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

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Institution Title Type Date Author(s) Abstract Link
HKUST Risk Management in BIM Projects Report 06/2020 SIO Wai Lam
CHEONG Ka Yi
The objectives of the project are to identify the risks with high risk level and mitigation with higher effectiveness in BIM industry. The survey was conducted to collect the data of risks and mitigations adopted by different groups of people. Overall analysis, by-group analysis and cross-group analysis were performed.

Thus, the risks were analyzed and discussed with two approaches - level of consequence and level of probability. The level of risk was identified combining these two approaches. The assumption and resolution of identified risks were discussed. Mitigation strategies with higher appropriateness were identified and relevant comments were made.

It is found that the level of risk of C6 (Poor participation / contribution from project team in BIM adoption) and M1 (Lack of adequate expertise in BIM) are extreme, and are very high for risk T6 (Design conflict / clashes in BIM was not revealed / unresolved), C1 (Unclear requirements (e.g. EIR / AIR / contract) of BIM uses and specifications), C2 (Unclear roles, responsibility and liability in BIM implementation). As for mitigation strategy, it is found that mitigation #1 (Clear Employer’s Information Requirement) and #11 (BIM Education for Project Team) were mitigation strategies with the 1st and 2nd ranking in appropriateness/effectiveness. Mitigation can minimize risk C6, and mitigation #11 helps to mitigate risk M1.
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HKUST Risk Management in BIM Projects Report 06/2019 CHEUNG Kai Sum Hudson
Shane Syen Ee KOK
Building Information Modeling (BIM) is claimed to be as the future trend of the Architectural, Engineering and Construction (AEC) industry and a way to address the issues of AEC. A BIM model can be adopted in different stages of project’s life circle and result in better quality, but less time and cost consumed. Although quality, cost and time are improved by adopting BIM, risk is one of the critical problems in the adoption of BIM. This study is based on conducted surveys and literature research. In this study, risk factors related to BIM adoption were identified and prioritized based on the results of a questionnaire survey distributed to architects, engineering consultants, academics, and construction companies in the AEC industry, followed by a series of discussion on the major risk factors to provide better understanding. The sources were analyzed and used to explain and identify the main risk of BIM related issues. 14 sub-factors of legal risk will be studied and gathered into four big divisions. N.A.
HKUST Semi-automated generation of parametric BIM for steel structures based on terrestrial laser scanning data Journal 01/2020 Yang, L., Cheng, J.C.P., and Wang, Q. As-built building information models (BIMs) are increasingly needed for construction project handover and facility management. To create as-built BIMs, laser scanning technology has gained popularity in the recent decades due to its high measurement accuracy and high measurement speed. However, most existing methods for creating as-built BIMs from laser scanning data involve plenty of manual work, thus becoming labor intensive and time consuming. To address the problems, this study presents a semi-automated approach that can obtain required parameters to create as-built BIMs for steel structures with complex connections from terrestrial laser scanning data. An algorithm based on principal component analysis (PCA) and cross-section fitting techniques is developed to retrieve the position and direction of each circular structural component from scanning data. An image-assisted edge point extraction algorithm is developed to effectively extract the boundaries of planar structural components. Normal-based region growing algorithm and random sample consensus (RANSAC) algorithm are adopted to model the connections between structural components. The proposed approach was validated on a bridge-like steel structure with four different types of structural components. The extracted as-built geometry was compared with the as-designed geometry to validate the accuracy of the proposed approach. The results showed that the proposed approach could efficiently and accurately extract the geometry information and generate parametric BIMs of steel structures. Link
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.
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HKUST Simulation-based evolutionary optimization for energy-efficient layout plan design of high-rise residential buildings Journal -- Gan, V.J.L., Wong, H.K., Tse, K.T., Cheng, J.C.P., Lo, I.M.C., and Chan, C.M. Buildings consume 40% of global energy, in which residential buildings account for a significant proportion of the total energy used. Previous studies have attempted to optimize the layout plan of residential buildings for minimizing the total energy usage, mainly focusing on low-rise houses of a regular shape and having a limited number of design variables. However, layout design for high-rise residential buildings involves the complicated interaction among a large number of design variables (e.g., different types of flats with varying configurations) under practical design constraints. The number of possible solutions may increase exponentially which calls for new optimization strategies. Therefore, this study aims to develop an energy performance-based optimization approach to identify the most energy-efficient layout plan design for high-rise residential buildings. A simulation-based optimization method applying the evolutionary genetic algorithm (GA) is developed to systematically explore the best layout design for maximizing the building energy efficiency. In an illustrative example, the proposed optimization approach is applied to generate the layout plan for a 40-storey public housing in Hong Kong. The results indicate that GA attempts to maximize the use of natural-occurring energy sources (e.g., wind-driven natural ventilation and sunlight) for minimizing 30–40% of the total energy consumption associated with air-conditioning and lighting. The optimization approach provides a decision support basis for achieving substantial energy conservation in high-rise residential buildings, thereby contributing to a sustainable built environment. Link
HKUST Social BIMCloud – A Distributed Cloud-based BIM Framework for Object-based Lifecycle Information Exchange and Supply Chain Integration Thesis 08/2015 Moumita DAS Due to its fragmented and multi-domain architecture, the AEC (architecture, engineering, and construction) industry faces the issues of data transfer efficiency and data consistency while exchanging large BIM files. In this thesis, a cloud based BIM framework, called Social BIMCloud is presented for building design and management of lifecycle activities. Social BIMCloud addresses the issue of data transfer efficiency by reducing the size of the BIM files being exchanged through dynamic splitting and merging mechanisms. Data consistency is also improved by hosting a common integrated BIM model which is updated partially instead of generating a new BIM file for every new change, which usually leads to data duplicity. This collaborative framework, Social BIMCloud is termed “Social” in particular, as it captures and manages the formal and informal social interactions that take place in a construction project. The methodology for capturing and managing social interactions through Social BIMCloud has been demonstrated in this thesis by integrating it with popular BIM software, Autodesk Revit.

Social BIMCloud provides the scope for extending and integrating it with external planning and analysis applications in a plug-and-play manner for lifecycle integration. In this thesis, methodologies and demonstrations have been presented for extending and integrating Social BIMCloud for – (1) construction supply chain (CSC), (2) green building design, and (3) construction site layout planning. For CSC integration, an ontology based web service framework is presented. Ontologies incorporate data semantics in the information exchanged. Therefore, the information exchanging parties, i.e. software applications in the case of automatic information exchange, comprehend the meaning of the information and therefore facilitate smooth flow of heterogeneous information. Two example ontologies have developed by studying the CSC and those ontologies have been used to enrich the data model of Social BIMCloud for accommodating and supporting CSC integration.

Popular energy simulation software were studied to design and extend the schema of Social BIMCloud in order to integrate it with standard simulation and analysis engines through a web service based framework. Social BIMCloud has also been extended for managing construction logistics by integrating it with a construction site layout planning (CSLP) engine. For this integration, the data model of Social BIMCloud has been extended for construction schedule information like activity start date, end date and the relation of each activity with one or more building elements and the vice versa. Finally this thesis discusses the scope of future extensions and improvements on Social BIMCloud for facilitating smooth flow of information in the construction industry.
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