FYPs/Thesis/Journal from Higher Education Institutions in Hong Kong

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Institution Title Type Date Author(s) Abstract Link
HKUST A BIM-based Framework for Site Layout Optimization and Material Logistics Planning on Congested Construction Sites Thesis 08/2015 Srinath KUMAR Urban construction projects are characterized by the lack of available space on construction sites. Due to the confined nature of such sites, construction materials, equipment and manpower must be managed within the same area, leading to frequent conflicts. As a result, the construction site layout and material logistics plans should be carefully coordinated to ensure a seamless flow of materials, equipment and labor. Existing studies focus on developing systems to address construction site layout planning (CSLP) and material logistics planning (MLP). However, such systems fail to address the mutual impacts and inter-dependencies between the site layout and material logistics plans. Furthermore, existing systems suffer from a lack of automation and inability to address construction delays. Therefore, this research aims to develop a framework for planning the site layout and material logistics on construction sites making use of building information modeling (BIM) technology. BIM has been used in the construction industry for over a decade, but its use in construction planning is still limited to clash detection and 4D simulation. BIM models however, are rich information sources and can be used for construction site layout and material logistics planning as well.

This research presents an automated CSLP framework and a MLP framework that are developed based on BIM technology. The first framework utilizes information stored in BIM models to estimate the size, type and number of temporary facilities required by a construction project during different time intervals. By leveraging the functionality offered by the Autodesk Revit application programming interface (API), several of the computations are automated, significantly reducing manual effort. The second framework is designed to integrate material quantity information from BIM models with construction progress data and material delivery information. This framework coordinates material logistics along with the site layout, giving special emphasis on responding to construction delays. The two frameworks together can be used to facilitate CSLP and MLP on congested construction sites.
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HKUST A Building Information Modeling Framework for Waste Estimation and Embodied Carbon Calculation of Buildings Thesis 08/2012 Yinghui MA The construction industry is a major consumer of natural resources and energy, and a major contributor of waste and carbon emissions. Many countries have taken initiatives to reduce the negative environmental impacts in terms of waste and carbon emissions caused by construction activities; however, implementations of those strategies are often based on experience and heuristics rather than quantitative data. The value of estimating and evaluating construction and demolition (C&D) waste and carbon emissions in the construction industry has been indicated in literature. Nevertheless, tools that can accurately and conveniently estimate the amount of the waste from construction projects are lacking. On the other hand, current carbon emission analysis tools mostly focus on the estimation of operational carbon. Although embodied carbon (EC) of building materials has shown increasingly important in carbon emission analysis of buildings, the current tools that estimate EC are still primitive and not automated.

Therefore, this study aims to develop a framework for a lifecycle evaluation of waste and carbon emissions of buildings leveraging the building information modeling (BIM) technology. BIM represents the process of development and use of a computer generated model to simulate the planning, design, construction and operation of a building facility. BIM has been increasingly used in the architectural, engineering and construction industry for building performance analysis and construction planning. However, the use of BIM for estimation and planning of C&D waste and EC is still lacking. This thesis presents the automated BIM-based C&D waste estimation system and the automated BIM-based EC estimation system that the author has developed. The first system was designed to extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. The second system was designed to integrate extracted material and element information with external carbon inventory databases for embodied carbon and energy estimation.

With the two systems, decision making could be facilitated among clients, architects, engineers, and other stakeholders. The systems can also be used combined with current tools to perform a lifecycle analysis. As the BIM technology has been increasingly adopted and digital building information models will likely to be available for most buildings and even infrastructures in the future, our systems can be applied in various projects.
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HKUST BIM-based Automatic Piping Layout Design and Schedule Optimization Thesis 08/2020 Jyoti SINGH Piping system is one crucial component in civil infrastructure that is designed to collect and transport fluid from the various sources to the point of distribution. The design, manufacture, coordination, scheduling, and installation of pipe systems is an important and necessary task and is one of the most time-consuming and complicated jobs in any piping project. Therefore, it is important and necessary to perform pipe systems design and scheduling efficiently. Better understanding of the complex design logic and installation options of a pipe system can enhance the reliability of designing and scheduling, which is crucial to achieve smooth and steady design and schedule flow. An efficient designing and scheduling of piping systems become more and more challenging due to various constraints such as physical, design, economical, and installation constraint. Current practice in the architecture, engineering and construction (AEC) industry involves pipe system design and installation as per enforced design codes, either by manual calculations, or by partial automation using computer-aided design software. Manual calculations are based on the experience of consultants and design codes, which is labor intensive, time consuming, and unadaptable to changes, and often leads to mistakes due to tedious nature of pipe design and coordination problems and the numerous calculations and decision-making involved. Therefore, complete automation with design and schedule optimization are required to economically plan pipe system design layout and generation of installation schedule.

Nowadays, Building Information Modelling (BIM) has been increasingly applied for architectural and structural design in civil engineering, especially in the building sector, since BIM have advantages for digital representation and information management. BIM technology is used to capture the 3D geometric and semantic information of the ceiling space, building components and pipe system information and parameters. BIM technology is used to capture the valuable information from 3D models to assist time based 4D modeling. However, existing research of BIM application for piping system design in building sector is lacking. To tackle the limitation of existing research, this thesis aims to develop an automated BIM-based approach for pipe systems design and schedule optimization.

