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院校 題目 類型 日期 作者 摘要 網頁
HKUST A framework for 3D traffic noise mapping using data from BIM and GIS integration Journal 01/2016 Deng, Y., Cheng, J.C.P., and Anumba, C.J. Traffic noise is a major health concern for people living in urban environments. Noise mapping can help evaluating the noise level for certain areas in a city. Traditionally, noise mapping is performed in 2D geographic information system (GIS). The use of 3D GIS is also emerging in noise mapping in recent years. However, the current noise-mapping platforms can only conduct noise evaluation for the outdoor environment and the indoor environment separately. In addition, related information about absorption coefficient and transmission loss (TL) in noise calculation is not properly retrieved and is often replaced with a single value. In this research, building information modelling (BIM) and 3D GIS are integrated in order to combine traffic noise evaluation in both outdoor environments and indoor environments in a single platform. In our developed BIM–GIS integration platform, the built environment is represented in a 3D GIS model that contains information at a high level of detail from BIM. With the integration with BIM, the 3D GIS model now has access to detailed indoor features such as interior walls and interior rooms. Noise evaluation could therefore be performed at a room level in the developed platform. Essential parameters such as absorption coefficient and TL can be extracted directly from BIM for noise calculation. The 3D GIS model is connected with detailed BIM so that any changes in the indoor and outdoor features can be reflected to each other. The Italian C.N.R model is modified and applied in the platform to conduct noise calculation. This paper presents the details for the development of the noise-mapping BIM–GIS platform based on ArcGIS. Two use cases were analysed to show the role of such platform in the decision-making process of both urban planning and interior design. 連結
HKUST A financial decision making framework for construction projects based on 5D building information modeling (BIM) Journal 12/2015 Lu, Q., Won, J., and Cheng, J.C.P. Analyzing cash flows and undertaking project financing are important for contractors in managing construction projects. Traditional methods for cash flow analysis are based on the manual integration of time and cost information. However, the manual integration process can be automated by using five-dimensional building information modeling (5D BIM). Previous studies on 5D BIM have focused on estimating cash outflow rather than cash inflow analysis and project financing. This paper proposes a BIM-based methodology framework for cash flow analysis and project financing. The framework considers contract types and retainage to estimate cash inflow, and cash outflow patterns for equipment, manpower, and materials in order to more accurately measure cash outflow. Project financing scenarios can also be evaluated using the framework. Illustrative examples are demonstrated to validate the proposed framework by considering two what-if scenarios. Results show that the framework can help contractors analyze the cash flow and make appropriate decisions for different design and payment scheme alternatives in construction projects. 連結
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 A BIM-based web service framework for green building energy simulation and code checking Journal 06/2014 Cheng, J.C.P., and Das, M. Green building design has been a major trend in the last decade which has largely affected the AEC industry. As of 2013, for example, there were over 13,000 green buildings certified with LEED (Leadership in Energy and Environment Design) in the United States alone. Building Information Modeling (BIM) technolo- gy and computer simulations are adopted largely for green building design. However, while information sharing and automated, collaborative design review are important for the design of green buildings, the current way of BIM-based green building design relies mainly on individual file transfer and does not support collaboration in the distributed environment of construction projects. On the other hand, as the Internet becomes ubiquitous, the web provides convenient and cost-efficient means for multi-location cross-organizational collaboration. Energy analysis and validation against standard building codes are two major processes in green building design evaluation. This paper presents a modular web service based framework which integrates the information necessary for green building design, automates the building design evaluation processes, and facilitates simple updates on the building model on a common but distributed platform. This framework is based on BIM data models like gbXML (Green Building XML) which contain information for green building design like geometry of the building, material, and sensor information from more than one source. The BIM data models act as a single source of building information for all processes. Building design evaluation and updating are iterative in green building design and require information and inputs dispersed among various project participants. Since our framework follows a distributed architecture and is easily accessible from the Internet, it makes the information required to facilitate the iterative process and its results conveniently available to a multi-participant environment. The paper also presents an example scenario demonstrating the developed framework. 連結
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.
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HKUST A BIM-based location aware AR collaborative framework for facility maintenance management Journal 07/2019 Chen, K., Chen, W., Li, C.T., and Cheng, J.C.P. Facility maintenance management (FMM) accounts for a large amount of the total cost of facilities’ lifecycle, illustrating the importance of improving FMM efficiency. Many mechanical facilities, like ventilation ducts above ceilings, are normally hidden, indicating the necessity of applying certain technology that can enable users to visualize and update the information of hidden facilities. Real-time location information is also needed so
that users can be aware of their current location and the surrounding facility can be displayed accordingly. Therefore, this paper aims to develop location aware augmented reality (AR) framework for FMM, with building information modeling (BIM) as the data source, AR for the interaction between users and facilities, and Wi-Fi fingerprinting for providing real-time location information. The developed framework has the following features: (1) a proposed softmax-based weighted K nearest neighbour (S-WKNN) algorithm is used for Wi-Fi fingerprinting to obtain the current location of users; (2) a room identification method, based on BIM, the obtained location, and ray casting algorithm, is proposed to identify which room the user is currently in; (3) according to the obtained location and the identified room, users can visualize and interact with their surrounding facilities through the AR devices; and (4) users in a remote location can visualize site situation and interact with site facilities in real time through video streaming and the shared database. At the end of the paper, an experiment was designed to evaluate the effectiveness of the developed system. As shown by the experiment, the developed AR collaborative system can reduce the completion time of the designed task by around 65% compared with traditional 2D drawing-based method, and can provide a localization accuracy of around 1m
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