Year: 2025
Type: conference-paper
Abstract: Many existing concrete structures have been fulfilling their purpose for several decades, but they may no longer meet current structural safety standards due to various factors.This fact highlights the urgent need for innovative solutions to ensure the durability and performance of these structures under increasing load and changing environment.Digital twins can indeed provide very effective solutions in various contexts.A digital twin is a virtual representation of a physical object or system that is used to simulate, predict, and optimize performance.By creating a digital twin, one can analyze data and monitor systems to prevent problems before they occur, develop new opportunities, and plan for the future by using simulations.In this work, we focus on the load-bearing behavior of a specially reinforced existing pier of the Jauntal Bridge in Carinthia (DT Physical Model).This behavior is virtually simulated using a non-linear finite element model (DT Virtual Model).The aim is to draw conclusions about the constantly changing load conditions by observing the development of cracks and the geometric deformations (DT Monitoring, e.g., via orthographic and radar interferometry) and thus to make statements about the constantly fluctuating safety level and the fluctuating service life.Based on these findings, it should be possible to optimize the existing verification formats and the arrangement of the reinforcement measures, particularly the prestressing bars and the interaction between new and old concrete at the pier heads.Consequently, this would allow for a direct assessment of the constantly fluctuating loads and safety levels.
DOI: 10.21012/fc12.1105
Authors: Alfred Strauss, Benjamin Täubling-Fruleux, Drahomir Novák, Lukas Novák, David Lehký
Institutions: BOKU University, Brno University of Technology
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
Funders: European Commission, Interreg
OpenAlex ID: W4409437918
