Abstract Prefabricated construction has been used for public rental housing in Hong Kong. In order to speed up housing delivery, Hong Kong Housing Authority (HKHA) have employed advanced technologies, including Building Information Modelling (BIM) and Radio Frequency Identification (RFID), in some of their pilot prefabrication-based construction projects. However, the information obtained from BIM and RFID is not well connected and shared among relevant stakeholders. This paper introduces a multi-dimensional Internet of Things (IoT)-enabled BIM platform (MITBIMP) to achieve real-time visibility and traceability in prefabricated construction. Design considerations of a RFID Gateway Operating System, visibility and traceability tools, Data Source Interoperability Services, and decision support services are specified for developing the MITBIMP. A case study from a real-life construction project in Hong Kong is used as a pilot project to demonstrate advanced decision-making by using cutting-edge concepts and technologies within the MITBIMP to providing a basis for real-time visibility and traceability of the whole processes of prefabrication-based construction.
M. H. Rasmussen, Maxime Lefrançois, G. Schneider
et al.
Actors in the Architecture, Engineering, Construction, Owner and Operation (AECOO) industry traditionally exchange building models as files. The Building Information Modelling (BIM) methodology advocates the seamless exchange of all information between related stakeholders using digital technologies. The ultimate evolution of the methodology, BIM Maturity Level 3, envisions interoperable, distributed, web-based, interdisciplinary information exchange among stakeholders across the life-cycle of buildings. The World Wide Web Consortium Linked Building Data Community Group (W3C LBD-CG) hypothesises that the Linked Data models and best practices can be leveraged to achieve this vision in modern web-based applications. In this paper, we introduce the Building Topology Ontology (BOT) as a core vocabulary to this approach. It provides a high-level description of the topology of buildings including storeys and spaces, the building elements they contain, and their web-friendly 3D models. We describe how existing applications produce and consume datasets combining BOT with other ontologies that describe product catalogues, sensor observations, or Internet of Things (IoT) devices effectively implementing BIM Maturity Level 3. We evaluate our approach by exporting and querying three real-life large building models.
Abstract Additive manufacturing (AM) of construction materials has been one of the emerging advanced technologies that aim to minimise the supply chain in the construction industry through autonomous production of building components directly from digital models without human intervention and complicated formworks. However, technical challenges needs to be addressed for the industrial implementation of AM, e.g. materials formulation standardization, and interfacial bonding quality between the deposited layers amongst others. AM as one of the most highlighted key enabling technologies has the potential to create disruptive solutions, the key for its successful implementation is multidisciplinary effort in synergy involving materials science, architecture/design, computation, and robotics. There are crucial links between the material design formulations and the printing system for the manufacturing of the complex 3D geometries. Understanding and optimising the mix design for fresh rheology of materials and sufficient adhesion/cohesion of interface can allow the incorporation of complexity in the geometry.
L. Àkànbí, Lukumon O. Oyedele, Kamil Omoteso
et al.
Abstract Despite the relevance of building information modelling for simulating building performance at various life cycle stages, Its use for assessing the end-of-life impacts is not a common practice. Even though the global sustainability and circular economy agendas require that buildings must have minimal impact on the environment across the entire lifecycle. In this study therefore, a disassembly and deconstruction analytics system is developed to provide buildings’ end-of-life performance assessment from the design stage. The system architecture builds on the existing building information modelling capabilities in managing building design and construction process. The architecture is made up of four different layers namely (i) Data storage layer, (ii) Semantic layer, (iii) Analytics and functional models layer and (iv) Application layer. The four layers are logically connected to function as a single system. Three key functionalities of the disassembly and deconstruction analytics system namely (i) Building Whole Life Performance Analytics (ii) Building Element Deconstruction Analytics and (iii) Design for Deconstruction Advisor are implemented as plug-in in Revit 2017. Three scenarios of a case study building design were used to test and evaluate the performance of the system. The results show that building information modelling software capabilities can be extended to provide a platform for assessing the performance of building designs in respect of the circular economy principle of keeping the embodied energy of materials perpetually in an economy. The disassembly and deconstruction analytics system would ensure that buildings are designed with design for disassembly and deconstruction principles that guarantee efficient materials recovery in mind. The disassembly and deconstruction analytics tool could also serve as a decision support platform that government and planners can use to evaluate the level of compliance of building designs to circular economy and sustainability requirements.
