AI Based Surrogate Model for Digital Twins in Reinforced Concrete

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F28399269%3A_____%2F25%3AN0000007" target="_blank" >RIV/28399269:_____/25:N0000007 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

AI Based Surrogate Model for Digital Twins in Reinforced Concrete

Original language description

Artificial Intelligence (AI), particularly using Artificial Neural Networks (ANNs), is increasingly integrated into various domains of human activity and industrial applications. A significant area of application is the development of real-time, fast-response surrogate models within the digital twin framework for structural health monitoring. Within the presented framework, ANNs serve two primary functions. First, during the calibration phase, ANNs ensure that the virtual twin accurately reflects the behavior of the physical structure. Once calibrated, the virtual twin facilitates the training of the ANN through physically informed deep learning, utilizing data derived from sensitivity analyses conducted via nonlinear finite element analysis using ATENA software. The second function involves deploying the trained ANN as a fast-response surrogate model, providing critical safety information for the ongoing structural health monitoring of bridges. This paper outlines the development of an efficient and accurate ANN-based surrogate model, emphasizing the advancements in physically informed deep learning methodologies for structural analysis and life cycle assessment of infrastructures.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

20102 - Construction engineering, Municipal and structural engineering

Project

<a href="/en/project/TM04000012" target="_blank" >TM04000012: A concrete bridge health interpretation system based on mutual boost of big data and physical mechanism</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů