Lifespan Prediction Technique for Digital Twin-Based Noise Barrier Tunnels

Kim, Jinwooung; Kim, Sung-Ah

doi:10.3390/su12072940

Cited by 25 publications

(13 citation statements)

References 9 publications

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“…Predictive twins model the behavior of the products or systems based on the historical data of their real-time simulated instances. The remaining useful life of a product can be approximated with the help of historical observations gathered from the product and components, or other similar devices, or a combination of those [17][18][19]. Such predictive model provides manufacturers with the ability to anticipate the future state of product and component conditions before offering trade-in prices.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain

2020

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Manufacturing and supply chain operations are on the cusp of an era with the emergence of groundbreaking technologies. Among these, the digital twin technology is characterized as a paradigm shift in managing production and supply networks since it facilitates a high degree of surveillance and a communication platform between humans, machines, and parts. Digital twins can play a critical role in facilitating faster decision making in product trade-ins by nearly eliminating the uncertainty in the conditions of returned end-of-life products. This paper demonstrates the potential effects of digital twins in trade-in policymaking through a simulated product-recovery system through blockchain technology. A discrete event simulation model is developed from the manufacturer’s viewpoint to obtain a data-driven trade-in pricing policy in a fully transparent platform. The model maps and mimics the behavior of the product-recovery activities based on predictive indicators. Following this, Taguchi’s Orthogonal Array design is implemented as a design-of-experiment study to test the system’s behavior under varying experimental conditions. A logistics regression model is applied to the simulated data to acquire optimal trade-in acquisition prices for returned end-of-life products based on the insights gained from the system.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain

2020

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“…Tunnels are complicated spatial structures and have multiple electromechanical components, such as ventilation systems, necessary for their operation. Digital Twins can support the operation and maintenance of tunnels and allow for lifecycle management analysis [30,31]. A Digital Twins prototype of noise barrier tunnels (NBTs) was implemented to predict the life and condition of the tunnel components using numerical behavior analysis.…”

Section: Digital Twin Applications For Tunnelsmentioning

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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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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“…Germany Bauhaus Universit€ at established a general tunnel information modeling framework, proposed a numerical simulation-based ground settlement prediction method and developed an interactive display system for ground settlement timing process caused by tunnel construction (Beer, 2003). Kim and Kim (2020) (NBTs) lifespan prediction where gyro sensors were implemented to analyze the change of physical component's behavior and a simple numerical method was utilized for fast lifespan prediction. The Neanex BIM portal contains a "twin" representation of the real physical tunnel, which can be navigated in 3D and displays all the necessary information for the highlighted individual asset (Neanex, 2020).…”

Section: Book Reviewmentioning

confidence: 99%

Digital twin: a state-of-the-art review of its enabling technologies, applications and challenges

Zhang

Deng

et al. 2021

JIMSE

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Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant attraction in both industry and academia, there is no systematic understanding of DT from its development history to its different concepts and applications in disparate disciplines. The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area. Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies. The review also provides a comprehensive survey of DT applications from two perspectives: (1) applications in four product-lifecycle phases, i.e. product design, manufacturing, operation and maintenance, and recycling and (2) applications in four categorized engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering and Internet of things (IoT) applications. DT frameworks, characteristic components, key technologies and specific applications are extracted for each DT category in this paper. A comprehensive survey of the DT references reveals the following findings: (1) The majority of existing DT models only involve one-way data transfer from physical entities to virtual models and (2) There is a lack of consideration of the environmental coupling, which results in the inaccurate representation of the virtual components in existing DT models. Thus, this paper highlights the role of environmental factor in DT enabling technologies and in categorized engineering applications. In addition, the review discusses the key challenges and provides future work for constructing DTs of complex engineering systems.

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Lifespan Prediction Technique for Digital Twin-Based Noise Barrier Tunnels

Cited by 25 publications

References 9 publications

Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain

Evaluation of Waste Electronic Product Trade-in Strategies in Predictive Twin Disassembly Systems in the Era of Blockchain

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

Digital twin: a state-of-the-art review of its enabling technologies, applications and challenges

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