Digital twinning of railway overhead line equipment from airborne lidar data

The automated generation of geometry-only digital twins of Overhead Line Equipment (OLE) system in existing railways from point clouds is an unsolved problem. Currently, this process is highly reliant upon manual inputs, needing 10 times more labour hours than scanning the physical asset. The resulting modelling cost counteracts the expected benefits of the digital twin. We tackle this challenge using a novel model-driven method that exploits the highly regulated and standardised nature of railways. It starts by restricting the search for OLE elements relative to point clusters of the railway masts. The resulting point clusters of the OLE elements are then converged with various parametric models of different catenary configurations to verify the presence of OLE elements and to find the best possible fit. The method outputs a geometry-only digital twin of the OLE system in Industry Foundation Classes (IFC) format. The method was tested on an 18 km railway point cloud and achieves overall detection rates of 93.2% F1 score for OLE cables and 98.1% F1 score for other OLE elements. The accuracy of the generated model is evaluated using distance-based metrics between the ground truth model and the automated model. The average modelling distance is 3.82 cm Root Mean Square Error (RMSE) for all 18 km dataCambridge Commonwealth, European & International Trust Bentley Systems UK Plc

Leveraging railway topology to automatically generate track geometric information models from airborne LiDAR data

Geometric information modelling from point cloud data (PCD) is a fundamental step of the digital twinning process for rail infrastructure. Currently, this onerous procedure outweighs the anticipated benefits of the resulting model and expends 74% of the modellers’ effort on converting PCD to a model. The cost of the resulting geometric information models (GIM) can be reduced by automating the modelling process. State-of-the-art methods cannot offer large-scale GIM generation required over kilometres without forfeiting precision and manual cost. This paper addresses the challenge of achieving such automation by leveraging the highly standardised topology of railways to automatically generate GIMs of rail track structures. The method first automatically segments rails and track beds, delivering labelled point clusters of track structure elements. Next, it converges the segmented rails with pre-defined parametric assemblies of different rail profiles and uses a mesh-based approach to reconstruct the geometry of the track bed, delivering industry foundation classes (IFC) files of railway track structure elements. Experiments on 18.5 km railway PCDs yielded an average segmentation of 98.1 % and 94.9% F1 scores and overall modelling accuracy of 3.5 cm and 2.8 cm root mean square error (RMSE)s for rails and track beds. The proposed method can realise an estimated time savings of 88.9% without needing any manual inputs.Cambridge Trust Scholarship Bentley Research Studentshi

Application of railway topology for the automated generation of geometric digital twins of railway masts

The digitisation of existing railway geometry from point clouds referred to as “twinning” is a laborious task; currently outweighing the perceived benefits of the resulting model. State-of-the-art methods have provided promising results, yet they cannot offer large-scale rail class segmentation requires over kilo-metres without forfeiting precision and labour cost. The authors exploit the potential benefits of railway topology to automate the twinning process. The preliminary step is automatically segmenting mast point clusters as their positions are critical for the subsequent railway assets’ class segmentation. The proposed method first removes vegetation and noise; then segments masts using the RANSAC algorithm relative to the track centerline, and delivers final models in IFC format. The authors validated the method on 18 km railway point cloud and yielded an overall segmentation accuracy of 90.1% F1 score. The proposed method lays foundations to efficiently generate geometry-only digital twins of railway assets with no prior information

Digital Twin Smart Cities for Disaster Risk Management: A Review of Evolving Concepts

Peer reviewed: TrueNatural hazard-induced disasters have caused catastrophic damage and loss to buildings, infrastructure, and the affected communities as a whole during the recent decades and their impact is expected to further escalate in the future. Thus, there is a huge demand for disaster risk management using digitalisation as a key enabler for effective and efficient disaster risk management systems. It is widely accepted that digital and intelligence technologies can help solve key aspects of disaster risk management such as disaster prevention and mitigation, and rescue and recovery. Digital Twin (DT) is one of the most promising technologies for multi-stage management which offers significant potential to advance disaster resilience. Smart Cities (SCs) use pervasive information and communications technology to monitor activities in the city. With increasingly large applications of DTs combined with big data generated from sensors in a SC, it is now possible to create Digital Twin Smart Cities (DTSCs). Despite the increasing prevalence of DTSC technologies and their profound impact on disaster risk management, a systematic and longitudinal view of the evolution to the current status of DTSC for disaster risk management does not exist. This review analyses 312 titles and abstracts and 72 full papers. To begin with, a scientific review of DT and SC is undertaken, where the evolution of DTSCs is reviewed. In addition, the intelligence technologies used in DTSCs for disaster risk management are assessed and their benefits are evaluated. Furthermore, the evolution and technical feasibility of DTSC-driven disaster risk management is evaluated by assessing current applications of DTSCs in disaster risk management. It was found that despite the significant potential benefits offered by DTSCs, they also add a new layer of complexities and challenges inherent to these technologies to the already complex web of complexities involved in disaster risk management. These challenges can be addressed by understanding how the process of utilising DTSCs in disaster risk reduction and sustainability is designed, which is essential for comprehending what DTSCs may offer, how it is implemented, and what it means to all involved stakeholders. This paper contributes to the knowledge by improving the understanding of the current status of DTSC technologies and their impact on disaster risk management, and articulating the challenges in implementing DTSC, which inspires the professional community to advance these technologies to address them in future research.</jats:p

