Developing a context-based bounded centrality approach of street patterns in flooding: a case study of London

Floods affect an average of 21 million people worldwide each year, and their frequency is expected to increase due to climate warming, population growth, and rapid urbanisation. Previous research on the robustness of transport networks during floods has mainly used percolation theory. However, giant component size of disrupted networks cannot capture the entire network’s information and, more importantly, does not reflect the local reality. To address this issue, this study introduces a novel approach to bounded context-based centrality to extract the local impact of disruption. In particular, we propose embedding travel behaviour into the road network to calculate bounded centrality and develop new measures characterising the size of connected components during flooding. Our analysis can identify critical road segments during floods by comparing the decreasing trend and dispersibility of component sizes on road networks. To demonstrate the feasibility of these approaches, a case study of London's transport infrastructure that integrates road networks with relevant urban contexts was developed. This approach is beneficial for practical risk management, helping decision-makers allocate resources efficiently in space and time

SeeCarbon: a review of digital approaches for revealing and reducing infrastructure, building and City's carbon footprint

Dealing with climate change and its consequences on the environment have been one of the biggest challenges nowadays, where reducing the carbon footprint has been the focus of most sustainable strategies. The infrastructure is the dominant sector responsible for the total carbon footprint, accounting for approximately 70% of global carbon emissions. This study aims to illustrate the state-of-the-art of digital development and transformation of revealing and reducing carbon footprint in the Architecture, Engineering, Construction and Facility Management (AEC/FM) sectors. The digital tools for revealing and reducing infrastructure’s carbon footprint would be summarized and also compared with other sectors, namely the tools for building and city. Current challenges and future development are also included

Digital Tools for Revealing and Reducing Carbon Footprint in Infrastructure, Building, and City Scopes

The climate change issue has been striking and bringing pressure on all countries and industries. The responsibility of the Architecture, Engineering, Construction and Facility Management (AEC/FM) industry is heavy because it accounts for over one-third of global energy use and greenhouse gas emissions. At the same time, the development of digital technology brings the opportunity to mitigate environmental issues. Therefore, this study intended to examine the state-of-the-art of digital development and transformation in the AEC/FM industry by collecting and reviewing the developed digital carbon footprint analysis tools in infrastructure, building, and city scopes. Specifically, this study (1) generated a review methodology for carbon footprint analysis results; (2) demonstrated the review results from the infrastructure, building, and city scopes, analysed and compared the results crossing the scopes from four aspects: carbon footprint analysis strategy, standards and protocols, rating systems, and general development level of digital tools; and (3) discussed the potential directions in the industry to address the environmental issues. This study indicated that the digitalisation level regarding carbon-related areas is still at an early stage, and efforts should be taken both academically and practically to drive the digital development confronting the harsh climate change issue

Gemini Principles-Based Digital Twin Maturity Model for Asset Management

Various maturity models have been developed for understanding the diffusion and implementation of new technologies/approaches. However, we find that existing maturity models fail to understand the implementation of emerging digital twin technique comprehensively and quantitatively. This research aims to develop an innovative maturity model for measuring digital twin maturity for asset management. This model is established based on Gemini Principles to form a systematic view of digital twin development and implementation. Within this maturity model, three main dimensions consisting of nine sub-dimensions have been defined firstly, which were further articulated by 27 rubrics. Then, a questionnaire survey with 40 experts involved is designed and conducted to examine these rubrics. This model is finally illustrated and validated by two case studies in Shanghai and Cambridge. The results show that the digital twin maturity model is effective to qualitatively evaluate and compare the maturity of digital twin implementation at the project level. It can also initiate the roadmap for improving the performance of digital twin supported asset management

Building information modelling execution plans: a global review

A building information modelling (BIM) execution plan is a process-management document that includes the standards, responsibilities and protocols used as a basis for a BIM project. Despite the increased interest in BIM implementation, there are a few studies in the literature specifically tailored to the development of an execution plan. A study was undertaken to review and analyse the literature and synthesise existing knowledge relevant to the topic. A thematic framework of content aspects and trends was developed to define grounds for developing execution plans by examining 36 publications from different organisations worldwide. Based on the framework, this research analysed a total of 29 topics classified into functional, informational, organisational and legal issues and identified their influential relationships where applicable. The study highlighted the current state of BIM management platforms and redefined the connection between BIM contracts, execution plans and model data. The paper has practical implications for defining project-specific execution plans and highlighting the research gaps. It also provides recommendations for future development of execution plans, to be used both as an instrument for advancing the use of BIM and as a regulator of the digitalised and collaborative practices

