| HKUST |
BIM Application for Construction and Demolition Waste Minimization |
Report |
06/2015 |
TAO Jiali |
Nowadays the construction industry is under pressure to explore effective and efficient techniques and tools to decrease its escalating waste production. Many countries have taken initiatives to reduce the construction and demolition waste. However, the current approaches, techniques and tools focus on separate projects onsite and limited effort is invested to put attention on pre-construction waste generation related to supply chain management issues and procurement, design and tender stages.
Therefore this study aims to develop the BIM-based approaches for C&D waste in the aspect of waste estimation, 3R, prefabrication and clash detection. Besides, this study will also demonstrate and validate the developed approaches for C&D waste minimization using example scenarios. All in all, the application of BIM in C&D waste minimization can be better realized. C&D Waste estimation via the quantity takeoff tool and waste index can clearly show the accurate amount of the waste before the commencement of the works. Classifying the different construction material in BIM model and set up suitable C&D waste management planning definitely improve the efficiency of the waste management. Providing accurate information of precast units ahead of time and assisting the supply chain management can be achieved in BIM model. Visual clash detection reduces rework to some extent. |
N.A. |
| HKUST |
Integration of BIM and GIS for City Planning |
Report |
06/2014 |
LI Zhi |
With the popularity of 3D digital maps for computers and mobile phones, the development of 3D city models has grown substantially in the last decades. 3D maps can not only support navigation, but also allow people to perform city planning and architectural and engineering designs with the consideration of the surrounding environment. Moreover, many other advanced applications have been studied to be equipped in 3D models, like disaster management, noise and pollutant diffusion analysis and so on. Earliest research on 3D digital city models was in 1990s and now there are about a total number of 1252 3D digital city models worldwide already.
Since the early 1990’s, lots of researchers have conducted studies in creation, application and maintenance of 3D city models. The study results indicate that the modeling construction techniques and application exploitability has improved significantly in last decades. However, the level of development of existing models varies widely in view of geographic locality (either city or country), creation time and many other factors. A standardized evaluation framework of the existing 3D city models is still in need.
Based on the purpose of setting up an evaluation framework, this review work was conducted. Mainly through literature review and searching on project websites, we collected original sources of more than 70 projects of 3D city models and 23 are chosen for detailed study and analysis. These city models are mainly categorized in four continents (North America, Europe, Asia and Oceania) and in four aspects (model coverage, modeling technology, application and maintenance).
To the point, a preliminary model estimation method is created, considering the maturity of five aspects during modeling procedures, i.e. data capturing, data processing, data storing and managing, data presenting and data updating. According to the evaluation framework, city models can be categorized into four maturity levels as 3D GIS as a Scene, 3D GIS as a Service, 3D GIS as an Infrastructure and 3D GIS as a Platform. Finally, based on the analysis results, some limitations of 3D city models in current situation are summarized, and recommendations of possible resolutions are presented correspondingly. |
N.A. |
| HKUST |
Mapping of 3D GIS Digital Building Models in CityGML Across Levels of Details (LoD) |
Report |
06/2013 |
DU Qianru |
GIS, a traditional technology used in many fields in the past hundreds years, now develops to a new height. With the fast development of 3D GIS technology, many new data formats established based on this kind of technology. Being a new format, CityGML is mainly used to represent the city models. It is really convenient due to the fact that different levels of detail exist in this kind of model format. Different LoDs have different attributes and used in diverse situations. Now, the models are often built in different LoDs. Therefore, to achieve one model which is in different LoDs, a translator needs to be published. However, until now neither OGC standard nor previous researchers provide an efficient translator for the transformation between different LoDs. Furthermore, the detailed definition for different LoDs was not provided either.
Based on these motivations, this project decided to focus on these two goals. The first part of this project focuses on the differences among different LoDs. Based on the differences, a translator is published and its methodology is also shown in the later part of this report. By using the translator established according to the method in this report, a 3D model sample is provided at the end of the report. This project not only provides a tool to realize the translation between different LoDs, but also offers a convenient method for further research. |
N.A. |
| HKUST |
Development of BIM-assisted Access Point Placement Optimization and Deep Learning based Multi-floor Identification Algorithms for Enhancing Indoor Positioning to Support Construction Applications |
Thesis |
08/2019 |
Kenneth Chun Ting LI |
Over the past decades, indoor positioning has been drawing wide attention in different fields of engineering. Indoor positioning technologies are complementary to the mature outdoor positioning technology such that the indoor positioning technologies can provide a real-time positioning service in any environment where there is a blockage of GNSS signals. In the fields of construction and facility management, indoor positioning technologies enable promising applications that can considerably enhance the productivity, efficiency and safety on construction sites, supporting five major applications, which are (1) construction safety management, (2) construction process monitoring and control, (3) inspection of construction structures and materials, (4) construction automation with robotics, and (5) the use of building information modelling (BIM) technology for construction progress management.
