Digital Twins and Road Construction Using Secondary Raw Materials

Meža, Sebastjan; Pranjić, Alenka Mauko; Vezočnik, Rok; Osmokrović, Igor; Lenart, Stanislav

doi:10.1155/2021/8833058

Cited by 30 publications

(25 citation statements)

References 30 publications

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“…Highways are less complicated when compared to other transportation systems in terms of their structure, nevertheless due to their expansion over a vast network and the use of vast quantities of materials their lifecycle management and material durability are always a concern. Multi-sourced data integration enabled by Digital Twins facilitates the prediction of highway materials performance, allows better visualization of key performance indicators (KPIs), and supports reliable and datadriven decision-making [32,33]. A framework combining Digital Twins and multiple time series stacking (MTSS) was employed to predict the performance of highway tunnel pavement performance [32].…”

Section: Digital Twin Applications For Highwaysmentioning

confidence: 99%

“…The proposed framework was validated using a case study, and it was found that the visuals provided by Digital Twins allowed for conducting preventive maintenance. Similarly, the authors of [33] established a fully functioning Digital Twin of a road constructed using secondary raw materials (SRMs). The model included structured geometric and attribute data related to SRMs such as material data, chemical and mineralogical composition, strength, and unstructured data including real-time material characteristics collected by sensors.…”

Section: Digital Twin Applications For Highwaysmentioning

confidence: 99%

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Perspective Chapter: Roadmap to a Holistic Highway Digital Twin – A Why, How, and Why Framework

Ammar¹,

Nassereddine²,

Dadi³

2024

Critical Infrastructure - Modern Approach and New Developments

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The advent and spread of the COVID-19 pandemic shifted the world’s focus toward investing in social structure projects that would improve urbanization and enhance equity. This shift compiled with the emergence of innovative technologies namely Digital Twins, allowed for investigating new approaches for designing and delivering infrastructures, thus paving the road toward smarter infrastructures. Smart infrastructures achieved by connecting the physical aspect of the infrastructure with its digital aspect will allow for optimizing the performance of infrastructure systems by digitally enhancing the asset value and leveraging the value of asset data. Digital Twins can be applied to several civil infrastructure projects including the transportation sector. Also, Digital Twins can be implemented for different spatial scales, on a national level, on the level of the city, and for a network of assets. Few case studies described how to transfer a Digital Twin vision to practice; thus, this chapter presents the journey for a holistic Digital Twin for a highway system formed of a network of assets by discussing the Why, How, and What framework. A holistic highway Digital Twin will allow for cross-asset data analysis, conducting predictive and preventive maintenance, and efficient resource allocation based on data-driven decision-making.

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Section: Digital Twin Applications For Highwaysmentioning

confidence: 99%

Section: Digital Twin Applications For Highwaysmentioning

confidence: 99%

Perspective Chapter: Roadmap to a Holistic Highway Digital Twin – A Why, How, and Why Framework

Ammar¹,

Nassereddine²,

Dadi³

2024

Critical Infrastructure - Modern Approach and New Developments

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“…Han et al [15] researched the change detection in aerial images of road construction using a convolutional neural network to monitor the road construction progress. Meza et al [16] introduced the Digital Twin (DT) model of the road project to visualize the road progress using the synthetic BIM model of the proposed project.…”

Section: Literature Reviewmentioning

confidence: 99%

Sensor-based Pavement layer change detection using Long-Short Term Memory (LSTM)

Patel

Brian

Guo

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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During construction, pavement projects often suffer from a lack of progress certainty, which leads to cost and time overruns. The pavement construction progress should be monitored in a timely and accurate manner to provide prompt feedback and ensure project success. However, current pavement construction progress monitoring practices (e.g., data collection, processing and analysis) are manual, time-consuming, tedious, inconsistent, subjective and error-prone. The previous research study was limited to only incremental road construction progress measurement. This preliminary study proposes a novel sensor-based method to identify pavement layer changes during construction using a time series algorithm for the approach development of automated as-built measurement of road construction. In this study, data were collected from generating various road construction scenarios in a controlled environment by simulating layer changes using a ground vehicle equipped with a laser ToF (time-of-flight) distance-ranging sensor. Subsequently, Long Short Term Memory (LSTM) was utilized on collected data for feature detection as ‘layer up’, ‘layer down’ and ‘layer not changed’ to classify road layer change. The experimental result demonstrates 84.91% as a promising overall average accuracy of road layer change classification on the control environment data, confirming the potential implementation suitability to detect pavement layers in real pavement construction projects. However, low-performance measures (low precision, recall and F1 score) of layer up and layer down suggest further improvement to enhance the robustness of the proposed model. This method can be extended to automate pavement construction progress monitoring by validating the proposed approach in a real case.

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“…The main challenges facing the development of DTs are further detailed in [73]. Firstly, there is a lack of standardised semantics.…”

Section: Data Challenges and Quality Controlmentioning

confidence: 99%

Digital Twins in Civil Infrastructure Systems

et al. 2021

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This research explores the existing definitions, concepts and applications surrounding the efficient implementation and use of digital twins (DTs) within civil infrastructure systems (CISs). The CISs within the scope of this research are as follows: transportation, energy, telecommunications, water and waste, as well as Smart Cities, which encompasses all of the previous. The research methodology consists of a review of current literature, a series of semi-structured interviews and a detailed survey. The outcome of this work is a refined definition of DTs within CISs, in addition to a set of recommendations for both future academic research and industry best practice.

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Digital Twins and Road Construction Using Secondary Raw Materials

Cited by 30 publications

References 30 publications

Perspective Chapter: Roadmap to a Holistic Highway Digital Twin – A Why, How, and Why Framework

Perspective Chapter: Roadmap to a Holistic Highway Digital Twin – A Why, How, and Why Framework

Sensor-based Pavement layer change detection using Long-Short Term Memory (LSTM)

Digital Twins in Civil Infrastructure Systems

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