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Chen, Siyuan
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Chen, Siyuan
Official Name
Chen, Siyuan
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Now showing 1 - 2 of 2
- PublicationStructural Health Monitoring Developments in TRUSS Marie Sklodowska-Curie Innovative Training Network(2017-12)
; ; ; ; ; ; ; This paper reports on recent contributions by the Marie Sklodowska-Curie Innovative Training Network titled TRUSS (Training in Reducing Uncertainty of Structural Safety) to the field of structural safety in rail and road bridges (http://trussitn.eu). In TRUSS, uncertainty in bridge safety is addressed via cost efficient structural performance monitoring and fault diagnostics methods including: (1) the use of the rotation response due to the traffic traversing a bridge and weigh-in-motion concepts as damage indicator, (2) the combination of design parameters in probabilistic context for geometrical and material properties, traffic data and assumption on level of deterioration to evaluate bridge safety (via Bayesian updating and a damage indicator based on real time measurement), (3) the application of a fuzzy classification technique via feature selection extracted using empirical mode decomposition to detect failure, and (4) the testing of alternative vibration based damage sensitive features other than modal parameters. Progress has also been made in improving modern technologies based on optical fiber distributed sensing, and sensors mounted on instrumented terrestrial and on aerial vehicles, in order to gather more accurate and efficient info about the structure. More specifically, the following aspects have been covered: (a) the spatial resolution and strain accuracy obtained with optical distributed fiber when applied to concrete elements as well as the ideal adhesive, and the potential for detecting crack or abnormal deflections without failure or debonding, (b) the possibility of using the high-resolution measurement capabilities of the Traffic Speed Deflectometer for bridge monitoring purposes and, (c) the acquisition of bridge details and defects via unmanned aerial vehicles.288 - PublicationTRUSS Training in Reducing Uncertainty in Structural Safety: D5.2 Final Report: WP5 - Rail and Road Infrastructure(European Commission, 2019-02-28)
; ; ; ; ; ; ; This deliverable reports on the outputs of eight Early Stage Researchers (ESR7-ESR14) in work package, WP5 (Rail and Road Infrastructure), under the supervision of academic and industrial experts during the three years of their projects within the EU TRUSS (Training in Reducing Uncertainty in Structural Safety, 2015-2018) Innovative Training Network (ITN) programme (http://trussitn.eu/). Two types of infrastructure are analysed in WP5: bridges (ESR7-ESR12) and pavements (ESR13-ESR14). The first six projects aim to reduce uncertainty in bridge safety. They address areas of work such as bridge condition assessment (ESR7), probabilistic modelling of bridge damage using damage indicators (ESR8), railway bridge condition monitoring and fault diagnostics (ESR9), condition assessment based on measured vibration level (ESR10), the use of optical fibre distributed sensing for monitoring (ESR11), and the use of displacement and velocity measurements for damage localisation (ESR12). The last two projects are on uncertainty in pavement safety, where ESR13 considers the use of truck sensors for road pavement performance and asset management and ESR14 investigates the possibility of using unmanned aerial vehicles and photogrammetry method for road and bridge inspections. Generally, the areas of work developed in this work package are vehicle-infrastructure interaction, traffic load modelling, road materials, uncertainty modelling, reliability analysis, field measurement and Structural Health Monitoring (SHM) of bridges.870