| HKUST |
Evaluation of the BIM Adoption for Civil Infrastructure and Development of a 5D BIM Financial Decision Making Framework |
Thesis |
08/2015 |
Qiqi LU |
Building Information Modeling (BIM) has been widely adopted in the building industry. However, the application of BIM in civil infrastructure facilities, sometimes referred to Civil Information Modeling (CIM), is relatively lacking and slow. Researchers and practitioners are increasingly putting efforts into CIM study and implementation, but so far there is no comprehensive review of their efforts in this regard. Such study can help the academia and industry find the gaps and identify future research direction. Therefore, this work firstly presents a framework to evaluate the current practices of CIM adoption for various civil infrastructure facilities. In this study, civil infrastructure facilities were divided into nine categories for evaluation and the efforts with regard to CIM adoption for each infrastructure category were evaluated in six aspects. This study summarizes the results of 171 case studies and 62 academic papers on CIM. Based on the evaluation and comparison results, research gaps and future direction are identified. For example, CIM uses for detailed design and documentation phase and O&M phase like 5D cost estimation, are seldom conducted and studied.
5D BIM has been studied in academic research and implemented in industry. However, existing studies on 5D BIM focus on cash outflow estimation rather than cash inflow analysis and project financing. This thesis proposes a 5D BIM-based framework for cash flow analysis and project financing. This framework considers contract types and retainage to estimate cash inflow, and cash outflow patterns for equipment, manpower and materials to accurately estimate cash outflow. Project financing scenarios can also be evaluated using the framework. One building case and one bridge case are demonstrated to validate the proposed framework by considering various what-if scenarios. The framework can help contractors analyze the cash flow and make appropriate decisions for different design and payment scheme alternatives in various types of construction projects. |
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 |
Earthquake scenario simulation of urban transportation hub: building information modeling and site-city interaction |
FYP |
06/2018 |
Yeung Tsun Fung
Chau Pang, Francis
Lam Ka Tsun |
Seismic capacity of an underground urban transportation hub becomes essential to reduce the risk of seismic hazards. By conducting a comprehensive seismic analysis, it is possible to predict the seismic hazard of the transportation hub more accurately. However, seismic design for the transportation hub is of importance to analyze the soil-structure interaction effect. Therefore, Kowloon Station is selected as a testbed to demonstrate whether the SSI effect is beneficial or detrimental. Today Building Information Modelling becomes a powerful tool to develop a three-dimensional digital model such that it can act as a database for further seismic analysis. Since the numerical finite element modelling method is a common approach to solve the problem, in this study, Plaxis 3D, a professional geotechnical FEM software, is selected to investigate the SSI effect on Kowloon Station. Advanced material models are provided to deal with the complexity of the problem.
The results show that the SSI effect has a beneficial effect which the peak acceleration of the structure base is smaller than that at the ground surface. To carry out a more realistic simulation, more laboratory tests should be carried out to obtain the dynamic soil properties. In order to examine the damage to structural and non-structural components of the structure, the recorded PGA can be applied in further studies such as fragility curves so as to analyze probability of the damage. |
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 |
Development of Approaches in Embodied Carbon of Buildings: From Construction Materials to Building Structural Design |
Thesis |
08/2016 |
Jielong GAN |
Global warming has been considered as a major environmental challenge nowadays. Among various sources of anthropogenic greenhouse gas (GHG) emissions, the building sector is one of the major contributors to global warming, in which a substantial amount of the GHG emissions are embodied carbon from construction material production and transportation. Embodied carbon can account for 50% of the life cycle GHG emissions in buildings, and this percentage can become more significant for those buildings with shorter service life or higher energy efficiency. Therefore, reducing the embodied carbon in buildings is critically important and can help decrease the life cycle GHG emissions in buildings, thereby pushing human’s living environment towards a sustainable and low carbon future.