Competencies Expected from an Information Manager Working in BIM Based Projects

An Information Manager (IM) has an exclusive and unique role to play in a project. Yet, the competencies expected of an IM have not been adequately defined. The other professionals in the construction industry define this role in their own way ignoring the industry needs. Thus, this study aimed to define the competencies expected of an IM. To achieve this, the tasks expected of an IM were first determined through a desk study using BIM guidelines. Secondly, an informal public opinion study was carried out using online data sources. The collected data were then analyzed using NVIVO software to outline the competencies required of an IM for each task. Finally, an expert interview survey was carried out to validate the outcomes of the study. The findings revealed that an IM must be a construction professional well-versed in construction technology and contract administration and that the IM must be competent in using Building Information Modeling (BIM) workflows/software. The study contributes to knowledge by identifying the gap that currently exists between industry needs and the performance of professionals working as IMs, which would be invaluable when designing a curriculum for a course on information management within a BIM environment

Strategies to develop effective BIM models to suit 4d modelling

Rapid upsurge of technology accredited 4D Building Information Modelling (BIM) as a BIM centric scientifically-derived scheduling process. It upgrades the project outcome, by reducing the substantial uncertainty exists with quality, cost and time. However, 3D BIM models are being advanced not only for 4D models but also for many other visualizing and informative purposes. Hence, necessity ascends to verify whether generally developed BIM models satiate required features of 4D modelling. Consequently, research aims to identify and verify extent of suitability and practicability of using BIM models in 4D modelling. The aim accomplished through a qualitative approach utilized with a desk study, unstructured interviews and a content analysis. It documented strategies and recommendations on how BIM models could be technologically advanced to ensemble 4D visualization. It was revealed that, prevailing BIM models are not readily acceptable for 4D modelling, which need to be refined marginally for real-world approach. Structural work packages, plant, equipment and accessories of building works can be directly used to 4D modelling as already developed whereas, integrated elements and finishing need few adaptations. Despite of few limitations, it is recommended more than 90% of elements developed in BIM models can be used for 4D modelling with certain modifications

Comparative effectiveness of quantity surveying in BIM implementation

Over the past eras, dawn of innovative technologies in construction industry intensified, where Building Information Modelling (BIM) has established as a collaborative tool. Although construction industry is deemed to be conservative, the adoption of BIM redefined traditional professional boundaries. Quantity Surveyor (QS) is one prominent role which needs to compete with aforesaid challenge, where the history provides substantial evidences to its amenability. However, this conversion may influence in either way, where it can upgrade or downgrade the profession since unwieldiness may adhere to the situation, it‘s being used. Hence, this paper aimed at identifying comparative effectiveness of BIM in performing QSs‘ tasks. Through an extensive literature study features of BIM, QSs‘ practices, and the competency of performing BIM adhered QSs‘ tasks were discovered. A documentary survey utilized for the identification of potential capabilities of performing QSs‘ tasks through BIM tools finally, a content analysis was conducted to analyse the data using a qualitative approach. It was revealed that when executing traditional QSs‘ tasks, BIM has proven a great adeptness and contrariwise for modern tasks. Tasks directly linked with numerals experience splendid benefits through BIM. Thus, it was concluded it is advantageous to perform traditional QSs‘ tasks throug

Real-virtual synchronisation: a review on the state-of-the-art geometric digital twinning of infrastructure

In the United Kingdom (UK), recent developments in the construction industry have increased the demand for digitised infrastructure, which facilitates the investigation of the as-is performance of assets. This establishes the need to create and maintain up-todate digital copies of infrastructure assets, often labelled as Digital Twins. Digital twins are obtained by converting the unstructured data formats of the real-world assets, such as point clouds, into high-level digital representations. Yet, only few assets today have usable digital twins because of the high costs of the latter. This counteracts the benefits of the twins and reduces dramatically their true potential. Hence, there is a pressuring need to automate the process of creating digital twins. Geometric digital twin, the most basic form of the twin, contains only the geometry of the physical asset. This paper reviews the work done in computer vision, geometry processing, and civil engineering fields to determine the potential that exists for automatically producing geometric digital twins of infrastructure