Abstract One approach to decarbonising the cement and construction industry is to replace Portland cement systems with lower carbon alternatives that have suitable properties. We show that seven cementitious binders comprised of metakaolin, silica fume and nano-silica have improved thermal performance compared with Portland cement and we calculate the full CO 2 emissions associated with manufacture and transport of each binder for the first time. Due to their high porosity, the thermal conductivity of these novel cements is 58–90% lower than Portland cement, and we show that a thin layer (20 mm), up to 80% thinner than standard insulating materials, is enough to bring energy emissions in domestic construction into line with the UK 2013 Building Regulations. Carbon emissions in domestic construction can be reduced by c . 20–50% and these cementitious binders are able to be recycled, unlike traditional insulation materials.
Abstract Effective asset management plays a significant role in delivering the functionality and serviceability of buildings. However, there is a lack of efficient strategies and comprehensive approaches for managing assets and their associated data that can help to monitor, detect, record, and communicate operation and maintenance (O&M) issues. With the importance of Digital Twin (DT) concepts being proven in the architecture, engineering, construction and facility management (AEC/FM) sectors, a DT-enabled anomaly detection system for asset monitoring and its data integration method based on extended industry foundation classes (IFC) in daily O&M management are provided in this study. This paper presents a novel IFC-based data structure, using which a set of monitoring data that carries diagnostic information on the operational condition of assets is extracted from building DTs. Considering that assets run under changing loads determined by human demands, a Bayesian change point detection methodology that handles the contextual features of operational data is adopted to identify and filter contextual anomalies through cross-referencing with external operation information. Using the centrifugal pumps in the heating, ventilation and air-cooling (HVAC) system as a case study, the results indicate and prove that the novel DT-based anomaly detection process flow realizes a continuous anomaly detection of pumps, which contributes to efficient and automated asset monitoring in O&M.
Abstract 3D printing is a promising technology in construction industry. Unlike conventional construction process, 3D printing buildings are extruded by a nozzle layer-over-layer without the requirement of formwork. This paper investigates the rheological and harden properties of the high-thixotropy 3D printing concrete. Flowability, rheological property (viscosity, yield stress, thixotropy) and open time are considered as critical wet properties to control the printable property (pumpability, extrudability and buildability) of such concrete material. Five different mixtures are systematically investigated to obtain the optimum mix and then it’s used to study the harden property, such as anisotropy (compression and flexural), elastic modulus and drying shrinkage. At last, a large-scale components-bus station preliminarily was prepared by using this technology.
Over the past few years, the application of camera-equipped Unmanned Aerial Vehicles (UAVs) for visually monitoring construction and operation of buildings, bridges, and other types of civil infrastructure systems has exponentially grown. These platforms can frequently survey construction sites, monitor work-in-progress, create documents for safety, and inspect existing structures, particularly for hard-to-reach areas. The purpose of this paper is to provide a concise review of the most recent methods that streamline collection, analysis, visualization, and communication of the visual data captured from these platforms, with and without using Building Information Models (BIM) as a priori information. Specifically, the most relevant works from Civil Engineering, Computer Vision, and Robotics communities are presented and compared in terms of their potential to lead to automatic construction monitoring and civil infrastructure condition assessment.
Abstract With increasing attention on sustainable development, 3D printing construction and recycled concrete have drawn extensive interest as emerging construction technology and novel building materials. At this intersection, we attempted to evaluate the environmental impact and economic benefit of 3D printed buildings made of recycled concrete employing life-cycle assessment tools. Goal and scope definition, materials and scenarios, life-cycle inventory analysis, life-cycle assessment impact, and interpretation were detailed based on the characteristics of concrete 3D printing to better quantify the sustainability potential of recycled concrete used in 3D printed buildings. We found that although increases in using recycled aggregate could produce less pollutant emissions, the environmental impact caused by 3D printing concrete construction is generally larger than traditional cast-in-situ concrete construction. This is because additional cement is required in the 3D printing process to maintain dependable concrete performance. From the economic perspective, 3D printing concrete construction technology has significant advantages over traditional cast-in-situ concrete construction, saving the heavy cost of formwork and labor. Such benefit is even more pronounced in geometrically irregular buildings. We also found that the cost of buildings made of recycled concrete decreased as the proportion of recycled aggregate increased, owing to the higher price of natural aggregate. This paper contributes to identifying key factors in the life-cycle evaluation of 3D printing construction with cementitious materials.
