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

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Institution Title Type Date Author(s) Abstract Link
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. Link
HKUST Study on BIM Project Execution Plan and BIM Uses in Comparison with PMBOK Report 06/2020 Ka Wing Ngan
HUANG Li
Project successful strongly relies on PMBOK. Besides that, BIM is important because it is a powerful tool in delivery of BIM-based project. To implement BIM, BIM uses are defined based on project goals. To effective implement BIM as planned, BIM project execution plan (PXP) is necessary to control BIM. In the first section, this paper compares supporting infrastructure from BIM project execution plan (PXP) to PMBOK to find out the relationship. The categories of supporting infrastructure are BIM PXP overview, project information, key project contacts, project goals / BIM uses, organizational roles / staffing, BIM process design, BIM information exchanges, BIM and facility data requirement, collaboration procedures, quality control, technological infrastructure needs, model structure, project deliverables and delivery strategy / contract whereas PMBOK are integration, scope, time, cost, quality, human resources, communication, risk, procurement and stakeholder management. From the investigation, it is found that risk and cost management is not obviously applied from the categories of supporting infrastructure. In the second section, this paper investigate the relationship of various BIM uses in terms of PMBOK. The considerable BIM uses are design authoring, design review, 3D coordination, cost estimation, phase planning (4D Modelling), digital fabrication and site utilization planning. It is also found that scope, communication and human resources management is not obviously applied from the selected BIM uses. In the third section, we recommend that for BIM PXP additional section including project cost management and BIM risk management should be included; and for BIM uses attention should be paid in drafting BIM PXP to support BIM uses and other BIM uses maybe considered. Manager may benefit from the relationship developed and recommendation in BIM implementation. N.A.
HKUST Automated quality assessment of precast concrete elements with geometry irregularities using terrestrial laser scanning Journal 04/2016 Wang, Q., Kim, M.-K., Cheng, J.C.P., and Sohn, H. Precast concrete elements are popularly used and it is important to ensure that the dimensions of individual elements conforms to design codes. However, the current quality assessment of precast concrete elements is inaccurate and time-consuming. To address the problems, this study presents an automated quality assessment technique which estimates the dimensions of precast concrete elements with geometry irregularities using terrestrial laser scanners (TLS). While the scan data obtained from TLS represent the as-built condition of an element, a Building Information Modeling (BIM) model stores the as-design condition of the element. Taking the BIM model as a reference, the scan data are processed to estimate the as-built dimensions of the element. Experiments on a specimen demonstrated that the proposed technique can estimate the dimensions of elements effectively and accurately. Furthermore, a mirror-aided scanning approach, which aims to achieve reduced incident angles in real scanning environments, is proposed and validated by experiments. Link
HKUST Automated Quality Assessment of Precast Concrete Elements Using 3D Laser Scan Data Thesis 08/2017 Qian WANG Precast concrete elements are popularly adopted in buildings and civil infrastructures like bridges because they provide well-controlled quality, reduced construction time, and less environmental impact. To ensure the performance of complete precast concrete structures, individual precast concrete elements must be cast according to the as-designed blueprints. Any inconsistency between the as-built and as-designed dimensions can result in assembly difficulty or structure failure, causing delay and additional cost. Therefore, it is essential to conduct geometry quality assessment for precast concrete elements before they are shipped to the construction sites. Currently, the quality assessment of precast concrete elements is still relying on manual inspection, which is time-consuming and labor-intensive. Besides, due to tedious work, manual inspection is also error-prone and unreliable. Thus, automated, efficient, and accurate approaches for geometry quality assessment of precast concrete elements are desired. Nowadays, 3D laser scanning has been widely applied to the quality assessment of buildings and civil infrastructures because it can acquire 3D range measurement data at a high speed and high accuracy. However, existing research of laser scanning based quality assessment is mainly focused on simple-geometry elements, such as straight columns and rectangular concrete surfaces. There has been limited research on the quality assessment of precast concrete elements with complex shapes. To tackle the limitations of existing research, this research aims to develop automated, efficient, and accurate techniques for the geometry quality assessment of precast concrete elements using 3D laser scan data. The geometry quality assessment includes dimensional quality assessment, surface flatness and distortion assessment, and rebar position assessment.

For dimensional quality assessment, a dimensional quality assessment technique focusing on the side surfaces of precast concrete panels is developed. This technique aligns the laser scan data with the as-designed building information model (BIM), and extracts the as-built dimensions of the elements. Furthermore, an improved dimensional quality assessment and as-built BIM creation technique is developed to inspect the entire precast concrete element, rather than a surface only, and to automatically create a BIM model for storing the as-built dimensions for better visualization and management. As a supporting study, a novel mixed pixel filter is developed to remove noise data namely mixed pixels from raw laser scan data and to improve the dimension estimation accuracy. The proposed mixed pixel filter formulates the locations of mixed pixels, based on which the optimal threshold value is obtained to classify scan data into mixed pixels and valid points. Another supporting study is to investigate the influence factors for edge line estimation accuracy. Four influence factors are identified and the effect of each factor is analyzed based on numerical simulations. Implications are eventually suggested based on the analysis.