High-quality growth of the construction industry and an improved human settlements environment are essential to sustainable urbanization. Existing studies have paid limited systematic attention to the spatial and temporal dynamics of the coordinated development between the construction industry and human settlements, as well as the underlying factors driving regional disparities. This gap restricts the formulation of precise, differentiated sustainable policies tailored to regions at different development stages and with varying resource endowments. Southern China, characterized by pronounced spatial heterogeneity and unique development trends, offers a natural laboratory for examining the spatio-temporal interaction between these two dimensions. Using panel data for 15 southern provinces (2013–2022), we applied the entropy method, coupling coordination model, Dagum Gini coefficient, spatial trend surface analysis, gravity model, and grey forecasting to evaluate current conditions and predict future trends. The main findings are as follows. (1) The coupling coordination degree rose steadily, forming a stepped spatial pattern from the southwest through the center to the southeast. (2) The coupling coordination degree appears obvious polarization effect, presenting a spatial linkage pattern with Jiangsu-Shanghai-Zhejiang, Hubei-Hunan-Jiangxi, and Sichuan-Chongqing as the core of the three major clusters. (3) The overall Dagum Gini coefficient declined, but intra-regional disparities persisted: values were highest in the southeast, moderate in the center, and lowest in the southwest; inter-regional differences dominated the total inequality. (4) Forecasts for 2023–2027 suggest further improvement in the coupling coordination degree, yet spatial divergence will widen, creating a configuration of “eastern leadership, central catch-up acceleration, and differentiated southwestern development.” This study provides an evidence base for policies that foster high-quality construction sector growth and enhance the living environment. The findings of this study indicate that policymaking should prioritize promoting synergistic regional development, enhancing the radiating and driving role of core regions, and establishing a multi-level coordinated governance mechanism to bridge regional disparities and foster more balanced and sustainable development.
Abstract Data-driven green building design in BIM is challenged by the lack of a comprehensive data integration framework with the capabilities of building life-cycle performance data management and application. This paper proposes a performance integrated BIM (P-BIM) framework for building life cycle energy efficiency and environment optimization. A school building is presented as a case study to verify the P-BIM framework and the design optimization workflow established. The results show that the optimization can improve IEQ by 11.5% and reduce LCC by 36.8%. The influences of different envelope constructions on indoor environment, energy consumptions, and costs are also studied. The P-BIM framework and the optimization methodology built on it demonstrate that the methodology developed can expand the application scope of BIM and contribute to data-driven green building design. More application scenarios focusing on the stage of facility management and different sustainability performance will be conducted in P-BIM framework in future works.
Technology and innovations have fueled the evolution of Industry 4.0, the fourth industrial revolution. Industry 4.0 encourages growth and development through its efficiency capacity, as documented in the literature. The growth of the construction industry is a subset of the universal set of the gross domestic product value; thus, Industry 4.0 has a spillover effect on the engineering and construction industry. In this study, we aimed to map the state of Industry 4.0 in the construction industry, to identify its key areas, and evaluate and interpret the available evidence. We focused our literature search on Web of Science and Scopus between January 2015 and May 2019. The search was dependent on the following keywords: “Industry 4.0” OR “Industrial revolution 4.0” AND TOPIC: “construction” OR “building”. From the 82 papers found, 20 full-length papers were included in this review. Results from the targeted papers were split into three clusters: technology, security, and management. With building information modelling (BIM) as the core in the cyber-physical system, the cyber-planning-physical system is able to accommodate BIM functionalities to improve construction lifecycle. This collaboration and autonomous synchronization system are able to automate the design and construction processes, and improve the ability of handling substantial amounts of heterogeneity-laden data. Industry 4.0 is expected to augment both the quality and productivity of construction and attract domestic and foreign investors.
Organic Rankine cycle (ORC) has been considered as one of the most promising technologies in industrial waste heat utilization and power generation. During the actual operation of ORC system, due to the fluctuation of cooling and heat sources, the system operates under off-design conditions in most cases. In this paper, thermodynamic model, heat transfer process description and power equipment model are established to evaluate the operating parameters of ORC for the off-design conditions. Evaporation temperature and condensation temperature are taken as independent parameters for the operation of ORC system. Genetic algorithm is adopted to optimize the independent parameters under the maximum net output power. The results show that the effect of optimizing independent parameters is to make the working fluid at the outlet of the preheater as close as possible to a saturated liquid state, and the working fluid at the inlet of the screw expander should be in a saturated gas state. With the optimal power output increasing by 19.1% for every 5 °C increase in hot water inlet temperature, 9.2% for every 20 kg/s increase in hot water mass flow rate, and 3.9% for every 1 °C decrease in cooling water temperature. The optimization method of off-design operating conditions has good system performance and good engineering application prospects.
Environmental technology. Sanitary engineering, Building construction