Purpose: A robust method in environmental load assessment of buildings is urgently required to reduce the environmental burden of the construction industry. While the industry utilizes the life cycle assessment (LCA) method to assess environmental impacts of detailed designs, the implementation of changes at that late stage of development is often expensive and undesirable. On the other hand, during the early design stages, the LCA method is severely limited by the lack of information available, e.g., uncertainty about final materials to be used. This research study investigates how building information modeling (BIM) can facilitate LCA analysis at an early design stage.Design/methodology/approach: A literature review is conducted to establish a framework for BIM and LCA integration, which creates the foundation for the development of a new BIM-based LCA tool. The tool is empirically evaluated on a large case study of a residential building in Denmark.Findings: Case study results show that the new tool facilitates decision-making in an integrated design process, providing reliable LCA results on an early stage model, while avoiding intermediate manual input by the end user in contrast to other commercial LCA tools.Originality/value: A first prototype of a BIM-based tool is demonstrated, which allows professionals, small architectural companies, students and researchers to calculate the environmental loads of the building in the early design stage in an automated, transparent and time-saving manner.

Over the past few years, the AECO Industry has undergone a shift toward digital transformation, with a growing trend towards adopting innovative technologies such as Digital Twin (DT). DT offers a wide range of applications throughout the building development process. However, some specific factors impede its widespread adoption in the building industry. This study aims to systematically review the available literature on the building project development process from the perspective of DT, with a particular focus on predictive simulations, i.e., co-sims. The review provides a comprehensive overview of drivers and barriers to DT adoption through an analysis of 147 studies between 2013 and 2023. The research identifies seven external and 41 internal drivers, including efficient project management and monitoring, predictive maintenance, and the collection and visualization of real-time data, all of which contribute to improved decision-making processes and reduced operational expenses. Further, the study identifies nine external and 31 internal barriers that impede the adoption of DT in the building development process. These barriers encompass challenges such as a high initial investment cost, a scarcity of a skilled workforce, difficulties in data interoperability, and resistance to change within the organization. A key outcome of the literature review is having identified the opportunity to exploit technologies developed in the automotive sector that enable a seamless integration of specialized simulator models in building development processes, resulting in collaborative simulations. Thus, we propose the concept of a Building Simulation Identity Card (BSIC) to be pursued in future research that would enable stakeholders to address the challenges of collaboration, cooperation, coordination, and communication by creating a common vocabulary to effectively facilitate the adoption of DT in the building's development process.

We propose a human-centred model for abstraction, modelling and computing in function-driven spatial design for architecture. The primitive entities of our design conception ontology and computing framework are driven by classic notions of `structure, function, and affordance' in design, and are directly based on the fundamental human perceptual and analytical modalities of visual and locomotive exploration of space. With an emphasis on design semantics, our model for spatial design marks a fundamental shift from contemporary modelling and computational foundations underlying engineering-centred computer aided design systems. We demonstrate the application of our model within a system for human-centred computational design analysis and simulation. We also illustrate the manner in which our design modelling and computing framework seamlessly builds on contemporary industry data modelling standards within the architecture and construction informatics communities.