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	Integrating BIM and Internet of Things for Building Facility Management and Energy Management	Report	06/2019	Yaoming HU Bonan Zhang	This project studies sensor location determination in a complex conference room as a part of Smart HVAC system. It describes the background of HVAC system and how the system can be upgraded as a smart system, automated system, to save energy. The project mainly studies the methodology and uses some factors in IAQ, indoor air quality, to illustrate possible locations for sensor placement. In this project, Autodesk Revit is used to build a BIM model of a conference room. The building of BIM of the room is important since it will reflect the true structural setup of the room. Autodesk CFD is then introduced to run simulations. For CFD simulation, materials and boundary conditions are applied to the model in order to run simulations that can reflect distribution as realistic as possible. In the CFD simulations, some major IAQ factors such as, temperature, air velocity, thermal comfort, CO2, VOC (formaldehyde) and dust (PM 2.5) are predicted in the environment. To analyze the temperature distribution, different numbers of people are introduced to examine the difference of heat distribution due to number of people. Pollutants are examined using assumed values according to average emission values. The goal is not to determine whether or not the room is polluted but the distribution of pollutants inside the room. Eventually, the results of all simulations are collected and analyzed to determine the areas with high density of heat, pollutants where those high concentration areas are the prior locations sensors have to monitor. It is concluded that the simulation of air movement, heat, pollutant distribution, etc. is useful methodology to determine sensor locations. With the sensor placed in correct locations, HVAC system can run with higher efficiency and prevent hazardous environment.	N.A.
HKUST	BIM-based Daylighting and Energy Analysis on the HKUST Campus	Report	06/2019	Quazi Samira Rahman	Building Information Modelling (BIM) based simulation models have been consistently used to automate prolonged building performance modelling processes such as thermal comfort assessment and energy analysis, enabling fast acquisition of results. Recent studies indicate that the demand for sustainable building facilities with minimal environmental impact is growing day by day. BIM is foreseen as a savior in terms of technology to unravel laborious engineering problems in a short span of time and analyse the conditions in a given space comprehensively as well as determine efficiency of built environment. This study presents how building information modelling can be utilized to address thermal comfort and energy efficiency in buildings in the operation phase, greatly contributing to achieving optimized solution. The study primarily deals with multi physical investigation on performance assured by ventilating system in supplying air quality and determining the potentials of comfort improvement and energy savings for the control of ventilation rate by proposing optimized method for relocating supply air duct. The focus of this thesis is limited to IAS lecture theatre at HKUST with respect to current set points for the supply air temperature.	N.A.
HKUST	Comparative Study on Global BIM Standards	Report	06/2019	Xiaoyang TANG	In the recent decade, the Building Information Model (BIM) is developing at an unbelievable high speed worldwide. Just two years ago, China has published its first BIM standard to unify the BIM project process. In this essay, several China BIM standards including GB/T 51269, GB/T 51212 and GB/T 51301 are compared with other released global BIM standards according to its category. Mainly, there are three types of standards in the world, which are the International Framework for Dictionaries (IFD), Information Delivery Manual (IDM) and Industry Foundation Class (IFC). First, two types of standards are focused, which IFD will compare the GB/T 51269 with OmniClass from America, while IDM will compare the GB/T 51212 and GB/T 51301 with CIC BIM standard from Hong Kong, Singapore BIM Guide Version 2 and PAS 1192.2 from the UK. In order to compare these standards with a logic method, CIC BIM standard’s structure is chosen as the example for IDM while IFC follows GB/T. All the sections mentioned in the standards have been compared to summarize the advantages and disadvantages of China BIM standards. After compared all the standards, it could conclude that the GB/T standards are general information for most sections, which means it is suitable for most types of BIM projects. However, several sections are missing compared with other global BIM standards. For example, one of the most important BIM section called Individual Discipline Modelling is missing in any GB/T standards. Therefore, there is still room for improvement in the future.	N.A.
HKU	Defining QS-BIM in Hong Kong	Thesis	04/2019	LEE Curtise	--	N.A.
HKUST	Natural-language-based intelligent retrieval engine for BIM object database	Journal	03/2019	Wu, S., Shen, Q., Deng, Y., and Cheng, J.C.P.	Rapid growth of building components in the BIM object database increases the difficulty of the efficient query of components that users require. Retrieval technology such as Autodesk Seek in America and BIMobject in Europe, which are widely used in BIM databases, are unable to understand what the search field truly means, causing a lack of completion and a low accuracy rate for results incapable of meeting the demands of users. To tackle such a problem, this paper puts forward a natural-language-based intelligent retrieval engine for the BIM object database and Revit modeling. First, a domain ontology is constructed for semantic understanding, and the BIM object database framework is established for testing our search engine. Second, “target keyword” and “restriction sequence” proposed are extracted from the natural sentences of users. Then, a final query is formed, combining concepts of “keyword” and “restriction sequence”, and its concepts are expanded through the semantic relationship in ontology. Finally, the results are presented after mapping from the final query to the BIM object database and ranking of results. Compared with traditional keyword-based methods, the experimental results demonstrate that our method outperforms the traditional methods.	連結
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.	N.A.