On the 9th of October, 2023, the ASHVIN project was proud to see its research article published in an international scientific journal, Structure and Infrastructure Engineering, that is dedicated to recent advances in maintenance, management and life-cycle performance of a wide range of infrastructures.
The published article is entitled “Digital twinning during load tests of railway bridges – case study: the high-speed railway network, Extremadura, Spain” and it is autohered by a group of ASHVIN project’s researchers, including; Rolando Chacon, Carlos Ramonell, Hector Posada and Pablo Sierra from the Polytechnical University of Catalonia (UPC) Rahul Tomar from Digital Twin Technology (DTT), Ilias Koulalis and Konstantinos Ioannidis from the Centre for Research and Technology (CERTH) and Stefan Wagmeister from Austrian Standards (ASI). Also, the ASHVIN demo site #X1 owners (external to the project’s construction) contributed to this article: Christian Martınez de la Rosab and Alejandro Rodriguezc from Drace Geosica.
This article presents a case study with various developments of digital twinning of a sample of loadtests performed on several railways bridges. The case study is located in Extremadura, South Western Spain (ASHVIN Demo Site #1), and its aim is the generation of a validated, multi-layered information construct in the form of a digital twin as the result of a load test. This result is conceived, not only to verify the assumptions of the design of the bridge but also, to optimize future maintenance plans of the network.
This particular case study is framed within a vaster European effort on digitization of the construction sector. Research and Innovation Actions within this demo case are aimed at integrating routine requirements and procedures of load tests with cutting edge digital technologies for the generation of validated virtual replica of these physical bridges. The generated twins during these load tests behaviourally match the obtained response during loading and as such, represent an ideal model for future simulations and behavioural predictions. Different data-gathering techniques and numerical models are integrated within a Common Data Environment (CDE). All efforts related to measurement, simulation, 3D modelling, assessment and validation can be wrapped up systematically for further use during regular operation of the asset.
View and download the full paper: https://zenodo.org/records/10159425