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院校 題目 類型 日期 作者 摘要 網頁
HKUST Automated quality assessment of precast concrete elements with geometry irregularities using terrestrial laser scanning Journal 04/2016 Wang, Q., Kim, M.-K., Cheng, J.C.P., and Sohn, H. Precast concrete elements are popularly used and it is important to ensure that the dimensions of individual elements conforms to design codes. However, the current quality assessment of precast concrete elements is inaccurate and time-consuming. To address the problems, this study presents an automated quality assessment technique which estimates the dimensions of precast concrete elements with geometry irregularities using terrestrial laser scanners (TLS). While the scan data obtained from TLS represent the as-built condition of an element, a Building Information Modeling (BIM) model stores the as-design condition of the element. Taking the BIM model as a reference, the scan data are processed to estimate the as-built dimensions of the element. Experiments on a specimen demonstrated that the proposed technique can estimate the dimensions of elements effectively and accurately. Furthermore, a mirror-aided scanning approach, which aims to achieve reduced incident angles in real scanning environments, is proposed and validated by experiments. 連結
HKUST Automated dimensional quality assurance of full-scale precast concrete elements using laser scanning and BIM Journal 09/2016 Kim, M.-K., Wang, Q., Park, J.-W., Cheng, J.C.P., Chang, C.-C., and Sohn, H. This study presents a quality inspection technique for full-scale precast concrete elements using laser scanning and building information modeling (BIM). In today's construction industry, there is an increasing demand for modularization of prefabricated components and control of their dimensional quality during the fabrication and assembly stages. To meet these needs, this study develops a non-contact dimensional quality assurance (DQA) technique that automatically and precisely assesses the key quality criteria of full-scale precast concrete elements. First, a new coordinate transformation algorithm is developed taking into account the scales and complexities of real precast slabs so that the DQA technique can be fully automated. Second, a geometry matching method based on the Principal Component Analysis (PCA), which relates the as-built model constructed from the point cloud data to the corresponding as-designed BIM model, is utilized for precise dimension estimations of the actual precast slab. Third, an edge and corner extraction algorithm is advanced to tackle issues encountered in unexpected conditions, i.e. large incident angles and external steel bars being located near the edge of precast concrete elements. Lastly, a BIM-assisted storage and delivery approach for the obtained DQA data is proposed so that all relevant project stakeholders can share and update DQA data through the manufacture and assembly stages of the project. The applicability of the proposed DQA technique is validated through field tests on two full-scale precast slabs, and the associated implementation issues are discussed. Field test results reveal that the proposed DQA technique can achieve a measurement accuracy of around 3.0 mm for dimension and position estimations. 連結
HKUST A BIM-based framework for lift planning in topsides disassembly of offshore oil and gas platforms Journal 03/2017 Tan, Y., Song, Y., Liu, X., Wang, X., and Cheng, J.C.P. Offshore oil and gas platforms (OOGPs) usually have a lifetime of 30–40 years. An increasing number of OOGPs across the world will be retired and decommissioned in the coming decade. Therefore, a safe and efficient approach in planning the disassembly of the topsides of OOGPs is required. One commonly applied disassembly method is reverse installation, which moves the OOGP modules from the platform deck to a heavy lift vessel (HLV) in reverse order of their installation. Considering the high risk and cost of working offshore, shortening the lift time is crucial. In contrast to the traditional experience-driven lift operations, this paper describes minimizing the lift path for each OOGP module during disassembly, leveraging building information modeling (BIM) technology and an improved A* algorithm. BIM models provide accurate component-based geometric and semantic information that can be used for planning and optimization. However, there has been no previous study on the use of BIM for offshore disassembly. Industry Foundation Classes (IFC), which is a neutral data model of BIM, is used in this study to represent OOGP models. In particular, the IfcBuildingElementProxy entity is used to represent the OOGP components, and the information in IfcBuildingElementProxy is automatically extracted to obtain the location and dimension information of each OOGP module. Then, for a given layout of modules on the removal vessel, the lift path and removal sequence of different modules, with the shortest lift path distance, are obtained. The lift path distance is calculated using the A* algorithm, which has been widely applied in 2D environments and is modified in this study to suit the 3D environment. Finally, the genetic algorithm (GA) technique is applied to optimize the layout plan on the removal vessel by minimizing the total lift path distance. The developed BIM-based framework is illustrated and evaluated through an illustrative example. The results show that the proposed framework can generate and visualize the shortest lift path for each OOGP module directly and automatically, and significantly improve the efficiency of OOGP disassembly. 連結