Abstract Building information modelling (BIM) and geographical information systems (GIS) provide digital representation of architectural and environmental entities. BIM focuses on micro-level representation of buildings themselves, and GIS provide macro-level representation of the external environments of buildings. Moreover, their combination can establish a comprehensive view of a built environment based on data integrated, which underpins the development and transition of the architecture, engineering and construction (AEC) industries in the digital era. This paper gives a comprehensive review on BIM-GIS integration in sustainable built environments in order to analyse the status quo and practical applications from four viewpoints: technologies for data integration, applications in the life cycle of AEC projects, building energy management, and urban governance. Three typical modes of BIM-GIS integration, namely, “BIM leads and GIS supports”, “GIS leads and BIM supports”, and “BIM and GIS are equally involved”, are categorised based on the different dominant positions of the two technologies. Furthermore, the research trends and future directions for the applications of BIM-GIS integration are discussed. Specifically, we underline that semantic models and third-party integration platforms should be optimised technically, and information about the whole process of AEC projects needs to be improved. Comprehensive information for building energy management should be digitised and quantified to improve its systematic integration and application to the urban built environment. This review can serve as a roadmap for researchers who focus on studies of BIM-GIS integration in the sustainable built environment.
Modern construction projects face persistent challenges with cost overruns and fragmented management across disconnected service phases. Whole-Process Engineering Consulting (WPEC) addresses these issues by integrating investment decision-making, design, supervision, and cost management into a unified delivery framework. Therefore, this study aims to develop a WPEC competitiveness influencing factor system to identify the key influencing factors and the impact pathways. Firstly, a WPEC competitiveness framework comprising five dimensions and 28 factors is developed. Secondly, the Analytic Hierarchy Process (AHP) is applied to calculate factor weights based on 225 questionnaires. Then, the multi-level structural model is constructed based on Interpretative Structural Modeling (ISM) to identify the critical impact pathways. Finally, BZ Consulting Enterprise was selected as a case study to verify the rationality and practical value. The results show that the Corporate Full-Service Consulting Capability and Corporate Foundational Resources are identified as the core pillars, in addition to highlighting three key pathways—resource-integration drive, legacy-capability transfer, and service-awareness transformation—all of which link foundational drivers to market performance. Theoretically, this study introduces a systematic analytical framework for WEPC by mapping its competitiveness factors into the multi-level structural model. Practically, it enables enterprises to assess their transition readiness and formulate targeted strategies to secure a sustainable competitive advantage in the integrated consulting market.
A project that stands out among Croatian hotel architecture of the second half of the 20th century is the unique Slavonia Hotel System (SHS), designed in the mid-1970s by a team of experts from the Urban Institute of Croatia and headed by architect Matija Salaj. The SHS project was based on the principle of standardization in terms of spatial-functional organization, architectural design, interior design, furnishing and visual communication elements as well as operation and market penetration, and was envisaged as the driving force behind continental tourism development in Slavonia and Baranja. This paper examines the planning framework, program specifications, and urban-architectural design of the hospitality and tourist facilities of the SHS (including a city hotel model in two variations, a spa hotel, and a motel) by utilizing sources from Salaj’s estate and archival documentation from the Urban Institute. Notably, it includes Salaj’s explanations of the SHS project and his perspectives on the features of hospitality and tourist facility architecture, as presented in professional journals and conference publications. These aspects are complemented by a review of tourism development trends in the 1970s and the characteristics of hotel architecture in market economy.
