| HKUST |
Integration of Building Information Modeling and Internet of Things for Facility Maintenance Management |
Thesis |
03/2019 |
Weiwei CHEN |
Facility management (FM) accounts for more than two thirds of the total cost of the whole life cycle of a building. FM staff do have inadequate visualization and often have difficulty in querying information using 2D drawings and traditional facility management systems. Currently, building information modeling (BIM) is increasingly applied to FM in the operations and maintenance (O&M) stage. BIM represents the geometric and semantic information of building facilities in 3D object-based digital models and enables facility managers to manage building facilities better in the O&M stage. At the same time, the Internet of Things (IoT) technology can be used to acquire operational data of building facilities and real-time environmental data to support FM. However, few studies have used BIM and IoT technologies together for automated management and maintenance of building facilities. Around 65%~80% of the FM comes from facility maintenance management (FMM). However, there is a lack of efficient maintenance strategies and appropriate decision making approaches that can reduce FMM costs. Facility managers usually undertake reactive maintenance or preventive maintenance strategies in the O&M stage. However, reactive maintenance cannot prevent failures and preventive maintenance cannot predict the future condition of building components, which leads to maintenance actions being performed after failure has occurred and it cannot keep the functionality of a building consistent. This study aims to apply a predictive maintenance strategy with BIM and IoT technologies to overcome these limitations. In addition, there is an information interoperability problem among BIM, IoT and the FM system. Therefore, this study aims to leverage the BIM and IoT technologies to improve the efficiency of FMM and to address the information interoperability problem of integrating BIM, IoT and the FM system.
In order to improve the efficiency of FMM, an FMM framework is proposed based on BIM and facility management systems (FMSs), which can provide automatic scheduling of maintenance work orders (MWOs) to enhance good decision making in FMM. In this framework, data are mapped between BIM and FMSs according to the developed Industry Foundation Classes (IFC) extension of maintenance tasks and MWO information in order to achieve data integration. Geometric and semantic information of the failure components is extracted from the BIM models in order to calculate the optimal maintenance path in the BIM environment. Moreover, the MWO schedule is automatically generated using a modified Dijkstra algorithm that considers four factors, namely, problem type, emergency level, distance among components, and location.
In order to provide a better maintenance strategy for building facilities, a data-driven predictive maintenance framework based on BIM and IoT technologies for FMM has been developed. The framework consists of an information layer and an application layer. Data collection and data integration among the BIM models, FM system, and IoT system are undertaken in the information layer, while the application layer contains four modules to achieve predictive maintenance, namely: (1) condition monitoring and sensor data acquisition, (2) condition assessment module, (3) condition prediction module, and (4) maintenance planning module. In addition, machine learning algorithms, i.e. artificial neural network (ANN) and support vector machine (SVM), are used to predict the future condition of building components.
For the information interoperability problem among BIM, IoT and FM system, an ontology-based methodology framework is proposed for data integration among the BIM, IoT and FM domains. The ontology-based approach is developed as a tool to facilitate knowledge management in BIM- and IoT-based FMM and improve the data integration process. First, three ontologies are developed for BIM, IoT, and FMM respectively according to the ontology development process and facility information requirement. Second, an ontology mapping method is designed to integrate the three developed ontologies based on mapping rules. Moreover, ontology reasoning rules are developed based on description logics to infer implicit facts from the integrated ontology and support quick information querying on FMM. The developed framework is validated through an illustrative example.
This research provides an automatic work order scheduling approach in FMM and predictive maintenance strategy for building facilities, thereby enabling great saving in time and labor costs for facility staff. In addition, the proposed ontology-based methodology can address the information interoperability problem and integrate data from BIM, IoT and FM system for facility maintenance activities. In the future, the ontology-based methodology will be applied for the operation management of building facilities. |
N.A. |
| HKUST |
Application of Building Information Modeling Technology for Safe Operations and Decommissioning of Offshore Oil and Gas Platforms |
Thesis |
08/2018 |
Yi TAN |
Offshore oil and gas platforms (OOGPs) usually have a lifetime of 30-40 years. The operation and maintenance stage takes up the most percentage of the whole lifetime of OOGPs. During the operations and maintenance, there are several safety issues. Emergent accidents and exposure to high level of noise are two main issues. Traditional emergency responses include 2D escape plan guidance and real drill exercises. 2D escape plan usually causes different understanding, while real drill exercises require extra time and workforce. As for current noise controls, only personal protective equipment has been commonly employed, which is the least effective noise control. In addition, as increasing number of OOGPs will be retired and decommissioned in the coming decade, disassembling offshore platforms is an unavoidable activity. During OOGP decommissioning stage, there are also several safety issues such as potential clashes when conducting heavy lift operations and lift vessel capsize. Besides, when multiple lift vessels are working together to disassemble multiple offshore platforms, more than one vessel working at the same platform, which can significantly increase lift clashes, is another safety issues. Current approaches to addressing these safety issues at the decommissioning stage are usually based on experience, and manually planned. Considering all these safety issues mentioned above, automated, efficient, and accurate approaches to improving safety management of OOGPs at both operation and decommissioning stages are desired. However, limited researches have been conducted to tackle these safety issues. Therefore, this research aims to develop automated, efficient, and accurate techniques and approaches for safer operations and decommissioning of OOGPs.
