香港專上院校所提供之論文/研究刊物 | 資源 | BIM

香港專上院校所提供之論文/研究刊物

香港專上院校所提供之論文/研究刊物

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以下資料由與建造業議會簽署合作備忘錄的專上學院提供。

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院校	題目	類型	日期	作者	摘要	網頁
HKUST	Development of BIM-assisted Access Point Placement Optimization and Deep Learning based Multi-floor Identification Algorithms for Enhancing Indoor Positioning to Support Construction Applications	Thesis	08/2019	Kenneth Chun Ting LI	Over the past decades, indoor positioning has been drawing wide attention in different fields of engineering. Indoor positioning technologies are complementary to the mature outdoor positioning technology such that the indoor positioning technologies can provide a real-time positioning service in any environment where there is a blockage of GNSS signals. In the fields of construction and facility management, indoor positioning technologies enable promising applications that can considerably enhance the productivity, efficiency and safety on construction sites, supporting five major applications, which are (1) construction safety management, (2) construction process monitoring and control, (3) inspection of construction structures and materials, (4) construction automation with robotics, and (5) the use of building information modelling (BIM) technology for construction progress management. Currently, there is no single perfect indoor positioning system that can perform optimally under any circumstances. In addition, due to the large variety of indoor positioning technologies and principles, as well as the complex and dynamic environment on construction sites, developing suitable indoor positioning systems on construction sites is a challenging task. Applying indoor positioning systems is essentially user-oriented and environment-specific. This thesis thus analyses the challenges to apply indoor positioning systems on construction sites, and then proposes six indoor positioning performance metrics, namely APP-CAT, for evaluating suitable on-site indoor positioning systems. Subsequently, the top 10 indoor positioning technologies, which are selected according to their evaluation results using APP-CAT and their popularity amongst the indoor positioning literature studies, are thoroughly discussed and compared. The promising recent trends of developing on-site indoor positioning systems, such as infrastructure-free positioning, collaborative positioning, game theory positioning, and device-free positioning, as well as integration of indoor positioning technologies with BIM models, are also highlighted. In this research work, the comprehensive discussion of current development in indoor positioning from different aspects is intended to help academics, researchers, and industry practitioners develop high-performing and suitable on-site indoor positioning systems for supporting various engineering and construction applications. Among various positioning technologies, Wi-Fi fingerprinting has emerged as a popular technique due to the wide coverage of Wi-Fi signals and its high compatibility with smartphones. Wi-Fi fingerprinting utilizes the patterns of the Wi-Fi signal strengths, which are measured by the Received Signal Strength Index (RSSI), for position estimation. Normally, Wi-Fi access points are placed arbitrarily, which causes a poor positioning accuracy. In fact, positioning accuracy can be considerably enhanced by optimizing the access point (AP) placement strategy. In light of the high popularity of Wi-Fi fingerprinting and the liberty to design AP placemnent strategies on construction sites, this thesis aims to conduct AP placement optimization is by finding the optimal AP placement strategy that maximizes the distinctiveness between individual Wi-Fi fingerprints in a 3D virtual environment. The use of BIM technology provides 3D geometric and semantic information to accurately reproduce the virtual environment for realistic simulation of Wi-Fi signal propagation. Wi-Fi signal propagation is usually modelled by a modified indoor radio wave path loss model, but such models cannot easily consider the multipath effect in an indoor environment. Therefore, in this thesis, an accurate Deep Belief Network (DBN) based path loss model, which considers the multipath effect emulated by the ray-tracing method using particle swarm optimization (PSO), is proposed and implemented to predict the indoor Wi-Fi signal strengths. Based on the results of the simulation, the optimal AP placement strategy as well as the geometrically-constrained optimal AP placement strategy can be obtained by using the genetic algorithm (GA). The test results in a university library have shown that the developed AP placement optimization algorithm could consistently enhance the accuracy of 3D indoor positioning under the circumstances of different numbers of APs and the presence of geometric constraints. Facility management is often performed in a multi-floor indoor environment such as shopping malls and airports. However, one of the major challenges facing the received signal strength indicator (RSSI) based fingerprinting is the inability to perform accurate indoor positioning in a multi-floor environment, despite their popularity. The multi-floor environment poses a large challenge to RSSI fingerprint-based indoor positioning because the uniqueness of RSSI fingerprints is largely lost in a multi-floor environment, especially when ring structure exists in the building. Such a ring structure is commonly found in large airports and shopping malls. In this thesis, in light of the analogy between visual images and a radio map, a novel twofold multi-floor localization algorithm based on convolutional neural network (CNN) is developed