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院校 題目 類型 日期 作者 摘要 網頁
HKUST Analytical review and evaluation of civil information modelling (CIM) Journal 04/2016 Cheng, J.C.P., Lu, Q., and Deng, Y. Building information modeling (BIM) has been widely adopted in the building industry. However, the use of BIM in civil infrastructure facilities, sometimes referred to as civil information modeling (CIM) has been slow in its application. Industry and academia are increasingly putting effort into CIM study and implementation, but so far there has been no comprehensive review of their effort in this regard. This paper presents a framework to evaluate the current practices of CIM adoption for various civil infrastructure facilities. In this study, civil infrastructure facilities were divided into nine categories for evaluation and the effort with regard to CIM adoption for each civil infrastructure category was evaluated in six aspects. Based on the evaluation and comparison results of 171 case studies and 62 academic papers on CIM, research gaps were identified and recommendations were made. For example, the findings show that data schema development for civil infrastructure facilities other than bridges, roads, and tunnels are lacking. The results and research gaps revealed by this study are useful for both researchers and practitioners. 連結
HKUST Application of Building Information Modeling Technology for Safe Operations and Decommissioning of Offshore Oil and Gas Platforms Thesis 08/2018 Yi TAN Offshore oil and gas platforms (OOGPs) usually have a lifetime of 30-40 years. The operation and maintenance stage takes up the most percentage of the whole lifetime of OOGPs. During the operations and maintenance, there are several safety issues. Emergent accidents and exposure to high level of noise are two main issues. Traditional emergency responses include 2D escape plan guidance and real drill exercises. 2D escape plan usually causes different understanding, while real drill exercises require extra time and workforce. As for current noise controls, only personal protective equipment has been commonly employed, which is the least effective noise control. In addition, as increasing number of OOGPs will be retired and decommissioned in the coming decade, disassembling offshore platforms is an unavoidable activity. During OOGP decommissioning stage, there are also several safety issues such as potential clashes when conducting heavy lift operations and lift vessel capsize. Besides, when multiple lift vessels are working together to disassemble multiple offshore platforms, more than one vessel working at the same platform, which can significantly increase lift clashes, is another safety issues. Current approaches to addressing these safety issues at the decommissioning stage are usually based on experience, and manually planned. Considering all these safety issues mentioned above, automated, efficient, and accurate approaches to improving safety management of OOGPs at both operation and decommissioning stages are desired. However, limited researches have been conducted to tackle these safety issues. Therefore, this research aims to develop automated, efficient, and accurate techniques and approaches for safer operations and decommissioning of OOGPs.

Building information modeling (BIM) technology is widely used in the building and infrastructure industries for the past decade considering the rich geometric and semantic information BIM contains. Therefore, this research applies BIM technology to efficiently provide required information of OOGPs when developing new approaches to addressing safety issues.

For the operation and maintenance stage of an offshore platform, to better respond to emergent accidents, a BIM-based evacuation evaluation model is developed to efficiently simulate and evaluate different emergency scenarios, and improve evacuation performance on offshore platforms. As for the noise control, this research proposes a BIM-supported 4D acoustics simulation approach. The proposed approach can automatically conduct noise simulation for offshore platforms using the information extracted from BIM models. Maintenance schedules can then be optimized based on simulated results. By minimizing the time of exposing to a high level of noise, the noise impact on maintenance workers is well mitigated.

For the decommissioning stage, first, a semi-automated approach to generate 4D/5D BIM models to evaluate different OOGP decommissioning option is developed. Second, automated topsides disassembly planning approach based on BIM is developed. Clash-free lift paths can be generated to avoid clashes during heavy lifts. Module layouts on vessels are optimized to minimize the total heavy lift time and to guarantee the stability of lift vessels. Besides, a schedule clash detection method is also developed to make sure that no more than one vessel is working at one offshore platform simultaneously.

All developed BIM-based approaches are illustrated with related examples. Compared to current practices, these proposed approaches improve the safety management performance of offshore platforms.
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HKU Application of information technology in materials logistics in the Hong Kong construction industry Thesis 04/2000 YAN Kwok Wing -- N.A.
HKUST Application of Mixed Reality Technology for Operations and Maintenance of Building Facilities Thesis 08/2019 Keyu CHEN The architecture, engineering, construction and operation (AECO) industry has been widely regarded as a highly resource consuming industry. Among different stages of the AECO industry, the operations and maintenance (O&M) lasts the longest in the lifecycle of a building and incurs more than 85% of the total costs, indicating the importance of optimizing management and improving efficiency during O&M. However, it was indicated that two-thirds of the estimated cost of facility management is lost due to inefficiencies during the O&M stage. With current approaches for O&M activities, it is difficult for people to directly visualize and update information of building facilities and many¬ facilities are hidden (e.g. ventilation ducts above ceilings and water pipes under floors). Therefore, this research aims to apply innovations to improve efficiency during the O&M stage. In recent years, professionals begin to realize the practical value of mixed reality (MR) technology, which can aid in various tasks during O&M. Through integrating virtual information with the real world, MR makes the information of users surrounding facilities readable and manipulable. However, there are two major limitations while implementing MR in O&M: (1) All existing methods for MR spatial registration have their own limitations in either accuracy or practicality. (2) There is a lack of efficient methods for data transfer from BIM to MR, which limits the functionality and complexity of MR applications. To tackle these limitations, this research develops an MR engine that can achieve accurate and robust MR spatial registration and efficient data transfer from BIM to MR.

