that energy conservation is the most significant element in the sustainable built environment, which brought the greatest impact on both society and industry in Malaysia. Based on the results, it is found that the digital adoption level in the Malaysian construction industry is still at a minimal level. Through the introduction of Indutry4wrd, National 4IR and Construction 4.0 Strategic Plan (2021–2025), the importance of digital tools and technologies is slowly being acknowledged. The result of the study is significant to benchmark the current digital tools adoption in the Malaysian sustainable built environment. Moreover, the contribution could be made in terms of better understanding and facilitating, where relevant, greater usage of digital tools in the construction industry to promote efficiency.

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Optimising energy performance of an Eco-Home using Building Information Modelling (BIM)

Cited by 14 publications

References 17 publications

Using Regression Model to Develop Green Building Energy Simulation by BIM Tools

Using Regression Model to Develop Green Building Energy Simulation by BIM Tools

Assessment of a Decision-Making Model for Monitoring the Success of a Project for Smart Buildings

Evaluation of Digital’s Role in Sustainable Built Environment

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