A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT

Building information modelling (BIM) could support different activities throughout the life cycle of a building and has been widely applied in design and construction phases nowadays. However, BIM has not been widely implemented in the operation and maintenance (O&M) phase. As-is information for the majority of existing buildings is not complete and even outdated or incorrect. Lack of accurate and complete as-is information is still one of the key reasons leading to the low-level efficiency in O&M. BIM performs as an intelligent platform and a database that stores, links, extracts and exchanges information in construction projects. It has shown promising opportunities and advantages in BIM applications for the improvement in O&M. Hence, an effective and convenient approach to record as-is conditions of the existing buildings and create as-is BIM objects would be the essential step for improving efficiency and effectiveness of O&M, and furthermore possibly refurbishment of the building. Many researchers have paid attention to different systems and approaches for automated and real-time object recognition in past decades. This paper summarizes state-of-the-art statistical matching-based object recognition methods and then presents the image-based Industry Foundation Classes (IFC) BIM object creation application, which extracts object information by simply conducting point-and-click operations. Furthermore, the object recognition research system is introduced, including recognizing structure object types and their corresponding materials. This paper combines the multi-attribute utility theory (MAUT) with the fuzzy set theory to be Fuzzy-MAUT, since the MAUT allows complex and powerful combinations of various criteria and fuzzy set theory assists improving the performance of this system. With the goal of creating an effective method for as-is IFC BIM objects construction, this image-based object recognition system and its recognition process are further validated and tested. Key challenges and promising opportunities are also addressed

Scavenging Vibration Energy from Seismically-isolated Bridges Using an Electromagnetic Harvester

The increasing worldwide efforts in securing renewable energy sources increase incentive for civil engineers to investigate whether the kinetic energy associated with the vibration of larger-scale structures can be harvested. Such a research remains challenging and incomplete despite that hundreds of related articles have been published in the last decade. Base isolation is one of the most popular means of protecting a civil engineering structure against earthquake forces. Seismic isolation hinges on the decoupling of the structure from the shaking ground, hence protecting the structure from stress and damage during an earthquake excitation. The low stiffness isolator inserted between the structure and the ground dominates the response leading to a structural system of longer vibration period. As a consequence of this period shift, the spectral acceleration is reduced, but higher response displacements are produced. To mitigate this side effect, usually isolators are combined with the use of additional energy dissipation. In this study, the feasibility of scavenging the need-to-be dissipated energy from the isolator installed in a seismically isolated bridge using an electromagnetic (EM) energy harvester is investigated. The EM energy harvester consists of an energy harvesting circuit and a capacitor for energy storage. A mathematical model for this proposed EM energy harvester is developed and implemented on an idealized base-isolated single-degree-of-freedom system. The effect of having this EM energy harvester on the performance of this seismic isolated system is analyzed and discussed. The potential of installing such an EM energy harvester on a seismically isolated bridge is also addressed

Modification of NFA-Conjugated Bridges with Symmetric Structures for High-Efficiency Non-Fullerene PSCs

As electron acceptors, non-fullerene molecules can overcome the shortcomings of fullerenes and their derivatives (such as high cost, poor co-solubility, and weak light absorption). The photoelectric properties of two potential non-fullerene polymer solar cells (PSCs) PBDB-T:IF-TN (PB:IF) and PBDB-T:IDT-TN (PB:IDT) are studied by density functional theory (DFT) and time-dependent DFT (TD-DFT). Based on the optimized structure of the ground state, the effects of the electron donor (D) and electron acceptor (A) (D/A) interfaces PBDB-T/IF-TN (PB/IF) and PBDB-T/IDT-TN (PB/IDT) are studied by a quantum-chemical method (QM) and Marcus theory. Firstly, for two non-fullerene acceptors (NFAs) IF-TN and IDT-TN, the NFA IDT-TN has better optical absorption ability and better electron transport ability than IF-TN. Secondly, for the D/A interfaces PB/IF and PB/IDT, they both have high optical absorption and electron transfer abilities, and PB/IDT has better optical absorption and lower exciton binding energy. Finally, some important parameters (open-circuit voltage, voltage loss, fill factor, and power conversion efficiency) are calculated and simulated by establishing the theoretical model. From the above analysis, the results show that the non-fullerene PSC PB:IDT has better photoelectric characteristics than PB:IF