For the development of the MR engine, an indoor localization approach is proposed for MR spatial registration. A transfer learning technique named transferable CNN-LSTM is proposed for improving the accuracy of localization and reducing Wi-Fi fingerprinting’s vulnerability to environmental dynamics. A deep learning approach that combines convolutional neural network (CNN) with long short term memory (LSTM) networks is first proposed to predict the locations of unlabeled fingerprints based on labeled fingerprints. Then the transferable CNN-LSTM model is derived from the CNN-LSTM networks based on transfer learning to improve the robustness against time and devices. The proposed transferable CNN-LSTM model is tested and compared with some conventional approaches and even some transfer learning approaches. Another part of the engine focuses on efficient mechanisms for BIM-to-MR data transfer. An ontology-based approach is proposed for transfer of semantic data. For geometric models, building components are classified into four types according to their different features and different model simplification algorithms are proposed accordingly. The algorithms were first tested with single components, and then a whole building was used to evaluate the overall performance of the developed mechanisms. As illustrated in the tests, the developed mechanisms can efficiently transfer both semantic information and geometric information of BIM models into MR applications, thus reducing the time for model transfer and improving the fluency of corresponding MR applications.

The developed MR engine is then applied to facility maintenance management (FMM) and emergency evacuation. To improve the efficiency of FMM, a BIM-based location aware MR collaborative framework is developed, with BIM as the data source, MR for interaction between users and facilities, and Wi-Fi fingerprinting for providing real-time location information. An experiment is designed to evaluate the effectiveness of the developed system framework. For emergency evacuation, a graph-based network is formed by integrating medial axis transform (MAT) with visibility graph (VG), with the addition of buffer zones. Closed-circuit television (CCTV) processing techniques are also developed to monitor the flow of people so that evacuees can avoid congested areas. An Internet of things (IoT) sensor network is established as well to detect the presence of hazardous areas. With the constructed graph-based network, congestion analysis and environment index of each area, an optimal evacuation path can be obtained and augmented with MR devices.

This research develops an MR engine that can improve the accuracy and robustness of conventional Wi-Fi fingerprinting based MR spatial registration and efficiency of BIM-to-MR data transfer. The developed MR engine has been implemented in FMM and emergency evacuation, illustrating the potential of the proposed approaches in improving the efficiency of O&M activities.
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HKUST As-built BIM Model Verification Through Field Inspection and Laser Scanning: A Comparative Study Report 06/2020 HUANG, Cong
ZHOU Haoran
LIU Hao
BIM model is a prerequisite for the Operation and Maintenance (O&M) of sustainable buildings. Only after having a reliable BIM model can start O&M related work, such as space management and energy management, all these works needs to confirm the accuracy of the BIM model. In this project, the author conducted a verify of the BIM model to ensure that the model was correct before the O&M work started.
This project first compared various survey methods, and based on their advantages and disadvantages, chose the laser scanning method and manual survey method for experiments. Then using two selected methods to do site surveying for HUKUST parking lot and LTK to SENG Commons. And the end, given survey recommendations for different types of as-built model verification based on the survey result.
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HKUST Automated Clash-free Steel Reinforcement Design in RC Structures Using BIM and GA Report 06/2018 Tommy Yuen Currently, building information modelling (BIM) technology has been increasingly popular in the architecture, engineering and construction (AEC) industry for some years, but it is not widely adopted in structural design. The objective of this project is to develop a framework for automated rebar design in RC beams using the building information modelling (BIM) technology.

This project presents an automated rebar design program, based on the latest BIM technology. Design constraints for the optimization are considered according to the Hong Kong Code of Practice. The developed program will make use of the analysis result from structural software to design RC beams, and then the tailor-made genetic algorithm will optimize the final rebar design. Finally, generate the rebars to BIM model in 3D environment.

The result shows that BIM can carry out repetitive works and complicated calculations automatically and accurately. Unlike human, they seldom make mistakes through over-tiredness, do not require rest breaks and can carry out in seconds what may take hours to do by manual methods. The overall design process is fully automated, smooth and without error. Therefore, it is anticipated that the time and manpower resource required for structural design and management could be reduced significantly.
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