National Transport Library Research Database

Belysning av inre skador: fiberoptisk styrd tillståndsbedömning av betongkonstruktioner med korroderade armeringsstänger (Shedding light on internal damage: fibre optic-driven condition assessment of corroded concrete structures)

  • Fernandez, Ignasi
  • Chalmers tekniska högskola AB, Universitet eller högskola, 556479-5598
Sponsors, duration, budget: Formas ; 2022-01-01 -- 2025-12-31 ; 4 000 000 kronorRegistration number:
  • Formas 2021-01103
Subject(s): Abstract: Syftet med projektet är att skapa modeller som kan agera och prediktera underhållsbehov på transportinfrastruktur med hjälp av sensordata. Modeller utvecklas med en kombination av experimentella data och senaste modelleringsteknik. Ett sekundärt syfte är att testa affärsmässigt hur modell tillsammans med ramverket kan fungera effektivt i branschen, vilket är en iterativ process – en co-creation process, mellan studenter-forskare-industri-myndighet med SensIT som utgångspunkt. Forskningen kombinerar tillgängliga experimentella resultat med avancerad matematisk statistik och Non-Linear Finite Element Analisys (NLFEA) meodeller, för att implementera och validera en modell som beskriver inre skador på grund av korrosion.Abstract: Ensuring the integrity and serviceability of our transport infrastructure is vital for the development and welfare of society. Consequently, guaranteeing the serviceability of our infrastructure by condition assessment and proper maintenance is imperative. Yet today, condition assessment strategies rely on labour-intensive on-site inspections, providing limited and subjective data. Particularly, the detection of corrosion processes in a structure is one of the degradation mechanisms where largest uncertainties exist. In this project, we will develop novel sensor-driven supported strategies based on distributed optical fiber sensing (DOFS) to promote a digital upgrade of the current condition assessment methods. By combining experimental data from cutting-edge DOFS and the latest advancements in modelling techniques, we will provide autonomous real-time damage detection through thorough and accurate descriptions of the internal damage due to corrosion. This information is the backbone for the current state-of-the-art assessment models. This will lead to a better planning of resources, the possibility to study optimal repair solutions and the application of timely preventive measures. As a result, the service-life of our infrastructure will be effectively extended while on-site inspections will be minimized, thereby enabling a better use of our limited resources while causing a lower impact to the users, with the consequent environmental and economic savings for society.
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