Hazard mitigation and risk assessment for built heritage are central to contemporary conservation strategies, particularly in seismic-prone areas like Italy. This study presents preliminary findings of a research project focusing on the seismic vulnerability of historical masonry churches in the Province of Parma, a region with moderate seismic risk and a rich architectural heritage. Churches are among the most seismically vulnerable structures due to their complex construction, undocumented modifications, and sometimes ineffective past interventions. The research integrates GIS-based territorial analysis with archival investigation to evaluate the effectiveness of seismic strengthening measures implemented after the 1983 earthquake, especially in light of subsequent seismic events. A comprehensive database has been developed, cataloguing construction typologies, damage reports, and intervention strategies. Statistical and comparative analysis at both territorial and building scales helps assess the relationship between masonry characteristics, reinforcement techniques and seismic performance. Findings underscore the crucial role of past interventions in influencing current structural behaviour – sometimes positively, but also with unintended consequences. The study highlights the value of a multidisciplinary, data-driven approach combining digital tools and historical knowledge to support risk-informed conservation strategies. Ultimately, it aims to inform prioritization and planning frameworks that enhance the resilience of cultural heritage against future seismic events.
We present a two-scale physics-informed neural network (TSPINN) algorithm to address structural parameter inversion problems involving small parameters. The algorithm’s core mechanism directly embeds small parameters into the neural network architecture. By constructing a two-scale neural network architecture, this approach enables the simultaneous analysis of structural dynamic responses and local parameter perturbation effects, which effectively addresses challenges posed by high-frequency oscillations and parameter sensitivity. Numerical experiments demonstrate that TSPINNs significantly improve prediction accuracy and convergence speed compared to conventional physics-informed neural networks (PINNs) and maintain robustness in high-stiffness scenarios. The T-shaped tower shaking table test results confirm that the model’s identification errors for stiffness reduction coefficients and mass parameters remain below 10% under lower noisy conditions, demonstrating high precision and strong generalization capability for multi-damage scenarios and random load excitations.
This paper discusses the home garden (Pekarangan) Physical structure in the current condition of Javanese agricultural villages. The discussion mainly focused on home garden layout, spatial elements, and vegetation characteristics. The study of Traditional Javanese village home gardens is summarized from the study of relevant literature. Current conditions were identified from the results of observation and field studies in three villages selected based on the distance of the urban area. A spatial analysis of the home garden’s layout and forming elements was carried out to determine the current condition of the home garden structure and its transformation. The result revealed that the typical Javanese home garden structure in the village still exists and is utilized by people. Some home gardens were also transformed into new structures based on their original form. Home garden spatial structure transformation can be seen in the changes in home garden spatial structure, land size, area coverage, and vegetation characteristics. Furthermore, the composition of the home garden’s spatial structure transformation influences the village’s spatial development.
Bharathi Kannan Nithyanantham, Tobias Sesterhenn, Ashwin Nedungadi
et al.
Bringing generative AI into the architecture, engineering and construction (AEC) field requires systems that can translate natural language instructions into actions on standardized data models. We present MCP4IFC, a comprehensive open-source framework that enables Large Language Models (LLMs) to directly manipulate Industry Foundation Classes (IFC) data through the Model Context Protocol (MCP). The framework provides a set of BIM tools, including scene querying tools for information retrieval, predefined functions for creating and modifying common building elements, and a dynamic code-generation system that combines in-context learning with retrieval-augmented generation (RAG) to handle tasks beyond the predefined toolset. Experiments demonstrate that an LLM using our framework can successfully perform complex tasks, from building a simple house to querying and editing existing IFC data. Our framework is released as open-source to encourage research in LLM-driven BIM design and provide a foundation for AI-assisted modeling workflows. Our code is available at https://show2instruct.github.io/mcp4ifc/.
Sebe Vanbrabant, Gustavo Rovelo Ruiz, Davy Vanacken
While the increased integration of AI technologies into interactive systems enables them to solve an equally increasing number of tasks, the black box problem of AI models continues to spread throughout the interactive system as a whole. Explainable AI (XAI) techniques can make AI models more accessible by employing post-hoc methods or transitioning to inherently interpretable models. While this makes individual AI models clearer, the overarching system architecture remains opaque. To this end, we propose an approach to represent interactive systems as sequences of structural building blocks, such as AI models and control mechanisms grounded in the literature. These can then be explained through accompanying visual building blocks, such as XAI techniques. The flow and APIs of the structural building blocks form an explicit overview of the system. This serves as a communication basis for both humans and automated agents like LLMs, aligning human and machine interpretability of AI models. We discuss a selection of building blocks and concretize our flow-based approach in an architecture and accompanying prototype interactive system.