Explore the vast range of titles available.

With the fast growth and rapid development of the construction industry, building design is not satisfied with only safety, accessibility, and habitability. People are requiring more multifunctional layouts and beautifully designed buildings. Thus, special and unique-shaped buildings with various curved curtain walls have emerged more than ever in recent years. As for these curtain walls, it is difficult to perform the size measurement for panel design and calibration, as well as the on-site material cutting and assembly accurately and efficiently. The occurrence and continuous progress of 3D laser scanning technology combined with building information modeling (BIM) technology have been paid attention to and applied for curtain wall engineering to overcome this problem, particularly the construction-related progress, such as developed design and on-site installation. The 3D laser scanning technology can achieve fast and high-precision measurement by creating a “point cloud” dataset of the target building and its components, based on which an accurate as-built 3D BIM model of the scanned items can be established. By comparing and calibrating with the as-planned curtain wall design, engineers can update the real-time information (locations, shape, dimensions, etc.) for the following developed design and assembly production of the curtain wall. Compared to the conventional approach using manual locating and measurement, the progress of the curtain wall design and installation can be achieved in a more accurate and efficient manner by employing 3D laser scanning technology. Based on these considerations, in this present study, the basic concept, workflow, a case study with practical strategies of the application of 3D laser scanning technology in the curtain wall design and installation field, including the scanning operation, point cloud data acquisition and processing, 3D BIM model reconstruction, and relevant BIM model practice have been elaborated and discussed. Also, the 3D model that represents the actual construction condition established based on the point cloud data was used to compare with the originally designed BIM model. It was found discrepancies existed in the dimensions and positions between the as-built and as-designed BIM models, which can thus be used to revise the manufacture design and improve the installation plan of curtain walls. Furthermore, the difference, benefits, great significance of replacing conventional methods with 3D laser scanning technology, and instructions, limitations, recommendations for practical application, along with challenges and future directions open to research in the curtain wall construction field, were also presented in this work. Therefore, this work provides technical support to the application of 3D laser scanning technology and its combination with the BIM platform in the curtain wall construction.

PurposeThe unitized curtain wall system (UCWS), a symbol of modern architecture, is gaining popularity among prefabricated components. Previous studies have focused on both construction technology advances and material selection strategies to facilitate the UCWS. However, the topic of client satisfaction, which drives industry development by targeting clients' demands, has gone unnoticed. Therefore, the current study aims to investigate client satisfaction with UCWS products in Hong Kong by finding its influential factors.Design/methodology/approachA systematic review was employed to first identify the influential factors. A semi-structured interview was employed to validate the reliability of the extracted factors. The machine learning algorithm Extreme Gradient Boosting (XGBoost) and the Pearson correlation were then employed to rank the importance and correlation of factors based on the 1–5 Likert scale scores obtained through a questionnaire survey.FindingsThe findings revealed that “reduction in construction time” and “reduction in construction waste” are the most important factors and have a strong positive influence on client satisfaction.Originality/valueUnlike previous studies, the present study focused on a novel research topic and introduces an objective analysis process using machine learning algorithms. The findings contribute to narrowing the knowledge gap regarding client preference for UCWS products from both individual and collaborative perspectives, providing decision-makers with an objective, quantitative and thorough reference before making investments in the curtain wall management development.

Under the excitation of strong wind load, the hidden frame glass curtain wall leads to the attenuation of safety performance, the fragmentation of glass panel, and the shedding of glass panel, which has a serious impact on the economic and social development and people’s safety. In this paper, a new health monitoring method was proposed for the glass panel of hidden frame glass curtain wall. The fuzzy comprehensive evaluation theory was used to establish the comprehensive evaluation model of the hidden frame glass panel. The factor set of the comprehensive evaluation model was established by the air tightness, deflection, natural frequency, and vibration amplitude of the hidden frame glass panel. The safety performance was divided into four levels of evaluation set, and the weight of each factor was calculated by analytic hierarchy process. The vibration signals of glass panel under different wind load conditions were processed by using the method of Hilbert vibration decomposition and envelope spectrum analysis, and the peak value and area of envelope spectrum were extracted to judge the vibration amplitude of glass panel, which was used as the evaluation index. The fuzzy comprehensive evaluation matrix was calculated by using the appropriate fuzzy operator, and the safety level of the glass panel was judged by using the principle of maximum membership degree for the calculation results. The feasibility of the method is proved by experiments, and it provides a theoretical basis for the subsequent health status monitoring of hidden frame glass curtain wall.

The feasibility of using vibration transfer rate as damage parameter is studied by simulation. The excitation mode, sensitive measuring point, structural adhesive damage identification and safety state evaluation of hidden frame glass curtain wall (HFGCW) are studied by experiment. The experimental results show that the accurate vibration spectrum can be obtained by using rubber hammer. The edge of glass plate is selected as the measuring point to obtain the accurate vibration transfer rate. The value of change rate of vibration transmissibility increases with the increase in damage degree of structural adhesive. A nondestructive testing method combining vibration transfer rate and discrete wavelet transform (DWT) is proposed, which can identify the degree of structural adhesive damage of HFGCW well. At the same time, the safety status evaluation model based on vibration transfer rate can evaluate the damage degree of structural adhesive of HFGCW.

