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香港專上院校所提供之論文/研究刊物
| 院校 | 題目 | 類型 | 日期 | 作者 | 摘要 | 網頁 |
|---|---|---|---|---|---|---|
| HKUST | Automatic generation of fabrication drawings for facade mullions and transoms through BIM models | Journal | 07/2019 | Deng, M., Gan, V.J.L., Singh, J., Joneja, A., and Cheng, J.C.P. | Fabrication drawings are essential for manufacturing, design evaluation and inspection of building components, especially for building façade structural components. In order to clearly represent the physical characteristics of the façade structural components, a large number of section views need to be produced, which is very time-consuming and labor intensive. Therefore, automatic generation of fabrication drawings for building façade components (such as mullions and transoms) is of paramount importance. In this paper, attempts have been made to develop an efficient framework in order to automatically generate fabrication drawings for building façade structural components, including mullions and transoms. To represent the complex physical characteristics (such as holes and notches) on mullions and transoms using minimum number of drawing views, a computational algorithm based on graph theory is developed to eliminate duplicated section views. Another methodology regarding the generation of breaks for top views is also proposed to further improve the quality of drawing layouts. The obtained drawing views are then automatically arranged using a developed approach. In addition, primary dimensions of the drawing views focusing on the physical features are also generated. Furthermore, in order to maintain the consistency of drawing formats across multiple drawings, a methodology is proposed to determine the scaling factors of the drawings by using clustering technique. In an illustrative example, the proposed framework is used to generate the fabrication drawings for a typical BIM model containing façade structural components, and saving in time is observed. | 連結 |
| 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. |
| HKUST | A BIM-based system for demolition and renovation waste estimation and planning | Journal | 03/2013 | Cheng, J.C.P., and Ma, L.Y.H. | Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C&D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D&R) works and the growing amount of D&R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D&R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D&R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation projects and be extended to facilitate project control. |
連結 |
| 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. |
N.A. |
| 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. | 連結 |
| HKUST | Automated optimization of steel reinforcement in RC building frames using building information modeling and hybrid genetic algorithm | Journal | 02/2018 | Mangal, M., and Cheng, J.C.P. | Design of steel reinforcement is an important and necessary task for designing reinforced concrete (RC) building structures. Currently, steel reinforcement design is performed manually or semi-automatically using computer software such as ETABS, with reference to building codes. These approaches are time consuming and sometimes error-prone. Recent advances in building information modeling (BIM) technology allow digital 3D BIM models to be leveraged for supporting different types of engineering analyses such as structural engineering design. With the aid of BIM technology, steel reinforcement design could be automated for fast, economical and error-free procedures. This paper presents a BIM-based framework using the developed three-stage hybrid genetic algorithm (GA) for automated optimization of steel reinforcement in RC frames. The methodology framework determines the selection and alignment of steel reinforcement bars in an RC building frame for the minimum steel reinforcement area, considering longitudinal tensile, longitudinal compressive and shear steel reinforcement. The first two stages optimize the longitudinal tensile and longitudinal compressive steel reinforcement while the third stage optimizes the shear steel reinforcement. International design code (BS8110) and buildability constraints are considered in the developed optimization framework. A BIM model in Industry Foundation Classes (IFC) is then automatically created to visualize the optimized steel reinforcement design results in 3D thereby facilitating design communication and generation of construction detailing drawings. A three-storey RC building frame is analyzed to check the applicability of the developed framework and its improvement over current design approaches. The results show that the developed methodology framework can minimize the steel reinforcement area quickly and accurately. | 連結 |