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Engineering with Computers

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09-05-2023 | Original Article

Digital twin based lifecycle modeling and state evaluation of cable-stayed bridges

Authors: Xin-Yu Guo, Sheng-En Fang

Published in: Engineering with Computers | Issue 2/2024

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Abstract

This paper proposes a digital twin (DT) modeling method for the lifecycle state evaluation of cable-stayed bridges, which cover a large time scale and simultaneously involve macroscopic and microcosmic exploration. First, the DT model at the design stage corresponds to the computer-aided design (CAD) model and then evolves to the computer-aided engineering (CAE) model during the construction stage. After that, the DT model for the operational stage starts from the completion model of the bridge and keeps evolving with the bridge physical entity in the long-term service. An information interaction media is used for the information interchange between the DT model and the bridge physical entity. And a fidelity index gives the quantitative estimation of similarity between the DT model and the bridge physical entity. Finally, the proposed method has been verified against a cable-stayed bridge model, whose DT model could reflect the actual state evolution of the physical entity.

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Title: Digital twin based lifecycle modeling and state evaluation of cable-stayed bridges
Authors: Xin-Yu Guo
Sheng-En Fang
Publication date: 09-05-2023
Publisher: Springer London
Published in: Engineering with Computers / Issue 2/2024
Print ISSN: 0177-0667
Electronic ISSN: 1435-5663
DOI: https://doi.org/10.1007/s00366-023-01835-6

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Abstract

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Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Topology optimization of a benchmark artifact with target stress states using evolutionary algorithms

Toward a shape-performance integrated digital twin based on hybrid reduced-order modeling for engineering structures

Retraction Note to: Chaotic simulation of the multi-phase reinforced thermo-elastic disk using GDQM

A neural network approach for solving nonlinear differential equations of Lane–Emden type

FluTO: Graded multi-scale topology optimization of large contact area fluid-flow devices using neural networks

GAS-AU: an average uncertainty-based general adaptive sampling approach