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Towards Automated Pipelines for Processing Load Test Data on a HS Railway Bridge in Spain using a Digital Twin

Authors: Ramonell Cazador, Carlos; Chacón Flores, Rolando Antonio;

Towards Automated Pipelines for Processing Load Test Data on a HS Railway Bridge in Spain using a Digital Twin

Abstract

On the 14th of July 2022, UPC represented ASHVIN at the ISARC 2022, International Symposium on Automation and Robotics in Construction organized in Bogota, Colombia. UPC, a project partner, presented there a scientific publication entitled “Towards Automated Pipelines for Processing Load Test Data on an HS Railway Bridge in Spain using a Digital Twin". This paper was co-authored by Carlos Ramonell (UPC) and Rolando Chacón (UPC) and is related to the ASHVIN Demonstration Site #1 research. Abstract This document presents an automated pipeline to process sensor-based data produced during load tests on digitally twinned HS railway bridges. The research is developed within the frame of the H2020 European project ASHVIN, related to Assistants for Healthy, Safe, and Productive Virtual Construction, Design, Operation & Maintenance using Digital Twins. The pipeline is developed within a digital twin application based on event-driven microservices, which integrates the ASHVIN IoT platform, the IFC building information model, and an array of services dedicated to automating processes performed during the structural assets operation stage. A load test carried out on a bridge located on a HS railway in Spain is used as a demonstrator.

Country
Spain
Keywords

IoT, :Enginyeria civil::Materials i estructures::Tipologies estructurals [Àrees temàtiques de la UPC], Ponts, Bridges, Data processing, Digital Twin, Load tests, Àrees temàtiques de la UPC::Enginyeria civil::Materials i estructures::Tipologies estructurals, BIM, Automated pipeline, Event-based microservice architecture

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
4
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Average
Top 10%
90
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