This thesis uses two approaches to reducing the embodied carbon in buildings. The first approach focuses on the construction material aspect and aims to reduce the embodied carbon from the manufacturing processes and transportations of construction materials. In this thesis, only the cement-based material (i.e., concrete) and quarried material (i.e., aggregate) are studied using the construction materials approach, as they account for more than 60% of the embodied carbon in a reinforced concrete (RC) building. Methods to the reduction of embodied carbon of aggregate and concrete are proposed, considering the feature of each material. Aggregate is very heavy and generates a large amount of emissions during transportation, therefore the aggregate study presents a mathematical model based on life cycle assessment (LCA) and multi-objective optimization (MOO) in order to plan the optimal amount of aggregate from different supply sources. The model can help stakeholders formulate sustainable material supply strategies that minimize the embodied carbon and material cost. For the concrete study, embodied carbon from concrete mix proportions is more important. Thus, a systematic embodied carbon quantification and mitigation framework is proposed for low carbon concrete mix design. The parameters that significantly affect the mix design and embodied carbon of concrete, namely the compressive strength class, the cement type, the supplementary cementitious materials (SCMs) and the maximum aggregate size, are considered. The proposed framework can be used to identify the low carbon mix design for concrete, and the results serves as a basis for reducing the embodied carbon emissions in buildings.
Another approach to reducing the embodied carbon in buildings considers different kinds of construction materials together, and focuses on building design aspect in order to minimize the total amounts of construction materials and embodied carbon in buildings. While the previous studies in this particular stream concentrated on low-rise building, they overlooked the analysis on high-rise buildings. However, the structural forms, construction materials and component designs in high-rise buildings are different from those in low-rise buildings, which can cause a large variability in the embodied carbon estimates. Therefore, an embodied carbon accounting methodology based on building information modeling (BIM) for high-rise buildings is proposed in this thesis, and relationships between embodied carbon and the critical parameters in high-rise building design are evaluated through BIM and CFD technologies. A 60-story composite core-outrigger building is designed based on the structure of a typical high-rise building in Hong Kong (i.e., Cheung Kong Center), and then used as a reference for the comparative studies. The results of embodied carbon are expressed in terms of carbon dioxide equivalent (CO2-e). The first comparative study focuses on the material procurement strategies. The embodied carbon in the reference building is evaluated with different assumptions for the material manufacturing processes, the amounts of recycled scrap and cement substitutes, and the transportation distance. It is found that structural steel and rebar from traditional blast furnace account for 76% of the embodied carbon in high-rise buildings. If a contractor chooses to use steel from electric arc furnace (with 100% recycled scrap as the feedstock), the embodied carbon of a high-rise building can be decreased by 60%. As for concrete, 10-20% embodied carbon reduction is achieved by using 35% fly ash (FA) or 75% ground granulated blast-furnace slag (GGBS) in mix design. Comparative studies are also carried out to determine the embodied carbon associated with different construction materials, building heights and structural forms. The 60-story composite core-outrigger reference building has a unitary embodied carbon of 557 kg CO2-e/m2 gross floor area (GFA). If the construction material changes to structural steel, the unitary embodied carbon increases to 759 kg CO2-e/m2 GFA, while the value of embodied carbon decreases to 537 kg CO2-e/m2 GFA if RC is used in construction. Core-frame structures are suitable for buildings of 40 stories or below, with the minimum embodied carbon at 525 kg CO2-e/m2 GFA. The optimal height range for core-outrigger structures is from 50-story to 70-story with 530 kg CO2-e/m2 GFA, whereas tubular structures are in the range between 70-story and 90-story at 540 kg CO2-e/m2 GFA. The results serve as a basis for more environmentally friendly building design, thereby improving our built environment towards a sustainable and low carbon future. |
N.A. |
| HKUST |
Developing efficient mechanisms for BIM-to-AR/VR data transfer |
Journal |
06/2020 |
Chen, K., Chen, W., Wang, Q., and Cheng, J.C.P. |
Augmented reality/virtual reality (AR/VR) has been increasingly adopted to enhance visualization of building information modeling (BIM) models. However, there is a lack of mechanisms for efficient data transfer from BIM to AR/VR. On one hand, most semantic information is lost while importing BIM models into AR/VR engines. On the other hand, huge and complicated BIM models can increase the time for model transfer, increase the computation work load while rendering, and reduce the fluency when using AR/VR applications. Therefore, this paper aims to develop efficient mechanisms for BIM-to-AR/VR data transfer to better utilize the information of BIM. In this paper, an ontology-based approach is proposed to transfer semantic information of BIM. Building components in geometric models are classified according to their features and simplified with different polygon reduction methods. As shown in the experimental validation, the proposed mechanisms have the capability to efficiently transfer semantic information of BIM to AR/VR, greatly reduce the number of triangles for geometric models while maximizing the consistency of the overall shape, and improve the framerate in corresponding AR/VR applications. |
N.A. |
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