to perform robust and accurate multi-floor localization. To support the twofold CNN model and to improve the localization accuracy, the similar selective search algorithm and data augmentation algorithm are proposed. Lastly, with the support of inertial measuring units (IMUs), the snapping algorithm is proposed to convert a random trajectory to a grid shape for the purpose of localization. Per the validation results, the proposed multi-floor localization algorithm is capable of identifying on which floor the user is located such that the “floor jumping” problem is mitigated, and thus the overall indoor positioning accuracy on RSSI fingerprint-based indoor positioning is substantially improved during indoor navigation. To summarise, this thesis provides a comprehsive review of the top 10 indoor positioning technologies for their usage on construction sites, and aims to develop a BIM-assisted access point placement optimization and deep learning based multi-floor identification algorithms for enhancing indoor positioning to support construction applications for both construction management and facility managment.	N.A.
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.	N.A.
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	Semi-automatic Generation of BIM models from Point Cloud Data for Facility Management	Report	06/2018	Duan Feiran Siyu SHEN	Nowadays, BIM has transformed architecture, engineering and construction. However, the great potential of BIM is to provide accurate, timely, and relevant information not just during design and construction for a single building, but also throughout the lifecycle of an entire portfolio of facilities, such as the facility management. It has many competencies and plays an important role in the total life cycle of the building. The process of facility management need the support of lots of information which could then be provided by BIM model. Therefore, BIM model plays an important role in facility management. BIM models are usually created from designed information which is called as-designed BIM model. However, there are lots of existing buildings do not have BIM model when they are built. For new buildings, there are also many changes may occur during construction, and the as-designed models could not present the real conditions. Therefore, an as-build BIM model may be needed to help the visualize and renovation of the project. What’s more, the current method for creating BIM models are mainly concentrated on regular buildings. However, more and more architect would like to design building with irregular buildings. Therefore, a new method should be used to create BIM model for irregular buildings. This project aims to find a semi-automatic method to create BIM models for irregular building which could be applied for facility management. It takes a real project in industry as example and try to build the BIM model for a sky light bridge located in Hong Kong Airport by a combination of different software. This method firstly extracts the geometry information for each member from the point cloud data that gain from laser scanning. Then, it convert those conditions into BIM model with the help of Dynamo and Revit.	N.A.
HKUST	Developing a BIM- and GIS-based Facility Management Framework for Underground Utilities	Report	06/2017	Starry Xing LI Liu YANG	Nowadays there is a trend of integrating Building Information Modeling (BIM) and Geographic Information System (GIS) to develop the construction projects, including the projects of underground utilities. Compared with BIM and GIS, traditional utility management has plenty of limitations. Traditional utility management keeps 2D CAD drawings, which are separated by utility type and lack of surrounding information. Besides, it is difficult to find the specific utility pipe in 2D drawings under special situation. The working sequence arrangement for those pipes are sometimes not effective. This study aims to improve underground utility management in Hong Kong by using ArcGIS. The improvements consist of 3D visualization, querying and working sequence arrangement. 3D visualization of underground pipes and geological layers is created with reference to relevant Hong Kong standards and researches. Three cases are described to demonstrate the practical application of querying function. Working sequence of project in case 3 is analyzed through Excel.	N.A.
HKUST	Minimization of Construction Waste through BIM-based Clash Detection and Quantification	Report	06/2016	Baoshan KUANG Pik Kei LAM	Nowadays the construction industry is under pressure to explore effective and efficient techniques and tools to decrease its escalating waste generation. However, the current approaches, techniques and tools focus on separate projects on site and limited effort is invested to put attention on pre-construction waste generation related to design stages. Waste that is induced by improper design accounts for a major proportion of the total construction waste. Therefore, this report aims to develop a BIM-based approach in the aspect of waste minimization. With the clash detection tool in Navisworks, this report demonstrates the clash classification, resolution and the corresponding waste generation of 3 pairs of general component models of a villa, which are architectural model vs. structural model, structural model vs. mechanical model and mechanical vs. plumbing model. Then, compare the result obtained with BIM and that estimated with the current waste factor approach and find out whether the BIM-based waste minimization can be better realized. Consequently, coordinating the models of each building components with clash detection enables efficient management of construction waste.	N.A.