The Automated Building Information Modeling (BIM) reconstruction of existing building curtain walls is crucial for promoting digital Operation and Maintenance (O&M). However, existing 3D reconstruction technologies are mainly designed for general architectural scenes, and there is currently a lack of research specifically focused on the BIM reconstruction of curtain walls. This study proposes a BIM reconstruction method from unmanned aerial vehicle (UAV) images based on neural radiance field (NeRF) and deep learning-based semantic segmentation. The proposed method compensates for the lack of semantic information in traditional NeRF methods and could fill the gap in the automatic reconstruction of semantic models for curtain walls. A comprehensive high-rise building is selected as a case study to validate the proposed method. The results show that the overall accuracy (OA) for semantic segmentation of curtain wall point clouds is 71.8%, and the overall dimensional error of the reconstructed BIM model is less than 0.1m, indicating high modeling accuracy. Additionally, this study compares the proposed method with photogrammetry-based reconstruction and traditional semantic segmentation methods to further validate its effectiveness.

Glass curtain walls are widely used in the enclosure structure of airport terminals due to their advantages of lightweight and beautiful appearance, good lighting, and easy installation. However, coastal areas are constantly affected by typhoons, and under the influence of strong winds, complex pressure distributions are generated on the surface of curtain walls. Therefore, studying the wind pressure distribution characteristics of glass curtain walls is crucial for the structural safety and durability of coastal airport terminals. Based on this, accurately predicting wind pressure distribution not only helps to improve the design safety of airport terminals but also effectively prevents potential damage under strong wind conditions. To achieve effective prediction of wind pressure on glass curtain walls, this paper adopts a combination of wind tunnel tests and neural network prediction models. Real wind pressure coefficient data is obtained through wind tunnel tests, and a CNN–Transformer combination model is proposed to predict wind pressure coefficients. The results show that the prediction accuracy of the combined model is higher than that of the CNN and Transformer single models. MAE is optimized by 0.04~0.10 compared with the former and 0.16~0.34 compared with the latter; RMSE has been optimized by 0.02–0.10 and 0.30–0.34, respectively. This article can provide reference for the prediction research of wind pressure on the surface of glass curtain walls in airport terminals.

Glass facades are known to be fascinating building systems that require specific design strategies, experimental protocols and simulation tools. Especially for seismic-resistant buildings, their mechanical performance should be verified against possible failure mechanisms. For this, both numerically optimized and robust approaches are needed, along with tools to support designers. Fragility curves represent, in this sense, a practical approach for many structural typologies and systems. In this paper, attention is given to the development and assessment of a geometrically simplified and mechanically optimized FE numerical model for the non-linear dynamic analysis of glass curtain walls (GCWs). Its potential and gaps in its calibration and prediction capacity, both at the global and local level, are addressed on the base of earlier experimental and numerical studies. A fragility analysis is then carried out by taking advantage of the cloud analysis method to verify the real capacity of a typical GCW and the performance restrictions that are presently recommended by existing standards for construction. A total of 60 non-linear dynamic analyses are carried out for GCWs under real seismic acceleration to capture the maximum effects and possible failure mechanisms. An analysis of the parametric results is then carried out for several performance indicators of practical interest and various technical documents of the literature. As shown, there is a major effect of global and local mechanisms that optimized numerical models should properly capture. At the same time, according to existing technical documents, there is a clear need for more efficient limit values and performance indicators for the design of safe and optimized seismic-resistant GCWs.

The energy consumption requirement of high-rise buildings necessitates effective innovations in architectural designs. The aim is to revolutionise high-rise buildings’ thermal features and energy efficiency. This paper combines quantitative analyses through improved thermal simulations and qualitative information from surveys of stakeholders, including architects, engineers, and urban planners. Key performance indicators such as U-values, R-values, HVAC efficiency, Solar Heat Gain Coefficient (SHGC), and Energy Use Intensity (EUI) are examined in detail to assess the thermal and energy performance of contemporary façade systems. Energy-efficient building design is paramount in this time of unprecedented urban development and escalating global temperatures. However, a gap exists in understanding how these practices can be adapted and integrated effectively into modern architecture. The findings show that high-rises with optimized pattern curtain wall façades reveal considerable savings in energy usage, particularly in cooling loads, which enhances indoor thermal comfort and reduces environmental effects. Actionable recommendations are provided for architects, urbanists, and policymakers, including the designs of region-specific façade constructions, their connection with renewable energy, and compliance with high energy performance standards. All these strategies help to improve the operational efficiency, environmental sustainability, and stability of built environments in growing, developed urban areas.

The effects of parallel curtain walls on the characteristics and mass loss rate of the upward flame spread over polymethyl methacrylate (PMMA) have been experimentally studied. The experimental research variables were the sample size and separation distance of the curtain wall. In the experimental setup, a PMMA plate was attached to one of the curtain walls. The results were analyzed to assess the effect of the curtain wall separation distance on the flame height. The special condition of two curtain walls with only a small distance between them was also analyzed. Analysis of experiments with systematically varied distances between the curtain walls has provided insight into factors such as air entrainment and the chimney effect. The results show the flame height evolution trend with the separation distance, and a new correlation to predict the global mass loss rate of the PMMA plate under the influence of parallel curtain walls, which can potentially be used in curtain wall design through optimization of the separation distance given fire safety requirements and practical needs.

Curtain wall systems have evolved from aesthetic façade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness. This review presents a comprehensive examination of curtain walls from an energy-engineering perspective, highlighting their structural typologies (Stick and Unitized), material configurations, and integration with smart technologies such as electrochromic glazing, parametric design algorithms, and Building Management Systems (BMS). The study explores the thermal, acoustic, and solar performance of curtain walls across various climatic zones, supported by comparative analyses and iconic case studies including Apple Park, Burj Khalifa, and Milad Tower. Key challenges—including installation complexity, high maintenance costs, and climate sensitivity—are critically assessed alongside proposed solutions. A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows, reduce HVAC loads, and enhance occupant comfort. The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging from approximately 5% to 27%, depending on climate, control strategy, and façade typology. The findings offer a valuable reference for architects, energy engineers, and decision-makers seeking to integrate high-performance façades into future-ready building designs.