For surface flatness and distortion assessment, the developed technique identifies a few measures for both surface flatness and distortion. These measures are then automatically calculated from the laser scan data of the precast concrete surface for surface quality assessment. Furthermore, an automated rebar position estimation technique is developed to estimate the rebar positions for rebar positioning quality assessment. The technique can recognize individual rebars from the laser scan data of reinforced precast concrete elements and accurately estimate the rebar positions.

This research provides automated approaches for the quality assessment of precast concrete elements, which are able to greatly save the labor cost and time for quality assessment. In addition, the quality of precast concrete structures can be improved due to the faster and more economical quality assessment, thereby further promoting the adoption of precast concrete elements in the construction industry.
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HKUST Automatic as-built BIM creation of precast concrete bridge deck panels using laser scan data Journal 02/2018 Wang, Q., Sohn, H., and Cheng, J.C.P. Precast concrete bridge deck panels are commonly used for bridge constructions because they enable faster construction and have less impact on traffic flow. The quality of connections between adjacent precast elements must be ensured to guarantee the overall structural integrity of precast systems. Therefore, the dimensional quality of precast concrete panels should be inspected before they are shipped to construction sites for installation. However, current quality inspection of precast concrete elements primarily relies on manual inspection. Furthermore, the as-built dimensions of precast elements are usually stored in paper sheets or Microsoft Excel spreadsheets, making it difficult to visualize and manage the as-built dimensions. This study develops a technique to automatically estimate the dimensions of precast concrete bridge deck panels and create as-built building information modeling (BIM) models to store the real dimensions of the panels. First, the proposed technique conducts scan planning to find the optimal scanner locations for scan data acquisition. Then, the scan data of the target panel are acquired and preprocessed to remove noise data and to register multiple scans in a global coordinate system. From the registered scan data, the as-built geometries of the target panel are estimated. In the last step, an as-built BIM model is created on the basis of the previously estimated geometries. The proposed technique is validated on a laboratory-scale specimen and a full-scale precast concrete bridge deck panel. The experimental results show that the proposed technique can accurately and efficiently estimate the dimensions of full-scale precast concrete bridge deck panels with an accuracy of 3 mm and automatically create as-built BIM models of the panels. Link
HKUST BIM-based Automatic Piping Layout Design and Schedule Optimization Thesis 08/2020 Jyoti SINGH Piping system is one crucial component in civil infrastructure that is designed to collect and transport fluid from the various sources to the point of distribution. The design, manufacture, coordination, scheduling, and installation of pipe systems is an important and necessary task and is one of the most time-consuming and complicated jobs in any piping project. Therefore, it is important and necessary to perform pipe systems design and scheduling efficiently. Better understanding of the complex design logic and installation options of a pipe system can enhance the reliability of designing and scheduling, which is crucial to achieve smooth and steady design and schedule flow. An efficient designing and scheduling of piping systems become more and more challenging due to various constraints such as physical, design, economical, and installation constraint. Current practice in the architecture, engineering and construction (AEC) industry involves pipe system design and installation as per enforced design codes, either by manual calculations, or by partial automation using computer-aided design software. Manual calculations are based on the experience of consultants and design codes, which is labor intensive, time consuming, and unadaptable to changes, and often leads to mistakes due to tedious nature of pipe design and coordination problems and the numerous calculations and decision-making involved. Therefore, complete automation with design and schedule optimization are required to economically plan pipe system design layout and generation of installation schedule.

Nowadays, Building Information Modelling (BIM) has been increasingly applied for architectural and structural design in civil engineering, especially in the building sector, since BIM have advantages for digital representation and information management. BIM technology is used to capture the 3D geometric and semantic information of the ceiling space, building components and pipe system information and parameters. BIM technology is used to capture the valuable information from 3D models to assist time based 4D modeling. However, existing research of BIM application for piping system design in building sector is lacking. To tackle the limitation of existing research, this thesis aims to develop an automated BIM-based approach for pipe systems design and schedule optimization.

For the design of pipe system layout, various factors such as building space geometry, system requirements, design code specifications, and locations and configurations of relevant equipments are considered. A framework based on building information modeling (BIM) for automatic pipe system design optimization in 3D environment. Heuristic algorithms are modified and used in a directed weighted graph to obtain the optimal feasible route for pipe system layout. Clashes among pipes and with building components are considered and subsequently avoided in the design optimization. The developed framework considers one-to-one, one-to-many, many-to-one connections of the pipe network routing. Comparison between heuristic routing algorithms is also presented in this research.

For installation schedule generation, this research proposes a new approach to automate pipe installation coordination and schedule optimization using 4D BIM. Category-based matching rules are used to automate the pairing and integration between 3D BIM models and installation activities. Constraint based analysis by sequence rule is developed to generate favorable sequence and coordination between pipe systems. Heuristic algorithm is adopted to optimize the generated practical schedules based on formulated objective function. All developed BIM-based framework and approaches are illustrated with related examples. Compared to current practices, these proposed approaches significantly reduce the time and cost for pipe system design layout and generating installation schedule.

This research has three parts. The first part is background study and literature review on pipe systems design and scheduling. The second part applies BIM-based framework to design piping system, including the following three studies: (1) an automated single pipe system design using modular approach, (2) multiple pipe system layout design optimization, and (3) comparison of developed approach with other optimization methods. The third part applies BIM-based framework for piping coordination and scheduling optimization
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