For the design of pipe system layout, various factors such as building space geometry, system requirements, design code specifications, and locations and configurations of relevant equipments are considered. A framework based on building information modeling (BIM) for automatic pipe system design optimization in 3D environment. Heuristic algorithms are modified and used in a directed weighted graph to obtain the optimal feasible route for pipe system layout. Clashes among pipes and with building components are considered and subsequently avoided in the design optimization. The developed framework considers one-to-one, one-to-many, many-to-one connections of the pipe network routing. Comparison between heuristic routing algorithms is also presented in this research.

For installation schedule generation, this research proposes a new approach to automate pipe installation coordination and schedule optimization using 4D BIM. Category-based matching rules are used to automate the pairing and integration between 3D BIM models and installation activities. Constraint based analysis by sequence rule is developed to generate favorable sequence and coordination between pipe systems. Heuristic algorithm is adopted to optimize the generated practical schedules based on formulated objective function. All developed BIM-based framework and approaches are illustrated with related examples. Compared to current practices, these proposed approaches significantly reduce the time and cost for pipe system design layout and generating installation schedule.

This research has three parts. The first part is background study and literature review on pipe systems design and scheduling. The second part applies BIM-based framework to design piping system, including the following three studies: (1) an automated single pipe system design using modular approach, (2) multiple pipe system layout design optimization, and (3) comparison of developed approach with other optimization methods. The third part applies BIM-based framework for piping coordination and scheduling optimization
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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 Integration of Building Information Modeling and Internet of Things for Facility Maintenance Management Thesis 03/2019 Weiwei CHEN Facility management (FM) accounts for more than two thirds of the total cost of the whole life cycle of a building. FM staff do have inadequate visualization and often have difficulty in querying information using 2D drawings and traditional facility management systems. Currently, building information modeling (BIM) is increasingly applied to FM in the operations and maintenance (O&M) stage. BIM represents the geometric and semantic information of building facilities in 3D object-based digital models and enables facility managers to manage building facilities better in the O&M stage. At the same time, the Internet of Things (IoT) technology can be used to acquire operational data of building facilities and real-time environmental data to support FM. However, few studies have used BIM and IoT technologies together for automated management and maintenance of building facilities. Around 65%~80% of the FM comes from facility maintenance management (FMM). However, there is a lack of efficient maintenance strategies and appropriate decision making approaches that can reduce FMM costs. Facility managers usually undertake reactive maintenance or preventive maintenance strategies in the O&M stage. However, reactive maintenance cannot prevent failures and preventive maintenance cannot predict the future condition of building components, which leads to maintenance actions being performed after failure has occurred and it cannot keep the functionality of a building consistent. This study aims to apply a predictive maintenance strategy with BIM and IoT technologies to overcome these limitations. In addition, there is an information interoperability problem among BIM, IoT and the FM system. Therefore, this study aims to leverage the BIM and IoT technologies to improve the efficiency of FMM and to address the information interoperability problem of integrating BIM, IoT and the FM system.

In order to improve the efficiency of FMM, an FMM framework is proposed 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 developed Industry Foundation Classes (IFC) extension of maintenance tasks and MWO information in order to achieve data integration. Geometric and semantic information of the failure components is extracted from the BIM models in order to calculate the optimal maintenance path in the BIM environment. Moreover, 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.

In order to provide a better maintenance strategy for building facilities, a data-driven predictive maintenance framework based on BIM and IoT technologies for FMM has been developed. The framework consists of an information layer and an application layer. Data collection and data integration among the BIM models, FM system, and IoT system are undertaken in the information layer, while the application layer contains four modules to achieve predictive maintenance, namely: (1) condition monitoring and sensor data acquisition, (2) condition assessment module, (3) condition prediction module, and (4) maintenance planning module. In addition, machine learning algorithms, i.e. artificial neural network (ANN) and support vector machine (SVM), are used to predict the future condition of building components.

For the information interoperability problem among BIM, IoT and FM system, an ontology-based methodology framework is proposed for data integration among the BIM, IoT and FM domains. The ontology-based approach is developed as a tool to facilitate knowledge management in BIM- and IoT-based FMM and improve the data integration process. First, three ontologies are developed for BIM, IoT, and FMM respectively according to the ontology development process and facility information requirement. Second, an ontology mapping method is designed to integrate the three developed ontologies based on mapping rules. Moreover, ontology reasoning rules are developed based on description logics to infer implicit facts from the integrated ontology and support quick information querying on FMM. The developed framework is validated through an illustrative example.

This research provides an automatic work order scheduling approach in FMM and predictive maintenance strategy for building facilities, thereby enabling great saving in time and labor costs for facility staff. In addition, the proposed ontology-based methodology can address the information interoperability problem and integrate data from BIM, IoT and FM system for facility maintenance activities. In the future, the ontology-based methodology will be applied for the operation management of building facilities.
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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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