The architecture, engineering, and construction sector requires carbon-intensive materials, such as steel, in the construction process and generates a large amount of waste in the life cycle. This causes global warming and waste problems. The demand for the reuse of construction materials is increasing, although it is not the convention, to reduce the environmental impact. Although the sustainable effect of the reuse of materials has been proven in several studies, materials are not always reused in practice, owing to the lack of an information system for reusable materials and the economic uncertainty. In this study, we propose a framework for designing structures using reusable steel beams. The design framework consists of a material bank and a design support tool. The material bank provides information on reusable materials based on the building information modeling. The design support tool generates efficient material procurement plans and provides information about the environmental and economic impact of the project. In a case study used to verify the framework, CO₂ emissions were reduced by up to 77% through material reuse, which was consistent with the results of previous studies. However, owing to the cost of processing reusable materials, the overall cost was found to increase by up to about 40%. Therefore, an economic analysis over the entire life cycle when using reusable materials needs to be done.

Economic feasibility and cost analysis in the preliminary planning stage of early-phase construction projects have a significant impact on project management and implementation. However, while estimating the construction cost per unit area, the existing approaches do not account for factors other than the area-related information, causing estimation error. Therefore, a construction cost estimation model that can be utilized in the early phase of a construction project is developed in this study based on BIM in the architectural planning stage. Moreover, goodness of fit and accuracy of the model were verified through a validation method considering the BIM design process. The proposed model showed higher accuracy than the conventional models in terms of the floor area. Furthermore, it was possible to confirm the model performance based on the cost estimation accuracy range presented by the AACE. In addition, the developed model can generate estimation results corresponding to Class 1–3, a subsequent construction project stage. The findings of this study emphasize the importance of jointly considering the processes related to construction cost estimation and indicate that parameters other than the floor area need to be considered for construction cost estimation in the early phase of a construction project.

Noise barrier tunnels (NBTs) comprise prefabricated components that are easily replaceable, reusable, and have the capacity to improve performance when applied to components as their replacements. Reusing NBTs is more price competitive and environmentally friendly than producing new components. However, determining the remaining life of components before they need to be dismantled, using existing NBTs and their maintenance methods, is a considerable challenge. Therefore, this study used a prototype of the digital twin of an NBT to predict the condition and life of tunnel components using numerical behavior analyses. The prototype of the digital twin used in this study could be used to analyze behaviors using a gyro sensor, thereby enabling life analyses. Girders are structural components that have shorter life expectancies than components close to the ground. Component analysis results indicated that our proposed method confirmed changes in the life of girders and column components. Moreover, a negligible change in the life of the purlin component was confirmed. Life cycles management using digital twins can help reduce NBT installation costs, facilitate resource recycling, and make the installation process eco-friendly as they can aid in identifying components that require replacements in the initial designing stage and establish a procurement plan.

This study presents a real-time monitoring system integrating Building Information Modeling (BIM) and digital twin technology to enhance maintenance efficiency and safety in urban infrastructure. Unlike conventional periodic inspections, which miss dynamic changes and increase costs, this system uses a BIM model at LOD 400 for a solar-powered noise barrier tunnel integrated with the Wansan Tunnel in South Korea. It incorporates IoT sensor data, including vibration, tilt, light, air quality, and water detection, which are synchronized via the Autodesk Forge API, and WebSockets and visualized on a web-based dashboard. A demonstration from 22 October to 7 November 2024 confirmed that this system had stable data transmission, with light sensor rates exceeding 90%, and enabled the detection of anomalies such as irregular illuminance and structural shifts, thereby supporting informed maintenance decisions. While it is proven that BIM–digital twin integration improves NBT management, partial air quality data gaps highlight areas for refinement. This framework lays the groundwork for predictive maintenance through advanced analytics.

One of the most critical challenges for architects in façade design is providing an effective view from the indoors to the outdoors of a building for users, although the main role of the parametric façade is covering openings to control daylight and temperature. This study uses a genetic algorithm to optimize and evaluate the number and place of nodes and the position of supports required for a parametric façade based on the geometric patterns. Using the dataset with genetic algorithms is effective in reducing or replacing the nodes and supports of the façade. It also creates broader and irregular patterns just around the windows, which decreases the visual disturbance experienced by occupants. Accordingly, optimal building facade operation in terms of both building aesthetics and performance is important. The method used in this study, validated through three geometric grid patterns based on node positions, can be used to analyze dataset-incorporated patterns for potential irregular façade extensions. The nodes are considered by analyzing the cross-section optimization using the Galapagos program, and then data are obtained with Karamba based on reaction force, node force, and the deformation energy. The results show that among the three grid patterns, i.e., triangular, square, and hexagonal, the hexagonal grid is most efficient, exhibiting up to 60% lower reaction force, 40% lower node force, and 30% less deformation energy than the square grid pattern. The proposed GA also shows its effectiveness in enhancing the performance of parametric façades with patterns, thereby improving the occupants’ visual experience.