Currently, there is no single perfect indoor positioning system that can perform optimally under any circumstances. In addition, due to the large variety of indoor positioning technologies and principles, as well as the complex and dynamic environment on construction sites, developing suitable indoor positioning systems on construction sites is a challenging task. Applying indoor positioning systems is essentially user-oriented and environment-specific. This thesis thus analyses the challenges to apply indoor positioning systems on construction sites, and then proposes six indoor positioning performance metrics, namely APP-CAT, for evaluating suitable on-site indoor positioning systems. Subsequently, the top 10 indoor positioning technologies, which are selected according to their evaluation results using APP-CAT and their popularity amongst the indoor positioning literature studies, are thoroughly discussed and compared. The promising recent trends of developing on-site indoor positioning systems, such as infrastructure-free positioning, collaborative positioning, game theory positioning, and device-free positioning, as well as integration of indoor positioning technologies with BIM models, are also highlighted. In this research work, the comprehensive discussion of current development in indoor positioning from different aspects is intended to help academics, researchers, and industry practitioners develop high-performing and suitable on-site indoor positioning systems for supporting various engineering and construction applications.
Among various positioning technologies, Wi-Fi fingerprinting has emerged as a popular technique due to the wide coverage of Wi-Fi signals and its high compatibility with smartphones. Wi-Fi fingerprinting utilizes the patterns of the Wi-Fi signal strengths, which are measured by the Received Signal Strength Index (RSSI), for position estimation. Normally, Wi-Fi access points are placed arbitrarily, which causes a poor positioning accuracy. In fact, positioning accuracy can be considerably enhanced by optimizing the access point (AP) placement strategy. In light of the high popularity of Wi-Fi fingerprinting and the liberty to design AP placemnent strategies on construction sites, this thesis aims to conduct AP placement optimization is by finding the optimal AP placement strategy that maximizes the distinctiveness between individual Wi-Fi fingerprints in a 3D virtual environment. The use of BIM technology provides 3D geometric and semantic information to accurately reproduce the virtual environment for realistic simulation of Wi-Fi signal propagation. Wi-Fi signal propagation is usually modelled by a modified indoor radio wave path loss model, but such models cannot easily consider the multipath effect in an indoor environment. Therefore, in this thesis, an accurate Deep Belief Network (DBN) based path loss model, which considers the multipath effect emulated by the ray-tracing method using particle swarm optimization (PSO), is proposed and implemented to predict the indoor Wi-Fi signal strengths. Based on the results of the simulation, the optimal AP placement strategy as well as the geometrically-constrained optimal AP placement strategy can be obtained by using the genetic algorithm (GA). The test results in a university library have shown that the developed AP placement optimization algorithm could consistently enhance the accuracy of 3D indoor positioning under the circumstances of different numbers of APs and the presence of geometric constraints.
Facility management is often performed in a multi-floor indoor environment such as shopping malls and airports. However, one of the major challenges facing the received signal strength indicator (RSSI) based fingerprinting is the inability to perform accurate indoor positioning in a multi-floor environment, despite their popularity. The multi-floor environment poses a large challenge to RSSI fingerprint-based indoor positioning because the uniqueness of RSSI fingerprints is largely lost in a multi-floor environment, especially when ring structure exists in the building. Such a ring structure is commonly found in large airports and shopping malls. In this thesis, in light of the analogy between visual images and a radio map, a novel twofold multi-floor localization algorithm based on convolutional neural network (CNN) is developed to perform robust and accurate multi-floor localization. To support the twofold CNN model and to improve the localization accuracy, the similar selective search algorithm and data augmentation algorithm are proposed. Lastly, with the support of inertial measuring units (IMUs), the snapping algorithm is proposed to convert a random trajectory to a grid shape for the purpose of localization. Per the validation results, the proposed multi-floor localization algorithm is capable of identifying on which floor the user is located such that the “floor jumping” problem is mitigated, and thus the overall indoor positioning accuracy on RSSI fingerprint-based indoor positioning is substantially improved during indoor navigation.
To summarise, this thesis provides a comprehsive review of the top 10 indoor positioning technologies for their usage on construction sites, and aims to develop a BIM-assisted access point placement optimization and deep learning based multi-floor identification algorithms for enhancing indoor positioning to support construction applications for both construction management and facility managment. |
N.A. |
| HKUST |
Evaluation and Development of Automated Detailing Design Optimization Framework for RC Slabs Using BIM and Metaheuristics |
Thesis |
08/2019 |
Muhammad AFZAL |
Reinforced concrete (RC) structural design optimization has been undertaken for several decades and plays an important role in maximizing the reliability, cost efficiency, and environmental sustainability of RC structures. However, optimization of RC structural design is challenging and requires advanced strategies during different life cycle phases of RC structures. Over the past few decades, substantial fundamental research efforts in RC structural design optimization have been undertaken, but there is a lack of a comprehensive review of these efforts that can provide academic and industry practitioners with sufficient detailed insights. Therefore, this research introduces a critical evaluation of previous research related to the optimization of RC structures for minimizing the amount of construction materials, the material cost, and the environmental effects, with more emphasis on detailing design (such as steel reinforcement), aiming to identify the common research themes and highlight the future directions. Based on the critical evaluation, the portfolio of 348 available research articles presents the identified research gaps and potential future research directions. For example, the adoption of clash-free rebar design optimization, detailing design optimization of complex and irregular RC components, and the concentration of design for manufacture and assembly (DfMA) aspects, are seldom conducted and studied.
