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香港專上院校所提供之論文/研究刊物
| 院校 | 題目 | 類型 | 日期 | 作者 | 摘要 | 網頁 |
|---|---|---|---|---|---|---|
| HKU | A Study to Review and Redefine the QS Core Competencies in a BIM Environment in Hong Kong | Thesis | 04/2018 | YU Kin Kwan | -- | N.A. |
| 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 |
| HKUST | Developing an evacuation evaluation model for offshore oil and gas platforms using BIM and agent-based model | Journal | 02/2018 | Cheng, J.C.P., Tan, Y., Song, Y., Mei, Z., Gan, V.J.L., and Wang, X. | Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering the demanding environment where such platforms are located and the complicated topsides structure that the platforms have. Conducting evacuation planning on OOGPs is challenging. Computational tools are considered as a good way to plan evacuation by emergency simulation. However, the complex structure of OOGPs and various evacuation behaviors can weaken the advantages of computational simulation. Therefore, this study develops a simulation model for OOGPs to evaluate different evacuation plans to improve evacuation performance by integrating building information modeling (BIM) technology and agent-based model (ABM). The developed model consists of four parts: evacuation model input, simulation environment modeling, agent definition, and simulation and comparison. Necessary platform information is extracted from BIM and then used to model the simulation environment by integrating matrix model and network model. In addition to essential attributes, environment sensing and dynamic escape path planning functions are developed and assigned to agents in order to improve simulation performance. Total evacuation time for all agents on an offshore platform is used to evaluate the evacuation performance of each simulation. An example OOGP BIM topsides with different emergency scenarios is used to illustrate the developed evacuation evaluation model. The results show that the developed model can accurately simulate evacuation and improve evacuation performance on OOGPs. The developed model is also applicable to other industries such as the architecture, engineering, and construction industry, where there is an increasing demand for evacuation planning and simulation. | 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 | Automatic as-built BIM creation of precast concrete bridge deck panels using laser scan data | Journal | 02/2018 | Wang, Q., Sohn, H., and Cheng, J.C.P. | Precast concrete bridge deck panels are commonly used for bridge constructions because they enable faster construction and have less impact on traffic flow. The quality of connections between adjacent precast elements must be ensured to guarantee the overall structural integrity of precast systems. Therefore, the dimensional quality of precast concrete panels should be inspected before they are shipped to construction sites for installation. However, current quality inspection of precast concrete elements primarily relies on manual inspection. Furthermore, the as-built dimensions of precast elements are usually stored in paper sheets or Microsoft Excel spreadsheets, making it difficult to visualize and manage the as-built dimensions. This study develops a technique to automatically estimate the dimensions of precast concrete bridge deck panels and create as-built building information modeling (BIM) models to store the real dimensions of the panels. First, the proposed technique conducts scan planning to find the optimal scanner locations for scan data acquisition. Then, the scan data of the target panel are acquired and preprocessed to remove noise data and to register multiple scans in a global coordinate system. From the registered scan data, the as-built geometries of the target panel are estimated. In the last step, an as-built BIM model is created on the basis of the previously estimated geometries. The proposed technique is validated on a laboratory-scale specimen and a full-scale precast concrete bridge deck panel. The experimental results show that the proposed technique can accurately and efficiently estimate the dimensions of full-scale precast concrete bridge deck panels with an accuracy of 3 mm and automatically create as-built BIM models of the panels. | 連結 |
| HKUST | Trends and opportunities of BIM-GIS integration in the architecture, engineering and construction industry: A review from a spatio-temporal statistical perspective | Journal | 12/2017 | Song, Y., Wang, X., Tan, Y., Wu, P., Sutrisna, M., Cheng, J.C.P., et al. | The integration of building information modelling (BIM) and geographic information system (GIS) in construction management is a new and fast developing trend in recent years, from research to industrial practice. BIM has advantages on rich geometric and semantic information through the building life cycle, while GIS is a broad field covering geovisualization-based decision making and geospatial modelling. However, most current studies of BIM-GIS integration focus on the integration techniques but lack theories and methods for further data analysis and mathematic modelling. This paper reviews the applications and discusses future trends of BIM-GIS integration in the architecture, engineering and construction (AEC) industry based on the studies of 96 high-quality research articles from a spatio-temporal statistical perspective. The analysis of these applications helps reveal the evolution progress of BIM-GIS integration. Results show that the utilization of BIM-GIS integration in the AEC industry requires systematic theories beyond integration technologies and deep applications of mathematical modeling methods, including spatio-temporal statistical modeling in GIS and 4D/nD BIM simulation and management. Opportunities of BIM-GIS integration are outlined as three hypotheses in the AEC industry for future research on the in-depth integration of BIM and GIS. BIM-GIS integration hypotheses enable more comprehensive applications through the life cycle of AEC projects. | 連結 |