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

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Institution Title Type Date Author(s) Abstract 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.
N.A.
HKUST Developing a Facility Monitoring and Management Framework for Buildings Based on BIM and Sensor Technologies Report 06/2016 Fehong HE
Jiaying HUANG
Guishan LI
Building Information Modeling (BIM) is a global trend which is gaining significant benefits in facility management. It can reduce cost and time to address building management problems. Currently there is little information on how to realize the benefits from BIM with monitoring the real time state of a building environment.

In this thesis, a sensor based BIM framework is presented for building controlling and management. Building environment, space, equipment and safety information can be captured by unique sensors automatically instead of human detect. We have simulated the sensor installation in a popular BIM software Autodesk Revit, and use HKUST Hall 7 as an example model to perform our platform. We use SQL database to store all the sensor ID because it have a good linkage with BIM model. With the pragmatic sensor management plugin we can realize visualization interface in BIM model to management those sensors and get the specific information. After realize the real time data acquisition, we have researched some relative criteria and build an assessment system for further facility management.
N.A.
HKUST Creating a Connected Digital Twin of HKUST Campus for Smart Campus Facility Management FYP 06/2020 FONG, Tsz Yan
KONG, Yu Hin
Experts in engineering defines BIM as a representation of a digital twin which is a virtual replica of a physical system (Marr 2017). A digital twin provides rich semantic and geometric information for facilitating construction and FM processes. Through Facility Management Systems (FMSs) and Building Management Systems (BMSs) linked with sensors, information can be garnered to support building FM. FMS or BMS is a computer-based system installed in offices or buildings ensuring that all buildings are structurally sound and serviceable.

In this research, we initially plan to incorporate two common FM software, namely ArchiBUS and Maximo with the HKUST FM system for the sake of maximizing the FM effectiveness and facilitating FM process. However, we did not get either one of the licenses of both software, so it turns out that we have to use other machine learning set of tools to do predictions for our library. The specific goals were (1) to build a machine learning model to perform temperature forecasting; (2) to make suggestion on the operative temperature of AC in library to ensure thermal comfort; (3) to provide common campus FM capabilities by setting up and demonstrating tailor-made user interfaces by using Power BI.
N.A.
HKU Is Building Information Modelling (BIM) a Tool or a Substitute to Quantity Surveyors? Thesis 04/2015 FU Ka Chun -- N.A.
HKUST Holistic BIM framework for sustainable low carbon design of high-rise buildings Journal 06/2018 Gan, V.J.L., Deng, M., Tse, K.T., Chan, C.M., Lo, I.M.C., and Cheng, J.C.P. In high-density, high-rise cities such as Hong Kong, buildings account for nearly 90% of energy consumption and 61% of the carbon emissions. Therefore, it is important to study the design of buildings, especially high-rise buildings, so as to achieve lower carbon emissions. The carbon emissions of a building consist of embodied carbon from the production of construction materials and operational carbon from energy consumption during daily operation (e.g., air-conditioning and lighting). While most of the previous studies concentrated mainly on either embodied or operational carbon, an integrated analysis of both types of carbon emissions can improve the sustainable design of buildings. Therefore, this paper presents a holistic framework using building information modeling (BIM) technology in order to enhance the sustainable low carbon design of high-rise buildings. BIM provides detailed physical and functional characteristics of buildings that can be integrated with various environmental modeling approaches to achieve a holistic design and assessment of low carbon buildings. In a case study, the proposed framework is examined to evaluate the embodied and operational carbon in a high-rise residential building due to various envelope designs. The results demonstrate how the BIM framework provides a decision support basis for evaluating the key carbon emission sources throughout a building's life cycle and exploring more environmentally sustainable measures to improve the built environment. Link
HKUST Parametric modeling and evolutionary optimization for cost-optimal and low-carbon design of high-rise reinforced concrete buildings Journal 07/2019 Gan, V.J.L., Wong, C.L., Tse, K.T., Cheng, J.C.P., Lo, I.M.C., and Chan, C.M. Design optimization of reinforced concrete structures helps reducing the global carbon emissions and the construction cost in buildings. Previous studies mainly targeted at the optimization of individual structural elements in low-rise buildings. High-rise reinforced concrete buildings have complicated structural designs and consume tremendous amounts of resources, but the corresponding optimization techniques were not fully explored in literature. Furthermore, the relationship between the optimization of individual structural elements and the topological arrangement of the entire structure is highly interactive, which calls for new optimization methods. Therefore, this study aims to develop a novel optimization approach for cost-optimal and low-carbon design of high-rise reinforced concrete structures, considering both the structural topology and individual element optimizations. Parametric modelling is applied to define the relationship between individual structural members and the behavior of the entire building structure. A novel evolutionary optimization technique using the genetic algorithm is proposed to optimize concrete building structures, by first establishing the optimal structural topology and then optimizing individual member sizes. In an illustrative example, a high-rise reinforced concrete building is used to examine the proposed optimization approach, which can systematically explore alternative structural designs and identify the optimal solution. It is shown that the carbon emissions and material cost are both reduced by 18–24% after performing optimization. The proposed approach can be extended to optimize other types of buildings (such as steel framework) with a similar problem nature, thereby improving the cost efficiency and environmental sustainability of the built environment. Link