Building information modeling (BIM) technology is widely used in the building and infrastructure industries for the past decade considering the rich geometric and semantic information BIM contains. Therefore, this research applies BIM technology to efficiently provide required information of OOGPs when developing new approaches to addressing safety issues.
For the operation and maintenance stage of an offshore platform, to better respond to emergent accidents, a BIM-based evacuation evaluation model is developed to efficiently simulate and evaluate different emergency scenarios, and improve evacuation performance on offshore platforms. As for the noise control, this research proposes a BIM-supported 4D acoustics simulation approach. The proposed approach can automatically conduct noise simulation for offshore platforms using the information extracted from BIM models. Maintenance schedules can then be optimized based on simulated results. By minimizing the time of exposing to a high level of noise, the noise impact on maintenance workers is well mitigated.
For the decommissioning stage, first, a semi-automated approach to generate 4D/5D BIM models to evaluate different OOGP decommissioning option is developed. Second, automated topsides disassembly planning approach based on BIM is developed. Clash-free lift paths can be generated to avoid clashes during heavy lifts. Module layouts on vessels are optimized to minimize the total heavy lift time and to guarantee the stability of lift vessels. Besides, a schedule clash detection method is also developed to make sure that no more than one vessel is working at one offshore platform simultaneously.
All developed BIM-based approaches are illustrated with related examples. Compared to current practices, these proposed approaches improve the safety management performance of offshore platforms. |
N.A. |
| 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. |
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 |
Mapping of BIM and GIS for Interoperable Geospatial Data Management and Analysis for the Built Environment |
Thesis |
08/2015 |
Yichuan DENG |
The Building Information Modeling (BIM) domain and the Geographic Information System (GIS) domain share a mutual need for information from each other. Information from GIS can facilitate BIM applications such as site selection and onsite material layout, while models from BIM help generate detailed models in GIS and achieve better utility management. The mapping between the key schemas in the BIM domain and the GIS domain is the most critical step towards interoperability between the two domains. In this research, Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) were chosen as the key schemas due to their wide applications in the BIM domain and the GIS domain, respectively. A review of previous studies on the integration between BIM and GIS reveals that so far there is no bi-directional mapping considering both geometric and semantic information between IFC and CityGML. Moreover, the transformation between different Levels of Detail (LoDs) in 3D GIS models has not been fully studied. The objective of this research is to develop techniques and tools to allow bi-directional mapping between key schemas in the BIM domain and the GIS domain considering transformation of geometry, semantic information and LoDs. Three use cases based on the integration between BIM and GIS are presented to show how the integration can facilitate problem solving in the architecture, engineering and construction (AEC) industry.
First, the sufficiency of the IFC schema for storing GIS data was evaluated using text analysis techniques and version different analysis. An extension for IFC 4 was developed to store data from CityGML. Then a linguistic-based semi-automatic mapping framework for IFC and CityGML was developed and evaluated, which showed promising results. The bi-directional mapping between IFC and CityGML was developed using instance-based mapping with reference ontology. The mapping framework was compared to previous studies to show its effectiveness.
Second, the transformation between LoDs in 3D GIS models was developed based on the LoD definitions in CityGML. This is a critical step for mapping between BIM and GIS as 3D GIS models are usually represented in different LoDs. An exterior shell extraction algorithm was proposed to facilitate the transformation between LoDs in CityGML. The algorithms of transformation from higher LoDs to lower LoDs were developed and validated using complex and large-scale 3D GIS models.
Finally, three use cases were developed to show how BIM and GIS can facilitate problem solving in the AEC industry. The first use case aimed to build 3D noise maps for urban environments using data from BIM and GIS. The Italian C.N.R. model was used for noise prediction. The highlight of this use case study is that by using BIM and GIS integration, the noise mapping can be performed at room level and the design models can be flexibly updated. The second use case considered construction supply chain management (CSCM) using BIM and GIS integration. The allocation of consolidation centers for multiple construction sites, which is a problem seldom studied by previous literature, is formulated and solved by integrating BIM and GIS. The third case aimed to develop a 3D underground utility management system for urban environments. The system uses modeling functions in BIM as data sources for utility management. Moreover, an algorithm was developed to allow transforming 2D CAD drawings into 3D utility lines. |
N.A. |
| 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. |
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