Moreover, steel reinforcement detailing design of RC structures is one of the common and important tasks in building construction. Currently, despite having introduced advanced computing technologies in the architecture, engineering, and construction (AEC) industry, the rebar detailing design process is still predominantly performed by manual or at least semi-manual approaches, with the aid of computer software packages following the regional design codes. Manual or semi-manual perspectives often result in conservative, uncertain, and sometimes unacceptable outcomes. Additionally, the simple design of RC structural elements can potentially face constructability issues such as congestion, collision, and complexity which may cause complications during the procurement of rebars and other elements all along the construction phase. These issues also hinder concrete pouring and as a result, generate improper compounding of concrete with the rebars which disturb the integrity of the RC structure. All these concerns substantially increase the construction cost, time and quality and thus are uneconomical for AEC industry stakeholders. Although a few previous studies have conducted detailing design optimization of RC structures, very little attention has been given to the above-mentioned issues. Therefore, this research also aims to develop a holistic BIM-based framework utilizing the different meta-heuristic algorithms (such as SGA, SGA-SQP, and PSO-SQP, etc.) for the optimal detailing design of RC solid slabs, considering the minimization of overall construction cost. The main objective function determines the overall minimized construction cost of the RC solid slab, including the cost of steel reinforcement bars in all reinforcing layers, the cost of concrete, and the cost of labor for installing the steel reinforcement bars and pouring the concrete in the RC solid slab. The optimization process is handled in such a way that the first stage optimizes the steel reinforcement present in all four reinforcing layers (two layers each at the bottom and top of solid slab), while the second stage optimizes the solid slab thickness based on the characteristic concrete strength.
For the optimum design to be directly constructible without any further alterations, aspects such as available standard rebar diameters, spacing requirements of the rebars, relevant regional design provisions (i.e. British Standards), and the above-mentioned constructability (more specifically clash-avoidance) concerns, are also incorporated into the development of optimization model. In this research, a case study of a typical RC solid slab containing one-way and two-way spanning slab panels is analyzed to investigate the capabilities of the proposed framework. The results demonstrate the potential of the developed model in producing optimum and realistic design solutions. The developed model can be utilized as a design tool to retrieve economical design solutions at the early-stage structural detailing design. |
N.A. |
| HKUST |
BIM-based Automatic Generation of Fabrication Drawings for Building Facades |
Thesis |
08/2018 |
Min DENG |
Many modern commercial buildings involve complex shaped façades, resulting in increasing complexity as well as challenges in façade fabrication and assembly processes. Currently, fabrication drawings are essential for fabrication, design evaluation and inspection of building components. Computer-aided automation, which can significantly improve the efficiency and accuracy of the fabrication and assembly process, is thus essential for the generation of façade fabrication drawings, thereby supporting the fabrication and assembly of the building façade components. Among current computer-aided technologies, building information modeling (BIM) has been widely applied to many sophisticated building projects due to its comprehensive ability in digital representation of building models. BIM has demonstrated its advantages over generating different types of drawings. However, generating fabrication drawings for façade panels using conventional approaches is time-consuming and error prone, especially when the number of façade components become huge. Therefore, this thesis aims to develop BIM-based methodologies to automate the generation of fabrication drawings for façade components, thereby facilitating the whole construction process.
For façade panels, a BIM-based framework is proposed for the automatic generation of fabrication drawings for façade panels. The framework integrates both graphical and non-graphical information from BIM models and other external data sources. Specific algorithms are applied to automatically generate the graphical information on the drawing templates based on the BIM geometric models. Title blocks of the drawing templates are also automatically filled in with corresponding non-graphical information. Complete fabrication drawings as well as a tabulated file with essential graphical information on similar components are then generated automatically.
For structural components such as mullions and transoms, it is important to represent their physical characteristics clearly, thus a large number of section views need to be produced, which is a time-consuming process and very labor intensive. Therefore, automatic generation of fabrication drawings for building façade components (such as mullions and transoms) is of paramount importance. In this thesis, 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 front 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 the drawing formats, a methodology is proposed to simulate the scales of the drawings by using clustering technique.
With the adoption of the proposed BIM-based methodologies, time and human effort in the generation of fabrication drawings for façade components can be significantly reduced, and all the fabrication drawings for similar components will follow a consistent drawing format with explicit layout, thereby enhancing their readability. |
N.A. |
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