HKUST Identifying potential opportunities of building information modeling for construction and demolition waste management and minimization Journal 03/2017 Won, J., and Cheng, J.C.P. The amount of waste generated in construction and demolition (C&D) processes is enormous. Therefore, many studies on efficient C&D waste minimization and management have been conducted. However, 21 process-related and 8 technology-related limitations in C&D waste management and minimization have not yet been resolved. Building information modeling (BIM) helps project participants improve the processes and technologies in the planning, design, construction, and demolition phases, thereby managing and minimizing C&D waste efficiently. Therefore, this paper identifies the potential opportunities of BIM for efficient C&D waste management and minimization, such as design review, 3D coordination, quantity take-off, phase planning, site utilization planning, construction system design, digital fabrication, and 3D control and planning. The BIM-based approaches can support C&D waste management and minimization processes and technologies by addressing existing limitations through in-depth literature review. The roles of project participants and information required for each BIM-based approach in C&D waste management and minimization are discussed with illustrative process maps. 連結
HKUST Automated optimization of steel reinforcement in RC building frames using building information modeling and hybrid genetic algorithm Journal 02/2018 Mangal, M., and Cheng, J.C.P. Design of steel reinforcement is an important and necessary task for designing reinforced concrete (RC) building structures. Currently, steel reinforcement design is performed manually or semi-automatically using computer software such as ETABS, with reference to building codes. These approaches are time consuming and sometimes error-prone. Recent advances in building information modeling (BIM) technology allow digital 3D BIM models to be leveraged for supporting different types of engineering analyses such as structural engineering design. With the aid of BIM technology, steel reinforcement design could be automated for fast, economical and error-free procedures. This paper presents a BIM-based framework using the developed three-stage hybrid genetic algorithm (GA) for automated optimization of steel reinforcement in RC frames. The methodology framework determines the selection and alignment of steel reinforcement bars in an RC building frame for the minimum steel reinforcement area, considering longitudinal tensile, longitudinal compressive and shear steel reinforcement. The first two stages optimize the longitudinal tensile and longitudinal compressive steel reinforcement while the third stage optimizes the shear steel reinforcement. International design code (BS8110) and buildability constraints are considered in the developed optimization framework. A BIM model in Industry Foundation Classes (IFC) is then automatically created to visualize the optimized steel reinforcement design results in 3D thereby facilitating design communication and generation of construction detailing drawings. A three-storey RC building frame is analyzed to check the applicability of the developed framework and its improvement over current design approaches. The results show that the developed methodology framework can minimize the steel reinforcement area quickly and accurately. 連結
HKUST BIM-based framework for automatic scheduling of facility maintenance work orders Journal 03/2018 Chen, W., Chen, K., Cheng, J.C.P., Wang, Q., and Gan, V.J.L. Although more than 65% of the total cost in facility management (FM) comes from facility maintenance management (FMM), there is a lack of efficient maintenance strategies and right decision making approaches to reduce FMM costs. Building information modeling (BIM) has been developed as a potential technology for FMM in buildings. This study proposes an FMM framework based on BIM and facility management systems (FMSs), which can provide automatic scheduling of maintenance work orders (MWOs) to enhance good decision making in FMM. In this framework, data are mapped between BIM and FMSs according to the Industry Foundation Classes (IFC) extension of maintenance tasks and MWO information in order to achieve data integration. After bi-directional data transmission between the BIM models and FMSs, work order information is visualized in BIM via API to identify components that have failed. Second, geometric and semantic information of the failure components is extracted from the BIM models to calculate the sub-optimal maintenance path in the BIM environment. Third, the MWO schedule is automatically generated using a modified Dijkstra algorithm that considers four factors, namely, problem type, emergency level, distance among components, and location. Illustrative examples are given in the paper to validate the feasibility and effectiveness of the proposed framework in indoor and outdoor 3D environments. 連結